Biology subjects

Chakravarty, M.

Publications and source records attributed to Chakravarty, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Aberrant Connectivity Across the Lifespan in a Mouse Model of Alzheimer's disease and Rescue by mGlur5 Modulator Treatment

Amyloid accumulation in Alzheimers disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD (AppNL-G-F/hMapt), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.

neuroscience↗

bioRxiv2023

Network Enrichment Significance Testing in Brain-Phenotype Association Studies

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

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bioRxiv2023

FONDUE: Robust resolution-invariant denoising of MR Images using Nested UNets

Recent human neuroimaging studies tend to have increased magnetic resonance image (MRI) acquisition resolutions, seeking finer levels of detail and more accurate brain morphometry. However, higher-resolution images inherently contain greater amounts of noise contamination, leading to poorer quality brain morphometry if not addressed adequately. This study proposes a novel, robust, resolution-invariant deep learning method to denoise structural human brain MRIs. We explore denoising of T1-weighted (T1w) brain images from varying field strengths (1.5T to 7T), voxel sizes (1.2mm to 250{micro}m), scanner vendors (Siemens, GE, and Phillips), and diseased and healthy participants from a wide age range (young adults to aging individuals). Our proposed Fast-Optimized Network for Denoising through residual Unified Ensembles (FONDUE) method demonstrated stable denoising capabilities across multiple resolutions with performance comparable to the state-of-the-art methods. FONDUE was capable of denoising 0.5mm3 isotropic T1w images in under 3 minutes on an NVIDIA RTX 3090 GPU using less than 8GB of video memory. We have also made the repository of FONDUE as well as its trained weights publicly available on: https://github.com/waadgo/FONDUE.

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bioRxiv2023

Large Data on the Small Brain: Population-wide Cerebellar Growth Models of Children and Adolescents

In the past, the cerebellum has been best known for its crucial role in motor function. However, increasingly more findings highlight the importance of cerebellar contributions in cognitive functions and neurodevelopment. Using large scale, population-wide neuroimaging data, we describe and provide detailed, openly available models of cerebellar development in childhood and adolescence, an important time period for brain development and onset of neuropsychiatric disorders. Next to a traditionally used anatomical parcellation of the cerebellum, we generated growth models based on a recently proposed functional parcellation. In both, we find an anterior-posterior growth gradient mirroring the age-related improvements of underlying behavior and function, which is analogous to cerebral maturation patterns and offers new evidence for directly related cerebello-cortical developmental trajectories. Finally, we illustrate how the current approach can be used to detect cerebellar abnormalities in clinical samples.

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bioRxiv2023

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimers Disease. They are indicative of vascular pathology but represent a mixture of microstructural tissue alterations that is highly variable between individuals. To better understand these alterations, we leveraged the signal of different MRI contrasts sampled within WMHs, which have differential sensitivity to microstructural properties. Subsequently, we sought to examine the asso of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimers Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimers Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimers Disease (n=9) as a means of ascertaining a spectrum of impairment. We sampled the median signal within WMHs on weighted MRI images that are commonly acquired (T1-weighted [T1w], T2-weighted [T2w], T1w/T2w ratio, Fluid-Attenuated Inversion Recovery [FLAIR]), and the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. Main analyses were performed with a periventricular/deep/superficial white matter parcellation and were repeated with a lobar white matter parcellation. We demonstrated that the correlations between WMH signal measures were variable, suggesting that they are likely influenced by different microstructural properties. We observed that the WMH qT2* and FLAIR measures displayed different age- and disease-related trends compared to normal-appearing white matter, highlighting sensitivity to WMH-specific tissue deterioration. Further, WMH qT2* particularly in periventricular and occipital white matter regions was consistently associated with several of our clinical variables of interest using both parcellation schemes in univariate analyses, and further showed high contributions to a pattern of brain variables that was associated with age and cognitive variables in multivariate Partial Least Squares Correlation analyses. qT1 and FLAIR measures showed consistent clinical relationships in multivariate analyses only, while T1w, T2w, and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to WMHs. Combining volumetric and signal measures of WMH, particularly qT2* and to a lesser extent qT1 and FLAIR, should be considered to more precisely characterize the severity of WMHs in vivo. These findings may have implications in determining the reversibility of WMHs and potential efficacy of cardio- and cerebrovascular treatments.

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bioRxiv2022

The impact of study design choices on significance and generalizability of canonical correlation analysis in neuroimaging studies

This technical note describes the effects of different data reduction methods and sample sizes for neuroimaging studies in the context of canonical correlation analysis (CCA). CCA is a multivariate statistical technique which has gained increasing popularity in neuroimaging research in recent years. Here, we investigate the parcellation methods impact on elucidating neuroanatomical relationships (based on cortical thickness) with known risk factors related to Alzheimers disease risk using data from the UK Biobank. The cortical thickness values were parcellated using four common methods in neuroimaging (atlas-based parcellation, spectral clustering, principal component analysis, and independent component analysis) and results from CCA were compared. The results show that the choice of parcellation technique impacts the strength and significance of the correlation between the brain and behaviours. Principal component analysis and independent component analysis result in the strongest correlations. Additionally, we show that regardless of parcellation technique, smaller sample sizes of participants result in inflated correlation strength and significance.

bioinformatics↗

bioRxiv2022

Functional network organization of the mouse cortex determined by wide-field fluorescence imaging shares some --but not all-- properties revealed with simultaneous fMRI-BOLD

Work in humans and animals shows that the brain can be decomposed into large-scale functional networks. Whereas most studies, especially in humans, use the blood-oxygenation-level-dependent (BOLD) signal, the relationship between BOLD and neuronal activity is complex and incompletely understood. This limits our ability to interpret and apply measures derived from fMRI-BOLD. Here, we employ wide-field Ca2+ imaging simultaneously recorded with fMRI-BOLD in highly-sampled mice expressing GCaMP6f in excitatory neurons. These unique data enabled us to characterize the similarities and differences between networks discoverable by each modality. Importantly, we applied a network partitioning approach that uses a mixed-membership algorithm, which allows brain regions to participate in multiple networks with varying strengths. This contrasts with assuming regions belong to only one network. Our findings demonstrate that (1) most BOLD networks are detected via Ca2+ signals. (2) There is considerable overlapping--as opposed to disjoint--network organization that is evident from both modalities. (3) Large-scale networks determined by Ca2+ signals at low temporal frequencies (0.01 - 0.5 Hz)--as opposed to higher frequencies (0.5 - 5 Hz)--are more similar to those determined by BOLD. (4) Despite many similarities, differences emerge across modes including the spatial distribution of membership diversity (the extent to which regions affiliate with multiple networks). In sum, Ca2+ imaging of excitatory neurons confirms that the mouse cortex is functionally organized into overlapping large-scale networks in a manner that reflects many, but not all, properties observable with simultaneous fMRI-BOLD; affirming the neural origins of patterns of brain organization that are evident in a clinically accessible neuroimaging modality.

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bioRxiv2022

Human Brain Development: a cross-sectional and longitudinal study integrating multiple neuromorphological features

Brain maturation studies typically examine relationships linking a single morphometric feature with aspects of cognition, behavior, age, or other demographic characteristics. However, the coordinated spatiotemporal arrangement of morphological features across development and their associations with behavior are unclear. Here, we examine covariation across multiple cortical features (cortical thickness [CT], surface area [SA], local gyrification index [GI], and mean curvature [MC]) using magnetic resonance images from the long-running National Institute of Mental Health developmental cohort (ages 5-25). Neuroanatomical covariance was examined using non-negative matrix factorization (NMF), which decomposes covariance resulting in a parts-based representation. Cross-sectionally, we identified six components of covariation which demonstrate differential contributions of CT, GI, and SA in hetero- vs. unimodal areas. We sought to use this technique longitudinally to examine covariance in rates of change, which highlighted a preserved SA in unimodal areas and changes in CT and GI in heteromodal areas. Using behavioral partial least squares (PLS), we identified a single latent variable (LV; 96 % covariance explained) that recapitulated patterns of reduced CT, GI, and SA that are generally related to older age, with limited contributions of IQ and SES. Longitudinally, PLS revealed three LVs that demonstrated a nuanced developmental pattern that highlighted a higher rate of maturational change in SA and CT in higher IQ and SES females. This novel characterization of brain maturation provides an important understanding of the interdependencies between morphological measures, their coordinated development, and their relationship to biological sex, cognitive ability, and the resources of the local environment. SignificanceThe complex anatomy of the cortical sheet is best characterized using multiple morphometric characteristics. We expanded on recent developments in matrix factorization to identify spatial patterns of covariance across the cortical sheet. Using a large, well-characterized dataset, we examined the differential contributions of neuroanatomical features to cortical covariation in a single analytical framework using both cross-sectional and longitudinal data. We identified dominant modes of covariance between cortical morphometric features and their coordinated pattern of change, demonstrating sexually differentiated patterns and a strong association with variability in age, socioeconomic status, and cognitive ability. This novel characterization of cortical morphometry provides an important understanding of the interdependencies between neuroanatomical measures in the brain and behavioral development context.

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bioRxiv2022

Variation in subcortical anatomy: relating interspecies differences, heritability, and brain-behavior relationships

There has been an immense research focus on the topic of cortical reorganization in human evolution, but much less is known regarding the reorganization of subcortical circuits which are intimate working partners of the cortex. Here, by combining advanced image analysis techniques with comparative neuroimaging data, we systematically map organizational differences in striatal, pallidal and thalamic anatomy between humans and chimpanzees. We relate interspecies differences, a proxy for evolutionary changes, to genetics and behavioral correlates. We show that highly heritable morphological measures are significantly expanded across species, in contrast to previous findings in the cortex. The identified morphological-cognitive latent variables were associated with striatal expansion, and affective latent variables were associated with more evolutionarily-conserved areas in the thalamus and globus pallidus. These findings provide new insight into the architecture of these subcortical hubs and can provide greater information on the role of these structures in health and illness.

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bioRxiv2022

Neuromaps: structural and functional interpretation of brain maps

Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Modern scientific discovery relies on making comparisons between new maps (e.g. task activations, group structural differences) and these reference maps. Although recent data sharing initiatives have increased the accessibility of such brain maps, data are often shared in disparate coordinate systems (or "spaces"), precluding systematic and accurate comparisons among them. Here we introduce the neuromaps toolbox, an open-access software package for accessing, transforming, and analyzing structural and functional brain annotations. We implement two registration frameworks to generate high-quality transformations between four standard coordinate systems commonly used in neuroimaging research. The initial release of the toolbox features >40 curated reference maps and biological ontologies of the human brain, including maps of gene expression, neurotransmitter receptors, metabolism, neurophysiological oscillations, developmental and evolutionary expansion, functional hierarchy, individual functional variability, and cognitive specialization. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. By combining open-access data with transparent functionality for standardizing and comparing brain maps, the neuromaps software package provides a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain.

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bioRxiv2021

Myelin imaging of the basal forebrain in first-episode psychosis

Cholinergic dysfunction has been implicated in the pathophysiology of psychiatric disorders such as schizophrenia, depression, and bipolar disorder. The basal forebrain (BF) cholinergic nuclei, defined as cholinergic cell groups Ch1-3 and Ch4 (Nucleus Basalis of Meynert; NBM), provide extensive cholinergic projections to the rest of the brain. Here, we examined microstructural neuroimaging measures of the cholinergic nuclei in patients with untreated psychosis ([~] 31 weeks of psychosis, <2 defined daily dose of antipsychotics) and used Magnetic Resonance Spectroscopy (1H-MRS) and transcriptomic data to support our findings. We used a cytoarchitectonic atlas of the BF to map the nuclei and obtained measures of myelin (quantitative T1, or qT1 as myelin surrogate) and microstructure (axial diffusion; AxD). In a clinical sample (n=85; 29 healthy controls, 56 first-episode psychosis), we found significant correlations between qT1 and 1H-MRS-based dorsal anterior cingulate choline in healthy controls, while this relationship was disrupted in FEP. Case-control differences in qT1 and AxD were observed in the Ch1-3, with increased qT1 (reflecting reduced myelin content) and AxD (reflecting reduced axonal integrity). We found clinical correlates between left NBM qT1 with manic symptom severity, and AxD with negative symptom burden in FEP. Intracortical and subcortical myelin maps were derived and correlated with BF myelin. BF-cortical and BF-subcortical myelin correlations demonstrate known projection patterns from the BF. Using data from the Allen Human Brain Atlas, cholinergic nuclei showed significant enrichment for schizophrenia and depression-related genes. Cell-type specific enrichment indicated enrichment for cholinergic neuron markers as expected. Further relating the neuroimaging correlations to transcriptomics demonstrated links with cholinergic receptor genes and cell type markers of oligodendrocytes and cholinergic neurons, providing biological validity to the measures. These results provide genetic, neuroimaging, and clinical evidence for cholinergic dysfunction in schizophrenia and other psychiatric disorders such as depression.

neuroscience↗

bioRxiv2021

Microstructural variation in the human striatum using non-negative matrix factorization

The striatum is a major subcortical connection hub that has been heavily implicated in a wide array of motor and cognitive functions. Here, we developed a normative multimodal, data-driven microstructural parcellation of the striatum using multiple magnetic resonance imaging-based metrics (mean diffusivity, fractional anisotropy, and the ratio between T1- and T2-weighted structural) from the Human Connectome Project Young Adult dataset (n=329 unrelated participants, age range: 22-35, F/M: 185/144). We further explored the biological and functional relationships of this parcellation by relating our findings to motor and cognitive performance in tasks known to involve the striatum as well as demographics. We identified 5 spatially distinct striatal components, for each hemisphere. We also show the gain in component stability when using multimodal versus unimodal metrics. Our findings suggest distinct microstructural patterns in the human striatum that are largely symmetric and that relate mostly to age and sex. Our work also highlights the putative functional relevance of these striatal components to different designations based on a Neurosynth meta-analysis.

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bioRxiv2021

Longitudinal characterization of neuroanatomical changes in the Fischer 344 rat brain during normal aging and between sexes

Animal models are widely used to study the pathophysiology of disease and to evaluate the efficacy of novel interventions, crucial steps towards improving disease outcomes in humans. The Fischer 344 (F344) wildtype rat is a common experimental background strain for transgenic models of disease and is also one of the most frequently used models in aging research. Despite frequency of use, characterization of neuroanatomical change with age has not been performed in the F344 rat. To this end, we present a comprehensive longitudinal examination of morphometric change in 73 brain regions and at a voxel-wise level during normative aging in a mixed-sex cohort of F344 rats. We identified age- and sex-related changes in regions such as the cortex, hippocampus, cingulum, caudoputamen, and nucleus accumbens, which are implicated in memory and motor control circuits frequently affected by aging and neurodegenerative disease. These findings provide a baseline for neuroanatomical changes associated with aging in male and female F344 rats, to which data from transgenic models or other background strains can be compared. HIGHLIGHTSO_LIIn vivo magnetic resonance imaging reveals altered neuroanatomy in aging Fischer rats C_LIO_LILinear and curvilinear age effects exist in both grey and white matter structures C_LIO_LISex differences are primarily seen in grey matter structures C_LIO_LIThis study clarifies normal aging trajectories across 73 brain regions in both sexes C_LIO_LIImproved understanding of normal aging will inform future pathological aging studies C_LI

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bioRxiv2021

Individual variation in brain microstructural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52{+/-} 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 {+/-}4.9 years) and late-life (mean age = 67.7 {+/-}4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 {+/-}4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions that are both positively and negatively associated with cortical structure.

neuroscience↗

bioRxiv2020

Hippocampus shape across the healthy lifespan and its relationship with cognition

The study of the hippocampus across the healthy adult lifespan has rendered inconsistent findings. While volumetric measurements have often been a popular technique for analysis, more advanced morphometric techniques have demonstrated compelling results that highlight the importance and improved specificity of shape-based measures. Here, the MAGeT Brain algorithm was applied on 134 healthy individuals aged 18-81 years old to extract hippocampal subfield volumes and hippocampal shape measurements, notably: local surface area (SA) and displacement. We used linear, second or third order natural splines to examine the relationships between hippocampal measures and age. In addition, partial least squares analyses were performed to relate measurements with cognitive and demographic information. Volumetric results indicated a relative preservation of the right cornus ammonis 1 with age and a global volume reduction linked with older age, female sex, lower levels of education and cognitive performance. Vertex-wise analysis demonstrated an SA preservation in the anterior hippocampus with a peak during the sixth decade, while the posterior hippocampal SA gradually decreased across lifespan. Overall, SA decrease was linked to older age, female sex and, to a lesser extent lower levels of education and cognitive performance. Outward displacement in the lateral hippocampus and inward displacement in the medial hippocampus were enlarged with older age, lower levels of cognition and education, indicating an accentuation of the hippocampal "C" shape with age. Taken together, our findings suggest that vertex-wise analyses have higher spatial specifity and that sex, education and cognition are implicated in the differential impact of age on hippocampal subregions throughout its antero-posterior and medial-lateral axes.

neuroscience↗

bioRxiv2020

Hippocampal subfield volumes across the healthy lifespan and the effects of MR sequence on estimates

The hippocampus has been extensively studied in various neuropsychiatric disorders throughout the lifespan. However, inconsistent results have been reported with respect to which subfield volumes are most related to age. Here, we investigate whether these discrepancies may be explained by experimental design differences that exist between studies. Multiple datasets were used to collect 1690 magnetic resonance scans from healthy individuals aged 18-95 years old. Standard T1-weighted (T1w; MPRAGE sequence, 1 mm3 voxels), high-resolution T2-weighted (T2w; SPACE sequence, 0.64 mm3 voxels) and slab T2-weighted (Slab; 2D turbo spin echo, 0.4 x 0.4 x 2 mm3 voxels) images were acquired. The MAGeT Brain algorithm was used for segmentation of the hippocampal grey matter (GM) subfields and peri-hippocampal white matter (WM) subregions. Linear mixed-effect models and Akaike information criterion were used to examine linear, second or third order natural splines relationship between hippocampal volumes and age. We demonstrated that stratum radiatum/lacunosum/moleculare and fornix subregions expressed the highest relative volumetric decrease, while the cornus ammonis 1 presented a relative volumetric preservation of its volume with age. We also found that volumes extracted from slab images were often underestimated and demonstrated different age-related relationships compared to volumes extracted from T1w and T2w images. The current work suggests that although T1w, T2w and slab derived subfield volumetric outputs are largely homologous, modality choice plays a meaningful role in the volumetric estimation of the hippocampal subfields.

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bioRxiv2019

Ultra-high field imaging of hippocampal neuroanatomy in first episode psychosis demonstrates receptor-specific morphometric patterning

ObjectiveThe hippocampus is considered a putative marker in schizophrenia with early volume deficits of select subfields. Certain subregions are thought to be more vulnerable due to a glutamate-driven mechanism of excitotoxicity, hypermetabolism, and then degeneration. Here, we explored whether hippocampal anomalies in first-episode psychosis (FEP) correlate with glutamate receptor density via a serotonin receptor proxy by leveraging structural neuroimaging, spectroscopy (MRS), and gene expression.\n\nMethodsHigh field 7T brain MR images were collected from 27 control, 41 FEP participants, along with 1H-MRS measures of glutamate. Automated methods were used to delineate the hippocampus and atlases of the serotonin receptor system were used to map receptor density across the hippocampus and subfields. We used gene expression data from the Allen Human Brain Atlas to test for correlations between serotonin and glutamate receptor genes.\n\nResultsWe found reduced hippocampal volumes in FEP, replicating previous findings. Amongst the subfields, CA4-dentate gyrus showed greatest reductions. Gene expression analysis indicated 5-HTR1A and 5-HTR4 receptor subtypes as predictors of AMPA and NMDA receptor expression, respectively. Volumetric differences in the subfields correlated most strongly with 5-HT1A (R=0.64, p=4.09E-03) and 5-HT4 (R=0.54, p=0.02) densities as expected, and replicated using previously published data from two FEP studies. Measures of individual structure-receptor alignment were derived through normative modeling of hippocampal shape and correlations to receptor distributions, termed Receptor-Specific Morphometric Signatures (RSMS). Right-sided 5-HT4 RSMS was correlated with glutamate (R=0.357, p=0.048).\n\nConclusionsWe demonstrate glutamate-driven hippocampal remodeling in FEP through a receptor-density gated mechanism, thus providing a mechanistic explanation of how redox dysregulation affects brain structure and symptomatic heterogeneity in schizophrenia.

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bioRxiv2019

An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain for Automated Anatomical Segmentation

This paper reports the development of a high-resolution 3-D MRI atlas of the Fischer 344 adult rat brain. The atlas is a 60 m isotropic image volume composed of 256 coronal slices with 71 manually delineated structures and substructures. The atlas was developed using Pydpiper image registration pipeline to create an average brain image of 41 four-month-old male and female Fischer 344 rats. Slices in the average brain image were then manually segmented, individually and bilaterally, on the basis of image contrast in conjunction with Paxinos and Watsons (2007) stereotaxic rat brain atlas. Summary statistics (mean and standard deviation of regional volumes) are reported for each brain region across the sample used to generate the atlas, and a statistical comparison of a chosen subset of regional brain volumes between male and female rats is presented. On average, the coefficient of variation of regional brain volumes across all rats in our sample was 4%, with no individual brain region having a coefficient of variation greater than 13%. A full description of methods used, as well as the atlas, the template that the atlas was derived from, and a masking file, can be found at Zenodo at https://doi.org/10.5281/zenodo.3555556. To our knowledge, this is the first MRI atlas created using Fischer 344 rats and will thus provide an appropriate neuroanatomical model for researchers working with this strain. HIGHLIGHTS Open-access high-resolution anatomical MRI template for Fischer 344 rat brain. Segmented atlas of 71 regions for use as a tool in Fischer 344 preclinical research paradigms. Analysis of population variability of regional brain volumes. Analysis of sex-differences in regional brain volumes KEYWORDS: Fischer 344; Structural MRI; Segmentation; Rat brain template; Digital brain atlas; Sex-differences;

neuroscience↗