Biology subjects

Muhlert, N.

Publications and source records attributed to Muhlert, N..

14 recordsLinked to original sources

bioRxiv2026

Early life stress alters lifespan trajectories of amygdala development: a cross-species model of amygdala burnout

Early-life stress is associated with alterations in amygdala volume, but findings vary across studies and species. Rodent models typically report increased amygdala volume, whereas human studies often find reductions or mixed effects. We propose the amygdala burnout hypothesis, which suggests that early-life stress alters amygdala developmental trajectories, producing initial volumetric increases that are followed by reductions later in life. To test this hypothesis, we examined amygdala development across rodent and human cohorts spanning adolescence to older adulthood. In rodents, chronic stress was associated with increased amygdala nuclei volumes during adolescence. Comparable increases were observed in adolescents from the IMAGEN consortium, with evidence of a dose-dependent association between childhood stress and amygdala developmental trajectories. In contrast, analyses of older adults from the UK Biobank revealed reduced bilateral amygdala volume associated with early-life stress. Together, these findings support a developmental model that reconciles previously conflicting observations across species and age groups. Early-life stress is associated with alterations in amygdala volume, but findings vary across studies and species. Rodent models typically report increased amygdala volume, whereas human studies often find reductions or mixed effects. We propose the amygdala burnout hypothesis, which suggests that early-life stress alters amygdala developmental trajectories, producing initial volumetric increases that are followed by reductions later in life. To test this hypothesis, we examined amygdala development across rodent and human cohorts spanning adolescence to older adulthood. In rodents, chronic stress was associated with increased amygdala nuclei volumes during adolescence. Comparable increases were observed in adolescents from the IMAGEN consortium, with evidence of a dose-dependent association between childhood stress and amygdala developmental trajectories. In contrast, analyses of older adults from the UK Biobank revealed reduced bilateral amygdala volume associated with early-life stress. Together, these findings support a developmental model that reconciles previously conflicting observations across species and age groups.

neuroscience↗

bioRxiv2026

Sex-specific associations of childhood adversity with frontostriatal network organization and anhedonia in young adulthood

IntroductionAnhedonia is a transdiagnostic psychiatric symptom linked to increased functional connectivity between the prefrontal cortex and striatum. Here, we examined how dimensions of early adversity contribute to this profile of connectivity. MethodsIn a European community sample of young adults (IMAGEN), we examined cross-sectional (n=613) and longitudinal (n=332) associations of adversity dimensions with resting-state fMRI-derived connectivity. We selected 10 ROIs from anhedonia literature, defined in the functional images as 4mm-radius spheres. We then used network-based regression models to identify clusters of ROI-ROI connections associated with threat and deprivation scores, using interaction terms to examine sex and age-specific associations. We also examined associations between adversity and anhedonia, operationalized using factor analysis of six items from self-report surveys. ResultsAt age 18-22, we identified sex-specific associations between deprivation and connectivity for a cluster of 9 ROI-ROI connections (p-FWE=0.038), primarily involving the nucleus accumbens. Specifically, we observed positive associations between deprivation and connectivity in males, and negative associations in females. In the longitudinal analysis, negative deprivation associations in females attenuated with age for a cluster of 14 connections (p-FWE=0.009). A cluster of 17 connections also had initial positive associations with threat in females that attenuated with age (p-FWE=0.008). No such longitudinal changes were observed in males. Higher deprivation was linked to increased later anhedonia in males but not females (p=0.026). ConclusionCompared to females, young adult males may be more vulnerable to developing anhedonia after experiencing deprivation in childhood. Dimensions of early adversity are linked to distinct pathways of frontostriatal development.

neuroscience↗

bioRxiv2026

Thalamic Nuclei Functional Controllability Accounts for Cognitive Impairment in Multiple Sclerosis Over and Above Structural Damage

BackgroundThe thalamus has emerged as a key region involved in cognitive dysfunction in multiple sclerosis (MS). While previous studies have identified associations between thalamic structural damage, altered functional connectivity, and cognitive performance, the specific contributions of individual thalamic nuclei and the added value of integrating structural and functional metrics remain poorly understood. MethodsT1-weighted MRI, diffusion MRI, resting-state fMRI, and neuropsychological data were collected from 102 individuals with MS and 27 healthy controls. Thalamic grey matter volume, white matter microstructural integrity, and functional controllability were calculated for each nucleus and compared between individuals with MS and healthy controls, as well as between MS cognitive subgroups. Partial Spearman correlations were used to examine the relationship between imaging metrics across the three modalities, and also between imaging metrics and cognitive performance in MS. Sparse canonical correlation analysis models were used to examine the covariance between thalamic imaging metrics and cognitive performance in MS. ResultsWidespread atrophy and microstructural damage were observed across all thalamic nuclei in individuals with MS, regardless of cognitive status. In contrast, alterations in functional controllability were more spatially specific, primarily affecting the medial dorsal anterior nuclei, and were most pronounced in cognitively impaired individuals. These functional controllability metrics were independent of grey matter volume, white matter integrity, and lesion load. Combining thalamic functional controllability with structural metrics yielded a stronger association with cognitive performance in MS than either modality alone. ConclusionThis study provides novel evidence that functional controllability in the thalamus, particularly within the medial dorsal anterior nuclei, plays a critical role in cognitive impairment in MS. By applying a network control framework, our findings offer a dynamic systems perspective that extends beyond traditional connectivity analyses, capturing the thalamuss role in supporting flexible cognitive transitions. The integration of structural and functional controllability metrics enhances the ability to characterise individual differences in cognitive performance and may inform future efforts to identify biomarkers of cognitive dysfunction in MS.

neuroscience↗

bioRxiv2026

Thalamic Nuclei Functional Controllability Explains Cognition Over and Above Grey and White Matter Structure

IntroductionThe thalamic nuclei play a crucial role in regulating information flow to the cortex and supports diverse cognitive functions. Although previous studies have linked thalamic structural and functional characteristics to cognition, these measures do not fully capture the thalamuss role in dynamic control, which is essential for complex cognitive processes. Moreover, it remains unclear how these different metrics relate to each other in the way they account for cognition. MethodsT1-weighted MRI, diffusion MRI, resting-state fMRI, and neuropsychological data were obtained from 419 unrelated participants in the Human Connectome Project. We measured grey matter volume, white matter integrity, and functional controllability of each thalamic nucleus to examine their associations with cognitive performance across domains identified through clustering analysis of the neuropsychological data. We also assessed the relationships among these structural and functional metrics and evaluated their individual and combined contributions in capturing covariance with performance in various cognitive domains. ResultsSignificant correlations were observed between thalamic grey matter volume and white matter integrity; however, thalamic functional controllability showed no significant association with either structural metric. White matter integrity demonstrated the strongest association with sequence working memory and language processing. In contrast, thalamic controllability metrics accounted more for performance in executive function, reasoning and encoding, visuospatial processing, and impulse control, outperforming the combination of grey and white matter structural metrics. ConclusionThis study highlights the critical role of the thalamus from a dynamic control perspective, demonstrating that thalamic structural and functional metrics provide complementary rather than redundant information related to cognitive performance. These findings underscore a promising new direction for understanding the complex and dynamic contributions of the thalamus to human cognition.

neuroscience↗

bioRxiv2025

Multi-Timescale Neural Adaptation Failure as a Mechanistic Signature of Major Depression

Major depression (MD) is usually characterized in terms of momentary abnormalities, such as negative bias or emotional blunting, derived from paradigms that measure only the first response to a stimulus. Yet depressive experience in daily life is repetitive and cumulative. Here we test the hypothesis that a failure of neural adaptation across repetitions is a core feature of MD. Using a repeated negative-stimulus paradigm, we quantified adaptation at micro (within-trial) and macro (across-session) scales via electroencephalography in 28 MD patients and 34 healthy controls, measuring both conventional event-related potentials and large-scale traveling-wave propagation. MD patients exhibited pervasive maladaptation: neural rigidity at the micro scale (absent repetition suppression) and progressive regulatory depletion at the macro scale (escalating emotional reactivity with declining cognitive control). Across analyses, adaptation-based metrics revealed larger group differences than single-shot indices, and classifiers built on adaptation features--especially traveling-wave dynamics--outperformed single-shot models (task AUC = 0.83 vs 0.78) and generalized to two independent datasets (up to AUC = 0.91). These findings challenge conventional symptom-based characterizations of MD, establishing adaptation failure--not initial reactivity--as the mechanistically primary pathological signature. This reframing provides a unified mechanistic explanation for rumination and cognitive inflexibility while offering a standardized, low-cost biomarker requiring minimal electrodes ([≤]8 channels), enabling large-scale screening in resource-limited settings.

neuroscience↗

bioRxiv2025

Information Shielding Through Neural Deactivation: A Fundamental Mechanism of Human Information Processing

Information processing is a core issue in cognitive neuroscience. The brain can either accept or shield information. However, information shielding has traditionally been regarded as a byproduct of other cognitive processes that prepare brain areas for activation, with the accompanying brain deactivation seen as merely supportive. Here, we offer an alternative perspective, demonstrating that people can directly perform information shielding without engaging other cognitive processes. Using information shielding as a novel investigative lens, we provide direct evidence that deactivation serves as a primary mechanism in its own right. We found that information shielding was characterized by a deactivation-dominant neural dynamic, with initial executive control region activation giving way to increased sensory region deactivation, especially after a 3-second boundary. Neural decoding results further confirmed this deactivation trend. This deactivation pattern was consistent across both auditory and visual modalities. Furthermore, non-invasive brain stimulation demonstrated a causal relationship between the deactivation pattern and information shielding, and we found that this deactivation mechanism extended to general unnecessary information processing, regardless of whether the necessity was determined objectively or subjectively. This challenges the conventional emphasis on activation as the primary mode of information processing and opens new fundamental avenues for understanding inhibitory cognitive processes.

neuroscience↗

bioRxiv2024

Cerebrovascular Health Mediates Processing Speed Change Through Anterior White Matter Alterations: A UK Biobank Study

Cerebrovascular disease is associated with an increased likelihood of developing dementia. While cardiovascular risk factors are modifiable and may reduce the risk of later-life cognitive dysfunction, the relationship between cerebrovascular risk factors, brain integrity and cognition remains poorly characterised. Using a large UK Biobank sample of predominantly middle-aged adults, without neurological disease, our structural equation mediation models showed that poor cerebrovascular health, indicated by the presence of cerebrovascular risk factors, was associated with slowed processing speed. This effect was best explained by anterior white matter microstructure changes, rather than posterior changes. Effects were also significantly reduced when considering other forms of cognition, demonstrating both regional- and cognitive-specificity of our effects. Critically, our findings also demonstrate that including measures of risk factor duration may be particularly important for improving estimations of cerebrovascular burden. In summary, our study demonstrates the specific impact of early cerebrovascular burden on brain structure and cognitive function, highlighting the necessary next steps for improving cerebrovascular burden quantification and improving clinical predictions.

neuroscience↗

bioRxiv2023

Thalamic network controllability changes and cognitive impairment in multiple sclerosis

Recent research suggests that individuals with multiple sclerosis (MS) and cognitive impairment exhibit more effortful and less efficient transitions in brain network activity. Previous studies further highlight the increased vulnerability of specific regions, particularly the thalamus, to disease-related damage. This study investigates whether MS affects the controllability of specific brain regions in driving network activity transitions across the brain and examines the relationship between these changes and cognitive impairment in patients. Resting-state functional MRI and neuropsychological data were collected from 102 MS and 27 healthy controls. Functional network controllability analysis was performed to quantify how specific regions influence transitions between brain activity patterns or states. Disease alterations in controllability were assessed in the main dataset and then replicated in an independent dataset of 95 MS and 45 healthy controls. Controllability metrics were then used to distinguish MS from healthy controls and predict cognitive status. MS-specific controllability changes were observed in the subcortical network, particularly the thalamus, which were further confirmed in the replication dataset. Cognitively impaired patients showed significantly greater difficulty in the thalamus steering brain transitions towards difficult-to-reach states, which are typically associated with high-energy-cost cognitive functions. Thalamic network controllability proved more effective than thalamic volume in distinguishing MS from healthy controls (AUC = 88.3%), and in predicting cognitive status in MS (AUC = 80.7%). This study builds on previous research highlighting early thalamic damage in MS, aiming to demonstrate how this damage disrupts activity transitions across the cerebrum and may predict cognitive deficits. Our findings suggest that the thalamus in MS becomes less capable of facilitating broader brain activity transitions essential for high-energy-cost cognitive functions, implying a potential pathological mechanism that links thalamic functional changes to cognitive impairment in MS.

neuroscience↗

bioRxiv2023

InSpectro-Gadget: A tool for estimating neurotransmitter and neuromodulator receptor distributions for MRS voxels

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and {gamma}-aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABAand glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool InSpectro-Gadget, that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget.

neuroscience↗

bioRxiv2023

Impact of brain parcellation on prediction error in models of cognition and demographics

Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predictive model performance. In this work, structural, functional and combined connectivity were each defined with 5 different parcellation schemes. The resolution and modality of the parcellation schemes were varied. Each connectivity defined with each parcellation was used to predict individual differences in age, education, sex, Executive Function, Self-regulation, Language, Encoding and Sequence Processing. It was found that low-resolution functional parcellation consistently performed above chance at producing generalisable models of both demographics and cognition. However, no single parcellation scheme proved superior at predictive modelling across all cognitive domains and demographics. In addition, although parcellation schemes impacted the global organisation of each connectivity type, this difference could not account for the out-of-sample prediction performance of the models. Taken together, these findings demonstrate that while high-resolution parcellations may be beneficial for modelling specific individual differences, partial voluming of signals produced by higher resolution of parcellation likely disrupts model generalisability.

neuroscience↗

bioRxiv2021

Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function.

The relationship between structural and functional brain networks has been characterised as complex: the two networks mirror each other and show mutual influence but they also diverge in their organisation. This work explored whether a combination of structural and functional connectivity can improve predictive models of cognitive performance. Principal Component Analysis (PCA) was first applied to cognitive data from the Human Connectome Project to identify components reflecting five cognitive domains: Executive Function, Self-regulation, Language, Encoding and Sequence Processing. A Principal Component Regression (PCR) approach was then used to fit predictive models of each cognitive domain based on structural (SC), functional (FC) or combined structural-functional (CC) connectivity. Self-regulation, Encoding and Sequence Processing were best modelled by FC, whereas Executive Function and Language were best modelled by CC. The present study demonstrates that integrating structural and functional connectivity can help predict cognitive performance, but that the added explanatory value may be (cognitive) domain-specific. Implications of these results for studies of the brain basis of cognition in health and disease are discussed. HighlightsO_LIWe assessed the relationship between cognitive domains and structural, functional and combined structural-functional connectivity. C_LIO_LIWe found that Executive Function and Language components were best predicted by combined models of functional and structural connectivity. C_LIO_LISelf-regulation, Encoding and Sequence Processing were best predicted by functional connectivity alone. C_LIO_LIOur findings provide insight into separable contributions of functional, structural and combined connectivity to different cognitive domains. C_LI

neuroscience↗

bioRxiv2020

The Effects of Social Stress on Memory: If, How and When

Physical stress, such as from the cold-pressor test, has been robustly associated with altered memory retrieval, but it is not yet clear whether the same happens following psychosocial stress. Studies using psychosocial stressors report mixed effects on memory, leading to uncertainty about the common cognitive impact of both forms of stress. The current study uses a stepped replication design, with four near-identical experiments, each differing by a single critical factor. In three experiments we induced psychosocial stress after participants encoded word stimuli, then assessed retrieval after a prolonged delay. These experiments found no group level influence of postencoding stress on recognition of neutral words or cued recall of word-pairs, but a small effect on recollection of semantically-related words. There was, however, some indication of positive relationships within the stress group between measures of stress (cortisol in experiment 1 and self-reported-anxiety in experiment 3) and recollection of single word stimuli. In the fourth experiment, we found that psychosocial stress immediately before retrieval did not influence word recognition. Overall, our findings demonstrate that psychosocial stress has a typically modest impact on memory, lower than previously claimed, but that individual differences in stress responsivity, particularly for tasks that tap recollection, may help to explain variability in previous findings.

neuroscience↗

bioRxiv2020

Individual differences in social reward and threat expectancies linked to grey matter volumes in key regions of the social brain

Prospection (mentally simulating future events) generates emotionally charged mental images that guide social decision-making. Positive and negative social expectancies - imagining new social interactions to be rewarding vs. threatening - are core components of social approach and avoidance motivation, respectively. Stable individual differences in such positive and negative future-related cognitions may be underpinned by distinct neuroanatomical substrates. Here, we asked 100 healthy adults to vividly imagine themselves in a novel self-relevant social scenario that was ambiguous with regards to possible social acceptance or rejection. During this task we measured their expectancies for social reward (e.g. anticipated feelings of social connection) or threat (e.g. anticipated feelings of rejection). On a separate day they underwent structural MRI; voxel-based morphometry (VBM) was used to explore the relation between their social reward and threat expectancies and regional grey matter volumes (rGMV). Increased rGMV in key regions involved in prospection, subjective valuation and emotion regulation (including ventromedial prefrontal cortex), correlated with both higher social reward and lower social threat expectancies. In contrast, social threat expectancies were uniquely linked with rGMV of regions involved in social attention (posterior superior temporal sulcus) and interoception (somatosensory cortex). These findings provide novel insight into the neurobiology of future-oriented cognitive-affective processes critical to adaptive social functioning.

neuroscience↗

bioRxiv2018

Fatigue and cognitive performance change in MS: multifactorial with disparate influences

BackgroundFatigue is a common and disabling symptom in Multiple Sclerosis (MS) with a variety of direct and indirect influences, but remains poorly understood. Performance-based and self-report measures of fatigue are only weakly correlated and may have independent predictors. We adopted a multifactorial approach, utilising a measure of concurrent cognitive performance change in order to examine the clinical, psychological, and cognitive factors influencing subjective and objective fatigue in MS.\n\nMethodsSixty-one people with MS were assessed. Subjective fatigue was measured using the Modified Fatigue Impact Scale, Fatigue Assessment Instrument, and a Visual Analogue Scale (VAS). The Conners Continuous Performance Test 3 (CCPT3) and VAS were administered before and after two hours of cognitive testing, representing a period of cognitive effort. The differences in scores formed measures of objective performance fatigue and subjective fatigue change, respectively. We examined differences across baseline fatigue, fatigue change and performance change classifications, using regression analysis to uncover predictors of subjective fatigue and performance change.\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@81ec81org.highwire.dtl.DTLVardef@1ce44e8org.highwire.dtl.DTLVardef@10e1bdeorg.highwire.dtl.DTLVardef@147c5ceorg.highwire.dtl.DTLVardef@10b831f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONDemographic and clinical features of the sample\n\nC_TABLECAPTION C_TBL ResultsDepression, sleep, and emotion-focused coping each predicted baseline fatigue and together explained 53.5% of variance. Increased subjective fatigue was linked with anxiety, lower self-efficacy and gender. Cognitive performance change on the CCPT3 was however predicted by estimated general cognitive ability, self-efficacy and post-intervention fatigue.\n\nConclusionSubjective fatigue in MS is a multifactorial construct, with subjective and objective cognitive performance fatigue largely influenced by indirect psychological and cognitive factors. The varying factors driving subjective and objective fatigue suggest that future studies need to take into account these disparate aspects when developing fatigue assessment tools. Targeting influential fatigue drivers such as psychological variables, and even using gender specific interventions may have the potential to improve the burden of fatigue and quality of life of people with MS.

neuroscience↗