Biology subjects

Davey, C.

Publications and source records attributed to Davey, C..

11 recordsLinked to original sources

bioRxiv2026

Mapping the neural circuitry of cognitive restructuring in depressive and anxiety disorders

BackgroundCognitive restructuring, the process of identifying and challenging negative thoughts, is a key technique for treating depressive and anxiety disorders. Although neuroimaging studies have characterised the brain systems supporting cognitive restructuring in healthy individuals, it remains unclear how these systems are altered in depression and anxiety, or whether each disorder is associated with distinct neural dysfunction. MethodsSeventy-three clinical participants with depressive or anxiety disorders and 70 healthy controls completed a cognitive restructuring paradigm during 7 Tesla functional magnetic resonance imaging (fMRI). The task required participants to either repeat a series of negative statements or challenge them using Socratic questioning. Group-level fMRI analyses examined the effects of depressive and anxiety symptom severity on brain activation, while dynamic causal modelling characterized the directional neural influences between implicated regions. ResultsDuring challenging compared to repeating statements, greater depressive symptoms were associated with reduced dorsolateral prefrontal cortex (dlPFC) activation. Conversely, greater anxiety symptoms were associated with greater dlPFC activation. Effective connectivity results revealed that depressive symptoms were associated with greater inhibition from the ventrolateral prefrontal cortex (vlPFC) to the ventromedial prefrontal cortex, whereas anxiety symptoms were associated with greater excitation from the dlPFC to amygdala and greater inhibition from the vlPFC to amygdala. ConclusionsWhile clinical participants modified negative beliefs as effectively as healthy controls, depressive and anxiety symptoms were associated with dissociable neural signatures during restructuring. This suggests that cognitive behavioral therapy may engage partially distinct mechanisms depending on symptom profile, a possibility that warrants longitudinal investigation of treatment response.

neuroscience↗

bioRxiv2026

Perm1 Gene Therapy Mitigates PRDM16-Associated Cardiomyopathy

BackgroundPathogenic variants in PR domain containing 16 (PRDM16) cause pediatric and adult cardiomyopathies characterized by ventricular dilation, systolic dysfunction, and impaired metabolic maturation. Cardiac deficiency of PRDM16 alters metabolic gene expression and long-chain fatty acid (FA) metabolites. However, the downstream mediators involved are not well characterized. Furthermore, whether improving mitochondrial FA metabolism can prevent PRDM16-associated cardiomyopathy is currently unknown. MethodsIn vivo and in vitro approaches using patient-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and mouse models with Prdm16 deletion/mutation were employed. Transcriptomics and proteomics analyses were conducted, and adeno-associated virus (AAV)-mediated therapy was tested. ResultsHere, we show that a defect in FA metabolism is an early hallmark of PRDM16 cardiac deficiency. We show, for the first time, that PERM1 is a direct downstream target of PRDM16 and is involved in the regulation of FA metabolism through coordinated action with PGC1. Most importantly, neonatal delivery of AAV9-Perm1 in cardiac-specific Prdm16 knockout (Prdm16 cKO) mice markedly improved contractile parameters, reduced left ventricular (LV) dilation, and extended survival. These cardioprotective effects of PERM1 gene therapy occurred independent of restoring FA oxidation. Transcriptional and proteomic analyses of AAV-Perm1-treated Prdm16 cKO mice demonstrated significant improvements in mitochondrial cristae architecture, preservation of sarcomere organization, reduced cardiomyocyte apoptosis, attenuated myocardial fibrosis, and diminished cardiac remodeling. ConclusionsWe identify PERM1 as a direct downstream effector of PRDM16 and uncover a previously unrecognized PRDM16-PGC1-PERM1 axis essential for FA metabolic regulation in the heart. Perm1 gene therapy ameliorated PRDM16-associated cardiomyopathy through post-transcriptional mechanisms involving preservation of mitochondrial and sarcomere integrity. The current study provides preclinical evidence suggesting that Perm1 gene therapy may be a promising therapeutic target to improve the cardiac outcomes of patients affected by pathogenic PRDM16 variants.

physiology↗

bioRxiv2025

Modelling Predictive Coding in the Primary Visual Cortex (V1): Layer 4 Receptive Field Properties in a Balanced Recurrent Spiking Neuronal Network

Understanding how the cortex encodes sensory input in a biologically efficient and computationally robust manner remains a central question in neuroscience. Predictive coding offers a compelling theoretical framework for such cortical processing, but existing models lack the biological detail to fully explain the function of the cortical microcircuits. This study introduces a spiking neural network model of layer 4 of the primary visual cortex (V1), grounded in predictive coding principles, to clarify how the thalamorecipient layer transforms feedforward input into prediction-error-like signals under realistic excitatory-inhibitory constraints and to yield testable circuit-level predictions. The model integrates structured feedforward input, distinct excitatory and inhibitory populations, and balanced lateral connectivity to simulate spontaneous and stimulus-driven activity. Network responses are systematically examined under spatially unstructured noise input and structured grating stimuli. Neural membrane potentials encode real-time reconstruction errors between external input and internal estimates, with spikes dynamically correcting these mismatches. The network reproduces hallmark in vivo features, including irregular spontaneous activity, sparse and selective responses, and emergent orientation and phase tuning. Excitatory-Inhibitory (E-I) balance was maintained across conditions, with inhibitory neurons exhibiting tighter input coupling than excitatory neurons. Furthermore, the network exhibited contrast-dependent modulation of firing rates and E-I balance, dynamically adjusting its activity to changes in input strength. Decoding analyses demonstrates that structured inputs can be robustly reconstructed under moderate noise levels, although decoding fidelity declines sharply under severe corruption. Together, these results suggest that cortical layer 4 may serve as a structured sensory encoding stage in a hierarchical predictive coding system, providing a biologically grounded foundation for modeling prediction error computations in higher cortical areas. Author summaryIn this Study, we present a biologically grounded spiking neural network model of layer 4 of the primary visual cortex, built within the predictive coding framework. The aim is to better understand how this early cortical layer encodes sensory information while maintaining realistic neural dynamics. Many predictive coding models focus on higher cortical layers 2/3 and overlook layer 4s role. To address this, we develop here a network that integrates structured feedforward input via Gaborfiltered receptive fields, distinct excitatory and inhibitory populations, and fixed lateral connectivity, all adhering to Dales law. The model reproduces several in vivo features observed in layer 4 of the visual cortex, including sparse, irregular spiking, emergent orientation and phase tuning, and contrast-dependent firing. Notably, excitation and inhibition are dynamically balanced across input conditions without requiring synaptic learning. We also show that decoding performance remains robust under moderate noise levels, supporting that layer 4 provides a stable sensory foundation for higher-level prediction. This model offers a biologically realistic implementation of prediction error computation and sets the stage for hierarchical extensions that include feedback and learning. Overall, this work provides insights into how structured sensory representations and balance emerge in cortical microcircuits through architecture alone.

neuroscience↗

bioRxiv2025

Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study

ImportanceMajor depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. ObjectiveTo use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. Design, setting, and participantsA normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Main outcome measuresZ-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. ResultsZ-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Conclusions and relevanceOur study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture. Key points QuestionCan z-scores derived from normative modelling shed light on the heterogeneous group-level findings of cortical thickness abnormalities in major depression and what characterises individuals at the extreme ends of cortical thickness abnormalities? FindingWe confirmed a large overlap in z-score distributions between depressed individuals and healthy controls and a heterogeneous spatial distribution of extreme z-deviations across brain regions across individual patients. Lower z-scores for cortical thickness were related to more severe clinical characteristics. MeaningOur findings confirm the heterogeneity in individual variation in the location and extent of CT abnormalities across patients with MDD and stress the importance of individualised predictions when examining cortical thickness abnormalities.

neuroscience↗

bioRxiv2024

Conserved Noncoding Cis-Elements Associated with Hibernation Modulate Metabolic and Behavioral Adaptations in Mice

Our study elucidates functional roles for conserved cis-elements associated with the evolution of mammalian hibernation. Genomic analyses found topologically associated domains (TADs) that disproportionately accumulated convergent genomic changes in hibernators, including the TAD for the Fat Mass & Obesity (Fto) locus. Some hibernation-linked cis-elements in this TAD form regulatory contacts with multiple neighboring genes. Knockout mice for these cis-elements exhibit Fto, Irx3, and Irx5 gene expression changes, impacting hundreds of genes downstream. Profiles of pre-torpor, torpor, and post-torpor phenotypes found distinct roles for each cis-element in metabolic control, while a high caloric diet uncovered different obesogenic effects. One cis-element promoting a lean phenotype influences foraging behaviors throughout life, affecting specific behavioral sequences. Thus, convergent evolution in hibernators pinpoints functional genetic mechanisms of mammalian metabolic control. One-sentence summaryDeletions of conserved cis-elements tied to hibernator evolution causes diverse metabolic traits in mice.

genomics↗

bioRxiv2023

A Brain Model of Disturbed Self-Appraisal in Social Anxiety Disorder

The brains default mode network has a central role in the processing of information concerning oneself. Dysfunction in this self-referential processing represents a key component of multiple mental health conditions, including social anxiety disorder (SAD). This case-control study aimed to clarify alterations to network dynamics present during self-appraisal in SAD participants. A total of 38 adolescents and young adults with SAD and 72 healthy control participants underwent a self-referential processing fMRI task. The task involved two primary conditions of interest: direct self-appraisal (thinking about oneself) and reflected self-appraisal (thinking about how others might think about oneself). Dynamic causal modelling and parametric empirical Bayes were then used to explore differences in the effective connectivity of the default mode network between groups. We observed connectivity differences between SAD and healthy control participants in the reflected self-appraisal but not the direct self-appraisal condition. Specifically, SAD participants exhibited greater excitatory connectivity from the posterior cingulate cortex (PCC) to medial prefrontal cortex (MPFC) and greater inhibitory connectivity from the inferior parietal lobule (IPL) to MPFC. In contrast, in the absence of task modulation, SAD participants exhibited reduced intrinsic connectivity, with reduced excitatory connectivity from the PCC to MPFC and reduced inhibitory connectivity from the IPL to MPFC. As such, participants with SAD showed changes to afferent connections to the MPFC which occurred during both reflected self-appraisal as well as intrinsically. The presence of connectivity differences in reflected and not direct self-appraisal is consistent with the characteristic fear of negative social evaluation that is experienced by people with SAD.

neuroscience↗

bioRxiv2021

Cortico-striatal activity characterizes human safety learning via Pavlovian conditioned inhibition

Safety learning generates associative links between neutral stimuli and the absence of threat, promoting the inhibition of fear and security-seeking behaviours. Precisely how safety learning is mediated at the level of underlying brain systems, particularly in humans, remains unclear. Here, we integrated a novel Pavlovian conditioned inhibition task with ultra-high field (UHF) fMRI to examine the neural basis of inhibitory safety learning in 49 healthy participants. In our task, participants were conditioned to two safety signals: a conditioned inhibitor that predicted threat-omission when paired with a known threat signal (A+/AX-), and a standard safety signal that generally predicted threat-omission (BC-). Both safety signals evoked equivalent autonomic and subjective learning responses but diverged strongly in terms of underlying brain activation. The conditioned inhibitor was characterized by more prominent activation of the dorsal striatum, anterior insular and dorsolateral prefrontal cortex compared to the standard safety signal, whereas the latter evoked greater activation of the ventromedial prefrontal cortex, posterior cingulate and hippocampus, among other regions. Further analyses of the conditioned inhibitor indicated that its initial learning was characterized by consistent engagement of dorsal striatal, midbrain, thalamic, premotor, and prefrontal subregions. These findings suggest that safety learning via conditioned inhibition involves a distributed cortico-striatal circuitry, separable from broader cortical regions involved with processing standard safety signals (e.g., CS-). This cortico-striatal system could represent a novel neural substrate of safety learning, underlying the initial generation of stimulus-safety associations, distinct from wider cortical correlates of safety processing, which facilitate the behavioral outcomes of learning. Significance statementIdentifying safety is critical for maintaining adaptive levels of anxiety, but the neural mechanisms of human safety learning remain unclear. Using ultra-high field fMRI, we compared learning-related brain activity for a conditioned inhibitor, which actively predicted threat-omission, and a standard safety signal (CS-), which was passively unpaired with threat. The inhibitor engaged an extended circuitry primarily featuring the dorsal striatum, along with thalamic, midbrain, and premotor/prefrontal cortex regions. The CS-exclusively involved cortical safety-related regions observed in basic safety conditioning, such as the vmPFC. These findings extend current models to include learning-specific mechanisms for encoding stimulus-safety associations, which might be distinguished from expression-related cortical mechanisms. These insights may suggest novel avenues for targeting dysfunctional safety learning in psychopathology.

neuroscience↗

bioRxiv2020

Place cells in head-fixed mice navigating a floating real-world environment

The hippocampal place cell system in rodents has provided a major paradigm for the scientific investigation of memory function and dysfunction. Place cells have been observed in area CA1 of the hippocampus of both freely moving animals, and of head-fixed animals navigating in virtual reality environments. However, spatial coding in virtual reality preparations has been observed to be impaired. Here we show that the use of a real-world environment system for head-fixed mice, consisting of a track floating on air, provides some advantages over virtual reality systems for the study of spatial memory. We imaged the hippocampus of head-fixed mice injected with the genetically encoded calcium indicator GCaMP6s while they navigated circularly constrained or open environments on the floating platform. We observed consistent place tuning in a substantial fraction of cells with place fields remapping when animals entered a different environment. When animals re-entered the same environment, place fields typically remapped over a time period of multiple days, faster than in freely moving preparations, but comparable with virtual reality. Spatial information rates were within the range observed in freely moving mice. Manifold analysis indicated that spatial information could be extracted from a low-dimensional subspace of the neural population dynamics. This is the first demonstration of place cells in head-fixed mice navigating on an air-lifted real-world platform, validating its use for the study of brain circuits involved in memory and affected by neurodegenerative disorders.

neuroscience↗

bioRxiv2020

Greater male than female variability in regional brain structure across the lifespan

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

neuroscience↗

bioRxiv2019

Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates

BackgroundDepression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum and insular cortex).\n\nMethodsK-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15-25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Insula surface area and thickness and ventral striatum volume were compared between the subtypes using structural MRI.\n\nResultsThree subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls and the moderate subtype.\n\nConclusionsOur findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.

neuroscience↗

bioRxiv2019

Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group

BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset. MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain predicted age difference (brain-PAD). FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohens d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004). InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates. FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.

neuroscience↗