Multimodal analyses identify linked functional and white matter abnormalities within the working memory network in schizophrenia
ABSTRACT Dysconnectivity between brain regions is thought to underlie the cognitive abnormalities that characterise schizophrenia (SZ). Consistent with this notion functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) studies in SZ have reliably provided evidence of abnormalities in functional integration and in white matter connectivity. Yet little is known about how alterations at the functional level related to abnormalities in anatomical connectivity.
We obtained fMRI data during the 2-back working memory task from 25 patients with SZ and 19 healthy controls matched for age, sex and IQ. DTI data were also acquired in the same session. In addition to conventional unimodal analyses we extracted "features" [contrast maps for fMRI and fractional anisotropy (FA) for DTI] that were subjected to joint independent component analysis (JICA) in order to examine interactions between fMRI and DTI data sources.
Conventional unimodal analyses revealed both functional and structural deficits in patients with SZ. The JICA identified regions of joint, multimodal brain sources that differed in patients and controls. The fMRI source implicated regions within the anterior cingulate and ventrolateral prefrontal cortex and in the cuneus where patients showed relative hypoactivation and within the frontopolar cortex where patients showed relative hyperactivation. The DTI source localised reduced FA in patients in the splenium and posterior cingulum.
This study promotes our understanding of structure-function relationships in SZ by characterising linked functional and white matter changes that contribute to working memory dysfunction in this disorder.
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ABSTRACT: Individuals at clinical high risk (CHR) of developing psychosis present with widespread functional abnormalities in the brain. Cognitive deficits, including working memory (WM) problems, as commonly elicited by n-back tasks, are observed in CHR individuals. However, functional MRI (fMRI) studies, comprising a heterogeneous cluster of general and social cognition paradigms, have not necessarily demonstrated consistent and conclusive results in this population. Hence, a comprehensive review of fMRI studies, spanning almost one decade, was carried out to observe for general trends with respect to brain regions and cognitive systems most likely to be dysfunctional in CHR individuals. 32 studies were included for this review, out of which 22 met the criteria for quantitative analysis using activation likelihood estimation (ALE). Task related contrast activations were firstly analysed by comparing CHR and healthy control participants in the total pooled sample, followed by a comparison of general cognitive function studies (excluding social cognition paradigms), and finally by only looking at n-back working memory task based studies. Findings from the ALE implicated four key dysfunctional and distinct neural regions in the CHR group, namely the right inferior parietal lobule (rIPL), the left medial frontal gyrus (lmFG), the left superior temporal gyrus (lSTG) and the right fronto-polar cortex (rFPC) of the superior frontal gyrus (SFG). Narrowing down to relatively few significant dysfunctional neural regions is a step forward in reducing the apparent ambiguity of overall findings, which would help to target specific neural regions and pathways of interest for future research in CHR populations.Journal of Psychiatric Research 09/2014; 61. DOI:10.1016/j.jpsychires.2014.08.018 · 4.09 Impact Factor
Article: Cognitive Network Neuroscience.[Show abstract] [Hide abstract]
ABSTRACT: Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.Journal of Cognitive Neuroscience 03/2015; DOI:10.1162/jocn_a_00810 · 4.69 Impact Factor
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ABSTRACT: a r t i c l e i n f o Background: White matter abnormality has been recently proposed as a pathophysiological feature of schizo-phrenia (SZ). However, most of the data available has been gathered from chronic patients, and was therefore possibly confounded by factors such as duration of the disease, and treatment received. The extent and localiza-tion of these changes is also not clear. Methods: We examined a population of early stage SZ patients using diffusion tensor imaging (DTI). 77 SZ pa-tients and 60 healthy controls (HCs) were included in the analysis using Tract-Based Spatial Statistics (TBSS). We have also analyzed 250 randomly created subsets of the original cohort, to investigate the relation between the result of TBSS analysis, and the size of the sample studied. Results: We have found a significant decrease in fractional anisotropy (FA) in the patient group. This change is present in most major white matter (WM) tracts including the corpus callosum, superior and inferior longitudi-nal fasciculi, inferior fronto-occipital fasciculus, and posterior thalamic radiation. Furthermore, we identified a clear trend towards an increase in the number and spatial extent of significant voxels reported, with an increas-ing number of subjects included in the analysis. Conclusion: Our study shows that FA is significantly decreased in patients at an early stage of schizophrenia, and that the extent of this finding is dependent on the size of studied sample; therefore underpowered studies might produce results with false spatial localization.Schizophrenia Research 02/2015; 162(1-3). DOI:10.1016/j.schres.2015.01.029 · 4.43 Impact Factor