Max Planck Institute for Human Cognitive and Brain Sciences

Hippocampal circuits in the brain enable two distinct cognitive functions: the construction of spatial maps for navigation, and the storage of sequential episodic memories1, 2, 3, 4–5. Although there have been advances in modelling spatial representations in the hippocampus6, 7, 8, 9–10, we lack good models of its role in episodic memory. Here we present a neocortical–entorhinal–hippocampal network model that implements a high-capacity general associative memory, spatial memory and episodic memory. By factoring content storage from the dynamics of generating error-correcting stable states, the circuit (which we call vector hippocampal scaffolded heteroassociative memory (Vector-HaSH)) avoids the memory cliff of prior memory models11,12, and instead exhibits a graceful trade-off between number of stored items and recall detail. A pre-structured internal scaffold based on grid cell states is essential for constructing even non-spatial episodic memory: it enables high-capacity sequence memorization by abstracting the chaining problem into one of learning low-dimensional transitions. Vector-HaSH reproduces several hippocampal experiments on spatial mapping and context-based representations, and provides a circuit model of the ‘memory palaces’ used by memory athletes¹³. Thus, this work provides a unified understanding of the spatial mapping and associative and episodic memory roles of the hippocampus.

Background Satisfaction with life is a key concept for most individuals. The Satisfaction With Life Scale (SWLS) for measuring general life satisfaction has been widely analyzed in terms of cross-sectional associations. However, the knowledge about long-term changes in life satisfaction and the associations between such changes and changes in other variables of physical and mental health is limited. Methods A community-based representative sample of the general population has been examined twice with a time interval of six years (n = 4,999), using the SWLS and several other scales. Results Over the six years, the mean SWLS score of the total sample remained nearly unchanged (M = 27.0, SD = 5.2, both at t1 and at t2). The test-retest correlation was rtt = 0.66 for the total sample, and there were only marginal differences in temporal stability between male and female respondents. Changes in the SWLS over the six years were correlated with changes in optimism (r = 0.23), mental health (r = 0.26), social functioning (r = 0.22), perceived social support (r = 0.21), anxiety (r = -0.30), and physical complaints (r = -0.18). These change score correlations were lower than the corresponding coefficients under the cross-sectional perspective. Measurement invariance across sex, age, and time was established. Conclusion The SWLS proved to be an appropriate tool for assessing changes in life satisfaction, and correlations between change scores of life satisfaction and health-related variables complement the knowledge about these associations from a cross-sectional perspective.

Background Obesity is a multifactorial disease reaching pandemic proportions with increasing healthcare costs, advocating the development of better prevention and treatment strategies. Previous research indicates that the gut microbiome plays an important role in metabolic, hormonal, and neuronal cross-talk underlying eating behavior. We therefore aim to examine the effects of prebiotic and neurocognitive behavioral interventions on food decision-making and to assay the underlying mechanisms in a Randomized Controlled Trial (RCT). Method This study uses a parallel arm RCT design with a 26-week intervention period. We plan to enroll 90 participants (male/diverse/female) living with overweight or obesity, defined as either a Waist-to-Hip Ratio (WHR) ≥ 0.9 (male)/0.85 (diverse, female) or a Body Mass Index (BMI) ≥ 25 kg/m². Key inclusion criteria are 18–60 years of age and exclusion criteria are type 2 diabetes, psychiatric disease, and Magnetic Resonance Imaging (MRI) contraindications. The interventions comprise either a daily supplementary intake of 30 g soluble fiber (inulin), or weekly neurocognitive behavioral group sessions, compared to placebo (equicaloric maltodextrin). At baseline and follow-up, food decision-making is assessed utilizing task-based MRI. Secondary outcome measures include structural MRI, eating habits, lifestyle factors, personality traits, and mood. Further, we obtain fecal and blood samples to investigate gut microbiome composition and related metabolites. Discussion This study relies on expanding research suggesting that dietary prebiotics could improve gut microbiome composition, leading to beneficial effects on gut-brain signaling and higher-order cognitive functions. In parallel, neurocognitive behavioral interventions have been proposed to improve unhealthy eating habits and metabolic status. However, causal evidence on how these “bottom-up” and “top-down” processes affect food decision-making and neuronal correlates in humans is still scarce. In addition, microbiome, and gut-brain-axis-related mediating mechanisms remain unclear. The present study proposes a comprehensive approach to assess the effects of these gut-brain-related processes influencing food decision-making in overweight and obesity. Trial registration ClinicalTrials.gov NCT05353504. Retrospectively registered on 29 April 2022.

Excitation‐inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole‐brain level, and its microcircuit‐level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting‐state fMRI time series, and microcircuit parameters are simulated using biophysical models. A broad decrease in the Hurst exponent is observed in pharmaco‐resistant temporal lobe epilepsy (TLE), suggesting more excitable network dynamics. Connectome decoders point to temporolimbic and frontocentral cortices as plausible network epicenters of E/I imbalance. Furthermore, computational simulations reveal that enhancing cortical excitability in TLE reflects atypical increases in recurrent connection strength of local neuronal ensembles. Mixed cross‐sectional and longitudinal analyses show stronger E/I ratio elevation in patients with longer disease duration, more frequent electroclinical seizures as well as interictal epileptic spikes, and worse cognitive functioning. Hurst exponent‐informed classifiers discriminate patients from healthy controls with high accuracy (72.4% [57.5%–82.5%]). Replicated in an independent dataset, this work provides in vivo evidence of a macroscale shift in E/I balance in TLE patients and points to progressive functional imbalances that relate to cognitive decline.

The cortex and cerebellum are densely connected through reciprocal input/output projections that form segregated circuits. These circuits are shown to differentially connect anterior lobules of the cerebellum to sensorimotor regions, and lobules Crus I and II to prefrontal regions. This differential connectivity pattern leads to the hypothesis that individual differences in structure should be related, especially for connected regions. To test this hypothesis, we examined covariation between the volumes of anterior sensorimotor and lateral cognitive lobules of the cerebellum and measures of cortical thickness (CT) and surface area (SA) across the whole brain in a sample of 270 young adults drawn from the HCP dataset. We observed that patterns of cerebellar–cortical covariance differed between sensorimotor and cognitive networks. Anterior motor lobules of the cerebellum showed greater covariance with sensorimotor regions of the cortex, while lobules Crus I and Crus II showed greater covariance with frontal and temporal regions. Interestingly, cerebellar volume showed predominantly negative relationships with CT and predominantly positive relationships with SA. Individual differences in SA are thought to be largely under genetic control while CT is thought to be more malleable by experience. This suggests that cerebellar–cortical covariation for SA may be a more stable feature, whereas covariation for CT may be more affected by development. Additionally, similarity metrics revealed that the pattern of covariance showed a gradual transition between sensorimotor and cognitive lobules, consistent with evidence of functional gradients within the cerebellum. Taken together, these findings are consistent with known patterns of structural and functional connectivity between the cerebellum and cortex. They also shed new light on possibly differing relationships between cerebellar volume and cortical thickness and surface area. Finally, our findings are consistent with the interactive specialization framework which proposes that structurally and functionally connected brain regions develop in concert.

Background Alzheimer’s disease (AD) is thought to result from a complex cascade of events involving several pathological processes. Recent studies have reported alterations in white matter (WM) microstructure in the early phase of AD, but WM remains understudied. We used a multivariate approach to capture the complexity and heterogeneity of WM pathologies and its links to cognition and AD risk factors in a more holistic manner. Method The MRI data of 134 cognitively unimpaired older adults with a family history of AD from the PREVENT‐AD cohort were analysed. Diffusion‐weighted imaging and multi‐echo magnetization transfer, proton density and T1‐weighted data were used to compute several WM metrics (see Fig. 1b‐c). We used the Mahalanobis distance (D2) to summarize the MRI metrics into a single score, indicative of the degree a voxel’s microstructure differs relative to a reference. Voxel‐wise D2 was computed for each subject relative to the group average of all other subjects using the MVComp tool and D2 maps were residualized for age (Fig. 2). Partial Least Squares (PLS) analyses were then performed to relate WM D2 with cognition (RBANS) and AD risk factors, separately in each sex. Result In males, there was only one significant latent variable (LV 1). There were extensive brain WM regions associated with this LV pattern: higher white matter D2, was associated with higher BMI, lower total cholesterol (likely due to lower HDL) and worse cognitive performance in all cognitive domains except attention (Fig. 2a‐b). In females, only the first LV was significant. Higher D2 in several WM tracts, including the inferior and superior longitudinal fasciculus, and the parahippocampal cingulum, was associated with lower education, and worse cognitive performance in all cognitive domains except attention and visuospatial construction. Higher WM D2 was also associated with several metabolic risk factors in females including higher SBP, higher BMI, higher glycated hemoglobin (HbA1c) and lower cholesterol (Fig. 2c‐d). Conclusion The different patterns of associations observed suggest there are sex‐specific risk profiles associated with WM microstructure differences in this population of older adults at risk of AD. The WM tracts affected in each sex were also associated with specific cognitive profiles.

Background Memory decline, which is especially prevalent in Alzheimer’s disease (AD), has been studied via fMRI, primarily focusing on the prefrontal cortex and hippocampus. However, emerging evidence suggests that the brainstem, alongside various midbrain regions, is an initial target for pathological processes like hyperphosphorylated TAU protein accumulation. Among these, the locus coeruleus, a noradrenergic nucleus in the pons, projects to critical midbrain areas supporting memory encoding. Hence, our study aimed to investigate BOLD task activations in AD relevant to memory, while focusing on differences in responses to emotional versus neutral stimuli in the brainstem and midbrain. Method Using event‐related fMRI, 53 subjects (28 healthy older adults, 25 with mild cognitive impairment (MCI)) (see table 1) underwent an incidental recognition memory task involving emotional and neutral images. Memory tests followed immediately, and 4 hours after encoding. Group differences in brain activations for remembered versus not remembered images using the study template were examined. Result Results revealed a trend for greater activation in the left caudate nucleus in older adults, compared to those with MCI, when subsequently remembered items were compared with not remembered ones (small volume correction (SVC), cluster level pFWE‐corr = 0.08). Similarly, a significant increased activation was observed in the locus coeruleus (SVC, cluster level pFWE‐corr = 0.018). However, after adjusting for group and individual differences in LC integrity and global grey matter volume (GMV), no significant differences persisted, suggesting that structural changes contribute significantly to differences in LC activation between healthy controls and MCI participants (see Figures 1 and 2). Conclusion In conclusion, our findings underscore the caudate nucleus’s role in memory encoding for healthy older adults versus those with MCI. A decline in LC function in MCI appears related to a decline in LC integrity. These insights contribute to understanding memory mechanisms in healthy aging versus MCI. Future studies are needed to explore potential neural memory compensatory processes in MCI.

Background The Locus Coeruleus (LC) is prominently affected by neuronal loss in the earliest stages of Alzheimer’s disease (AD). Assessing LC integrity can serve as an important early biomarker for assessing AD progression. Neuromelanin (NM) accumulates in LC neurons and NM imaging has therefore been proposed as a means of imaging the LC. As signal intensity is taken as a proxy for cell density, a quantitative imaging approach of the LC, which is less variable across sites and time is desirable. The present study used a multi‐parameter mapping (MPM) protocol optimized for LC imaging to compare weighted and quantitative maps in healthy younger, healthy older adults and individuals with AD. Methods Structural MRI data was acquired in a group of 26 healthy young adults, 26 healthy older adults and 26 individuals with Alzheimer’s disease. Three sets of T1‐weighted, MT‐weighted, and PD‐weighted images yielded quantitative maps (R1, MTsat, PD, and R2*) in each individual within one scan session. Qualitative and quantitative methods were used to assess weighted and quantitative maps for LC imaging across groups. Results Qualitatively, LC visibility was higher in weighted images. The LC was also apparent in R1 maps, but less clearly visible in MTsat and R2* maps (Figure 1). LC contrast ratio (with pons as reference), was reduced in Alzheimer’s disease compared to younger adults as detected by MTw scans (p = .001) and to older adults as detected by T1w (p<.001), MTw (p<.001), and PDw scans (p = .007). No group differences were detected in quantitative maps, suggesting less sensitivity to pick up typical LC integrity reductions. PD maps could not be reliably estimated in the modified setup of the MPMs. Conclusion Although among the quantitative maps LC was most visible in R1 images, our findings indicate that R1 maps capture the LC signal intensity less well as compared to non‐quantitative LC imaging, as suggested by a qualitative assessment of LC visibility and inability to detect known group differences. Further research should improve sensitivity of quantitative maps for LC assessment by combining sequences capturing different aspects of LC tissue properties.

Background Locus coeruleus (LC) is a primary source of noradrenalin in the brain and plays a complex role in human behavior. In healthy aging and Alzheimer’s disease (AD), LC cell loss has been linked to a decline in overall cognitive function. This study aimed to explore age‐ and AD‐related differences in a proxy measure of LC activity. Using pupil dilation (PD) as a non‐exclusive proxy measure of the LC‐NE system activity, we examined whether pupillometric recordings during cognitive tasks are possible in early AD and whether they reveal differences in attentional modulation in aging and AD. Method 37 subjects (14 healthy OA and 23 individuals with AD) completed an auditory and visual oddball task to assess attentional modulation; 62 subjects (22 healthy YA, 20 healthy OA, and 20 individuals with AD) completed a Simon task to assess attention and cognitive control. LC integrity was assessed using neuromelanin‐sensitive MRI. Result A larger PD response for oddball compared to standard stimuli was observed, with no difference between OA and AD participants. In the visual task, greater PD correlated with faster reaction times (RTs) for hits in both groups, indicating the interindividual differences in PD can reflect heightened attentional involvement in aging and AD. Similarly, a consistent Simon effect, i.e., lower accuracy and longer RTs for incongruent trials, was observed in all groups, suggesting cognitive effort in discriminating between congruences. PD was higher for incongruent than congruent trials across all age groups, yet YA exhibited a less pronounced Simon effect, indicating age‐related differences in attentional resource allocation with a potentially larger need in OA and AD for attentional control on incongruent stimuli. In YA, slower RTs correlated with smaller PD in incongruent trials. YA and AD individuals with a stronger Simon effect in PD showed faster processing for incongruent trials and better performance for congruent trials, respectively. Conclusion Using PD as a measure of attentional allocation and effort during cognitive control is possible in AD. Moreover, it allows for the assessment of interindividual differences in the extent of attentional modulation in AD. Assessing PD could be a useful tool for distinguishing between healthy aging and early AD.

Background Alzheimer’s disease (AD) is thought to result from a complex cascade of events involving several pathological processes. Recent studies have reported alterations in white matter (WM) microstructure in the early phase of AD, but WM remains understudied. We used a multivariate approach to capture the complexity and heterogeneity of WM pathologies and its links to cognition and AD risk factors in a more holistic manner. Method The MRI data of 134 cognitively unimpaired older adults with a family history of AD from the PREVENT‐AD cohort were analysed. Diffusion‐weighted imaging and multi‐echo magnetization transfer, proton density and T1‐weighted data were used to compute several WM metrics (see Figure 1b‐c). We used the Mahalanobis distance (D2) to summarize the MRI metrics into a single score, indicative of the degree a voxel’s microstructure differs relative to a reference. Voxel‐wise D2 was computed for each subject relative to the group average of all other subjects using the MVComp tool and D2 maps were residualized for age (Figure 2). Partial Least Squares (PLS) analyses were then performed to relate WM D2 with cognition (RBANS) and AD risk factors, separately in each sex. Result In males, there was only one significant latent variable (LV 1). There were extensive brain WM regions associated with this LV pattern: higher white matter D2, was associated with higher BMI, lower total cholesterol (likely due to lower HDL) and worse cognitive performance in all cognitive domains except attention (Figure 2a‐b). In females, only the first LV was significant. Higher D2 in several WM tracts, including the inferior and superior longitudinal fasciculus, and the parahippocampal cingulum, was associated with lower education, and worse cognitive performance in all cognitive domains except attention and visuospatial construction. Higher WM D2 was also associated with several metabolic risk factors in females including higher SBP, higher BMI, higher glycated hemoglobin (HbA1c) and lower cholesterol (Figure 2c‐d). Conclusion The different patterns of associations observed suggest there are sex‐specific risk profiles associated with WM microstructure differences in this population of older adults at risk of AD. The WM tracts affected in each sex were also associated with specific cognitive profiles.

Background There is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial. Method We included 269 amyloid‐β‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [¹⁸F]AV1451/[¹⁸F]flortaucipir/Tauvid, 27% [¹⁸F]MK6240, 19% [¹⁸F]PI2620). Using Gaussian mixture modeling including amyloid‐β‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly. Result Tau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Figure 1). In line with this, tau epicenters were highly heterogeneous across variants (Figure 1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Figure 2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Figure 3). Conclusion This multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

Introduction Cardiovascular diseases (CVDs) present differently in women and men, influenced by host-microbiome interactions. The roles of sex hormones in CVD outcomes and gut microbiome in modifying these effects are poorly understood. The XCVD study examines gut microbiome mediation of sex hormone effects on CVD risk markers by observing transgender participants undergoing gender-affirming hormone therapy (GAHT), with findings expected to extrapolate to cisgender populations. Methods and analyses This observational, longitudinal cohort study includes baseline, 1- and 2-year follow-ups with transgender participants beginning GAHT. It involves comprehensive phenotyping and microbiome genotyping, integrating computational analyses of high-dimensional data. Microbial diversity will be assessed using gut, skin, and oral samples via 16S rRNA and shotgun metagenomic sequencing of gut samples. Blood measurements will include sex hormones, CVD risk markers, cardiometabolic parameters, cytokines, and immune cell counts. Hair samples will be analysed for cortisol. Participants will complete online questionnaires on physical activity, mental health, stress, quality of life, fatigue, sleep, pain, and gender dysphoria, tracking medication use and diet to control for confounders. Statistical analyses will integrate phenomic, lifestyle, and multi-omic data to model health effects, testing gut microbiome mediation of CVD risk as the endocrine environment shifts between that typical for cisgender men to women and vice versa. Ethics and dissemination The study adheres to Good Clinical Practice and the Declaration of Helsinki. The protocol was approved by the Charité Ethical Committee (EA1/339/21). Signed informed consent will be obtained. Results will be published in peer-reviewed journals and conferences and shared as accessible summaries for participants, community groups, and the public, with participants able to view their data securely after public and patient involvement review for accessibility. Trial registration number The XCVD study was registered on ClinicalTrials.gov ( NCT05334888 ) as ‘Sex-differential host-microbiome CVD risk — a longitudinal cohort approach (XCVD)" on 4 April 2022. Data set link can be found at https://classic.clinicaltrials.gov/ct2/show/NCT05334888 .

Scene recognition is a core sensory capacity that enables humans to adaptively interact with their environment. Despite substantial progress in the understanding of the neural representations underlying scene recognition, the relevance of these representations for behavior given varying task demands remains unknown. To address this, we aimed to identify behaviorally relevant scene representations, to characterize them in terms of their underlying visual features, and to reveal how they vary across different tasks. We recorded fMRI data while human participants viewed scenes and linked brain responses to behavior in three tasks acquired in separate sessions: man-made/natural categorization, basic-level categorization, and fixation color discrimination. We found correlations between categorization response times and scene-specific brain responses, quantified as the distance to a hyperplane derived from a multivariate classifier. Across tasks, these effects were found in largely distinct parts of the ventral visual stream. This suggests that different scene representations are relevant for behavior depending on the task. Next, using deep neural networks as a proxy for visual feature representations, we found that intermediate layers mediated the relationship between scene representations and behavior for both categorization tasks, indicating a contribution of mid-level visual features to these representations. Finally, we observed opposite patterns of brain-behavior correlations in the man-made/natural and the fixation task, indicating interference of representations with behavior for task demands that do not align with the content of representations. Together, these results reveal the spatial extent, content, and task-dependence of the visual representations that mediate behavior in complex scenes.

People enjoy engaging with music. Live music concerts provide an excellent option to investigate real‐world music experiences, and at the same time, use neurophysiological synchrony to assess dynamic engagement. In the current study, we assessed engagement in a live concert setting using synchrony of cardiorespiratory measures, comparing inter‐subject, stimulus–response, correlation, and phase coherence. As engagement might be enhanced in a concert setting by seeing musicians perform, we presented audiences with audio‐only (AO) and audio‐visual (AV) piano performances. Only correlation synchrony measures were above chance level. In comparing time‐averaged synchrony across conditions, AV performances evoked a higher inter‐subject correlation of heart rate (ISC‐HR). However, synchrony averaged across music pieces did not correspond to self‐reported engagement. On the other hand, time‐resolved analyses show that synchronized deceleration‐acceleration heart rate (HR) patterns, typical of an “orienting response” (an index of directed attention), occurred within music pieces at salient events of section boundaries. That is, seeing musicians perform heightened audience engagement at structurally important moments in Western classical music. Overall, we could show that multisensory information shapes dynamic engagement. By comparing different synchrony measures, we further highlight the advantages of time series analysis, specifically ISC‐HR, as a robust measure of holistic musical listening experiences in naturalistic concert settings.

Accurate diagnosis and monitoring of neurodegenerative diseases require reliable biomarkers. Cerebrospinal fluid (CSF) proteins are promising candidates for reflecting brain pathology; however, their diagnostic utility may be compromised by natural variability between individuals, weakening their association with disease. Here, we measured the levels of 69 pre-selected proteins in cerebrospinal fluid using antibody-based suspension bead array technology in a multi-disease cohort of 499 individuals with neurodegenerative disorders including Alzheimer’s disease (AD), behavioral variant frontotemporal dementia, primary progressive aphasias, amyotrophic lateral sclerosis (ALS), corticobasal syndrome, primary supranuclear palsy, along with healthy controls. We identify significant inter-individual variability in overall CSF levels of brain-derived proteins, which could not be attributed to specific disease associations. Using linear modelling, we show that adjusting for median CSF levels of brain-derived proteins increases the diagnostic accuracy of proteins previously identified as altered in CSF in the context of neurodegenerative disorders. We further demonstrate a simplified approach for the adjustment using pairs of correlated proteins with opposite alteration in the diseases. With this approach, the proteins adjust for each other and further increase the biomarker performance through additive effect. When comparing the diseases, two proteins—neurofilament medium and myelin basic protein—showed increased levels in ALS compared to other diseases, and neurogranin showed a specific increase in AD. Several other proteins showed similar trends across the studied diseases, indicating that these proteins likely reflect shared processes related to neurodegeneration. Overall, our findings suggest that accounting for inter-individual variability is crucial in future studies to improve the identification and performance of relevant biomarkers. Importantly, we highlight the need for multi-disease studies to identify disease-specific biomarkers.

Proper names are linguistic expressions referring to unique entities, such as individual people or places. This sets them apart from other words like common nouns, which refer to generic concepts. And yet, despite both being individual entities, one's closest friend and one's favorite city are intuitively associated with very different pieces of knowledge—face, voice, social relationship, autobiographical experiences for the former, and mostly visual and spatial information for the latter. Neuroimaging research has revealed the existence of both domain-general and domain-specific brain correlates of semantic processing of individual entities; however, it remains unclear how such commonalities and similarities operate over a fine-grained temporal scale. In this work, we tackle this question using EEG and multivariate (time-resolved and searchlight) decoding analyses. We look at when and where we can accurately decode the semantic category of a proper name and whether we can find person- or place-specific effects of familiarity, which is a modality-independent dimension and therefore avoids sensorimotor differences inherent among the two categories. Semantic category can be decoded in a time window and with spatial localization typically associated with lexical semantic processing. Regarding familiarity, our results reveal that it is easier to distinguish patterns of familiarity-related evoked activity for people, as opposed to places, in both early and late time windows. Second, we discover that within the early responses, both domain-general (left posterior-lateral) and domain-specific (right fronto-temporal, only for people) neural patterns can be individuated, suggesting the existence of person-specific processes.

Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., low-frequency neural oscillations) may set an upper limit of 2–3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learned chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.

During memory formation, the hippocampus is presumed to represent the content of stimuli, but how it does so is unknown. Using computational modelling and human single-neuron recordings, we show that the more precisely hippocampal spiking variability tracks the composite features of each individual stimulus, the better those stimuli are later remembered. We propose that moment-to-moment spiking variability may provide a new window into how the hippocampus constructs memories from the building blocks of our sensory world.

Objective Among patients with acute stroke, we aimed to identify those who will later develop central post‐stroke pain (CPSP) versus those who will not (non‐pain sensory stroke [NPSS]) by assessing potential differences in somatosensory profile patterns and evaluating their potential as predictors of CPSP. Methods In a prospective longitudinal study on 75 acute stroke patients with somatosensory symptoms, we performed quantitative somatosensory testing (QST) in the acute/subacute phase (within 10 days) and on follow‐up visits for 12 months. Based on previous QST studies, we hypothesized that QST values of cold detection threshold (CDT) and dynamic mechanical allodynia (DMA) would differ between CPSP and NPSS patients before the onset of pain. Mann–Whitney U ‐tests and mixed analysis of variances with Bonferroni corrections were performed to compare z‐normalized QST scores between both groups. Results In total, 26 patients (34.7%) developed CPSP. In the acute phase, CPSP patients showed contralesional cold hypoesthesia compared to NPSS patients ( p = 0.04), but no DMA differences. Additional exploratory analysis showed NPSS patients exhibit cold hyperalgesia on the contralesional side compared to the ipsilesional side, not seen in CPSP patients ( p = 0.011). A gradient‐boosting approach to predicting CPSP from QST patterns before pain onset had an overall accuracy of 84.6%, with a recall and precision of 75%. Notably, both in the acute and the chronic phase, approximately 80% of CPSP and NPSS patients showed bilateral QST abnormalities. Interpretation Cold perception differences between CPSP and NPSS patients appear early post stroke before pain onset. Prediction of CPSP through QST patterns seems feasible. ANN NEUROL 2024