Brain Imaging and Behavior

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Article
Type 2 diabetes mellitus (T2DM) is associated with brain damage and cognitive decline. Despite the fact that the thalamus involves aspects of cognition and is typically affected in T2DM, existing knowledge of subregion-level thalamic damage and its associations with cognitive performance in T2DM patients is limited. The thalamus was subdivided into 8 subregions in each hemisphere. Resting-state functional and structural MRI data were collected to calculate resting-state functional connectivity (rsFC) and gray matter volume (GMV) of each thalamic subregion in 62 T2DM patients and 50 healthy controls. Compared with controls, T2DM patients showed increased rsFC of the medial pre-frontal thalamus, posterior parietal thalamus, and occipital thalamus with multiple cortical regions. Moreover, these thalamic functional hyperconnectivity were associated with better cognitive performance and lower glucose variability in T2DM patients. However, there were no group differences in GMV for any thalamic subregions. These findings suggest a possible neural compensation mechanism whereby selective thalamocortical functional hyperconnectivity facilitated by better glycemic control help to preserve cognitive ability in T2DM patients, which may ultimately inform intervention and prevention of T2DM-related cognitive decline in real-world clinical settings.
 
The flow diagram of the systematic review process
A schematic representation of the detection likelihood of presymptomatic radiological change in the most common FTD-associated genetic variants. In C9orf72 mutation carriers, it is hypothesized that neurodevelopmental factors may be at play in conjunction with slowly progressive neurodegeneration. In GRN mutation carriers, the disease process is thought to accelerate 2-years before phenoconversion. In MAPT mutation carriers, disease burden accrues 2-years before phenoconversion, but at a relatively slower rate than in GRN
Article
Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 ( C9orf72 ), progranulin ( GRN ), or microtubule-associated protein tau ( MAPT ) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3–141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1–8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.
 
Article
Non-small cell lung cancer (NSCLC) accounts for more than 85% of all lung cancer cases, and chemotherapy-related brain changes (known as “chemobrain”) in NSCLC patients were found in previous studies. However, the effects of platinum-based chemotherapy on brain structural networks are still unclear. Structural magnetic resonance imaging (sMRI) data were collected from 32 NSCLC patients following platinum-based chemotherapy, 36 NSCLC patients without chemotherapy, and 39 healthy controls. Clinical physiological indicators of patients were collected. Then, morphological similarity networks were constructed using MRI data, and topological properties were calculated using graph theory method. Differences between three groups were investigated using one-way ANOVA and two-sample t-test, and relations between topological properties and clinical physiological indicators were calculated. We found that degree and nodal efficiency in temporal-parietal networks were significantly reduced in NSCLC patients following platinum-based chemotherapy compared to healthy controls/patients without chemotherapy (F-test, p < 0.001; post hoc t-test, p < 0.01, Bonferroni corrected). These changes (p < 0.05) were positively correlated with clinical measures, including thrombocytes, granulocytes and hemoglobin, and were negatively correlated with measures of triglycerides and cholesterol levels. Network properties including clustering coefficient (F(2,104) = 41.435, p < 0.001), number of K-edges (F(2,104) = 40.304, p < 0.001), density of K-edges (F(2,104) = 40.304, p < 0.001), global efficiency (F(2,104) = 42.585, p < 0.001) and small-world (F(2,104) = 37.132, p < 0.001) were also significantly reduced (post hoc t-test, p < 0.01, Bonferroni corrected). These results indicate that platinum-based chemotherapy might cause cerebrovascular damage and clinical indicators’ changes, which then cause the properties of morphological similarity networks’ changes in the temporal and parietal lobes. This study may help us better understand the “chemobrain” in NSCLC patients.
 
Differences between the pre- and post-intervention in functional connectivity (FC) of the salience network (SLN). The results showed increased FC of the SLN following the 10 week mindfulness intervention. The regions with increased FC of the SLN are linked to the default mode network (supra-marginal gyrus, ventromedial pre-frontal cortex -vmPFC, posterior cingulate cortex - PCC, amygdala and hippocampus, inferior temporal gyrus-ITG), visual perception (superior occipital gyrus, inferior occipital gyrus ), sensorimotor function (putamen, primary motor cortex and somatosensory cortex), cognitive functions (dorsolateral pre-frontal cortex - dlPFC, inferior frontal gyrus - IFG, superior parietal lobule), or attention (anterior cingulate cortex - ACC, mid-cingulate cortex and insula)
Differences between the pre- and post-intervention time-points in the functional connectivity (FC) of: (A) Frontal-Parietal network (FPN) and (B) the Medial-inferior temporal component (MTG) of the Default Mode Network (DMN). The results showed increased FC of the FPN and MTG following the 10-week mindfulness intervention. The regions with increased FC of the FPN are linked to the sensorimotor (primary sensory and motor cortices (S1, M1), supplementary motor area (SMA), middle frontal gyrus (MFG), cognitive and executive (dlPFC, dmPFC, vmPFC, inferior frontal gyrus (IFG)), and attention (insular cortex (INS), ACC). The regions with increased FC of the MTG of the DMN are linked to different brain functions including the dmPFC, ACC, IFG, MFG, superior frontal gyrus (SFG).
Article
Mindfulness training has been associated with improved attention and affect regulation in preadolescent children with anxiety related attention impairments, however little is known about the underlying neurobiology. This study sought to investigate the impact of mindfulness training on functional connectivity of attention and limbic brain networks in pre-adolescents. A total of 47 children with anxiety and/or attention issues (aged 9-11 years) participated in a 10-week mindfulness intervention. Anxiety and attention measures and resting-state fMRI were completed at pre- and post-intervention. Sustained attention was measured using the Conners Continuous Performance Test, while the anxiety levels were measured using the Spence Children’s Anxiety Scale. Functional networks were estimated using independent-component analysis, and voxel-based analysis was used to determine the difference between the time-points to identify the effect of the intervention on the functional connectivity. There was a significant decrease in anxiety symptoms and improvement in attention scores following the intervention. From a network perspective, the results showed increased functional connectivity post intervention in the salience and fronto-parietal networks as well as the medial-inferior temporal component of the default mode network. Positive correlations were identified in the fronto-parietal network with Hit Response Time and the Spence Children’s Anxiety Scale total and between the default mode network and Hit Response Time. A 10-week mindfulness intervention in children was associated with a reduction in anxiety related attention impairments, which corresponded with concomitant changes in functional connectivity.
 
Cortical area alterations among subjects with schizophrenia who had a history of suicide attempts compared with patients without suicide attempts
Note. The color bar represents the range of t statistics of the history of suicide attempts in regression on the cortical area in each Desikan-Killiany region adjusting for the whole brain surface area, age, sex, phase of illness (first-episode vs. chronic), and study center. Only t > 1.96 was presented. No region survived FDR correction
Decreased cortical thickness among subjects with schizophrenia who had a history of suicide attempts compared with patients without suicide attempts.
Note. The color bar represents the range of t statistics of the history of suicide attempts in regression on cortical thickness in each Desikan-Killiany region adjusting for age, sex, phase of illness (first-episode vs. chronic), and study center. Only t > 1.96 was presented. Only the association between the thickness of the right superior temporal gyrus and suicide attempts remained significant after FDR correction
Article
Individuals with schizophrenia have higher rates of suicide attempts than the general population. Specific cortical abnormalities (e.g., the cortical surface area and thickness) may be associated with a history of suicide attempts. We recruited 74 individuals with schizophrenia (37 suicide attempters were individually matched with 37 non-attempters on age, sex, phase of illness, and study center) and 37 healthy volunteers. The cortical surface area and thickness data were extracted from structural MRI and compared between the groups. Suicide attempters showed significantly smaller surface areas in the whole brain (p = .028, Cohen’s d = -0.54) than non-attempters. No association was found between the cortical surface area of individual brain regions and a history of suicide attempts. The mean cortical thickness did not differ significantly between the groups; however, suicide attempters demonstrated a thinner cortex in the right superior temporal gyrus (p < .001, q = 0.037, Cohen’s d = -0.88). These findings indicate that a history of suicide attempts among individuals with schizophrenia is associated with a reduction in the global cortical surface area and specific cortical thinning of the right superior temporal gyrus. The morphometric alteration of the right superior temporal gyrus may represent a biomarker of suicidal behavior in individuals with schizophrenia.
 
Mean (+ SEM) auditory thresholds in the noise group and control group at 1 month post noise exposure using the auditory brainstem response test. Thresholds at all frequencies (2,4,8,16,32 kHz) are significantly higher in the noise group compared to the control group
Memory retrieval on Morris Water Maze test is impaired in the noise group compared to the control group. (A) Mean (+ SEM) escape latency to find the platform on training days 1–5 in the control group versus noise group. (B) Mean (+ SEM) swimming distance in meters on training days 1–5 in the control group versus noise group. Representative swim tracks of the noise exposure rat (C) and the control rat (D) during Morris Water Maze test. (E) Mean (+ SEM) number of crossings on the probe trial into the quadrant that formerly contained the hidden platform in the control group versus noise group. The control group spent more time than the noise group searching in the quadrant where the platform was previously located. (F) Mean (+ SEM) distance traveled in control versus the noise group during the 90 s probe test. *, p < 0.05
ROI-wise interregional connectivity in the auditory network and default mode network at 0 day and 6 months post noise exposure. (A) Anatomical representation of the auditory network regions in the analysis: ventral cochlear nucleus (VCN), inferior colliculus (IC), medial geniculate body (MGB), primary auditory cortex (Au1), dorsal secondary auditory cortex (AuD), ventral secondary auditory cortex (AuV) and temporal association cortex (TeA). (B) Colored matrix indicating t values of interactions in the auditory network at 0 day post noise exposure. (C) Colored matrix indicating t values of interactions in the auditory network at 6 months post noise exposure. (D) Anatomical representation of the default mode network regions in the analysis: cingulate cortex (Cg 1 and 2), orbital cortex (Orb), prelimbic cortex (PrL), retrosplenial dysgranular cortex (RSD), retrosplenial granular cortex b (RSGb) and c (RSGc). (E) Colored matrix indicating t values of interactions in the default mode network at 0 day post noise exposure. (F) Colored matrix indicating t values of interactions in the default mode network at 6 months post noise exposure. (p < 0.01, uncorrected)
Noise-induced hearing loss alters functional connectivity in specific brain regions at four time points (0 day, 1, 3 and 6 months post noise exposure) using the left primary auditory cortex as the seed. (A) The left primary auditory cortex shows increased connectivity with left hippocampus (HIP), superior colliculus (SC), retrosplenial granular cortex b (RSGb), retrosplenial dysgranular cortex (RSD) and secondary visual cortex (V2) at 0 day post noise. (B) No significant changes are observed at 1 month post noise. (C) The left primary auditory cortex shows decreased connectivity with right HIP and parafloccular lobe (PFL) at 3 months post noise. (D) The left primary auditory cortex shows decreased connections with right retrosplenial granular cortex c (RSGc), left primary somatosensory cortex (S1HL) and posterior parietal cortex (PPC) at 6 months post noise. Scale bar shown in the right. (uncorrected p < 0.005, cluster size > 20 voxels)
Noise-induced hearing loss alters functional connectivity in specific brain regions at four time points (0 day, 1, 3 and 6 months post noise exposure) using the left cingulate cortex as the seed. (A) The left cingulate cortex shows enhanced connectivity with left retrosplenial dysgranular cortex (RSD). (B) No significant changes are observed at 1 month post noise. (C) The left cingulate cortex shows weak connectivity with left parafloccular lobe (PFL) at 3 months post noise. (D) The left cingulate cortex shows weak connectivity with left cerebellum, inferior colliculus (IC) and bilateral auditory cortex (ACx) at 6 months post noise. Scale bar shown in the right. (uncorrected p < 0.005, cluster size > 20 voxels)
Article
This study aimed to investigate the alterations of cognition and functional connectivity post noise, and find the progress and neural substrates of noise induced hearing loss (NIHL)-associated cognitive impairment. We exposed rats to 122 dB broad-band noise for 2 h to induce hearing loss and the auditory function was assessed by measuring auditory brainstem response thresholds. Morris water maze test and resting state MRI were computed at 0 day, 1, 3, 6 months post noise to reveal cognitive ability and neural substrate. The interregional connections in the auditory network and default mode network, as well as the connections using the auditory cortex and cingulate cortex as seeds were also examined addtionally. The deficit in spatial learning/memory was only observed at 6 months after noise exposure. The internal connections in the auditory network and default mode network were enhanced at 0 day and decreased at 6 months post noise. The connectivity using the auditory cortex and cingulate cortex as seeds generally followed the rule of “enhancement-normal-decrease-widely decrease”. A new model accounting for arousal, dementia, motor control of NIHL in is proposed. Our study highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.
 
The connected network showing decreased functional connections in patients with RUHL and its relationship with the cognitive function. A Region pairs exhibiting abnormal functional connections in patients with RUHL. These connections form a single connected network with 15 nodes and 19 connections, the functional connectivity strength of which are significantly lower (P < 0.001, NBS-corrected) than HCs. All the 15 nodes belong to the visual network of the Power-264 atlas. The BrainNet Viewer package (www.nitrc.org/projects/bnv) was used to map the nodes and connections onto the cortical surface. B The box-and-whisker of the mean functional connectivity of this connected network among the RUHL, LUHL and HCs groups. Boundaries of boxes indicate lower and upper quartiles, horizontal lines within the box indicate the median and whiskers reflect the 10th and 90th percentiles. * Significant difference between RUHL and HCs. (P < 0.001, NBS corrected) (C) Scatter plot of the mean functional connectivity of this connected network against SDMT score. SDMT = Symbol Digit Modalities Test
Altered small-world properties of brain functional networks. The graphs show the changes in the γ and σ as a function of sparsity thresholds (0.1 ≤ S ≤ 0.45, interval = 0.01). Curves and shades denote the mean value and standard error of mean. The inset box-and-whisker plots show the AUC for each topological measure. Boundaries of boxes indicate lower and upper quartiles, horizontal lines within the box indicate the median and whiskers reflect the 10th and 90th percentiles. AUC, area under the curve. ● Significant difference between UHL and HCs. (P < 0.05, FDR corrected). ▲ Significant difference among the three groups. (ANCOVA, P < 0.05, FDR corrected; post hoc: RUHL < HCs). * Significant difference between groups at p < 0.05
Scatterplots of the relationship between network metrics and hearing loss duration in patients with RUHL
Article
Neuroimaging studies have identified alterations in functional connectivity between specific brain regions in patients with unilateral hearing loss (UHL) and different influence of the side of UHL on neural plasticity. However, little is known about changes of whole-brain functional networks in patients with UHL and whether differences exist in topological organization between right-sided UHL (RUHL) and left-sided UHL (LUHL). To address this issue, we employed resting-state fMRI (rs-fMRI) and graph-theoretical approaches to investigate the topological alterations of brain functional connectomes in patients with RUHL and LUHL. Data from 44 patients with UHL (including 22 RUHL patients and 22 LUHL patients) and 37 healthy control subjects (HCs) were collected. Functional brain networks were constructed for each participant, following by graph-theoretical network analyses at connectional and global (e.g., small-worldness) levels. The correlations between brain network topologies and clinical variables were further studied. Using network-based analysis, we found a subnetwork in the visual cortex which had significantly lower connectivity strength in patients with RUHL as compared to HCs. At global level, all participants showed small-world architecture in functional brain networks, however, significantly lower normalized clustering coefficient and small-worldness were observed in patients with RUHL than in HCs. Moreover, these abnormal network metrics were demonstrated to be correlated with the clinical variables and cognitive performance of patients with RUHL. Notably, no significant alterations in the functional brain networks were found in patients with LUHL. Our findings demonstrate that RUHL (rather than LUHL) is accompanied with aberrant topological organization of the functional brain connectome, indicating different pathophysiological mechanisms between RUHL and LUHL from a viewpoint of network topology.
 
Overview of the prevalence of complaints (%) per group and per domain (OA-mTBI: older adults with mTBI; OA-HC: older adults-healthy controls; DOM: complaint domain). Complaints ordered by prevalence in the older adults with mTBI group from highest to lowest within each of the five identified complaint domains. Asterisks indicated significant differences between groups (Chi-square tests; *p < 0.05, FDR-corrected; †p < 0.05, uncorrected)
Effects of group on spatial map intensity (SMI). (A, C): Significant effect of group (older adults with mild traumatic brain injury; OA-mTBI vs. older adults-Healthy controls; OA-HCs) for SMI of intrinsic connectivity network (ICN) showing increased SMI for OA-mTBI in the left middle temporal gyrus on ICN13, and decreased SMI for OA-mTBI in the right posterior fusiform gyrus on ICN5 (p < 0.05, FDR-corrected) in representative slices. (B, D): Boxplots of the SMI averaged over all significant voxels across participants, per group. Cog-C/Lan: Cognitive-language domain; Vis-CB: Visual(-cerebellar) domain
Group × sqrt(HISC) interaction effect on spatial map intensity (SMI) of older adults with mild traumatic brain injury (OA-mTBI) and older adults HCs (OA-HCs). (A, C, E): Voxels with significant Group × sqrt(HISC) interaction effect for SMI of intrinsic connectivity network (ICN) in the anterior fusiform and middle occipital gyri on ICN7 (A), in the cerebellum VI and Crus I bilaterally on ICN7 (C) and in the cuneus on ICN4 (E) (p < 0.05, FDR-corrected). (B, D, F): Scatterplot of sqrt(HISC) against SMI (z-score) averaged over all significant voxels across participants. Blue: OA-HCs; red: OA-mTBI; sqrt(HISC): square root transformed severity of complaints score. Vis-CB: Visual(-cerebellar) domain
Article
Older age is associated with worsened outcome after mild traumatic brain injury (mTBI) and a higher risk of developing persistent post-traumatic complaints. However, the effects of mTBI sequelae on brain connectivity at older age and their association with post-traumatic complaints remain understudied. We analyzed multi-echo resting-state functional magnetic resonance imaging data from 25 older adults with mTBI (mean age: 68 years, SD: 5 years) in the subacute phase (mean injury to scan interval: 38 days, SD: 9 days) and 20 age-matched controls. Severity of complaints (e.g. fatigue, dizziness) was assessed using self-reported questionnaires. Group independent component analysis was used to identify intrinsic connectivity networks (ICNs). The effects of group and severity of complaints on ICNs were assessed using spatial maps intensity (SMI) as a measure of within-network connectivity, and (static) functional network connectivity (FNC) as a measure of between-network connectivity. Patients indicated a higher total severity of complaints than controls. Regarding SMI measures, we observed hyperconnectivity in left-mid temporal gyrus (cognitive-language network) and hypoconnectivity in the right-fusiform gyrus (visual-cerebellar network) that were associated with group. Additionally, we found interaction effects for SMI between severity of complaints and group in the visual(-cerebellar) domain. Regarding FNC measures, no significant effects were found. In older adults, changes in cognitive-language and visual(-cerebellar) networks are related to mTBI. Additionally, group-dependent associations between connectivity within visual(-cerebellar) networks and severity of complaints might indicate post-injury (mal)adaptive mechanisms, which could partly explain post-traumatic complaints (such as dizziness and balance disorders) that are common in older adults during the subacute phase.
 
The significant difference of cortical thickness between patients with TRD and healthy controls
The association between the cortical thickness and the mean error in 2-back working memory task
Article
Accumulating evidence suggests the critical role of cortical thinning in the pathophysiology of major depressive disorder. However, the association of cortical thickness and cognitive impairment with treatment-resistant depression (TRD) has rarely been investigated. In total, 48 adult patients with TRD and 48 healthy controls were recruited and administered a series of neurocognitive and neuroimaging examinations, including 1-back and 2-back working memory tasks and brain magnetic resonance imaging (MRI). Whole-brain cortical thickness analysis was performed to investigate the differences in the cortical thickness between patients with TRD and controls. The patients had reduced cortical thickness in the frontal cortex, particularly at the left frontal pole, left inferior frontal cortex, and left anterior cingulate cortex, and left middle temporal cortex compared with the healthy controls. Moreover, in the 2-back working memory task, the cortical thickness in the left frontal pole and left anterior cingulate cortex was positively associated with mean error in the patients, but not in the controls. Reduced cortical thickness in the frontal pole and anterior cingulate cortex is associated with TRD and related cognitive impairment. Our study indicated the crucial effects of the frontal and temporal cortical thickness on the pathophysiology of TRD and cognitive impairment in patients with TRD.
 
Changes of ALFF in patients with CSF1R-related leukoencephalopathy. (A)The patients group showed increased ALFF in left dorsolateral superior frontal gyrus, left postcentral gyrus, left precentral gyrus, right precuneus, as well as bilateral insula, parahippocampal gyrus, hippocampus, midbrain and cingulate gyrus, and the ALFF value decreased in right paracentral lobule and precentral gyrus (PFWE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${P}_{FWE}$$\end{document} < 0.05) The t-values are color-coded. (B) The average signals of each cluster in patients with different mutations
Changes of ReHo in patients with CSF1R-related leukoencephalopathy. (A)The ReHo value of the patient group increased in right superior occipital gyrus, right precentral gyrus, left angular gyrus, as well as bilateral parahippocampal gyrus, hippocasSmpus, middle occipital gyrus, supramarginal gyrus and extra-nuclear, while decreased in bilateral supplementary motor area and paracentral lobule (PFWE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${P}_{FWE}$$\end{document} < 0.05). The t-values are color-coded. (B) The average signals of each cluster in patients with different mutations
Article
CSF1R-related leukoencephalopathy is an adult-onset white matter disease with high disability and mortality, while little is known about its pathogenesis. This study introduced amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) based on resting-state functional magnetic resonance imaging(rsfMRI) to compare the spontaneous brain activities of patients and healthy controls, aiming to enhance our understanding of the disease. RsfMRI was performed on 16 patients and 23 healthy controls, and preprocessed for calculation of ALFF and ReHo. Permutation tests with threshold free cluster enhancement (TFCE) was applied for comparison (number of permutations = 5,000). The TFCE significance threshold was set at PFWE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${P}_{FWE}$$\end{document} < 0.05. In addition, 10 was set as the minimum cluster size. Compared to healthy controls, the patient group showed decreased ALFF in right paracentral lobule, and increased ALFF in bilateral insula, hippocampus, thalamus, supramarginal and precentral gyrus, right inferior, middle and superior frontal gyrus, right superior and middle occipital gyrus, as well as left parahippocampal gyrus, fusiform, middle occipital gyrus and angular gyrus. ReHo was decreased in right supplementary motor area, paracentral lobule and precentral gyrus, while increased in right superior occipital gyrus and supramarginal gyrus, left parahippocampal gyrus, hippocampus, fusiform, middle occipital gyrus and angular gyrus, as well as bilateral middle occipital gyrus and midbrain. These results revealed altered spontaneous brain activities in CSF1R-related leukoencephalopathy, especially in limbic system and motor cortex, which may shed light on underlying mechanisms.
 
The distribution of the participants’ age.
The brain regions showed all the nodes within the SSN which were associated with the PSQI score. These regions (red hot colored area) included right paracentral lobule (PCL.R), the right precentral gyrus (PreCG.R), the right postcentral gyrus (PoCG.R), the right precuneus (PCUN.R), the right supplementary motor area (SMA.R), the left paracentral lobule (PCL.L), the left precentral gyrus (PreCG.L), left postcentral gyrus (PoCG.L), the left precuneus (PCUN.L) and the left inferior paracentral lobule (IPL.L).
The functional connectivity of the brain regions (PCL. L, PCL. R, SMA. R, PoCG. L, PoCG. R, PreCG. L, PreCG. R, PCUN. L, PCUN. R, IPL. L, color red) within SSN and its correlation with PSQI score.
The functional connectivity of the brain regions within SSN and its correlation with the sub-component of PSQI score. A: The correlations between the subjective sleep quality and the rsFC of regions (i.e., left PCL, left PoCG, right PCUN, left PreCG, right PCL, right PoCG, right SMA); B: The correlations between the sleep latency and the rsFC of regions (i.e., left PoCG, right PCUN); C: The correlations between the sleep disturbances and the rsFC of regions (i.e., left PCL, right PoCG, left PreCG); D: The correlations between the daytime dysfunction and the rsFC of regions (i.e., left PCL, left PoCG, right PoCG, left PreCG, right PreCG, right SMA, right PCL).
Article
Previous neuroimaging studies have demonstrated that sleep is associated with brain functional changes in some specific brain regions. However, few studies have examined the relationship between all possible functional connectivities (FCs) within the sensory/somatomotor network (SSN) and the sleep quality of young male samples. The SSN consists of two motor cortices and is known to play a critical role in sleep. Poor sleep quality may be associated with increased sensory/somatomotor functional connectivity during rest. Hence, 202 young male participants underwent a resting-state functional magnetic resonance imaging (fMRI) scan and completed the Pittsburgh Sleep Quality Index (PSQI). Results indicated that increased functional connectivity within the SSN was associated with poor sleep quality. Specifically, the total PSQI score was positively correlated with the increased functional connectivity of the left paracentral lobule (PCL), bilateral precentral gyrus (PreCG), supplementary motor area (SMA) and bilateral postcentral gyrus (PoCG). Additionally, our findings also exhibited that (a) the subjective sleep quality factor of PSQI was positively correlated with FC between the bilateral PoCG and the bilateral PCL as well as between the left PreCG and the right SMA; (b) the sleep latency factor of PSQI was positively correlated with FC between the left PoCG and the right precuneus (PCUN); (c) the sleep disturbances factor of PSQI was positively correlated with FC between the left PCL and the right PoCG, and (d) the daytime dysfunction factor of PSQI was positively correlated with FC between the bilateral PoCG and the left PCL as well as between the bilateral PreCG and the SMA. In short, our findings can be comprehensively understood as neural mechanisms of intrinsic SSN connectivity are associated with sleep quality of man. Meanwhile, it may expand our knowledge and provide new insight into a deeper understanding of the neurobiological mechanisms of sleep or sleep problems.
 
Structural white matter connectometry changes (3 months > Acute). Significant changes in connectometry showing increased structural white matter connectivity between (A) VMG and ABG (3 months > Acute) and (B) IMG and ABG (3 months > Acute). ABG = Audiobook group, IMG = Instrumental music group, L = left, QA = Quantitative anisotropy, R = right, VMG = Vocal music group
Comparison of significant connectometry findings. (A) Positively associated white matter tracts for VMG > ABG (red) and IMG > ABG (blue). (B) Positively associated white matter tracts for VMG only [(VMG > ABG) – (IMG > ABG)] (green) and IMG only [(IMG > ABG) – (VMG > ABG)] (yellow). ABG = Audiobook group, IMG = Instrumental music group, L = left, QA = Quantitative anisotropy, R = right, VMG = Vocal music group
Article
Post-stroke neuroplasticity and cognitive recovery can be enhanced by multimodal stimulation via environmental enrichment. In this vein, recent studies have shown that enriched sound environment (i.e., listening to music) during the subacute post-stroke stage improves cognitive outcomes compared to standard care. The beneficial effects of post-stroke music listening are further pronounced when listening to music containing singing, which enhances language recovery coupled with structural and functional connectivity changes within the language network. However, outside the language network, virtually nothing is known about the effects of enriched sound environment on the structural connectome of the recovering post-stroke brain. Here, we report secondary outcomes from a single-blind randomized controlled trial (NCT01749709) in patients with ischaemic or haemorrhagic stroke (N = 38) who were randomly assigned to listen to vocal music, instrumental music, or audiobooks during the first 3 post-stroke months. Utilizing the longitudinal diffusion-weighted MRI data of the trial, the present study aimed to determine whether the music listening interventions induce changes on structural white matter connectome compared to the control audiobook intervention. Both vocal and instrumental music groups increased quantitative anisotropy longitudinally in multiple left dorsal and ventral tracts as well as in the corpus callosum, and also in the right hemisphere compared to the audiobook group. Audiobook group did not show increased structural connectivity changes compared to both vocal and instrumental music groups. This study shows that listening to music, either vocal or instrumental promotes wide-spread structural connectivity changes in the post-stroke brain, providing a fertile ground for functional restoration.
 
Article
Subject-level independent component analysis (ICA) is a well-established and widely used approach in denoising of resting-state functional magnetic resonance imaging (fMRI) data. However, approaches such as ICA-FIX and ICA-AROMA require advanced setups and can be computationally intensive. Here, we aim to introduce a user-friendly, computationally lightweight toolbox for labeling independent signal and noise components, termed Alternative Labeling Tool (ALT). ALT uses two features that require manual tuning: proportion of an independent component’s spatial map located inside gray matter and positive skew of the power spectrum. ALT is tightly integrated with the commonly used FMRIB’s statistical library (FSL). Using the Open Access Series of Imaging Studies (OASIS-3) ageing dataset (n = 275), we found that ALT shows a high degree of inter-rater agreement with manual labeling (over 86% of true positives for both signal and noise components on average). In conclusion, ALT can be extended to small and large-scale datasets when the use of more complex tools such as ICA-FIX is not possible. ALT will thus allow for more widespread adoption of ICA-based denoising of resting-state fMRI data.
 
Flowchart representing study patients’ selection.
Tract-based spatial statistics analysis showing increased or decreased fractional anisotropy (FA) and mean diffusivity (MD) values in different white matter (WM) tracts of heart-kidney imbalance insomnia patients (HKIIPs). Green represents the mean FA or MD skeleton across all participants. Red yellow depicts the WM tracts whose FA or MD values were significantly changed (family-wise error correction, FWE, p < 0 .05 or cluster-correction, CC, p < 0.01 and cluster size > 50 voxels). (A) WM tracts with increased FA values in HKIIPs compared with health control (HC) (FWE, p < 0 .05); (B) WM tracts with decreased FA values in HKIIPs compared with HC (FWE, p < 0 .05); (C) WM tracts with decreased MD values in HKIIPs compared with HC (FWE, p < 0 .05); (D) WM tracts with decreased FA values in JTW group compared with placebo group (CC, p < 0.01 and cluster size > 50 voxels).
Article
Previous studies have reported changes in white matter microstructures in patients with insomnia. However, few neuroimaging studies have focused specifically on white matter tracts in insomnia patients after having received treatment. In this prospective study, diffusion-tensor imaging was used in two samples of heart-kidney imbalance insomnia patients who were treated with placebo or Jiao-Tai-Wan, a traditional Chinese medicine commonly used to treat heart-kidney imbalance insomnia, to assess the changes in white matter tracts. Tract-based spatial statistical analyses were first applied to compare the changes in mean diffusivity and fractional anisotropy of white matter between 75 heart-kidney imbalance insomnia patients and 41 healthy control participants. In subsequent randomized, double-blind, placebo-controlled trials, comparisons of mean diffusivity and fractional anisotropy were also performed in 24 heart-kidney imbalance insomnia patients (8 males; 16 females; 42.5 ± 10.4 years) with Jiao-Tai-Wan and 26 heart-kidney imbalance insomnia patients (11 males; 15 females; 39.7 ± 9.4 years) with a placebo, with age and sex as covariates. Fractional anisotropy values in left corticospinal tract were increased in heart-kidney imbalance insomnia patients. Heart-kidney imbalance insomnia patients showed lower mean diffusivity and fractional anisotropy values of several white matter tracts than healthy control participants, such as the bilateral anterior limb of internal capsule, bilateral superior longitudinal fasciculus and bilateral posterior corona radiata. After being treated with Jiao-Tai-Wan, heart-kidney imbalance insomnia patients showed a trend towards reduced fractional anisotropy values in the left corticospinal tract. Jiao-Tai-Wan may improve the sleep quality by reversing the structural changes of the left corticospinal tract caused by heart-kidney imbalance insomnia.
 
Thermal stimuli paradigms and offset analgesia evaluation. Thermal stimuli paradigms of offset analgesia were shown on the top panel. We evaluated the magnitude of offset analgesia (ΔOA) as the difference between the maximum VAS in T2 and the minimum VAS within the first 10 s of T3 in Offset: ΔOA = VASMaxT2 – VASMinT3 and ΔOA% as the ratio between ΔOA and VASMaxT2 (described in percentage): ΔOA% = (ΔOA / VASMaxT2) * 100%. In psychological interaction (PPI) analysis, we analyzed the OA-modulated functional connectivity differences within the first 15 s of T3 by contrasting Offset and Constant between groups (orange shadow in the bottom panel). The present figure was
adopted from our previous study of Zhang’s (Zhang et al., 2018). HC, healthy control subjects; CP, patients with chronic pain
OA-modulated functional connectivity differences between CP patients and HC subjects using PPI analysis. We found that OA-modulated functional connectivity (FC) attenuated in DMN, enhanced in SMN and EN, and disrupted in DPMS in CP patients compared to HC subjects (Fig. 2A). The representative seed-voxel FC modulated by OA was shown as an example for each network/system (Fig. 2B). Color bar indicated T value. OA, offset analgesia; CP, chronic pain; HC, healthy control; FC, functional connectivity; DMN, default mode network; SMN, sensorimotor network; EN, emotional network; DPMS, descending pain modulatory system; PCG, posterior cingulate gyrus; MPFC, medial prefrontal cortex; PreCG, precentral gyrus; LG, lingual gyrus; FG, fusiform gyrus; Ins, insular cortex; Cd, caudate nucleus; PostCG, postcentral gyrus; Pa, pallidum; Th, thalamus; R, right; L, left
Patients with CP showed a negative correlation between pain intensity (VAS) and OA-modulated functional connectivity between PCG and right MPFC. OA, offset analgesia; VAS, visual analog scale; PCG, posterior cingulate gyrus; MPFC, medial prefrontal cortex; R, right
Article
Patients with neuropathic pain and fibromyalgia showed reduced or absent offset analgesia (OA) response and attenuated cerebral activity in descending pain modulatory and reward systems in patients. However, neural network modifications of OA in chronic pain have not been determined. We enrolled 23 patients with various chronic pain and 17 age- and gender- matched healthy controls. All participants were given OA-related noxious thermal stimuli, including 3 repeats of offset analgesia paradigm at 46–47-46 °C and constant paradigm at 46 °C on the left volar forearm under whole-brain functional magnitude resonance imaging (fMRI). We evaluated magnitude of OA, examined OA modulated functional connectivity using psychophysiological interaction analysis and resting-state functional connectivity analysis and explored their behavioral correlations in patients compared with controls. Compared to controls, chronic pain patients showed smaller magnitude of OA (P = 0.047). OA modulated connectivity decreased between posterior cingulate cortex (PCC) and right medial prefrontal cortex (MPFC) in proportion to current chronic pain (P = 0.018); decreased between right pallidum and right thalamus, and increased between right caudate nucleus and left primary somatosensory cortex (PFDR < 0.05). The impaired PCC-MPFC connectivity might play an important role in dysfunction of OA and contribute to pain chronification.
 
Stroop Match-to-Sample fMRI Task Paradigm. Upper Panel: 4 trial types (1) congruent-match and (2) incongruent-match, where Stroop color-words are paired with prior color samples that match the ink color of the word (YES response), and (3) congruent-nonmatch and (4) incongruent-nonmatch, where Stroop color-words are paired with prior color samples that do not match the ink color of the word (NO response). Lower panel: fMRI blocked design combining trials in RS blocks requiring response switching between YES responses for match trials and NO responses for nonmatch trials and combining trials in RR blocks requiring the same YES (match trials only) and NO response (nonmatch trials only) repeatedly. Trials in RS and RR blocks were the same, only their order differed
Stroop Match-to-Sample Task Performance. Mean response times (RTs) in milliseconds (ms) to incongruent (inc) and congruent (con) Stroop color-word stimuli for response switching (RS) and response repetition (RR) blocks of trials and for each study group: healthy controls (CTL), people living with HIV (PLWH), and individuals with Parkinson’s disease (PD). Bar graphs denote fMRI task performance corrected for age and education. Note. A behavioral measure of cognitive control is the Stroop effect, denoted by longer RTs to incongruent than congruent color-words (RTinc > RTcon). A behavioral measure of motor control is the is the response switching effect, denoted by longer RTs for blocks of trials requiring response switches compared to blocks of trials requiring the same response repeatedly (RTRS > RTRR)
Cognitive Control Task Activation. Upper Panel: Stroop contrast (inc > con) independent of group. Lower Panel: Conjunction analysis showing frontoparietal activation overlap of all three groups; ANOVA showing differences in motor cortical activation among the three groups, follow-up paired comparisons depicting less motor cortical activation in PLWH compared to CTL (PLWH < CTL) and PD (PLWH < PD). Correlation graphs depicting the relationship between (A) age and sensorimotor activation in PLWH and CTL, (B) CD4⁺ T cell counts and left and right sensorimotor activation deficits in PLWH
Motor Control fMRI Task Activation. Upper Panel: Global activation contrast (RS > RR) independent of group. Lower Panel: Group activation differences among all three groups (ANOVA) and paired group contrasts depicting less striatal, PCC activation in PLWH than CTL (PLWH < CTL), less fronto-limbic activation in PD than CTL (PD < CTL), and more sensorimotor activation in PLWH than PD (PLWH > PD). Correlation graphs depicting the relationship between (A) age and striatal activation in PLWH with and without AIDS and (B) socioeconomic status (SES) and limbic (posterior cingulate cortical (PCC) and right hippocampal) activation deficits in PLWH with and without AIDS
HAND and parietal deficit in PLWH. Bar graph depicting the association between mild HAND/MNCI and PCC activation deficit during motor control in PLWH and PD groups. Covariates in the model were evaluated for SES = 28.56
Article
Expression of executive dysfunctions is marked by substantial heterogeneity in people living with HIV infection (PLWH) and attributed to neuropathological degradation of frontostriatal circuitry with age and disease. We compared the neurophysiology of executive function in older PLWH and Parkinson’s disease (PD), both affecting frontostriatal systems. Thirty-one older PLWH, 35 individuals with PD, and 28 older healthy controls underwent executive task-activated fMRI, neuropsychological testing, and a clinical motor exam. fMRI task conditions distinguished cognitive control operations, invoking a lateral frontoparietal network, and motor control operations, activating a cerebellar-precentral-medial prefrontal network. HIV-specific findings denoted a prominent sensorimotor hypoactivation during cognitive control and striatal hypoactivation during motor control related to CD4⁺ T cell count and HIV disease duration. Activation deficits overlapped for PLWH and PD, relative to controls, in dorsolateral frontal, medial frontal, and middle cingulate cortices for cognitive control, and in limbic, frontal, parietal, and cerebellar regions for motor control. Thus, despite well-controlled HIV infection, frontostriatal and sensorimotor activation deficits occurred during executive control in older PLWH. Overlapping activation deficits in posterior cingulate and hippocampal regions point toward similarities in mesocorticolimbic system aberrations among older PLWH and PD. The extent of pathophysiology in PLWH was associated with variations in immune system health, neural signature consistent with subclinical parkinsonism, and mild neurocognitive impairment. The failure to adequately engage these pathways could be an early sign for cognitive and motor functional decline in the aging population of PLWH.
 
Article
An association has been shown between chronic cigarette smoking and structural abnormalities in the brain areas related to several functions relevant to addictive behavior. However, few studies have focused on the structural alternations of chronic smoking by using magnetic resonance imaging (MRI). Also, it remains unclear how structural alternations are associated with tobacco-dependence severity and the positive/negative outcome expectances. The q-sampling imaging (GQI) is an advanced diffusion MRI technique that can reconstruct more precise and consistent images of complex oriented fibers than other methods. We aimed to use GQI to evaluate the impact of the neurological structure caused by chronic smoking. Sixty-seven chronic smokers and 43 nonsmokers underwent a MRI scan. The tobacco dependence severity and the positive/negative outcome expectancies were assessed via self-report. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among groups. Chronic smokers had smaller GM and WM volumes in the bilateral frontal lobe and bilateral frontal region. The GM/WM volumes correlated with dependence severity and outcome expectancies in the brain areas involving high-level functions. Chronic smokers had shape changes in the left hippocampal head and tail and the inferior brain stem. Poorer WM integrity in chronic smokers was found in the left middle frontal region, the right superior fronto-occipital fasciculus, the right temporal region, the left parahippocampus, the left anterior internal capsule, and the right inferior parietal region. WM integrity correlated with dependence severity and outcome expectancies in brain areas involving high-level functions. Chronic smokers had decreased local segregation and global integration among the brain regions and networks. Our results provide further evidence indicating that chronic smoking may be associated with brain structure and connectivity changes.
 
Diagram of convolutional neural network (CNN) based diagnosis. Figure 1 plotted the preprocessing, the structure of the CNN and the procedure of the greedy algorithm. The number indicated that (1). The architecture of CNN. The kernel size was 2 × 2 × 2. The convolution kernels ranged from 64 to 512; (2). The area under curve (AUC) for each region as calculated by receiver operating curve (ROC) analysis, with Yn from the corresponded CNN. (3). The first m regions in the initial combination, sorted by AUC in descending order. (4) The processing of dropout and add-in test; The j represented the region contained in the first m regions, j∈{1,2,…,m}. The k represented the regions not contained in the selected combination, which k∈{1,2,…,N-m}, (5). The final combination with the highest AUC
The averaged area under curve (AUC) with ten-fold cross-validation from the combination of multiple regions by the initial regions with the highest AUC or from random selection. The figure plotted the averaged AUC (in percentage) in the receiver operative curve analysis of fractional anisotropy (FA) and mean diffusivity (MD) in the combination by the greedy algorithm (panel A). Panel B plotted the averaged AUC by using both indices. solid: initial regions from the highest sorted AUC; dashed: initial regions from random selection. The standard deviation was calculated from the ten-fold cross-validation
The averaged area under curve (AUC) in the involved regions composed of the final combination in fractional anisotropy (FA) and mean diffusivity (MD). The figure plotted the AUC (in percentage) in the receiver operative curve analysis of the involved regions in final combination using (A) FA and (B) MD. The averaged AUC with standard deviation was calculated from the ten-fold cross-validation. * indicated the regions that involved in the combinations with reduced number of regions in FA and MD. # indicated the regions that involved in the combinations with reduced number of regions when using both indices
The visualization of involved regions in the final combination with the highest AUC value in fractional anisotropy (FA), mean diffusivity (MD), and both indices. The figure is a visualization of the parcellated brain regions as in the combination by using (A) FA, Upper Panel: the final combination (22 regions). Lower Panel: fewer regions of combinations (9 regions), (B) MD, Upper Panel: the final combination (41 regions). Lower Panel: fewer regions of combinations (12 regions), and (C) both indices, Upper Panel: the final combination (27 regions). Lower Panel: few region of combination (12 regions)
Article
The diagnostic performance of a combined architecture on Parkinson’s disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine the models from individual regions into a complex one. Total 305 Parkinson’s disease patients (aged 59.9±9.7 years old) and 227 healthy control subjects (aged 61.0±7.4 years old) were enrolled from 3 retrospective studies. The participants were divided into training with ten-fold cross-validation (N = 432) and an independent blind dataset (N = 100). Diffusion-weighted images were acquired from a 3T scanner. Fractional anisotropy and mean diffusivity were calculated and was subsequently parcellated into 90 cerebral regions of interest based on the Automatic Anatomic Labeling template. A convolutional neural network was implemented which contained three convolutional blocks and a fully connected layer. Each convolutional block consisted of a convolutional layer, activation layer, and pooling layer. This model was trained for each individual region. A greedy algorithm was implemented to combine multiple regions as the final prediction. The greedy algorithm predicted the area under curve of 94.1±3.2% from the combination of fractional anisotropy from 22 regions. The model performance analysis showed that the combination of 9 regions is equivalent. The best area under curve was 74.7±5.4% from the right postcentral gyrus. The current study proposed an architecture of convolutional neural network and a greedy algorithm to combine from multiple regions. With diffusion tensor imaging, the algorithm showed the potential to distinguish patients with Parkinson’s disease from normal control with satisfactory performance.
 
Trajectories of General Cognitive Performance (GCP) in the SAGES study participants stratified by participation in MRI and occurrence of postoperative delirium. Following our original goal of investigating neuroimaging predictors of cognitive decline associated with postoperative delirium (with delirium = blue; without delirium = green), we planned to assess the relationship between changes in neuroimaging measures over one year (with surgery in between) and subsequent long-term cognitive decline (LTCD). In the top panel the model-implied GCP scores (and 95% confidence regions) for the four groups defined by MRI participation (MRI = 1 had MRI; MRI = 0 did not have MRI) and delirium occurrence (DEL = 1 had delirium; DEL = 0, no delirium) during hospitalization are shown. In the bottom panel, the GCP score was centered at one year after surgery to highlight GCP changes from month 12 to 48. Here, the effect of delirium on LTCD is smaller in the MRI subsample (MRI = 1 DEL = 1, light blue line) compared to the participants who did not undergo MRI (MRI = 0 DEL = 1, dark blur line). Non-delirious participants within the MRI subsample (MRI = 1 DEL = 0, light green line) showed faster cognitive decline compared to non-delirious participants (MRI = 0 DEL = 0, dark green line) who did not undergo MRI; and delirious participants who underwent MRI showed slower cognitive decline compared to delirious participants with no MRI
Article
Due to cost and participant burden, neuroimaging studies are often performed in relatively small samples of voluntary participants. This may lead to selection bias. It is important to identify factors associated with participation in neuroimaging studies and understand their effect on outcome measures. We investigated the effect of postoperative delirium on long-term (over 48 months) cognitive decline (LTCD) in 560 older surgical patients (≥ 70 years), including a nested MRI cohort (n = 146). We observed a discrepancy in the effect of delirium on cognitive decline as a function of MRI participation. Although overall difference in cognitive decline due to delirium was not greater than what might be expected due to chance (p = .21), in the non-MRI group delirium was associated with a faster pace of LTCD (-0.063, 95% CI -0.094 to -0.032, p < .001); while in the MRI group the effect of delirium was less and not significant (-0.023, 95% CI -0.076, 0.030, p = .39). Since this limits our ability to investigate the neural correlates of delirium and cognitive decline using MRI data, we attempted to mitigate the observed discrepancy using inverse probability weighting for MRI participation. The approach was not successful and the difference of the effect of delirium in slope was essentially unchanged. There was no evidence that the MRI sub-group experienced delirium that differed in severity relative to MRI non-participants. We could not attribute the observed discrepancy to selection bias based on measured factors. It may reflect a power issue due to the smaller MRI subsample or selection bias from unmeasured factors.
 
Two-sample t-test for GM volumes. (A and B) Compared with HC subjects, patients with FCon exhibited decreased GM volumes in the INS_L, ACC, and MFG_R (cluster size-corrected, PFWE < 0.05). Age and gender were regressed out as covariates. (C) Behavioral measurements were significant negatively correlated with GM volumes. (D) Correlations between behavioral measurements
Alterations in SC between HC and FCon groups. FCon group showed significant decreased FA of the left INS-left MFG (A), right INS-right MFG (B), and ACC-right MFG (C, Bonferroni correction, P < 0.0005). Age and gender were regressed out as covariates
Article
Functional constipation (FCon) is one of the common functional gastrointestinal disorders (FGID). Previous studies reported alterations in cortical morphometry as well as changes in white matter (WM) fiber tracts and thalamo-limbic/parietal structural connectivity (SC). However, whether patients with FCon are implicated in changes in gray matter (GM) volume and associated SC remains unclear. Voxel-based morphometry (VBM) was first employed to examine differences in GM volume between 48 patients with FCon and 52 healthy controls (HC). Diffusion tensor imaging (DTI) with probabilistic tractography analysis was then employed to explore alterations in SC of these regions. Results showed abdominal symptoms were positively correlated with anxiety (SAS). Two sample t-test showed patients with FCon had decreased GM volumes in the right middle frontal gyrus (MFG_R), left insula (INS_L), and anterior cingulate cortex (ACC, PFWE < 0.05) which were negatively correlated with abdominal symptoms and difficulty of defecation respectively. Seed-based SC analysis showed patients with FCon had decreased fractional anisotropy of the ACC-right MFG and bilateral INS-MFG tracts. These findings reflect FCon is associated with changes in GM volumes and corresponding SC in brain regions within the salience network.
 
Flowchart depicting patient selection and inclusion/exclusion criteria for the study
Scatter diagram with linear regression line for frontal assessment battery score on normalised deep white matter hyperintensities volume
Article
Life expectancy in adults with congenital heart disease (ACHD) has increased. As these patients grow older, they experience aging-related diseases more than their healthy peers. To better characterize this field, we launched the multi-disciplinary BACH (Brain Aging in Congenital Heart disease) San Donato study, that aimed at investigating signs of brain injury in ACHD. Twenty-three adults with repaired tetralogy of Fallot and 23 age- and sex-matched healthy controls were prospectively recruited and underwent brain magnetic resonance imaging. White matter hyperintensities (WMHs) were segmented using a machine-learning approach and automatically split into periventricular and deep. Cerebral microbleeds were manually counted. A subset of 14 patients were also assessed with an extensive neuropsychological battery. Age was 41.78 ± 10.33 years (mean ± standard deviation) for patients and 41.48 ± 10.28 years for controls ( p = 0.921). Albeit not significantly, total brain ( p = 0.282) and brain tissue volumes ( p = 0.539 for cerebrospinal fluid, p = 0.661 for grey matter, p = 0.793 for white matter) were lower in ACHD, while total volume ( p = 0.283) and sub-classes of WMHs ( p = 0.386 for periventricular WMHs and p = 0.138 for deep WMHs) were higher in ACHD than in controls. Deep WMHs were associated with poorer performance at the frontal assessment battery (r = -0.650, p = 0.012). Also, patients had a much larger number of microbleeds than controls (median and interquartile range 5 [3–11] and 0 [0–0] respectively; p < 0.001). In this study, adults with tetralogy of Fallot showed specific signs of brain injury, with some clinical implications. Eventually, accurate characterization of brain health using neuroimaging and neuropsychological data would aid in the identification of ACHD patients at risk of cognitive deterioration.
 
A Statistic maps showing ANOVA differences in the amplitude of low-frequency fluctuations (ALFF) values among OCD patients with high consummatory anhedonia (OCD-HCA), OCD patients with low consummatory anhedonia (OCD-LCA) and healthy control group (HC). B Brain regions showing ALFF differences between OCD-HCA and HC. D Brain regions showing ALFF differences between OCD-LCA and HC. D Brain regions showing ALFF differences between OCD-HCA and OCD-LCA. The post-hoc t-tests results are expressed within a mask showing significant group differences from the ANOVA. Warm and cool colors, respectively, indicate ALFF increases and decreases, The color bar in panel A signifies the F-value of the ANOVA analysis, uncorrected p < 0.001, and color bar in other panels indicates the t values of the post-hoc t-tests, FWE corrected p < 0.05
A Scatter plots showing significant negative correlations between regional ALFF values in right fusiform gygrus and TEPS-CON scores B Scatter plots showing significant positive correlations between regional ALFF values in the right putamen and TEPS-CON socres. The significance threshold was defined as p < 0.05 with Bonferroni correction
Article
Background Accumulating evidence indicated that anhedonia as a transdiagnostic construct might be an inherent feature of obsessive–compulsive disorder(OCD). Moreover, our recent study demonstrated that OCD patients exhibited consummatory anhedonia but not anticipatory anhedonia. However, neural mechanisms of consummatory anhedonia in OCD has not been explored. This study aimed to investigate this issue using resting-state functional magnetic resonance imaging (fMRI). Methods 44 OCD patients with high consummatory anhedonia(OCD-HCA), 41 OCD patients with low consummatory anhedonia(OCD-LCA) and 47 healthy controls (HC) underwent fMRI scan. Spontaneous neural activity was analyzed and compared among the three groups by adopting the amplitude of low-frequency fluctuation (ALFF). Relationships between the consummatory anhedonia levels and regional ALFFs were examined in OCD patients. Results Compared with HC, OCD-HCA showed decreased ALFF in the right putamen and right thalamus, and OCD-LCA showed increased ALFF in the right orbitofrontal cortex and decreased ALFF in the right fusiform gyrus, left Precentral/postcentral gyrus. Notably, ALFF values differed between the two patient groups in the right putamen (OCD-HCA < OCD-LCA), and right fusiform gyrus (OCD-HCA > OCD-LCA). Further analysis revealed that the consummatory anhedonia was positively correlated with ALFF values in the right fusiform, and negatively correlated with ALFFs in the right putamen. Conclusions Spontaneous neural activity in right fusiform gyrus and right putamen is associated with consummatory anhedonia in OCD. The findings provided first insights into neural mechanism of consummatory anhedonia in OCD and confirmed the importance of exploring the transdiagnostic role of anhedonia.
 
Dissimilarity matrices for the visual pixel information, orthographic model, and phonological model (the four numbers in the coordinate axis represent 4 Mandarin lexical tones, 1 for high-level, 2 for low-rising, 3 for low-dipping and 4 for high-falling)
Group-level univariate activations of word reading. The four panels show activations for neural responses in the perceptual task (A), naming task (B), stronger activations in the perceptual task (C) and stronger activations in the naming task (D)
Box plots of information representation in the naming and perceptual tasks in the 6 ROIs (horizontal line, median; box, interquartile range; whiskers, minimum and maximum). Spearman correlations between neural dissimilarity and visual (left panel), orthographic (middle panel), and phonological (right panel) dissimilarity matrices. laFG, left anterior fusiform gyrus; lmFG, left middle fusiform gyrus; lpFG, left posterior fusiform gyrus; raFG, right anterior fusiform gyrus; rmFG, right middle fusiform gyrus; rpFG, right posterior fusiform gyrus. The asterisks indicate significant correlations in the non-parametric permutation tests. *p < .05; **p < .01; ***p < .001
Brain masks of the VWFA for one representative participant. Box plots of group-level correlations between neural pattern dissimilarity and information dissimilarity matrix in the perceptual and naming tasks (horizontal line, median; box, interquartile range; whiskers, minimum and maximum). The asterisks indicate significant correlations in the non-parametric permutation tests. *p < .05; **p < .01; ***p < .001
Article
As a key area in word reading, the left ventral occipitotemporal cortex is proposed for abstract orthographic processing, and its middle part has even been labeled as the visual word form area. Because the definition of the VWFA largely varies and the reading task differs across studies, the function of the left ventral occipitotemporal cortex in word reading is continuingly debated on whether this region is specific for orthographic processing or be involved in an interactive framework. By using representational similarity analysis (RSA), this study examined information representation in the VWFA at the individual level and the modulatory effect of reading task. Twenty-four subjects were scanned while performing the explicit (i.e., the naming task) and implicit (i.e., the perceptual task) reading tasks. Activation analysis showed that the naming task elicited greater activation in regions related to phonological processing (e.g., the bilateral prefrontal cortex and temporoparietal cortex), while the perceptual task recruited greater activation in visual cortex and default mode network (e.g., the bilateral middle frontal gyrus, angular gyrus, and the right middle temporal gyrus). More importantly, RSA also showed that task modulated information representation in the bilateral anterior occipitotemporal cortex and VWFA. Specifically, ROI-based RSA revealed enhanced orthographic and phonological representations in the bilateral anterior fusiform cortex and VWFA in the naming task relative to the perceptual task. These results suggest that lexical representation in the VWFA is influenced by the demand of phonological processing, which supports the interactive account of the VWFA.
 
The spatial pattern of BOLD activation produced by intravenous administration of 1 µg/kg fentanyl. Colored voxels in the maps passed a statistical clustering threshold of p < 0.05. Post < pre is shown in blue. There were no increases in BOLD signal (post > pre)
Changes in functional connectivity following fentanyl administration from the bilateral ACC (top right panels), NAc (middle right panels) and thalamus seed regions (bottom right panels). The 2 mm seed placements for each region are shown in the left panels. Post > pre is shown in red/yellow while post < pre is shown in blue. Additional details are shown in Table 1
Spatial maps representing overlapping changes in functional connectivity to whole brain from seeds placed in all three seed regions (ACC, NAc and thalamus) to show regional similarities in patterns of altered functional connectivity
Article
Functional magnetic resonance imaging (fMRI) has been used to study the influence of opioids on neural circuitry implicated in opioid use disorder, such as the cortico-striatal-thalamo-cortical (CSTC) circuit. Given the increase in fentanyl-related deaths, this study was conducted to characterize the effects of fentanyl on patterns of brain activation in awake nonhuman primates. Four squirrel monkeys were acclimated to awake scanning procedures conducted at 9.4 Tesla. Subsequently, test sessions were conducted in which a dose of fentanyl that reliably maintains intravenous (IV) self-administration behavior in monkeys, 1 μg/kg, was administered and the effects on patterns of brain activity were assessed using: (1) a pharmacological regressor to elucidate fentanyl-induced patterns of neural activity, and (2) seed-based approaches targeting bilateral anterior cingulate, thalamus, or nucleus accumbens (NAc) to determine alterations in CSTC functional connectivity. Results showed a functional inhibition of BOLD signal in brain regions that mediate behavioral effects of opioid agonists, such as cingulate cortex, striatum and midbrain. Functional connectivity between each of the seed regions and areas involved in motoric, sensory and cognition-related behavior generally decreased. In contrast, NAc functional connectivity with other striatal regions increased. These results indicate that fentanyl produces changes within CSTC circuitry that may reflect key features of opioid use disorder (e.g. persistent drug-taking/seeking) and thereby contribute to long-term disruptions in behavior and addiction. They also indicate that fMRI in alert nonhuman primates can detect drug-induced changes in neural circuits and, in turn, may be useful for investigating the effectiveness of medications to reverse drug-induced dysregulation.
 
Article
Obstructive sleep apnea (apnea) is thought to cause small vessel ischemic episodes in the brain from hypoxic events, postulated as white matter hyperintensities (hyperintensities) identified on MRI which are implicated in cognitive decline. This study sought to evaluate these correlations. A retrospective evaluation of adults who underwent polysomnography (4/1/2016 to 4/30/2017) and a brain MRI prior to apnea diagnosis or within a year post-diagnosis was completed. MRI visual evaluation of hyperintensities using Fazekas scores were collected blind to clinical data. Collated clinical/MRI data were stratified and analyzed using chi-square, fishers t-tests, ANOVA/ANCOVA and linear regression. Stratification by apnea category revealed no significant differences in any variables including hyperintensity measures (Fazekas p=0.1584; periventricular p=0.3238; deep p=0.4618; deep total p=0.1770). Stratification by Fazekas category, periventricular and deep hyperintensities revealed increasing prevalence with age (p=0.0001); however, apnea categories were not significantly associated (Fazekas p=0.1479; periventricular p=0.3188; deep p=0.4503), nor were any individual apnea indicators. Continuous apnea measurements werre not associated with any hyperintensity factor; total deep hyperintensities were not associated with any apnea factors. Continuous BMI was not found to be associated with any apnea or hyperintensity factors. Only hypertension was noted to be associated with Fazekas (p=0.0045), deep (p=0.0010) and total deep (p=0.0021) hyperintensities; however, hypertension was not associated with apnea category (p=0.3038) or any associated factors. These data suggest apneas alone from OSA are insufficient to cause WMH, but other factors appear to contribute to the complex development of small vessel ischemic injury associated with age and cognitive decline.
 
The flowchart of the framework. (A) FER-related brain activation. (B) Gene expression data processes. (C) Identification of the FER-related genes. (D) Gene set enrichment analysis of the FER-related genes. (E) Tissue-specific expression analysis and cell type enrichment analysis. (F) Protein-protein interaction network. (G) Enrichment analysis for psychiatric diseases
The group-level activation maps of group one in the facial expression recognition task. The color bar represents t-values of brain activation
GO enrichment for the FER-related genes. The size of each bubble represents the number of FER-related genes enriched in the GO terms. The x-axis represents -log10P (Bonferroni corrected). The y-axis represents gene ontology terms. GO, gene ontology
Cell type-specific expression analysis and tissue-specific expression analysis of FER-related genes. (A) Cell type-specific expression analysis. The size of the bullseyes represented pSI values (i.e., pSI = 0.05, 0.01, 0.001, and 0.0001). The color represented the P values (BH-FDR correction). (B) Tissue-specific expression analysis of FER-related genes. The colors represent the pSI = 0.05, 0.01, 0.001, and 0.0001. The y-axis represents -log10P (BH-FDR corrected)
Protein-protein networks and enrichment of FER-related genes for common psychiatric disorders. (A-B) Protein-protein networks constructed using the 371 FER-related genes. Each node represents a protein, and each edge represents an interaction between two proteins. (A) The whole PPI network constructed using 365 FER-related genes. (B) The representative hub genes: CTNNB1, CDH2, KRT19, EPCAM, and CDH3. (C) Enrichment of FER-related genes for common psychiatric disorders. The size of each bubble represents the number of FER-related genes overlapped with genes associated with common psychiatric disorders. The x-axis represents -log10 (P, Bonferroni corrected). The y-axis represents odds ratio values. The red line represents P = 0.05
Article
Previous studies identified some genetic loci of emotion, but few focused on human emotion-related gene expression. In this study, the facial expression recognition (FER) task-based high-resolution fMRI data of 203 subjects in the Human Connectome Project (HCP) and expression data of the six healthy human postmortem brain tissues in the Allen Human Brain Atlas (AHBA) were used to conduct a transcriptome-neuroimaging spatial association analysis. Finally, 371 genes were identified to be significantly associated with FER-related brain activations. Enrichment analyses revealed that FER-related genes were mainly expressed in the brain, especially neurons, and might be related to cell junction organization, synaptic functions, and nervous system development regulation, indicating that FER was a complex polygenetic biological process involving multiple pathways. Moreover, these genes exhibited higher enrichment for psychiatric diseases with heavy emotion impairments. This study provided new insight into understanding the FER-related biological mechanisms and might be helpful to explore treatment methods for emotion-related psychiatric disorders.
 
Image analysis process: 1) Merge seven serial images into time-sequence images 2) Motion correction and co-register to patient’s T1-weighted MRI images 3) Generate slope map (clearance rate from each image pixel) by pixelwise linear regression analysis 4) Create grey matter (GM) image using the patient’s T1-weighted MRI to further mask the slope map 5) Draw regions of interest (ROIs) of suspected seizure onset zone by iso-contour (3D iso-contouring VOI tools using region-growing) inside the automated anatomical labeling (AAL) template atlas
The slope map pattern color bar and example: Example of slow washout pattern (crosshair cursor at the SOZ shows pale red color as compare with the pale blue color of the contralateral normal region (top). The slope map pattern displays in split BWR (blue-white-red) color bar (bottom). Background color represents clearance rate = 0.0
Examples of slope maps in patients: Ictal slope map showed WASHIN (red) at left hippocampal sclerosis (a, b crosshair cursor in patient number 2). Aura and interictal slope maps showed FAST WASHOUT (blue) at right hippocampal sclerosis (c, d crosshair cursor in patient number 3) and left fusiform lesion (e, f crosshair cursor in patient number 7), respectively. Background color represents clearance rate = 0.0
Comparison of ECD clearance rates (%/hr) of seizure onset zones (SOZs) and the contralateral regions in three seizure states and normal: Paired t-tests between clearance rate of the SOZ and contralateral regions showed statistically significant difference in interictal state (p = 0.039), but no statistically significant difference were seen in ictal state, aura state and normal
Article
In this prospective study, we postulate that there is a difference between clearance of [99mTc]Tc- ethyl cysteinate dimer (ECD) in the seizure onset zone (SOZ) and other brain areas and thus SOZ localization by clearance patterns might become a potential novel method for SOZ localization in epilepsy. The parametric images of brain ECD clearance were generated by linear regression model analysis from serial brain SPECT scans from 30 to 240 min after ECD injection (7-times point) in 7 patients with drug-resistant epilepsy and 3 normal volunteers. Clearance patterns of the SOZ confirmed by good surgical outcome or consensus with other investigations were analyzed quantitatively and semi-quantitatively by visual grading (slower or faster washout than contralateral brain regions). The average [99mTc]Tc-ECD clearance rates of SOZs were + 1.08% ± 2.57%/hr (wash in), -7.02% ± 2.56%/hr (washout), and -5.37% ± 1.71%/hr (washout) in ictal, aura and interictal states, respectively. Paired t-tests between the SOZ and contralateral regions showed statistically significant difference (p = 0.039 in interictal state). Clearance patterns that can define the SOZs were 1) wash in and slow washout on ictal slope, 2) fast washout on aura slope and interictal slope with 100% (6/6), 100% (2/2) and 75% (6/8) localization using ictal, aura, and interictal slope maps, respectively. Our study provided the evidence that clearance pattern methods are potential additive diagnostic tools for SOZ localization when routine one-time point SPECT are unable to define the SOZ.
 
Decreased grey matter volume (GMV) in the drug-naïve first-episode early-onset schizophrenia (EOS) compared with healthy controls (HCs). Regions (colors of blue and green) showed significantly reduced GMV in the bilateral cerebellum anterior–posterior lobes, temporal, orbitofrontal, occipital, parietal, limbic lobes, sensorimotor areas, cingulate cortex and the precuneus in EOS compared with HCs (FDR corrected, p < 0.05; minimum cluster size of 50 voxels)
The regions of altered functional connectivity density (FCD) in early-onset schizophrenia (EOS) compared with healthy controls (HCs). EOS showed increased FCD in the bilateral cerebellum vermis (warm color) and decreased FCD in the bilateral precuneus compared to HCs (winter color) (FDR corrected, p < 0.05; minimum cluster size of 100 voxels)
Concurrent changes of GMV and FCD and their association in the left orbitofrontal cortex (OFC). The left OFC (MNI: -26, 32, -14) showed significantly decreased GMV while increased FCD in EOS compared with controls: Left panel, the left lateral orbitofrontal cortex (lOFC) showed significantly decreased GMV in patient. Middle panel, significantly increased FCD in the left lOFC was identified with age, gender and GMV as covariances. Right panel, there is no significant correlation between increased FCD and decreased GMV in left lOFC. *** p<0.001
Article
Schizophrenia which is an abnormally developmental disease has been widely reported to show abnormal brain structure and function. Enhanced functional integration is a predominant neural marker for brain mature. Abnormal development of structure and functional integration may be a biomarker for early diagnosis of schizophrenia. Fifty-five patients with early onset schizophrenia (EOS) and 79 healthy controls were enrolled in this study. Voxel-based morphometry (VBM) and functional connectivity density (FCD) were performed to explore gray matter volume (GMV) lesion, abnormal functional integration, and concurrent structural and functional abnormalities in the brain. Furthermore, the relationships between abnormalities structural and function and clinical characteristics were evaluated in EOS. Compared with healthy controls, EOS showed significantly decreased GMV in the bilateral OFC, frontal, temporal, occipital, parietal and limbic system. EOS also showed decreased FCD in precuneus and increased FCD in cerebellum. Moreover, we found concurrent changes of structure and function in left lateral orbitofrontal cortex (lOFC). Finally, correlation analyses did not find significant correlation between abnormal neural measurements and clinical characteristic in EOS. The results reveal disassociated and bound structural and functional abnormalities patterns in EOS suggesting structural and functional measurements play different roles in delineating the abnormal patterns of EOS. The concurrent structural and functional changes in lOFC may be a biomarker for early diagnosis of schizophrenia. Our findings will deepen our understanding of the pathophysiological mechanisms in EOS.
 
Clusters showing group difference in the ReHo. The crosses showed the peaks. The color bar showed the intensity. Warm colors showed MA > healthy control while the cold colors showed MA < healthy control
Article
Previous studies have reported evidence supporting structural and functional alterations in the brains of methamphetamine (MA) users. The aim of the present study was to extend current knowledge regarding brain function(s) in MA users by examining regional homogeneity (ReHo). Chronic MA users (51 male, 46 female), who were undergoing supervised abstinence for 12 to 621 days, and 79 healthy controls (43 male, 36 female) underwent resting-state functional brain magnetic resonance imaging. Voxel-wise whole-brain scale group differences in ReHo were examined. The mean ReHo values of significant clusters were extracted, and linear regression was used to identify factors that contributed to these mean ReHo values. MA users exhibited lower ReHo values in the left orbital part of the inferior frontal gyrus extending to the left insula and left temporal pole, left amygdala, and left fusiform gyrus. MA users also exhibited greater ReHo values in the bilateral pre- and postcentral gyri and right cerebellum. Characteristics of MA use, including duration, duration of abstinence from MA, and age at onset of MA use, demonstrated no reliable contribution to ReHo of the significant clusters. Findings of the present study demonstrated that chronic MA use was associated with regional specific disruption of ReHo, which is relatively independent of structural and functional alterations and, apparently, does not recover after relatively long-term abstinence. This disruption may underlie overall neurocognitive deficits in MA users, which is difficult to recover.
 
The FC patterns of the lateral amygdala, medial amygdala in the BD patients and HCs (p < 0.05, uncorrected). The color bar represents functional connection. The T value indicated the intensity of the significant difference which was obtained by one-sample t-test. FC, functional connectivity; BD, bipolar disorder; HCs, healthy controls
The significant FC differences between the two groups for amygdala seed, respectively (voxel p < 0.001, cluster p < 0.05, GRF corrected). FC, functional connectivity; GRF, Gaussian random field; L (R), left (right) hemisphere
The correlation between abnormal FC values (A: R medial amygdala-bilateral MFC, r = -0.320, p = 0.022; B: L medial amygdala-L TP, r = -0.320, p = 0.021) and TNF-α (p < 0.05). FC, functional connectivity; L (R), left (right) hemisphere; TP, temporal pole; MFC, medial frontal cortex; TNF, tumor necrosis factor
Article
The pathophysiological mechanisms of bipolar disorder (BD) are not completely known, and systemic inflammation and immune dysregulation are considered as risk factors. Previous neuroimaging studies have proved metabolic, structural and functional abnormalities of the amygdala in BD, suggesting the vital role of amygdala in BD patients. This study aimed to test the underlying neural mechanism of inflammation-induced functional connectivity (FC) in the amygdala subregions of BD patients. Resting-state functional MRI (rs-fMRI) was used to delineate the amygdala FC from two pairs of amygdala seed regions (the bilateral lateral and medial amygdala) in 51 unmedicated BD patients and 69 healthy controls (HCs). The levels of pro-inflammatory cytokines including interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α were measured in the serum. The correlation between abnormal levels of pro-inflammatory cytokines and FC values were calculated in BD patients. The BD group exhibited decreased FC between the right medial amygdala and bilateral medial frontal cortex (MFC), and decreased FC between the left medial amygdala and the left temporal pole (TP), right orbital inferior frontal gyrus compared with HCs. The BD patients had higher levels of TNF-α than HCs. Correlation analysis showed negative correlation between the TNF-α level and abnormal FC of the right medial amygdala-bilateral MFC; and negative correlation between TNF-α levels and abnormal FC of the left medial amygdala-left TP in BD group. These findings suggest that dysfunctional and immune dysregulation between the amygdala and the frontotemporal circuitry might play a critical role in the pathogenesis of BD.
 
Diffusion profiles of the CC tracts with significant differences among all subjects (a) and girls (b) are illustrated. In each figure with a frame, the x-axis represents the tract location (from node 1 to 100), and the y-axis represents the diffusion measures. Solid lines represent the mean, and dotted lines denote the standard error of the mean. (red, ADHD children; blue, TDC). Nodes that show significant differences are marked with red shading. (p < 0.05, FWE corrected). (c) Sex-by-diagnosis interactions in the CC tracts: girls with ADHD showed significant differences of diffusion parameters in the occipital, posterior parietal and superior parietal tracts, while boys with ADHD showed decreased volume in the anterior frontal tract. **shows indicates group differences; p < 0.005 (Bonferroni corrected)
Association of behavior/attention and control performance with diffusion measures in the occipital (a), posterior parietal (b) and superior parietal (c) tracts among children with ADHD and TDC
Article
Widespread alterations in the corpus callosum (CC) microstructure and organization have been found in children with attention-deficit/hyperactivity disorder (ADHD); however, few studies have investigated the diffusion characteristics and volume of transcallosal fiber tracts defined by specific cortical projections in ADHD, which is important for identifying distinct functional interhemispheric connection abnormalities. In the current study, an automated fiber-tract quantification (AFQ) approach based on diffusion tensor imaging identified seven CC tracts according to their cortical projections and estimated diffusion parameters and volume among 76 drug-naïve ADHD patients (53 boys and 23 girls) and 37 typically developing children (TDC) (20 boys and 17 girls) matched for age, IQ, and handedness. We found significantly lower fractional anisotropy (FA) in the occipital and superior parietal tracts and higher mean diffusivity (MD) in the posterior, superior parietal and anterior frontal tracts in children with ADHD compared with TDC. In addition, lower FA and higher radial diffusivity (RD) in the occipital callosal tract were significantly associated with higher hyperactivity and impulsivity performance in ADHD. In addition, sex-by-diagnosis interactions were observed in the occipital, posterior and superior parietal tracts. Girls with ADHD showed decreased FA and volume in the occipital tract, which were significantly associated with increased impulsivity performance and poor response control, and increased MD in the posterior and superior parietal callosal tracts, which were significantly associated with increased inattention performance, whereas boys with ADHD merely showed decreased volume in the frontal tract. Our results elucidated that sex-specific alterations in the CC tracts potentially underlie ADHD symptomatology and further suggested a differential contribution of abnormalities in different CC tracts to impulsivity and inattention among girls with ADHD.
 
Characterization of large-scale networks using group independent component analysis. (A) The spatial components related to functional hubs in the brain were identified using a group Independent Component Analysis (gICA) in FSL’s MELODIC (Jenkinson et al., 2012) and the large-scale network atlas developed by Yeo et al. (2011). The significant gICA components were overlaid onto the Montréal Neurological Institute standard space and resampled to a spatial resolution of 4mm isotropic. (B) All spatial components identified in (A) were concatenated spatially and binarized into one large-scale network region of interest masking all the voxels to be used in the subsequent analysis. These voxels represent functionally active cortical hubs that are consistent across both groups. The large-scale network mask (red) was overlaid onto the FreeSurfer (https://surfer.nmr.mgh.harvard.edu) surface-based brain (grey) to show the spatial distribution of voxels studied. LH = left hemisphere, RH = right hemisphere
Computation of BOLD-CBF coupling and distance-based functional connectivity strength maps. The BOLD-CBF coupling (A) and distance-based functional connectivity strength (short- and long-FCS; (B)) maps were computed based on voxels within the large-scale network identified in Fig. 1B. ASL = arterial spin labelling, BOLD = blood oxygenation level dependent, CBF = cerebral blood flow, gICA = group Independent Component Analysis, ROI = region-of-interest
Schematic of analysis pipeline used in this study to derive voxelwise cerebrovascular reactivity measurements. Following standard pre-processing of the BOLD-based functional data, cerebrovascular reactivity (CVR) was calculated at each voxel using an optimized pipeline that refines the time-scaled ramp regressor (red; (A)) using the Rapid Interpolation at Progressive Time Delays (RIPTiDE; (B); Frederick et al., 2012) and accounts for noise in the BOLD signal. The refined regressor was then used to determine the optimal delay time (i.e., lag (seconds)) between the breath-hold probe and the BOLD signal at each voxel (C) in order to improve the fitting of the signal in the general linear model (GLM; (D-E)). Axial slices for a sample CVR map in a representative young subject are shown to demonstrate the spatial distribution of the beta coefficient throughout the brain. BOLD = blood oxygenation level dependent, HRF = hemodynamic response function, TR = repetition time (seconds)
Voxelwise differences between groups in hemodynamic markers within the large-scale network region-of-interest. The statistical results (red-yellow; P < 0.05, corrected) from the voxelwise group comparisons of the BOLD-CBF coupling (A), baseline cerebral blood flow (CBF0; (B)) and cerebrovascular reactivity (CVR; (C)) were overlaid onto the FreeSurfer (https://surfer.nmr.mgh.harvard.edu) surface-based template brain (grey) to show that differences in physiology between the groups are spread across the large-scale network region identified in Fig. 1B. LH = left hemisphere, RH = right hemisphere
Spatial distribution of the voxelwise differences in functional connectivity strength between the young and elderly subjects. Statistical decreases in functional connectivity strength (FCS) were documented (red-yellow; P < 0.05, corrected) in the elderly patients relative to the younger subjects. The significant clusters were overlaid onto the MNI template (bottom) along with color-coded spatial components previously described in Fig. 1A to show the spatial distribution of the changes in FCS within five of the six cortical hubs studied. LH = left hemisphere, RH = right hemisphere
Article
The purpose of this study was to determine if differences in functional connectivity strength (FCS) with age were confounded by vascular parameters including resting cerebral blood flow (CBF0), cerebrovascular reactivity (CVR), and BOLD-CBF coupling. Neuroimaging data were collected from 13 younger adults (24 ± 2 years) and 14 older adults (71 ± 4 years). A dual-echo resting state pseudo-continuous arterial spin labeling sequence was performed, as well as a BOLD breath-hold protocol. A group independent component analysis was used to identify networks, which were amalgamated into a region of interest (ROI). Within the ROI, FC strength (FCS) was computed for all voxels and compared across the groups. CBF0, CVR and BOLD-CBF coupling were examined within voxels where FCS was different between young and older adults. FCS was greater in old compared to young (P = 0.001). When the effect of CBF0, CVR and BOLD-CBF coupling on FCS was examined, BOLD-CBF coupling had a significant effect (P = 0.003) and group differences in FCS were not present once all vascular parameters were considered in the statistical model (P = 0.07). These findings indicate that future studies of FCS should consider vascular physiological markers in order to improve our understanding of aging processes on brain connectivity.
 
An illustration of the experimental task. The graph shows a participant reaction times across time. Each bar represents a response, red bars indicate the 10% fastest responses, blue bars represent the 10% slowest responses and grey bars represent general responses that were not considered during data analysis. Under the graph there are screenshots of the experimental task showing a trial screen between two intertrial black screens
SPM comparing fast or slow responses with general activity during the experiment, and comparing fast with slow activity. Colored areas represent channels that have shown significant differences (p < 0.05). Colors represent t-values for each channel. Some relevant channels are numbered
HbO time courses. Note. Averaged time course across all participants of HbO concentration changes between fast and slow conditions. The count of 50 frames on x axis corresponds to approximately 6 s. Black vertical line represents stimulus presentation; gray vertical lines circumscribe the period from which data was considered for statistical tests. *ROIs that presented statistically significant differences between conditions on Wilcoxon test (p value <0,05)
Time courses of three specific channels. Note. Averaged time course across all participants of HbO concentration changes between attentive and inattentive conditions in channel 2 (FpZ-Afz), channel 3 (Af4-Fp2), and channel 42 (P2-P4). Fifty frames correspond to approximately 6 s. The black vertical line represents stimulus presentation; gray vertical lines circumscribe the period from which data was considered for statistical tests
Article
Attention is a basic human function underlying every other cognitive process. It is demonstrated in the functional Magnetic Resonance Imaging literature that frontoparietal networks are involved with attentive performance while default mode networks are involved with inattentive performance. Yet, it is still not clear whether similar results would be found with functional Near-Infrared Spectroscopy. The goal of our study was to investigate differences in hemodynamic activity measured by functional Near-Infrared Spectroscopy between fast and slow responses on a simple sustained attention task both before and after stimulus onset. Thirty healthy adults took part in the study. Our results have shown differences between fast and slow responses only on channels over medial frontal cortex and inferior parietal cortex (p < 0,05). These differences were observed both before and after stimulus presentation. It is discussed that functional Near-Infrared Spectroscopy is a good tool to investigate the frontoparietal network and its relationship with performance in attention tasks; it could be used to further investigate other approaches on attention, such as the dual network model of cognitive control and brain states views based on complex systems analysis; and finally, it could be used to investigate attention in naturalistic settings.
 
Flow chart of the identification of articles. BD, bipolar disorder; PCC, posterior cingulate; NH, network homogeneity; ReHo, regional homogeneity; ICA, independent component analysis; VBM, voxel-based morphometry; ALFF, amplitude low-frequency fluctuation
Regions showing increased (warm coded) and decreased (cold coded) functional connectivity with the PCC in patients with major depressive disorder compared to healthy controls. SFG, superior frontal gyrus; MTG, middle temporal gyrus; TP, temporal pole; PCUN, precuneus; MFG, middle frontal gyrus; L (R), left (right) hemisphere
Meta-analytic results of VBM and overlapped regions of aberrant PCC-based functional connectivity profile and VBM analysis. a PCC-based functional connectivity profile; (b) Meta-analytic results of VBM; (C) overlapped regions of the two methods. VBM, voxel-based morphometry
Results of meta-regression. a meta-regression with the depressive severity (HAMD score); (b) meta-regression with the percentage of drug naïve patients. SMA, supplementary motor area
Article
Disrupted whole-brain resting-state functional connectivity (RSFC) of the posterior cingulate (PCC) has been highlighted to associate with cognitive and affective dysfunction in major depressive disorder (MDD). However, prior findings showed certain inconsistency about the RSFC of the PCC in MDD. This study aims to investigate the aberrant RSFC of the PCC in MDD using anisotropic effect-size version of seed-based d mapping (AES-SDM). Web of Science and PubMed were searched for studies investigating PCC-based RSFC in MDD. A total of 17 studies, involving 804 patients and 724 healthy controls (HCs), fit our selection criteria. Additionally, to seek for the link between functional and structural differences, we did a meta-analysis on the studies in conjunction with voxel-based morphology (VBM) analysis. The PCC showed higher RSFC with the left middle temporal gyrus (MTG) and the right middle frontal gyrus (MFG), and lower RSFC with the left superior frontal gyrus (SFG) and the left precuneus in patients with MDD than HCs. Moreover, the meta-regression analysis revealed a negative correlation between the FC alteration of the right MFG with the PCC and depression severity. Notably, the left MTG and the left MFG demonstrated gray matter deviations in conjunction analysis. Our results indicated that the aberrant RSFC between the PCC and brain regions sub-serving cognitive control and emotional regulation in patients with MDD. And such functional alterations may have structural basis. These findings may underlie the mechanisms of deficits in cognitive control and emotional regulation of MDD.
 
Corpus callosum microstructural degradation in persons with multiple sclerosis (PwMS). The microstructural architecture was degraded in persons with multiple sclerosis across all of the transcallosal sensorimotor fiber bundles. Bar plots of the M1a (top) and PMd (bottom) display significantly elevated radial diffusivity, the MRI-derived tensor parameter, indirect marker of myelination, compared to the neurotypical cohort. Alongside the displayed plots are demonstrative models of the CSD tractography for each respective fiber bundle. Note: * significance between groups at p value < .05
Phase Coordination Index. A.) Displayed are plotted representation of the stride-by-stride coordinated patterns of neurotypical adults (top) and persons with multiple sclerosis (PwMS) (bottom) as quantified by the Phase Coordination Index (PCI). Within the plots, 180° (i.e., a perfectly coordinated phase(s) generation) is indicated by the red line, and deviations from this line are indicative of worse bilateral coordination. B.) PCI performance during the 2-min self-selected pace walk between persons with multiple sclerosis (5.19 ± 2.72) and neurotypical (3.79 ± 1.08) adults. The mean PCI value for each group represented by the colored bars (persons with multiple sclerosis: orange & neurotypical adults: gold) and the shapes denoting the individual values composing the PCI means for each group (persons with multiple sclerosis: darkened circles & neurotypical adults: open triangles). The single star indicates significance at the 5% level. The results and dataset described in this figure, have been previously reported in Richmond et al. (2020) (Sutton B. Richmond et al., 2020)
Correlations between transcallosal sensorimotor fiber microstructure and bilateral coordination in persons with multiple sclerosis. Significant, positive correlation between the phase coordination index and A.) microstructural integrity of the PMd transcallosal fiber bundle (rho = 0.527, p = 0.002) and B.) the M1a transcallosal fiber bundle (rho = 0.390, p = 0.022
Article
Bilateral coordination of the lower extremities is an essential component of mobility. The corpus callosum bridges the two hemispheres of the brain and is integral for the coordination of such complex movements. The aim of this project was to assess structural integrity of the transcallosal sensorimotor fiber tracts and identify their associations with gait coordination using novel methods of ecologically valid mobility assessments in persons with multiple sclerosis and age−/gender-matched neurotypical adults. Neurotypical adults (n = 29) and persons with multiple sclerosis (n = 27) underwent gait and diffusion tensor imaging assessments; the lower limb coordination via Phase Coordination Index, and radial diffusivity, an indirect marker of myelination, were applied as the primary outcome measures. Persons with multiple sclerosis possessed poorer transcallosal white matter microstructural integrity of sensorimotor fiber tracts compared to the neurotypical adults. Further, persons with multiple sclerosis demonstrated significantly poorer bilateral coordination of the lower limbs during over-ground walking in comparison to an age and gender-matched neurotypical cohort. Finally, bilateral coordination of the lower limbs was significantly associated with white matter microstructural integrity of the dorsal premotor and primary motor fiber bundles in persons with multiple sclerosis, but not in neurotypical adults. This analysis revealed that persons with multiple sclerosis exhibit poorer transcallosal microstructural integrity than neurotypical peers. Furthermore, these structural deficits were correlated to poorer consistency and accuracy of gait in those with multiple sclerosis. Together, these results, emphasize the importance of transcallosal communication for gait coordination in those with multiple sclerosis.
 
The demonstration figure on the Pentagon Copying Test (PCT) and examples of typical errors made by the patients in our study: (A) angle number error (2’), (B) closure error (0’), (C) intersection error (1’), (D) rotation error (1’)
Lesion overlap map. Voxels that are damaged in at least four participants are projected onto the 1 mm MNI-152 template. Z coordinates, ranging from -30 to 55, are shown along the top. Voxels are colored according to the number of patients with lesions in that voxel. The left in the picture is the participants’ left
Results of voxelwise Support Vector Regression Lesion-Symptom Mapping (SVR-LSM). The Z coordinate, ranging from -20 to 55, is shown along the top. The lesion-deficit association was determined by a linear SVR model with feature selection. Voxels associated with the indicated QPST subscores are shown in orange (-logP > 2, p<0.01) or yellow (-logP > 3, p<0.001). Most clusters are situated in the right hemisphere. The left in the picture is also the participants’ left
Results of region of interest (ROI)-level analyses using Support Vector Regression Lesion-Symptom Mapping (SVR-LSM). The lesion-deficit association was determined by a linear model in which the independent variable was regional acute ischemic lesion volume (in cm³). The Anatomical Automatic Labeling (AAL) and the International Consortium of Brain Mapping (ICBM) atlas segmented the brain into 166 ROIs, including 116 Gy matter tracts and 50 white matter tracts in both hemispheres. ROIs significantly associated with the indicated QPST score are colored orange (-logP > 2, p<0.01) or yellow (-logP > 4, p<0.0001). The left in the picture is also the participants’ left
Article
Pentagon Copying Test (PCT) is commonly used to assess visuospatial deficits, but the neural substrates underlying pentagon copying are not well understood. The Qualitative Scoring Pentagon Test (QSPT), an optimized scoring system, classifies five categories of errors patients make in pentagons copying and grades them depending on the errors’ severity. To determine the strategic brain regions involved in the PCT, we applied the QSPT system to evaluate the visuospatial impairment of 136 acute ischemic stroke patients on the PCT and used Support Vector Regression Lesion-Symptom Mapping to investigate relevant brain regions. The total QSPT score was correlated with the right supramarginal gyrus. The angle number errors and closure errors were principally associated with lesions of the posterior temporoparietal cortex, including the right middle occipital gyrus and middle temporal gyrus, while the intersection errors and rotation errors were related to the more anterior part of the right temporoparietal lobe with the additional frontal cortex. In conclusion, the right temporoparietal cortex is the strategic region for pentagon copying tasks. The angle number and closure represent the visuospatial processing of within-object features, while intersection and rotation require between-object manipulation. The posterior-anterior distinction in the right temporoparietal region underlies the differences of within-object and between-object processing.
 
Trial examples in MSIT. (A) Subjects are asked to select a number that differs from the other two numbers via button press once the number occurs on the screen. During control trials (left), the distractors are zeros (0) and target numbers are always placed congruently with their position on the button box. During interference trials (right), the distractors are other numbers (either 1, 2 or 3), and target number are never placed congruently with their position on the button box. In these two pictures, the correct answer would be “1” and “3” respectively. The sets will change every 1.75 s and subjects are required to answer as quickly as possible. (B) Time axis of the task. Subjects are asked not to do anything in the “Fixation” part. F, fixation; C, control trials; I, interference trials
Locations of four regions and their time series. The four regions are identified using FSL analysis based on task-related fMRI data. The time series are principal eigenvariates of regions. PFC, prefrontal cortex; MCC, mid-cingulate cortex; LPC, left parietal cortex; RPC, right parietal cortex
DCM models. (A) Models with interactions between the left and right superior parietal cortices. (B) Models with no interactions between the left and right superior parietal cortices. The red solid line represents bidirectional connectivity. The blue dotted line represents unidirectional connectivity. PFC, prefrontal cortex; MCC, mid-cingulate cortex; LPC, left parietal cortex; RPC, right parietal cortex
Winning models in cLBP and healthy controls. A. The results from Bayesian model selection at the group level showed that the fully connected model was the best model for both groups. Both the fixed effects analysis and random effects analysis revealed similar results. B. The winning model for the two groups. The number shows the connectivity parameters (Hz) of the winning model. The solid lines represent connectivity values greater than 0.1 Hz, and their thickness shows the size of the value. The dotted lines represent the connectivity values below 0.1 Hz. The blue octagons indicate the path showing significant effective connectivity in the single group analysis. The red octagons represent the path showing significant between-group differences. CLBP, chronic low back pain; FFX, fixed effects; RFX, random effects; PFC, prefrontal cortex; MCC, mid-cingulate cortex; LPC, left parietal cortex; RPC, right parietal cortex
Effective connectivity of the MCC-to-LPC pathway. The “task EC” represents the endogenous connectivity of the MCC-to-LPC pathway in both groups. EC, effective connectivity; MCC, midcingulate cortex; LPC, left parietal cortex; Interf, interference; HC, healthy controls; LBP, low back pain
Article
Dysfunction of the cingulo-frontal-parietal (CFP) cognitive attention network has been associated with the pathophysiology of chronic low back pain (cLBP). However, the direction of information processing within this network remains largely unknown. We aimed to study the effective connectivity among the CFP regions in 36 cLBP patients and 36 healthy controls by dynamic causal modeling (DCM). Both the resting-state and task-related (Multi-Source Interference Task, MSIT) functional magnetic resonance imaging (fMRI) data were collected and analyzed. The relationship between the effective connectivity of the CFP regions and clinical measures was also examined. Our results suggested that cLBP had significantly altered resting-state effective connectivity of the prefrontal cortex (PFC)-to-mid-cingulate cortex (MCC) (increased) and MCC-to-left superior parietal cortex (LPC) (decreased) pathways as compared with healthy controls. MSIT-related DCM suggested that the interference task could significantly increase the effective connectivity of the right superior parietal cortex (RPC)-to-PFC and RPC-to-MCC pathways in cLBP than that in healthy controls. The control task could significantly decrease the effective connectivity of the MCC-to-LPC and MCC-to-RPC pathways in cLBP than that in healthy controls. The endogenous connectivity of the PFC-to-RPC pathway in cLBP was significantly lower than that in healthy controls. No significant correlations were found between the effective connectivity within CFP networks and pain/depression scores in patients with cLBP. In summary, our findings suggested altered effective connectivity in multiple pathways within the CFP network in both resting-state and performing attention-demanding tasks in patients with cLBP, which extends our understanding of attention dysfunction in patients with cLBP.
 
Venn diagram (A) Associations between brain aging modes and psychiatric disorders; (B) Associations between gut microbiota and psychiatric disorders
Article
We aim to explore the potential interaction effects of brain aging and gut microbiota on the risks of sleep, anxiety and depression disorders. The genome-wide association study (GWAS) datasets of brain aging (N = 21,407) and gut microbiota (N = 3,890) were obtained from published studies. Individual level genotype and phenotype data of psychiatric traits (including sleep, anxiety and depression) were all from the UK Biobank (N = 107,947–374,505). We first calculated the polygenic risk scores (PRS) of 62 brain aging modes and 114 gut microbiota taxa as the instrumental variables, and then constructed linear and logistic regression analyses to systematically explore the potential interaction effects of brain aging and gut microbiota on psychiatric disorders. We observed the interaction effects of brain aging and gut microbiota on sleep, anxiety and depression disorders, such as Putamen/caudate T2* vs. Rhodospirillales (β = -0.012, P = 8.4 × 10–4) was negatively associated with chronotype, Fornix MD vs. Holdemanella (β = -0.007, P = 1.76 × 10–2) was negatively related to general anxiety disorder (GAD) scores, and White matter lesions vs. Acidaminococcaceae (β = 0.019, P = 1.29 × 10–3) was positively correlated with self-reported depression. Interestingly, Putamen volume vs. Intestinibacter was associated with all three psychiatric disorders, including chronotype (negative correlation), GAD scores (positive correlation) and self-reported depression (positive correlation). Our study results suggest the significant impacts of brain aging and gut microbiota on the development of sleep, anxiety and depression disorders, providing new clues for clarifying the pathogenesis of these disorders.
 
Significant clusters are shown as statistical t-maps at a cluster threshold of p-cluster < 0.01
Article
Metacognitive deficits affect Alzheimer’s disease (AD) patient safety and increase caregiver burden. The brain areas that support metacognition are not well understood. 112 participants from the Imaging and Genetic Biomarkers for AD (ImaGene) study underwent comprehensive cognitive testing and brain magnetic resonance imaging. A performance-prediction paradigm was used to evaluate metacognitive abilities for California Verbal Learning Test–II learning (CVLT-II 1–5) and delayed recall (CVLT-II DR); Visual Reproduction-I immediate recall (VR-I Copy) and Visual Reproduction-II delayed recall (VR-II DR); Rey-Osterrieth Complex Figure Copy (Rey-O Copy) and delayed recall (Rey-O DR). Vertex-wise multivariable regression of cortical thickness was performed using metacognitive scores as predictors while controlling for age, sex, education, and intracranial volume. Subjects who overestimated CVLT-II DR in prediction showed cortical atrophy, most pronounced in the bilateral temporal and left greater than right (L > R) frontal cortices. Overestimation of CVLT-II 1–5 prediction and DR performance in postdiction showed L > R associations with medial, inferior and lateral temporal and left posterior cingulate cortical atrophy. Overconfident prediction of VR-I Copy performance was associated with right greater than left medial, inferior and lateral temporal, lateral parietal, anterior and posterior cingulate and lateral frontal cortical atrophy. Underestimation of Rey-O Copy performance in prediction was associated with atrophy localizing to the temporal and cingulate areas, and in postdiction, with diffuse cortical atrophy. Impaired metacognition was associated to cortical atrophy. Our results indicate that poor insight into one’s cognitive abilities is a pervasive neurodegenerative feature associated with AD across the cognitive spectrum.
 
Attention Network Test (ANT-I). Participants completed 24 practice trials and were given immediate feedback indicating accuracy of responses. Following this, 288 test trials were presented that did not provide indicators of performance. For each trial, a visual stimulus (group of five arrows) appeared on the screen; the center arrow pointed left or right an equal number of times and the four surrounding arrows all pointed either the same (congruent) or different (incongruent) direction as the center arrow. Trials were presented at variable intervals ranging between 400 to 1600 ms. Between trials, a fixation cross was presented in the centre of the screen; the total length of each trial was 4450 ms. On half of the trials, a 2000 Hz tone was played (i.e., an alerting stimulus) for 50 ms. After 100 ms, an orienting cue (asterisk) was presented on two thirds of the trials for 50 ms. In random order, 48 trials were presented with a valid spatial cue, whereby the asterisk was presented either above or below the central fixation cross to indicate the correct position of where the target stimulus would appear, 48 trials presented an invalid cue (i.e., incorrect predictor of where the target will appear) and 48 trials had no cue. Half of all the trials consisted of congruent flankers and the other half were incongruent flankers
Results of ICA showing components in MNI space with high match to template for the (a) DMN, (b) SN, (c) left FPN, (d) right FPN, (e) DAN, and (f) SMN
3D glass brain image showing ICA (a) main effect of reaction time in DAN, (b) main effect of ISD in the SMN, (c) main effect of alerting score in the SN, (d) main effect of orienting scores in the DMN, and main effect of executive scores in the FPN. Red indicates a positive association with rsFC and blue indicates a negative association with rsFC
Mean reaction times for trails (N =29)
Article
Objective: To examine attention, executive control, and performance variability in healthy varsity athletes and identify unique resting-state functional connectivity (rsFC) patterns associated with measures of speed, stability, and attention. Method: A sample of 29 female university varsity athletes completed cognitive testing using the Attention Network Test- Interactions (ANT-I) and underwent resting-state functional MRI (rsfMRI) scans. Performance was characterized by examining mean reaction time (RT), variability in performance (ISD), and attention network scores on the ANT-I. RsfMRI data were analyzed using an independent component analysis (ICA) in the frontoparietal (FPN), dorsal attention (DAN), default mode, (DMN), salience (SN), and sensorimotor (SMN) networks. Group-level analyses using the performance variables of interest were conducted. Results: Athletes’ performance on the ANT-I revealed a main effect of orienting and executive control (ps<.001; partial η2 = .68 and .89, respectively), with performance facilitated (i.e., faster RT) when athletes were presented with valid cues and congruent flankers. Alerting, orienting, and executive control performance were associated with differences in rsFC within the SN, DMN, and FPN, respectively. Slower RTs were associated with greater rsFC between DAN and bilateral postcentral gyri (p<.001), whereas more stable performance was associated with greater FC between the SMN and the left precuneus (p<.05). Conclusions: Consistent with prior studies, we observed that efficiency in alerting, orienting, and executive control aspects of attention was associated with differences in rsFC in regions associated with the SN, DMS, and FPN. In addition, we observed differential patterns of rsFC for overall speed and variability of performance.
 
Location of left hemisphere brain tumor lesions, indicated by yellow arrows, in the five selected cases on 3D fluid attenuated inversion recovery (FLAIR) axial, sagittal and coronal sections. (A) Case #1: a 44-year-old female patient with an oligodendroglioma, displaying expansile, FLAIR hyperintense lesion involving both superior parietal cortex and underlying white matter as well as intratumoral hypointense signal (yellow arrow) corresponding to the previous biopsy site. (B) Case #2: a 46-year-old male patient with a diffuse astrocytoma, showing expansile, multifocal FLAIR hyperintense lesions located within the left middle temporal gyrus and left mesial occipito-temporal regions. (C) Case #3: a 34-year-old female patient with a ganglioglioma, displaying a FLAIR hyperintense, faint lesion involving the left mesial temporal lobe. (D) Case #4: a 48-year-old male patient with a diffuse oligodendroglioma, showing a hyperintense cortical and subcortical mass involving the left middle and superior temporal lobe and the left insula. (E) Case #5: a 69-year-old male patient with a glioblastoma, FLAIR MR image shows a hyperintense mass in the left mesial temporal lobe
Task-based fMRI and rs-fMRI overlap analysis pipeline
(A) Control group ICN of left triIFG (p < 0.0001, uncorrected T = 4.99, cluster size FWE-corrected). The white circle indicates the seed in the left triIFG [-56, 24, 15]. (B) Neurosynth database derived verb-generation tb-fMRI activation network (p < 0.01, FDR-corrected)
(a, b, c, d, e) Sagittal slices of subject-level rs-fMRI ICN of the triIFG on the left (p < 0.05; r ≥ 0.3) and auditory verb-generation tb-fMRI in the five selected cases on the right (p < 0.05 FWE corrected, cluster extent > 30 voxels). d—Auditory verb-generation tb-fMRI for Case #3 was shown using an uncorrected threshold (p < 0.001, uncorrected, cluster extent k > 10)
Left hemisphere overlap (yellow color) between IFG-ICN (red color) and AVG tb-fMRI (green) networks in the Case #1 (a), Case #2 (b), Case #4 (c) and Case #5 (d)
Article
Task-based functional MRI (tb-fMRI) represents an extremely valuable approach for the identification of language eloquent regions for presurgical mapping in patients with brain tumors. However, its routinely application is limited by patient-related factors, such as cognitive disability and difficulty in coping with long-time acquisitions, and by technical factors, such as lack of equipment availability for stimuli delivery. Resting-state fMRI (rs-fMRI) instead, allows the identification of distinct language networks in a 10-min acquisition without the need of performing active tasks and using specific equipment. Therefore, to test the feasibility of rs-fMRI as a preoperative mapping tool, we reconstructed a lexico-semantic intrinsic connectivity network (ICN) in healthy controls (HC) and in a case series of patients with gliomas and compared the organization of this language network with the one derived from tb-fMRI in the patient’s group. We studied three patients with extra-frontal gliomas who underwent functional mapping with auditory verb-generation (AVG) task and rs-fMRI with a seed in the left inferior frontal gyrus (IFG). First, we identified the functional connected areas to the IFG in HC. We qualitatively compared these areas with those that showed functional activation in AVG task derived from Neurosynth meta-analysis. Last, in each patient we performed single-subject analyses both for rs- and tb-fMRI, and we evaluated the spatial overlap between the two approaches. In HC, the IFG-ICN network showed a predominant left fronto-temporal functional connectivity in regions overlapping with the AVG network derived from a meta-analysis. In two patients, rs- and tb-fMRI showed comparable patterns of activation in left fronto-temporal regions, with different levels of contralateral activations. The third patient could not accomplish the AVG task and thus it was not possible to make any comparison with the ICN. However, in this patient, task-free approach disclosed a consistent network of fronto-temporal regions as in HC, and additional parietal regions. Our preliminary findings support the value of rs-fMRI approach for presurgical mapping, particularly for identifying left fronto-temporal core language-related areas in glioma patients. In a preoperative setting, rs-fMRI approach could represent a powerful tool for the identification of eloquent language areas, especially in patients with language or cognitive impairments.
 
The resting-state networks (RSNs). Thirty-eight components were estimated by the ICA in total. Sixteen of those components identified as meaningful RSNs. (A–D) showed the aDMN (c28), pDMN (c1), aDMN (c22), pDMN (c18), respectively. (E–F) corresponding showed the left FPN (c13) and right FPN (c15). (G–I) correspond to the VN, consisted of the lateral visual areas (c3), medial areas (c4), and occipital pole areas (c5). (J, K) revealed the location of DAN (c6, c8). Fig 1 L displayed the distribution of AUD (c2). (M, N) illustrated the allocation of VAN (c12, c14). Fig 1 O showed the location of SMN (c7). (P) revealed the distribution of limbic system (c10).
The differences in functional synchronization between MDD with childhood maltreatment group, MDD without childhood maltreatment group, and HC group. A) Group differences in the right medial superior frontal gyrus within the right FPN; B) Group differences in the left triangular inferior frontal gyrus within the left FPN; C) Multiple comparisons between groups.
Group differences in inter-functional network connectivity. A) Visualize of inter-functional network connectivity; B) Inter-network function changes between groups.
The correlation analysis between functional synchronization and score of CTQ.
Article
Although childhood maltreatment confers a high risk for the development of major depressive disorder, the neurobiological mechanisms underlying this connection remain unknown. The present study sought to identify the specific resting-state networks associated with childhood maltreatment. We recruited major depressive disorder patients with and without a history of childhood maltreatment (n = 31 and n = 30, respectively) and healthy subjects (n = 80). We used independent component analysis to compute inter- and intra- network connectivity. We found that individuals with major depressive disorder and childhood maltreatment could be characterized by the following network disconnectivity model relative to healthy subjects: (i) decreased intra-network connectivity in the left frontoparietal network and increased intra-network connectivity in the right frontoparietal network, (ii) decreased inter-network connectivity in the posterior default mode network—auditory network, posterior default mode network—limbic system, posterior default mode network—anterior default mode network, auditory network—medial visual network, lateral visual network - medial visual network, medial visual network—sensorimotor network, medial visual network - anterior default mode network, occipital pole visual network—dorsal attention network, and posterior default mode network—anterior default mode network, and (iii) increased inter-network connectivity in the sensorimotor network—ventral attention network, and dorsal attention network—ventral attention network. Moreover, we found significant correlations between the severity of childhood maltreatment and the intra-network connectivity of the frontoparietal network. Our study demonstrated that childhood maltreatment is integrally associated with aberrant network architecture in patients with major depressive disorder.
 
Correlations between the nodal properties of the right hippocampus and the PRS in the two groups. (a), The NGe of the right hippocampus was positively correlated with the PRS (r = 0.366, P < 0.001) in the individuals with type 2 diabetes; (b), The NLp of the right hippocampus was negatively correlated with the PRS (r = -0.366, P < 0.001) in the individuals with type 2 diabetes; (c), The Nd of the right hippocampus was positively correlated with the PRS (r = 0.320, P = 0.001) in the individuals with type 2 diabetes. Nd, nodal degree; NGe, nodal global efficiency; NLp, nodal shortest path length; R right
Correlations between the nodal properties of the right hippocampus and the episodic memory tests in the individuals with type 2 diabetes. The NGe of the right hippocampus was positively correlated with the ROCF immediate recall (r = 0.252, P = 0.048 after FDR correction) (a), and the AVLT long-term memory (r = 0.268, P = 0.042 after FDR correction) (b) in the individuals with type 2 diabetes. The NLp of the right hippocampus was negatively correlated with the AVLT long-term memory (r = -0.273, P = 0.042 after FDR correction) (c) in the individuals with type 2 diabetes. AVLT, Auditory Verbal Learning Test; NGe, nodal global efficiency; NLp, nodal shortest path length; R right; ROCF, Rey-Osterrieth Complex Figure Test
Mediation model of the PRS, the NGe of the right hippocampus, and episodic memory in individuals with type 2 diabetes. A significant direct effect was detected from the PRS to the NGe of the right hippocampus; and from the NGe of the right hippocampus to the episodic memory tests (ROCF immediate recall score, AVLT long-term memory) in individuals with type 2 diabetes. A significant indirect effect was also found from the PRS to the episodic memory tests (ROCF immediate recall score, AVLT long-term memory) mediated by the NGe of the right hippocampus. AVLT, Auditory Verbal Learning Test; NGe, nodal global efficiency; R right; ROCF, Rey-Osterrieth Complex Figure Test
Mediation model of the PRS, the NLp of the right hippocampus, and episodic memory in individuals with type 2 diabetes. A significant direct effect was detected from the PRS to the NLp of the right hippocampus; and from the NLp of the right hippocampus to the AVLT long-term memory in individuals with type 2 diabetes. A significant indirect effect was also found from the PRS to the AVLT long-term memory mediated by the NLp of the right hippocampus. AVLT, Auditory Verbal Learning Test; NLp, nodal shortest path length; R right
Article
Type 2 diabetes is associated with a higher risk of dementia. The pathogenesis is complex and partly influenced by genetic factors. The hippocampus is the most vulnerable brain region in individuals with type 2 diabetes. However, whether the genetic risk of type 2 diabetes is associated with the hippocampus and episodic memory remains unclear. This study explored the influence of polygenic risk score (PRS) of type 2 diabetes on the white matter topological properties of the hippocampus among individuals with and without type 2 diabetes and its associations with episodic memory. This study included 103 individuals with type 2 diabetes and 114 well-matched individuals without type 2 diabetes. All the participants were genotyped, and a diffusion tensor imaging-based structural network was constructed. PRS was calculated based on a genome-wide association study of type 2 diabetes. The PRS-by-disease interactions on the bilateral hippocampal topological network properties were evaluated by analysis of covariance (ANCOVA). There were significant PRS-by-disease interaction effects on the nodal topological properties of the right hippocampus node. In the individuals with type 2 diabetes, the PRS was correlated with the right hippocampal nodal properties, and the nodal properties were correlated with the episodic memory. In addition, the right hippocampal nodal properties mediated the effect of PRS on episodic memory in individuals with type 2 diabetes. Our results suggested a gene-brain-cognition biological pathway, which might help understand the neural mechanism of the genetic risk of type 2 diabetes affects episodic memory in type 2 diabetes.
 
Anatomical location of the left and right uncinate fasciculus, defined as per the JHU ICBM-DTI-81 atlas (Mori et al., 2008), is displayed on the JHU template. The left uncinate fasciculus is outlined in the color red, and the right uncinate fasciculus is outlined in the color green. R = right; L = left; A = anterior; S = superior; I = inferior; P = posterior
Article
Both men and women scoring high on psychopathy exhibit similar structural and functional neural abnormalities, including reduced volume of the orbitofrontal cortex (OFC) and reduced hemodynamic activity in the amygdala during affective processing experimental paradigms. The uncinate fasciculus (UF) is a white matter (WM) tract that connects the amygdala to the OFC. Reduced structural integrity of the UF, measured via fractional anisotropy (FA), is commonly associated with men scoring high on psychopathy. However, only one study to date has investigated the relationship between psychopathic traits and UF structural integrity in women, recruiting participants from a community sample. Here, we investigated whether Hare Psychopathy Checklist-Revised (PCL-R) facet scores (measuring interpersonal, affective, lifestyle/behavioral, and antisocial psychopathic traits, respectively) were associated with reduced FA in the left and right UF in a sample of 254 incarcerated women characterized by a wide range of psychopathy scores. We observed that PCL-R Facet 3 scores, assessing lifestyle/behavioral psychopathic traits, were associated with reduced FA in the left and right UF, even when controlling for participant’s age and history of previous substance use. The results obtained in the current study help improve our understanding of structural abnormalities associated with women scoring high on psychopathy. Specifically, reduced UF structural integrity may contribute to some of the deficits commonly associated with women scoring high on psychopathy, including emotion dysregulation.
 
Correlation matrix of each group of cortex thickness. The upper row is the cortical thickness correlation matrices of PTSD, TEC, HC groups after excluding self-connections. The color bar indicates the strength of the correlation coefficients. The lower row is the binary matrix for each group. PTSD, post-traumatic stress disorder; TEC, trauma-exposed control; HC, healthy control
Significant changes in global network parameters as a function of network density (0.1, 0.01, 0.34). (A) the clustering coefficient, (B) local efficiency, and (C) sigma, small-world index. PTSD, post-traumatic stress disorder; TEC, trauma-exposed control; HC, healthy control
Differences between groups in global network parameters as a function of network density (0.1–0.34). Clustering coefficient (A, D, G), local efficiency (B, E, H), and small-world index (C, F, I) of three SCNs. The 95% confidence interval is represented in upper and lower blue lines, and the black line in the middle is the mean difference after 1000 permutations. The red line represents the true differences between groups, which fall outside the confidence interval indicate significant differences between groups (p < .05) under the current threshold. PTSD, post-traumatic stress disorder; TEC, trauma-exposed control; HC, healthy control; C, clustering coefficient; Elocal, local efficiency
Regions showing significant between-group differences in nodal centralities (p < .05, uncorrected). (A-C) nodal efficiency, (D-F) betweenness, and (G-I) nodal degree. L, left; R, right; ISTC, isthmus cingulate cortex; SF, superior frontal gyrus; PSTS, postcentral gyrus; RMF, rostral middle frontal gyrus; SMAR, supramarginal gyrus; TP, temporal pole; INS, insula; PTSD, post-traumatic stress disorder; TEC, trauma-exposed control; HC, healthy control
Article
The topological properties of functional brain networks in post-traumatic stress disorder (PTSD) have been thoroughly examined, whereas the topology of structural covariance networks has been researched much less. Based on graph theoretical approaches, we investigated the topological architecture of structural covariance networks among PTSD, trauma-exposed controls (TEC), and healthy controls (HC) by constructing covariance networks driven by inter-regional correlations of cortical thickness. Structural magnetic resonance imaging (sMRI) scans and clinical scales were performed on 27 PTSD, 33 TEC, and 29 HC subjects. Group-level structural covariance networks were established using pearson correlations of cortical thickness between 68 brain areas, and the graph theory method was utilized to study the global and nodal properties. PTSD and HC subjects did not differ at the global level. When PTSD subjects were compared to TEC subjects, they had significantly higher clustering coefficient (p = .014) and local efficiency (p = .031). Nodes having different nodal centralities between groups did not pass the false-discovery rate correction at the node level. According to the structural brain network topological characteristics discovered in this study, PTSD manifests differently compared to the TEC group. In the PTSD group, the SCN keeps the small-world characteristics, but the degree of functional separation is enhanced. The TEC group’s reduced small worldness and the tendency for brain network randomization could be signs of trauma recovery.
 
The localized shape differences between the HC and PDM groups using vertex-wise surface analyses of the amygdala.Orange regions indicate the part of the amygdala shown to be abnormal in patients with PDM. (A) The group difference in the left amygdala was located in the superficial nuclei of the amygdala. (B) The group difference in the right amygdala was located in the superficial nuclei and basolateral nuclei of the amygdala
Vector graphs of the amygdala according to the traditional surface-based vertex analysis displayed by the 3D mesh. A is left amygdala; B is right amygdala. The color bar indicates the T value. The arrows on the surface indicate the direction of change. The arrows outward the surface indicate the direction of the difference showing that the amygdala is expansive here compared with the healthy control group
The clinical significance of the altered shape of the amygdala in the PDM group. A the altered shape of the BL of the right amygdala is positively correlated with VAS score in PDM; B the altered shape of the BL of the right amygdala is negatively correlated with the serum level of PEG2 in PDM group; C and D the altered shape of the SF of the left amygdala is positively correlated with SAS score and disease duration in PDM; Abbreviations: PDM, primary dysmenorrhea; BL, basolateral; SF, superficial; VAS, visual analogue scale; PGE2, Prostaglandin E2; SAS, self-rating anxiety scale
Hypertrophic left amygdala mediated the association between duration and anxiety severity in PDM patients. Abbreviations: PDM, primary dysmenorrhea; SAS, self-rating anxiety scale
Article
Background Primary dysmenorrhea (PDM) is highly associated with mood symptoms. However, the neuropathology of these comorbidities is unclear. In the present study, we aimed to investigate the structural changes in the amygdala of patients with PDM during the pain-free phase using a surface-based shape analysis. Methods Forty-three PDM patients and forty healthy controls were recruited in the study, and all participants underwent structural magnetic resonance imaging scans during their periovulatory phase. FMRIB’s Integrated Registration and Segmentation Tool (FIRST) was employed to assess the subcortical volumetric and surface alterations in patients with PDM. Moreover, correlation and mediation analyses were used to detect the clinical significance of the subcortical morphometry alteration. Results PDM patients showed hypertrophic alteration of the amygdala in the left superficial nuclei and right basolateral and superficial nuclei but not for the whole amygdala volume. The hypertrophic amygdala was associated with disease duration, pain severity and anxiety symptoms during the menstrual period. Furthermore, the hypertrophic left amygdala could mediate the association between disease duration and anxiety severity. Conclusions The results of the current study demonstrated that the localized amygdala shape hypertrophy was present in PDM patients even in the pain-free phase. In addition, the mediator role of the hypertrophic amygdala indicates the potential target of amygdala for anxiety treatment in PDM treatment in the pain-free phase.
 
A Colour-coded correlation matrix of the cortical surface areas (B) Colour-coded correlation matrix of the cortical volumes
Violin plots of the lateralization of the cortical surface areas. The figure represents lateralization indexes (mm²), which is the difference between left and right cortical region
Violin plots of the lateralization of the cortical volumes. The figure represents lateralization indexes (mm³), which is the difference between left and right cortical region
Article
The human brain develops dynamically during early childhood, when the child is sensitive to both genetic programming and extrinsic exposures. Recent studies have found links between prenatal and early life environmental factors, family demographics and the cortical brain morphology in newborns measured by surface area, volume and thickness. Here in this magnetic resonance imaging study, we evaluated whether a similar set of variables associates with cortical surface area and volumes measured in a sample of 170 healthy 5-year-olds from the FinnBrain Birth Cohort Study. We found that child sex, maternal pre-pregnancy body mass index, 5 min Apgar score, neonatal intensive care unit admission and maternal smoking during pregnancy associated with surface areas. Furthermore, child sex, maternal age and maternal level of education associated with brain volumes. Expectedly, many variables deemed important for neonatal brain anatomy (such as birth weight and gestational age at birth) in earlier studies did not associate with brain metrics in our study group of 5-year-olds, which implies that their effects on brain anatomy are age-specific. Future research may benefit from including pre- and perinatal covariates in the analyses when such data are available. Finally, we provide evidence for right lateralization for surface area and volumes, except for the temporal lobes which were left lateralized. These subtle differences between hemispheres are variable across individuals and may be interesting brain metrics in future studies.
 
Cortical thickness and surface area differences in right hemisphere between groups. (A) Smaller surface area regions in OCD in comparison to HC. (B) Thinner cortical regions in OCD in comparison to HC. (C) Thinner cortical regions in SIB in comparison to HC. (D) Regions where both the OCD and SIB groups showed lower cortical thickness in comparison to HC. Horizontal lines represent group means
Article
Little is known about the underlying neurobiological mechanisms in patients with obsessive-compulsive disorder (OCD). We aimed to examine cortical thickness and surface area in individuals with OCD and their unaffected siblings, comparing them to healthy controls. 30 patients with OCD, 21 unaffected siblings (SIB) and 30 controls underwent structural magnetic resonance imaging. Structural images were analyzed using the FreeSurfer software package (version 6.0). Compared to healthy controls, both OCD and SIB groups showed significantly lower cortical thickness in the right anterior insula. Surface areas of the superior frontal gyrus, paracentral gyrus and precuneus of the right hemisphere were also reduced in OCD patients compared to controls. There were no significant differences in cortical thickness and surface area between the OCD and SIB groups. We did not detect any significant differences in subcortical volumes between groups. Lower cortical thickness in the right anterior insula in both OCD patients and unaffected siblings may represent a potential structural endophenotype for OCD.
 
The significant time (baseline and 4-year follow-up) and frequency (typical band, slow-5, slow-4, slow-3, and slow-2) interaction effects on ALFF (voxel-level P < 0.001, cluster-level P < 0.05, GRF corrected). The red-yellow regions represent significant interaction between time and frequency. For the bar maps, * illustrated significance in post hoc paired-sample t-test after Bonferroni correction (8 clusters × 5 bands), P < 0.00125 (0.05/40). IFG, inferior frontal gyrus; SFG, superior frontal gyrus; ROL, Rolandic operculum
Brain regions with significant ALFF differences over four years at different frequency bands. Significant changes in resting state ALFF were observed at typical band, slow-5 band, slow-4 band, slow-3 band, and slow-2 band. Two-tailed, voxel-level P < 0.001, cluster-level P < 0.05, GRF corrected. All the clusters were survived after Bonferroni correction, P < 0.01 (0.05/5)
Correlations between the changed cognition and changed ALFF values. The scatter plot shows the correlation between ΔAttention/processing speed and ΔzALFF in the (a) left CPL, the left SPG at typical band, (b) the left SPG at slow-5 band, (c) the left and right CPL at slow-4 band, (e) the right SFG at slow-2 band; the correlation between ΔLanguage and ΔzALFF in the (b) right MFG at slow-5 band; the correlation between ΔGlobal cognition and ΔzALFF in the (d) right MFG at slow-3 band. Δ, post-test minus pre-test for the zALFF value or the component cognitive domain value. CPL, cerebellum posterior lobe, SPG, superior parietal gyrus, MFG, middle frontal gyrus, SFG, superior frontal gyrus. Two-tailed, voxel-level P < 0.001, cluster-level P < 0.05, GRF corrected. All the correlations were survived after Bonferroni correction (6 cognitive variables × 5 bands), P < 0.0016 (0.05/30)
Article
Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (typical band, slow-5, slow-4, slow-3, and slow-2) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal gyrus, superior frontal gyrus, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at typical band, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging.
 
Top-cited authors
Martha E. Shenton
  • Harvard Medical School
Alexander Lin
  • Brigham and Women's Hospital
Robert A Stern
  • Boston University
Inga Katharina Koerte
  • Ludwig-Maximilians-University of Munich
Sylvain Bouix
  • École de Technologie Supérieure