Functional corticostriatal connection topographies predict goal directed behaviour in humans

Resting-State Changes in Aging and Parkinson's Disease Are Shaped by Underlying Neurotransmission: A Normative Modeling Study

BACKGROUND

Human healthy and pathological aging is linked to a steady decline in brain resting-state activity and connectivity measures. The neurophysiological mechanisms that underlie these changes remain poorly understood.

METHODS

Making use of recent developments in normative modeling and availability of in vivo maps for various neurochemical systems, we tested in the UK Biobank cohort (n = 25,917) whether and how age- and Parkinson's disease-related resting-state changes in commonly applied local and global activity and connectivity measures colocalize with underlying neurotransmitter systems.

RESULTS

We found that the distributions of several major neurotransmitter systems including serotonergic, dopaminergic, noradrenergic, and glutamatergic neurotransmission correlated with age-related changes across functional activity and connectivity measures. Colocalization patterns in Parkinson's disease deviated from normative aging trajectories for these, as well as for cholinergic and GABAergic (gamma-aminobutyric acidergic) neurotransmission. The deviation from normal colocalization of brain function and GABAA correlated with disease duration.

CONCLUSIONS

These findings provide new insights into molecular mechanisms underlying age- and Parkinson's-related brain functional changes by extending the existing evidence elucidating the vulnerability of specific neurochemical attributes to normal aging and Parkinson's disease. The results particularly indicate that alongside dopamine and serotonin, increased vulnerability of glutamatergic, cholinergic, and GABAergic systems may also contribute to Parkinson's disease-related functional alterations. Combining normative modeling and neurotransmitter mapping may aid future research and drug development through deeper understanding of neurophysiological mechanisms that underlie specific clinical conditions.

Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps

Finding an interpretable and compact representation of complex neuroimaging data is extremely useful for understanding brain behavioral mapping and hence for explaining the biological underpinnings of mental disorders. However, hand-crafted representations, as well as linear transformations, may inadequately capture the considerable variability across individuals. Here, we implemented a data-driven approach using a three-dimensional autoencoder on two large-scale datasets. This approach provides a latent representation of high-dimensional task-fMRI data which can account for demographic characteristics whilst also being readily interpretable both in the latent space learned by the autoencoder and in the original voxel space. This was achieved by addressing a joint optimization problem that simultaneously reconstructs the data and predicts clinical or demographic variables. We then applied normative modeling to the latent variables to define summary statistics ('latent indices') and establish a multivariate mapping to non-imaging measures. Our model, trained with multi-task fMRI data from the Human Connectome Project (HCP) and UK biobank task-fMRI data, demonstrated high performance in age and sex predictions and successfully captured complex behavioral characteristics while preserving individual variability through a latent representation. Our model also performed competitively with respect to various baseline models including several variants of principal components analysis, independent components analysis and classical regions of interest, both in terms of reconstruction accuracy and strength of association with behavioral variables.

A shifting role of thalamocortical connectivity in the emergence of cortical functional organization

The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.

Linking functional and structural brain organisation with behaviour in healthy adults

Multimodal data integration approaches, such as Linked Independent Component Analysis (LICA), increase sensitivity to brain-behaviour relationships and allow us to probe the relationship between modalities. Here we focus on inter-regional functional and structural organisation to determine if organisational patterns persist across modalities and if investigating multi-modality organisations provides increased sensitivity to brain-behaviour associations. We utilised multimodal magnetic resonance imaging (MRI; T1w, resting-state functional [fMRI] and diffusion weighted [DWI]) and behavioural data from the Human Connectome Project (HCP, n=676; 51% female). Unimodal features were extracted to produce individual grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps from the T1w, DWI and fMRI data, respectively. DWI and fMRI analyses were restricted to subcortical regions for computational reasons. LICA was then used to integrate features, generating 100 novel independent components. Associations between these components and demographic/behavioural (n=308) variables were examined. 15 components were significantly associated with various demographic/behavioural measures. 2 components were strongly related to various measures of intoxication, driven by DWI and resemble components previously identified. Another component was driven by striatal functional data and related to working memory. A small number of components showed shared variance between structure and function but none of these displayed any significant behavioural associations. Our working memory findings provide support for the use of fMRI connectopic mapping in future research of working memory. Given the lack of behaviourally relevant shared variance between functional and structural organisation, as indexed here, we question the utility of integrating connectopic maps and tractography data.

Neurocomputational model of compulsivity: deviating from an uncertain goal-directed system

Despite a theory that an imbalance in goal-directed versus habitual systems serve as building blocks of compulsions, research has yet to delineate how this occurs during arbitration between the two systems in obsessive-compulsive disorder. Inspired by a brain model in which the inferior frontal cortex selectively gates the putamen to guide goal-directed or habitual actions, this study aimed to examine whether disruptions in the arbitration process via the fronto-striatal circuit would underlie imbalanced decision-making and compulsions in patients. Thirty patients with obsessive-compulsive disorder [mean (standard deviation) age = 26.93 (6.23) years, 12 females (40%)] and 30 healthy controls [mean (standard deviation) age = 24.97 (4.72) years, 17 females (57%)] underwent functional MRI scans while performing the two-step Markov decision task, which was designed to dissociate goal-directed behaviour from habitual behaviour. We employed a neurocomputational model to account for an uncertainty-based arbitration process, in which a prefrontal arbitrator (i.e. inferior frontal gyrus) allocates behavioural control to a more reliable strategy by selectively gating the putamen. We analysed group differences in the neural estimates of uncertainty of each strategy. We also compared the psychophysiological interaction effects of system preference (goal-directed versus habitual) on fronto-striatal coupling between groups. We examined the correlation between compulsivity score and the neural activity and connectivity involved in the arbitration process. The computational model captured the subjects' preferences between the strategies. Compared with healthy controls, patients had a stronger preference for the habitual system (t = -2.88, P = 0.006), which was attributed to a more uncertain goal-directed system (t = 2.72, P = 0.009). Before the allocation of controls, patients exhibited hypoactivity in the inferior frontal gyrus compared with healthy controls when this region tracked the inverse of uncertainty (i.e. reliability) of goal-directed behaviour (P = 0.001, family-wise error rate corrected). When reorienting behaviours to reach specific goals, patients exhibited weaker right ipsilateral ventrolateral prefronto-putamen coupling than healthy controls (P = 0.001, family-wise error rate corrected). This hypoconnectivity was correlated with more severe compulsivity (r = -0.57, P = 0.002). Our findings suggest that the attenuated top-down control of the putamen by the prefrontal arbitrator underlies compulsivity in obsessive-compulsive disorder. Enhancing fronto-striatal connectivity may be a potential neurotherapeutic approach for compulsivity and adaptive decision-making.

Systematically altered connectome gradient in benign childhood epilepsy with centrotemporal spikes: Potential effect on cognitive function

OBJECTIVE

Benign childhood epilepsy with centrotemporal spikes (BECTS) affects brain network hierarchy and cognitive function; however, itremainsunclearhowhierarchical changeaffectscognition in patients with BECTS. A major aim of this study was to examine changes in the macro-network function hierarchy in BECTS and its potential contribution to cognitive function.

METHODS

Overall, the study included 50 children with BECTS and 69 healthy controls. Connectome gradient analysis was used to determine the brain network hierarchy of each group. By comparing gradient scores at each voxel level and network between groups, we assessed changes in whole-brain voxel-level and network hierarchy. Functional connectivity was used to detect the functional reorganization of epilepsy caused by these abnormal brain regions based on these aberrant gradients. Lastly, we explored the relationships between the change gradient and functional connectivity values and clinical variables and further predicted the cognitive function associated with BECTS gradient changes.

RESULTS

In children with BECTS, the gradient was extended at different network and voxel levels. The gradient scores frontoparietal network was increased in the principal gradient of patients with BECTS. The left precentral gyrus (PCG) and right angular gyrus gradient scores were significantly increased in the principal gradient of children with BECTS. Moreover, in regions of the brain with abnormal principal gradients, functional connectivity was disrupted. The left PCG gradient score of children with BECTS was correlated with the verbal intelligence quotient (VIQ), and the disruption of functional connectivity in brain regions with abnormal principal gradients was closely related to cognitive function. VIQ was significantly predicted by the principal gradient map of patients.

SIGNIFICANCE

The results indicate connectome gradient disruption in children with BECTS and its relationship to cognitive function, thereby increasing our understanding of the functional connectome hierarchy and providing potential biomarkers for cognitive function of children with BECTS.

Human striatal association megaclusters

The striatum receives projections from multiple regions of the cerebral cortex consistent with the role of the basal ganglia in diverse motor, affective, and cognitive functions. Within the striatum, the caudate receives projections from association cortex, including multiple distinct regions of prefrontal cortex. Building on recent insights about the details of how juxtaposed cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging initially in two intensively scanned individuals (each scanned 31 times). Results revealed that the caudate has side-by-side regions that are coupled to at least five distinct distributed association networks, paralleling the organization observed in the cerebral cortex. We refer to these spatial groupings of regions as striatal association megaclusters. Correlation maps from closely juxtaposed seed regions placed within the megaclusters recapitulated the five distinct cortical networks, including their multiple spatially distributed regions. Striatal association megaclusters were explored in 15 additional participants (each scanned at least 8 times), finding that their presence generalizes to new participants. Analysis of the laterality of the regions within the megaclusters further revealed that they possess asymmetries paralleling their cortical counterparts. For example, caudate regions linked to the language network were left lateralized. These results extend the general notion of parallel specialized basal ganglia circuits with the additional discovery that, even within the caudate, there is fine-grained separation of multiple distinct higher-order networks that reflects the organization and lateralization found in the cerebral cortex.NEW & NOTEWORTHY An individualized precision neuroimaging approach reveals juxtaposed zones of the caudate that are coupled with five distinct networks in association cortex. The organization of these caudate zones recapitulates organization observed in the cerebral cortex and extends the notion of specialized basal ganglia circuits.

Transparency and Reproducibility in the Adolescent Brain Cognitive Development (ABCD) Study

Background

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

Methods

Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.

Results

There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (β=-0.77, 95% -1.02, -0.51; p-value < 0.0001).

Conclusion

These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

The efficacy of low frequency repetitive transcial magnetic stimulation for treating auditory verbal hallucinations in schizophrenia: Insights from functional gradient analyses

Background

Auditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the underlying mechanisms of its efficacy necessitate further elucidation.

Objective

This study investigated the cortical gradient characteristics and their associations with clinical responses in schizophrenia patients with AVH, mediated through 1 Hz rTMS targeting the left temporoparietal junction.

Method

Functional gradient metrics were employed to examine the hierarchy patterns of cortical organization, capturing whole-brain functional connectivity profiles in patients and controls.

Results

The 1 Hz rTMS treatment effectively ameliorated the positive symptoms in patients, specifically targeting AVH. Initial evaluations revealed expanded global gradient distribution patterns and specific principal gradient variations in certain brain regions in patients at baseline compared to a control cohort. Following treatment, these divergent global and local patterns showed signs of normalizing. Furthermore, there was observed a closer alignment in between-network dispersion among various networks after treatment, including the somatomotor, attention, and limbic networks, indicating a potential harmonization of brain functionality.

Conclusion

Low-frequency rTMS induces alternations in principal functional gradient patterns, may serve as imaging markers to elucidate the mechanisms underpinning the therapeutic efficacy of rTMS on AVH in schizophrenia.

Abnormalities in subcortical function and their treatment response in Wilson's disease

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson's disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD.

Caudate functional networks influence brain structural changes with aging

Neurogenesis decline with aging may be associated with brain atrophy. Subventricular zone neuron precursor cells possibly modulate striatal neuronal activity via the release of soluble molecules. Neurogenesis decay in the subventricular zone may result in structural alterations of brain regions connected to the caudate, particularly to its medial component. The aim of this study was to investigate how the functional organization of caudate networks relates to structural brain changes with aging. One hundred and fifty-two normal subjects were recruited: 52 young healthy adults (≤35 years old), 42 middle-aged (36 ≤ 60 years old) and 58 elderly subjects (≥60 years old). In young adults, stepwise functional connectivity was used to characterize regions that connect to the medial and lateral caudate at different levels of link-step distances. A statistical comparison between the connectivity of medial and lateral caudate in young subjects was useful to define medial and lateral caudate connected regions. Atrophy of medial and lateral caudate connected regions was estimated in young, middle-aged and elderly subjects using T1-weighted images. Results showed that middle-aged and elderly adults exhibited decreased stepwise functional connectivity at one-link step from the caudate, particularly in the frontal, parietal, temporal and occipital brain regions, compared to young subjects. Elderly individuals showed increased stepwise functional connectivity in frontal, parietal, temporal and occipital lobes compared to both young and middle-aged adults. Additionally, elderly adults displayed decreased stepwise functional connectivity compared to middle-aged subjects in specific parietal and subcortical areas. Moreover, in young adults, the medial caudate showed higher direct connectivity to the basal ganglia (left thalamus), superior, middle and inferior frontal and inferior parietal gyri (medial caudate connected region) relative to the lateral caudate. Considering the opposite contrast, lateral caudate showed stronger connectivity to the basal ganglia (right pallidum), orbitofrontal, rostral anterior cingulate and insula cortices (lateral caudate connected region) compared to medial caudate. In elderly subjects, the medial caudate connected region showed greater atrophy relative to the lateral caudate connected region. Brain regions linked to the medial caudate appear to be more vulnerable to aging than lateral caudate connected areas. The adjacency to the subventricular zone may, at least partially, explain these findings. Stepwise functional connectivity analysis can be useful to evaluate the role of the subventricular zone in network disruptions in age-related neurodegenerative disorders.

Local structural and functional MRI markers of compulsive behaviors and obsessive-compulsive disorder diagnosis within striatum-based circuits

BACKGROUND

Obsessive-compulsive disorder (OCD) is a classic disorder on the compulsivity spectrum, with diverse comorbidities. In the current study, we sought to understand OCD from a dimensional perspective by identifying multimodal neuroimaging patterns correlated with multiple phenotypic characteristics within the striatum-based circuits known to be affected by OCD.

METHODS

Neuroimaging measurements of local functional and structural features and clinical information were collected from 110 subjects, including 51 patients with OCD and 59 healthy control subjects. Linked independent component analysis (LICA) and correlation analysis were applied to identify associations between local neuroimaging patterns across modalities (including gray matter volume, white matter integrity, and spontaneous functional activity) and clinical factors.

RESULTS

LICA identified eight multimodal neuroimaging patterns related to phenotypic variations, including three related to symptoms and diagnosis. One imaging pattern (IC9) that included both the amplitude of low-frequency fluctuation measure of spontaneous functional activity and white matter integrity measures correlated negatively with OCD diagnosis and diagnostic scales. Two imaging patterns (IC10 and IC27) correlated with compulsion symptoms: IC10 included primarily anatomical measures and IC27 included primarily functional measures. In addition, we identified imaging patterns associated with age, gender, and emotional expression across subjects.

CONCLUSIONS

We established that data fusion techniques can identify local multimodal neuroimaging patterns associated with OCD phenotypes. The results inform our understanding of the neurobiological underpinnings of compulsive behaviors and OCD diagnosis.

Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease

Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.

Human Striatal Association Megaclusters

The striatum receives projections from multiple regions of the cerebral cortex consistent with its role in diverse motor, affective, and cognitive functions. Supporting cognitive functions, the caudate receives projections from cortical association regions. Building on recent insights about the details of how multiple cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging (n=2, each participant scanned 31 times). Detailed analysis revealed that the caudate has side-by-side zones that are coupled to at least Give distinct distributed association networks, paralleling the specialization observed in the cerebral cortex. Examining correlation maps from closely juxtaposed seed regions in the caudate recapitulated the Give distinct cerebral networks including their multiple spatially distributed regions. These results extend the general notion of parallel specialized basal ganglia circuits, with the additional discovery that even within the caudate, there is Gine-grained separation of multiple distinct higher-order networks.

A phylogenetically-conserved axis of thalamocortical connectivity in the human brain

The thalamus enables key sensory, motor, emotive, and cognitive processes via connections to the cortex. These projection patterns are traditionally considered to originate from discrete thalamic nuclei, however recent work showing gradients of molecular and connectivity features in the thalamus suggests the organisation of thalamocortical connections occurs along a continuous dimension. By performing a joint decomposition of densely sampled gene expression and non-invasive diffusion tractography in the adult human thalamus, we define a principal axis of genetic and connectomic variation along a medial-lateral thalamic gradient. Projections along this axis correspond to an anterior-posterior cortical pattern and are aligned with electrophysiological properties of the cortex. The medial-lateral axis demonstrates phylogenetic conservation, reflects transitions in neuronal subtypes, and shows associations with neurodevelopment and common brain disorders. This study provides evidence for a supra-nuclear axis of thalamocortical organisation characterised by a graded transition in molecular properties and anatomical connectivity.

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions

The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.

Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits

Sensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergent functioning of the underlying somatosensory region and its association with ASD phenotype features is limited. We applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ('connectopy') at rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. We first demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the S1 somatotopic organization. We then found that its spatial characteristics were linked to the individuals' adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. All in all, variation of adaptive skills appears to be reflected in the brain's mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.

The hierarchical organization of the precuneus captured by functional gradients

The precuneus shows considerable heterogeneity in multiple dimensions including anatomy, function, and involvement in brain disorders. Leveraging the state-of-the-art functional gradient approach, we aimed to investigate the hierarchical organization of the precuneus, which may hold promise for a unified understanding of precuneus heterogeneity. Resting-state functional MRI data from 793 healthy individuals were used to discover and validate functional gradients of the precuneus, which were calculated based on the voxel-wise precuneus-to-cerebrum functional connectivity patterns. Then, we further explored the potential relationships of the precuneus functional gradients with cortical morphology, intrinsic geometry, canonical functional networks, and behavioral domains. We found that the precuneus principal and secondary gradients showed dorsoanterior-ventral and ventroposterior-dorsal organizations, respectively. Concurrently, the principal gradient was associated with cortical morphology, and both the principal and secondary gradients showed geometric distance dependence. Importantly, precuneus functional subdivisions corresponding to canonical functional networks (behavioral domains) were distributed along both gradients in a hierarchical manner, i.e., from the sensorimotor network (somatic movement and sensation) at one extreme to the default mode network (abstract cognitive functions) at the other extreme for the principal gradient and from the visual network (vision) at one end to the dorsal attention network (top-down control of attention) at the other end for the secondary gradient. These findings suggest that the precuneus functional gradients may provide mechanistic insights into the multifaceted nature of precuneus heterogeneity.

Functional connectivity gradients of the cingulate cortex

Heterogeneity of the cingulate cortex is evident in multiple dimensions including anatomy, function, connectivity, and involvement in networks and diseases. Using the recently developed functional connectivity gradient approach and resting-state functional MRI data, we found three functional connectivity gradients that captured distinct dimensions of cingulate hierarchical organization. The principal gradient exhibited a radiating organization with transitions from the middle toward both anterior and posterior parts of the cingulate cortex and was related to canonical functional networks and corresponding behavioral domains. The second gradient showed an anterior-posterior axis across the cingulate cortex and had prominent geometric distance dependence. The third gradient displayed a marked differentiation of subgenual and caudal middle with other parts of the cingulate cortex and was associated with cortical morphology. Aside from providing an updated framework for understanding the multifaceted nature of cingulate heterogeneity, the observed hierarchical organization of the cingulate cortex may constitute a novel research agenda with potential applications in basic and clinical neuroscience.

Connectopic mapping techniques do not reflect functional gradients in the brain

Functional gradients, in which response properties change gradually across a brain region, have been proposed as a key organising principle of the brain. Recent studies using both resting-state and natural viewing paradigms have indicated that these gradients may be reconstructed from functional connectivity patterns via "connectopic mapping" analyses. However, local connectivity patterns may be confounded by spatial autocorrelations artificially introduced during data analysis, for instance by spatial smoothing or interpolation between coordinate spaces. Here, we investigate whether such confounds can produce illusory connectopic gradients. We generated datasets comprising random white noise in subjects' functional volume spaces, then optionally applied spatial smoothing and/or interpolated the data to a different volume or surface space. Both smoothing and interpolation induced spatial autocorrelations sufficient for connectopic mapping to produce both volume- and surface-based local gradients in numerous brain regions. Furthermore, these gradients appeared highly similar to those obtained from real natural viewing data, although gradients generated from real and random data were statistically different in certain scenarios. We also reconstructed global gradients across the whole-brain - while these appeared less susceptible to artificial spatial autocorrelations, the ability to reproduce previously reported gradients was closely linked to specific features of the analysis pipeline. These results indicate that previously reported gradients identified by connectopic mapping techniques may be confounded by artificial spatial autocorrelations introduced during the analysis, and in some cases may reproduce poorly across different analysis pipelines. These findings imply that connectopic gradients need to be interpreted with caution.

Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions

The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.

Apathy in melancholic depression and abnormal neural activity within the reward-related circuit

Major depressive disorder is a heterogeneous syndrome, of which the most common subtype is melancholic depression (MEL). Previous studies have indicated that anhedonia is frequently a cardinal feature in MEL. As a common syndrome of motivational deficit, anhedonia is closely associated with dysfunction in reward-related networks. However, little is currently known about apathy, another syndrome of motivational deficits, and the underlying neural mechanisms in MEL and non-melancholic depression (NMEL). Herein, the Apathy Evaluation Scale (AES) was used to compare apathy between MEL and NMEL. On the basis of resting-state functional magnetic resonance imaging, functional connectivity strength (FCS) and seed-based functional connectivity (FC) were calculated within reward-related networks and compared among 43 patients with MEL, 30 patients with NMEL, and 35 healthy controls. Patients with MEL had higher AES scores than those with NMEL (t = -2.20, P = 0.03). Relative to NMEL, MEL was associated with greater FCS (t = 4.27, P < 0.001) in the left ventral striatum (VS), and greater FC of the VS with the ventral medial prefrontal cortex (t = 5.03, P < 0.001) and dorsolateral prefrontal cortex (t = 3.18, P = 0.005). Taken together the results indicate that reward-related networks may play diverse pathophysiological roles in MEL and NMEL, thus providing potential directions for future interventions in the treatment of various depression subtypes.

Functional gradients of the medial parietal cortex in a healthy cohort with family history of sporadic Alzheimer's disease

BACKGROUND

The medial parietal cortex is an early site of pathological protein deposition in Alzheimer's disease (AD). Previous studies have identified different subregions within this area; however, these subregions are often heterogeneous and disregard individual differences or subtle pathological alterations in the underlying functional architecture. To address this limitation, here we measured the continuous connectivity gradients of the medial parietal cortex and assessed their relationship with cerebrospinal fluid (CSF) biomarkers, ApoE ε4 carriership and memory in asymptomatic individuals at risk to develop AD.

METHODS

Two hundred sixty-three cognitively normal participants with a family history of sporadic AD who underwent resting-state and task-based functional MRI using encoding and retrieval tasks were included from the PREVENT-AD cohort. A novel method for characterizing spatially continuous patterns of functional connectivity was applied to estimate functional gradients in the medial parietal cortex during the resting-state and task-based conditions. This resulted in a set of nine parameters that described the appearance of the gradient across different spatial directions. We performed correlation analyses to assess whether these parameters were associated with CSF biomarkers of phosphorylated tau181 (p-tau), total tau (t-tau), and amyloid-ß1-42 (Aß). Then, we compared the spatial parameters between ApoE ε4 carriers and noncarriers, and evaluated the relationship between these parameters and memory.

RESULTS

Alterations involving the superior part of the medial parietal cortex, which was connected to regions of the default mode network, were associated with higher p-tau, t-tau levels as well as lower Aß/p-tau levels during the resting-state condition (p < 0.01). Similar alterations were found in ApoE ε4 carriers compared to non-carriers (p < 0.003). In contrast, lower immediate memory scores were associated with changes in the middle part of the medial parietal cortex, which was connected to inferior temporal and posterior parietal regions, during the encoding task (p = 0.001). No results were found when using conventional connectivity measures.

CONCLUSIONS

Functional alterations in the medial parietal gradients are associated with CSF AD biomarkers, ApoE ε4 carriership, and lower memory in an asymptomatic cohort with a family history of sporadic AD, suggesting that functional gradients are sensitive to subtle changes associated with early AD stages.

Gradients of striatal function in antipsychotic-free first-episode psychosis and schizotypy

Both psychotic illness and subclinical psychosis-like experiences (PLEs) have been associated with cortico-striatal dysfunction. This work has largely relied on a discrete parcellation of the striatum into distinct functional areas, but recent evidence suggests that the striatum comprises multiple overlapping and smoothly varying gradients (i.e., modes) of functional organization. Here, we investigated two of these functional connectivity modes, previously associated with variations in the topographic patterning of cortico-striatal connectivity (first-order gradient), and dopaminergic innervation of the striatum (second-order gradient), and assessed continuities in striatal function from subclinical to clinical domains. We applied connectopic mapping to resting-state fMRI data to obtain the first-order and second-order striatal connectivity modes in two distinct samples: (1) 56 antipsychotic-free patients (26 females) with first-episode psychosis (FEP) and 27 healthy controls (17 females); and (2) a community-based cohort of 377 healthy individuals (213 females) comprehensively assessed for subclinical PLEs and schizotypy. The first-order "cortico-striatal" and second-order "dopaminergic" connectivity gradients were significantly different in FEP patients compared to controls bilaterally. In the independent sample of healthy individuals, variations in the left first-order "cortico-striatal" connectivity gradient were associated with inter-individual differences in a factor capturing general schizotypy and PLE severity. The presumed cortico-striatal connectivity gradient was implicated in both subclinical and clinical cohorts, suggesting that variations in its organization may represent a neurobiological trait marker across the psychosis continuum. Disruption of the presumed dopaminergic gradient was only noticeable in patients, suggesting that neurotransmitter dysfunction may be more apparent to clinical illness.

Evaluate the efficacy and reliability of functional gradients in within-subject designs

The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain-general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between-group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within-subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting-state conditions from 145 participants. We found significantly lower within-network dispersion of visual network (VN) (p = 7.3 × 10^-4 ) as well as sensorimotor network (SMN) (p = 1 × 10^-5 ) and between-network dispersion of VN (p = 2.3 × 10^-4 ) under EC than EO, while frontoparietal network (p = 9.2 × 10^-4 ) showed significantly higher between-network dispersion during EC than EO. Test-retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within-network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting-state conditions, such that this method could be generalized to other within-subject designs.

Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus

Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.

Disrupted subcortical functional connectome gradient in drug-naïve first-episode schizophrenia and the normalization effects after antipsychotic treatment

Antipsychotics are thought to improve schizophrenia symptoms through the antagonism of dopamine D2 receptors, which are abundant mainly in subcortical regions. By introducing functional gradient, a novel approach to identify hierarchy alterations by capturing the similarity of whole brain fucntional connectivity (FC) profiles between two voxels, the present study aimed to characterize how the subcortical gradient is associated with treatment effects and response in first-episode schizophrenia in vivo. Two independent samples of first-episode schizophrenia (FES) patients with matched healthy controls (HC) were obtained: the discovery dataset included 71 patients (FES0W) and 64 HC at baseline, and patients were re-scanned after either 6 weeks (FES6W, N = 33) or 12 months (FES12M, N = 57) of antipsychotic treatment, of which 19 patients finished both 6-week and 12-month evaluation. The validation dataset included 22 patients and 24 HC at baseline and patients were re-scanned after 6 weeks. Gradient metrics were calculated using BrainSpace Toolbox. Voxel-based gradient values were generated and group-averaged gradient values were further extracted across all voxels (global), three systems (thalamus, limbic and striatum) and their subcortical subfields. The comparisons were conducted separately between FES0W and HC for investigating illness effects, and between FES6W/FES12M and FES0W for treatment effects. Correlational analyses were then conducted between the longitudinal gradient alterations and the improvement of clinical ratings. Before treatment, schizophrenia patients exhibited an expanded range of global gradient scores compared to HC which indicated functional segregation within subcortical systems. The increased gradient in limbic system and decreased gradient in thalamic and striatal system contributed to the baseline abnormalities and led to the disruption of the subcortical functional integration. After treatment, these disruptions were normalized and the longitudinal changes of gradient scores in limbic system were significantly associated with symptom improvement. Similar illness and treatment effects were also observed in the validation dataset. By measuring functional hierarchy of subcortical organization, our findings provide a novel imaging marker that is sensitive to treatment effects and may make a promising indicator of treatment response in schizophrenia.

Evidence for embracing normative modeling

In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate the wider adoption of normative modeling across the neuroimaging community.

Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.

Striatal connectopic maps link to functional domains across psychiatric disorders

Transdiagnostic approaches to psychiatry have significant potential in overcoming the limitations of conventional diagnostic paradigms. However, while frameworks such as the Research Domain Criteria have garnered significant enthusiasm among researchers and clinicians from a theoretical angle, examples of how such an approach might translate in practice to understand the biological mechanisms underlying complex patterns of behaviors in realistic and heterogeneous populations have been sparse. In a richly phenotyped clinical sample (n = 186) specifically designed to capture the complex nature of heterogeneity and comorbidity within- and between stress- and neurodevelopmental disorders, we use exploratory factor analysis on a wide range of clinical questionnaires to identify four stable functional domains that transcend diagnosis and relate to negative valence, cognition, social functioning and inhibition/arousal before replicating them in an independent dataset (n = 188). We then use connectopic mapping to map inter-individual variation in fine-grained topographical organization of functional connectivity in the striatum-a central hub in motor, cognitive, affective and reward-related brain circuits-and use multivariate machine learning (canonical correlation analysis) to show that these individualized topographic representations predict transdiagnostic functional domains out of sample (r = 0.20, p = 0.026). We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.

Functional Gradients of the Cerebellum: a Review of Practical Applications

Gradient-based analyses have contributed to the description of cerebellar functional neuroanatomy. More recently, functional gradients of the cerebellum have been used as a multi-purpose tool for neuroimaging research. Here, we provide an overview of the many practical applications of cerebellar functional gradient analyses. These practical applications include examination of intra-cerebellar and cerebellar-extracerebellar organization; transformation of functional gradients into parcellations with discrete borders; projection of functional gradients calculated within cerebellar structures to other extracerebellar structures; interpretation of cerebellar neuroimaging findings using qualitative and quantitative methods; detection of differences in patient populations; and other more complex practical applications of cerebellar gradient-based analyses. This review may serve as an introduction and catalog of options for neuroscientists who wish to design and analyze imaging studies using functional gradients of the cerebellum.

Preserved Motility after Neonatal Dopaminergic Lesion Relates to Hyperexcitability of Direct Pathway Medium Spiny Neurons

In Parkinson's disease patients and rodent models, dopaminergic neuron loss (DAN) results in severe motor disabilities. In contrast, general motility is preserved after early postnatal DAN loss in rodents. Here we used mice of both sexes to show that the preserved motility observed after early DAN loss depends on functional changes taking place in medium spiny neurons (MSN) of the dorsomedial striatum (DMS) that belong to the direct pathway (dMSN). Previous animal model studies showed that adult loss of dopaminergic input depresses dMSN response to cortical input, which likely contributes to Parkinson's disease motor impairments. However, the response of DMS-dMSN to their preferred medial PFC input is preserved after neonatal DAN loss as shown by in vivo studies. Moreover, their response to inputs from adjacent cortical areas is increased, resulting in reduced cortical inputs selectivity. Additional ex vivo studies show that membrane excitability increases in dMSN. Furthermore, chemogenetic inhibition of DMS-dMSN has a more marked inhibitory effect on general motility in lesioned mice than in their control littermates, indicating that expression of normal levels of locomotion and general motility depend on dMSN activity after early DAN loss. Contrastingly, DMS-dMSN inhibition did not ameliorate a characteristic phenotype of the DAN-lesioned animals in a marble burying task demanding higher behavioral control. Thus, increased dMSN excitability likely promoting changes in corticostriatal functional connectivity may contribute to the distinctive behavioral phenotype emerging after developmental DAN loss, with implications for our understanding of the age-dependent effects of forebrain dopamine depletion and neurodevelopment disorders.SIGNIFICANCE STATEMENT The loss of striatal dopamine in the adult brain leads to life-threatening motor impairments. However, general motility remains largely unaffected after its early postnatal loss. Here, we show that the high responsiveness to cortical input of striatal neurons belonging to the direct basal ganglia pathway, crucial for proper motor functioning, is preserved after early dopamine neuron loss, in parallel with an increase in these cells' membrane excitability. Chemogenetic inhibition studies show that the preserved motility depends on this direct pathway hyperexcitability/hyperconnectivity, while other phenotypes characteristic of this condition remained unaltered despite the dMSN inhibition. This insight has implications for our understanding of the mechanism underlying the behavioral impairments observed in neuropsychiatric conditions linked to early dopaminergic hypofunction.

Canonical Correlation Analysis and Partial Least Squares for Identifying Brain-Behavior Associations: A Tutorial and a Comparative Study

Canonical correlation analysis (CCA) and partial least squares (PLS) are powerful multivariate methods for capturing associations across 2 modalities of data (e.g., brain and behavior). However, when the sample size is similar to or smaller than the number of variables in the data, standard CCA and PLS models may overfit, i.e., find spurious associations that generalize poorly to new data. Dimensionality reduction and regularized extensions of CCA and PLS have been proposed to address this problem, yet most studies using these approaches have some limitations. This work gives a theoretical and practical introduction into the most common CCA/PLS models and their regularized variants. We examine the limitations of standard CCA and PLS when the sample size is similar to or smaller than the number of variables. We discuss how dimensionality reduction and regularization techniques address this problem and explain their main advantages and disadvantages. We highlight crucial aspects of the CCA/PLS analysis framework, including optimizing the hyperparameters of the model and testing the identified associations for statistical significance. We apply the described CCA/PLS models to simulated data and real data from the Human Connectome Project and Alzheimer's Disease Neuroimaging Initiative (both of n > 500). We use both low- and high-dimensionality versions of these data (i.e., ratios between sample size and variables in the range of ∼1-10 and ∼0.1-0.01, respectively) to demonstrate the impact of data dimensionality on the models. Finally, we summarize the key lessons of the tutorial.

Functional connectivity gradients of the insula to different cerebral systems

The diverse functional roles of the insula may emerge from its heavy connectivity to an extensive network of cortical and subcortical areas. Despite several previous attempts to investigate the hierarchical organization of the insula by applying the recently developed gradient approach to insula-to-whole brain connectivity data, little is known about whether and how there is variability across connectivity gradients of the insula to different cerebral systems. Resting-state functional MRI data from 793 healthy subjects were used to discover and validate functional connectivity gradients of the insula, which were computed based on its voxel-wise functional connectivity profiles to distinct cerebral systems. We identified three primary patterns of functional connectivity gradients of the insula to distinct cerebral systems. The connectivity gradients to the higher-order transmodal associative systems, including the prefrontal, posterior parietal, temporal cortices, and limbic lobule, showed a ventroanterior-dorsal axis across the insula; those to the lower-order unimodal primary systems, including the motor, somatosensory, and occipital cortices, displayed radiating transitions from dorsoanterior toward both ventroanterior and dorsoposterior parts of the insula; the connectivity gradient to the subcortical nuclei exhibited an organization along the anterior-posterior axis of the insula. Apart from complementing and extending previous literature on the heterogeneous connectivity patterns of insula subregions, the presented framework may offer ample opportunities to refine our understanding of the role of the insula in many brain disorders.

An evaluation of how connectopic mapping reveals visual field maps in V1

Abstract

Functional gradients, in which response properties change gradually across the cortical surface, have been proposed as a key organising principle of the brain. However, the presence of these gradients remains undetermined in many brain regions. Resting-state neuroimaging studies have suggested these gradients can be reconstructed from patterns of functional connectivity. Here we investigate the accuracy of these reconstructions and establish whether it is connectivity or the functional properties within a region that determine these “connectopic maps”. Different manifold learning techniques were used to recover visual field maps while participants were at rest or engaged in natural viewing. We benchmarked these reconstructions against maps measured by traditional visual field mapping. We report an initial exploratory experiment of a publicly available naturalistic imaging dataset, followed by a preregistered replication using larger resting-state and naturalistic imaging datasets from the Human Connectome Project. Connectopic mapping accurately predicted visual field maps in primary visual cortex, with better predictions for eccentricity than polar angle maps. Non-linear manifold learning methods outperformed simpler linear embeddings. We also found more accurate predictions during natural viewing compared to resting-state. Varying the source of the connectivity estimates had minimal impact on the connectopic maps, suggesting the key factor is the functional topography within a brain region. The application of these standardised methods for connectopic mapping will allow the discovery of functional gradients across the brain.

Protocol registration

The stage 1 protocol for this Registered Report was accepted in principle on 19 April 2022. The protocol, as accepted by the journal, can be found at 10.6084/m9.figshare.19771717.

Topographic organization of the human caudate functional connectivity and age-related changes with resting-state fMRI

The striatum is postulated to play a central role in gating cortical processing during goal-oriented behavior. While many human neuroimaging studies have treated the striatum as an undivided whole or several homogeneous compartments, some recent studies showed that its circuitry is topographically organized and has more complex relations with the cortical networks than previously assumed. Here, we took a gradient functional connectivity mapping approach that utilizes the entire anatomical space of the caudate nucleus to examine the organization of its functional relationship with the rest of the brain and how its topographic mapping changes with age. We defined the topography of the caudate functional connectivity using three publicly available resting-state fMRI datasets. We replicated and extended previous findings. First, we found two stable gradients of caudate connectivity patterns along its medial-lateral (M-L) and anterior-posterior (A-P) axes, supporting findings from previous tract-tracing studies of non-human primates that there are at least two main organizational principles within the caudate nucleus. Second, unlike previous emphasis of the A-P topology, we showed that the differential connectivity patterns along the M-L gradient of caudate are more clearly organized with the large-scale neural networks; such that brain networks associated with internal vs. external orienting behavior are respectively more closely linked to the medial vs. lateral extent of the caudate. Third, the caudate's M-L organization showed greater age-related reduction in integrity, which was further associated with age-related changes in behavioral measures of executive functions. In sum, our analysis confirmed a sometimes overlooked M-L functional connectivity gradient within the caudate nucleus, with its lateral longitudinal zone more closely linked to the frontoparietal cortical circuits and age-related changes in cognitive control. These findings provide a more precise mapping of the human caudate functional connectivity, both in terms of the gradient organization with cortical networks and age-related changes in such organization.

An Open MRI Dataset For Multiscale Neuroscience

Multimodal neuroimaging grants a powerful window into the structure and function of the human brain at multiple scales. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends (also referred to as gradients) in brain microstructure and connectivity, offering an integrative framework to study multiscale brain organization. Here, we share a multimodal MRI dataset for Microstructure-Informed Connectomics (MICA-MICs) acquired in 50 healthy adults (23 women; 29.54 ± 5.62 years) who underwent high-resolution T1-weighted MRI, myelin-sensitive quantitative T1 relaxometry, diffusion-weighted MRI, and resting-state functional MRI at 3 Tesla. In addition to raw anonymized MRI data, this release includes brain-wide connectomes derived from (i) resting-state functional imaging, (ii) diffusion tractography, (iii) microstructure covariance analysis, and (iv) geodesic cortical distance, gathered across multiple parcellation scales. Alongside, we share large-scale gradients estimated from each modality and parcellation scale. Our dataset will facilitate future research examining the coupling between brain microstructure, connectivity, and function. MICA-MICs is available on the Canadian Open Neuroscience Platform data portal ( https://portal.conp.ca ) and the Open Science Framework ( https://osf.io/j532r/ ).

Microglia involvement in sex-dependent behaviors and schizophrenia occurrence in offspring with maternal dexamethasone exposure

Fetal microglia that are particularly sensitive cells to the changes in utero environment might be involved in the sex-biased onset and vulnerability to psychiatric disorders. To address this issue, we administered a 50 µg/kg dexamethasone (DEX) to dams subcutaneously from gestational days 16 to 18 and a series of behavioral assessments were performed in the offspring. Prenatal exposure to dexamethasone (PN-DEX) induced schizophrenia (SCZ)-relevant behaviors in male mice and depressive-like behavior in female mice. SCZ-relevant behavioral patterns occurred in 10-week-old (10 W) male mice but not in 4-week-old (4 W) male mice. Microglia in the medial prefrontal cortex (mPFC) and the striatum (STR) of 10 W males prenatally treated with dexamethasone (10 W PN-DEX-M) showed hyper-ramified morphology and dramatically reduced spine density in mPFC. Immunofluorescence studies indicated that microglia in the mPFC of the 10 W PN-DEX-M group interacted with pre-synaptic Bassoon and post-synaptic density 95 (PSD95) puncta. PN-DEX-M also showed significantly changed dopamine system proteins. However, a testosterone surge during adolescence was not a trigger on SCZ-relevant behavior occurrence in 10 W PN-DEX-M. Furthermore, females prenatally treated with dexamethasone (PN-DEX-F) displayed depressive-like behavior, in addition to HPA-axis activation and inflammatory microglial phenotypes in their hippocampus (HPC). We propose that altered microglial function, such as increased synaptic pruning, may be involved in the occurrence of SCZ-relevant behavior in PN-DEX-M and sex-biased abnormal behavior in the PN-DEX model.

Mapping microstructural gradients of the human striatum in normal aging and Parkinson's disease

Mapping structural spatial change (i.e., gradients) in the striatum is essential for understanding the function of the basal ganglia in both health and disease. We developed a method to identify and quantify gradients of microstructure in the single human brain in vivo. We found spatial gradients in the putamen and caudate nucleus of the striatum that were robust across individuals, clinical conditions, and datasets. By exploiting multiparametric quantitative MRI, we found distinct, spatially dependent, aging-related alterations in water content and iron concentration. Furthermore, we found cortico-striatal microstructural covariation, showing relations between striatal structural gradients and cortical hierarchy. In Parkinson's disease (PD) patients, we found abnormal gradients in the putamen, revealing changes in the posterior putamen that explain patients' dopaminergic loss and motor dysfunction. Our work provides a noninvasive approach for studying the spatially varying, structure-function relationship in the striatum in vivo, in normal aging and PD.

The normative modeling framework for computational psychiatry

Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior, which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus 'healthy' control analytic approaches, probably owing to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case-control comparisons that rely on potentially noisy clinical labels. Here we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices and conclude by demonstrating several examples of downstream analyses that the normative model may facilitate, such as stratification of high-risk individuals, subtyping and behavioral predictive modeling. The protocol takes ~1-3 h to complete.

Ketamine-induced neurotoxicity is mediated through endoplasmic reticulum stress in vitro in STHdhQ7/Q7 cells

Ketamine has traditionally been used as a dissociative anesthetic agent and more recently as a treatment for treatment-resistant depression. However, there is growing concern over the increased use of ketamine in recreational and therapeutic settings due to the potential neurotoxic effects. Recent studies have demonstrated that ketamine is cytotoxic in several cell types, such as fibroblasts, hepatocytes, uroepithelial cells, and adult induced pluripotent stem cells (iPSCs). Ketamine has been shown to dysregulate calcium signalling, increase reactive oxygen species (ROS) production, and impair mitochondrial function, ultimately leading to apoptosis. However, it is unclear whether endoplasmic reticulum (ER) stress plays a role in ketamine associated neurotoxicity in striatal neurons. Disruption to ER homeostasis can initiate ER-mediated cell death, which has been implicated in several neurodegenerative diseases. Thus, the purpose of this study was to determine whether ketamine's neurotoxic effects involve an ER stress-dependent pathway and to elucidate the underlying mechanisms involved in its neurotoxic effects. Mouse striatal cells were treated with various concentrations of ketamine (10 μM, 100 μM, 1 mM) or DMEM for 9-72 hrs. Cell viability was assessed using the MTT assay, and changes in gene expression of ER stress markers were evaluated using RT-qPCR. MTT results revealed that 1 mM ketamine decreased cell viability in striatal cells after 24 h of treatment. Gene expression studies complemented these findings such that ketamine upregulated pro-apoptotic ER stress markers, including X-box binding protein 1 (XBP1), activating transcription factor 4 (ATF4), and C/EBP homologous protein (CHOP) and downregulated pro-survival ER stress proteins such as GRP78, MANF and CDNF. Ketamine activated all three stress sensing pathways including PERK, IRE1, and ATF6. Taken together, our results show that ketamine-induced neurotoxicity is mediated through an ER stress-dependent apoptotic pathway.

Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex

The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.

Unbalanced fronto-pallidal neurocircuit underlying set shifting in obsessive-compulsive disorder

Maladaptive habitual behaviours of obsessive-compulsive disorder are characterized by cognitive inflexibility, which hypothetically arises from dysfunctions of a certain cortico-basal ganglia-thalamo-cortical circuit including the ventrolateral prefrontal region. Inside this neurocircuit, an imbalance between distinct striatal projections to basal ganglia output nuclei, either directly or indirectly via the external globus pallidus, is suggested to be relevant for impaired arbitration between facilitation and inhibition of cortically initiated activity. However, current evidence of individually altered cortico-striatal or thalamo-cortical connectivities is insufficient to understand how cortical dysconnections are linked to the imbalanced basal ganglia system in patients. In this study, we aimed to identify aberrant ventrolateral prefronto-basal ganglia-thalamic subnetworks representing direct-indirect imbalance and its association with cognitive inflexibility in patients. To increase network detection sensitivity, we constructed a cortico-basal ganglia-thalamo-cortical network model incorporating striatal, pallidal and thalamic subregions defined by unsupervised clustering in 105 medication-free patients with obsessive-compulsive disorder (age = 25.05 ± 6.55 years, male/female = 70/35) and 99 healthy controls (age = 23.93 ± 5.80 years, male/female = 64/35). By using the network-based statistic method, we analysed group differences in subnetworks formed by suprathreshold dysconnectivities. Using linear regression models, we tested subnetwork dysconnectivity effects on symptom severity and set-shifting performance assessed by well-validated clinical and cognitive tests. Compared with the healthy controls, patients were slower to track the Part B sequence of the Trail Making Test when the effects of psychomotor and visuospatial functions were adjusted (t = 3.89, P < 0.001) and made more extradimensional shift errors (t = 4.09, P < 0.001). In addition to reduced fronto-striatal and striato-external pallidal connectivities and hypoconnected striato-thalamic subnetwork [P = 0.001, family-wise error rate (FWER) corrected], patients had hyperconnected fronto-external pallidal (P = 0.012, FWER corrected) and intra-thalamic (P = 0.015, FWER corrected) subnetworks compared with the healthy controls. Among the patients, the fronto-pallidal subnetwork alteration, especially ventrolateral prefronto-external globus pallidal hyperconnectivity, was associated with relatively fewer extradimensional shifting errors (β = -0.30, P = 0.001). Our findings suggest that the hyperconnected fronto-external pallidal subnetwork may have an opposite effect to the imbalance caused by the reduced indirect pathway (fronto-striato-external pallidal) connectivities in patients. This ventrolateral prefrontal hyperconnectivity may help the external globus pallidus disinhibit basal ganglia output nuclei, which results in behavioural inhibition, so as to compensate for the impaired set shifting. We suggest the ventrolateral prefrontal and external globus pallidus as neuromodulatory targets for inflexible habitual behaviours in obsessive-compulsive disorder.

Multimodal Gradient Mapping of Rodent Hippocampus

The hippocampus plays a central role in supporting our coherent and enduring sense of self and our place in the world. Understanding its functional organisation is central to understanding this complex role. Previous studies suggest function varies along a long hippocampal axis, but there is disagreement about the presence of sharp discontinuities or gradual change along that axis. Other open questions relate to the underlying drivers of this variation and the conservation of organisational principles across species. Here, we delineate the primary organisational principles underlying patterns of hippocampal functional connectivity (FC) in the mouse using gradient analysis on resting state fMRI data. We further applied gradient analysis to mouse gene co-expression data to examine the relationship between variation in genomic anatomy and functional organisation. Two principal FC gradients along a hippocampal axis were revealed. The principal gradient exhibited a sharp discontinuity that divided the hippocampus into dorsal and ventral compartments. The second, more continuous, gradient followed the long axis of the ventral compartment. Dorsal regions were more strongly connected to areas involved in spatial navigation while ventral regions were more strongly connected to areas involved in emotion, recapitulating patterns seen in humans. In contrast, gene co-expression gradients showed a more segregated and discrete organisation. Our findings suggest that hippocampal functional organisation exhibits both sharp and gradual transitions and that hippocampal genomic anatomy exerts only a subtle influence on this organisation.

Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field functional magnetic resonance imaging (fMRI) performed at 10.5 T to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole-brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity (FC) topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match FC gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.

Computational modelling of the speed-accuracy tradeoff: No evidence for an association with depression symptomatology

Successful decision making often requires finding the right balance between the speed and accuracy of responding: Emphasising speed can lead to error-prone performance, yet emphasising accuracy leads to a slowing of performance. Such speed-accuracy tradeoffs (SATs) therefore require establishing appropriate response settings to optimise performance in response to changing environmental demands. Such strategic adaptation of response settings relies on the striatum component of the basal ganglia, an area implicated in depression. The current study explored the association between depression symptomatology and SAT performance. Two experiments presented participants with an SAT paradigm embedded within a simple decision-making task, together with measures of depression symptomatology. Experiment 1 (N = 349) was correlational, whereas Experiment 2 was a two-phase experiment where participants (N = 501) were first pre-screened on depression symptomatology and extreme-low and extreme-high responders (total N = 91) were invited to Phase 2. Behavioural data were modelled with a drift diffusion model. Behavioural data and associated diffusion modelling showed large and robust SAT effects. Emphasising accuracy led to an increase in boundary separation, an increase in drift rate, and an increase in non-decision time. However, the magnitude of the changes of these parameters with SAT instructions was not associated with measures of depression symptomatology. The results suggest that the strategic adaptation of response settings in response to environmental changes in speed-accuracy instructions does not appear to be associated with depression symptomatology.

Mapping dopaminergic projections in the human brain with resting-state fMRI

The striatum receives dense dopaminergic projections, making it a key region of the dopaminergic system. Its dysfunction has been implicated in various conditions including Parkinson’s disease (PD) and substance use disorder. However, the investigation of dopamine-specific functioning in humans is problematic as current MRI approaches are unable to differentiate between dopaminergic and other projections. Here, we demonstrate that ‘connectopic mapping’ – a novel approach for characterizing fine-grained, overlapping modes of functional connectivity – can be used to map dopaminergic projections in striatum. We applied connectopic mapping to resting-state functional MRI data of the Human Connectome Project (population cohort; N = 839) and selected the second-order striatal connectivity mode for further analyses. We first validated its specificity to dopaminergic projections by demonstrating a high spatial correlation (r = 0.884) with dopamine transporter availability – a marker of dopaminergic projections – derived from DaT SPECT scans of 209 healthy controls. Next, we obtained the subject-specific second-order modes from 20 controls and 39 PD patients scanned under placebo and under dopamine replacement therapy (L-DOPA), and show that our proposed dopaminergic marker tracks PD diagnosis, symptom severity, and sensitivity to L-DOPA. Finally, across 30 daily alcohol users and 38 daily smokers, we establish strong associations with self-reported alcohol and nicotine use. Our findings provide evidence that the second-order mode of functional connectivity in striatum maps onto dopaminergic projections, tracks inter-individual differences in PD symptom severity and L-DOPA sensitivity, and exhibits strong associations with levels of nicotine and alcohol use, thereby offering a new biomarker for dopamine-related (dys)function in the human brain.

Neural mapping of anhedonia across psychiatric diagnoses: A transdiagnostic neuroimaging analysis

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Anhedonia is present in many different psychiatric disorders.

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Anhedonia has been associated with abnormal reward-related striatal dopamine functioning.

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This study tested whether transdiagnostic anhedonia expression mapped onto striatal volume.

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Our findings suggest volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

Anhedonia has been associated with abnormal reward-related striatal dopamine functioning in patients with different psychiatric disorders. Here, we tested whether anhedonia expression mapped onto striatal volume across several psychiatric diagnoses.

T1-weighted images from 313 participants including 89 healthy controls (HC), 22 patients with opioid use disorder (OUD), 50 patients with major depressive disorder (MDD), 45 patients with borderline personality disorder (BPD), 49 patients with first-episode psychosis (FEP), 43 patients with cocaine use disorder (CUD) and 15 patients with schizophrenia (SZ) were included. Anhedonia was assessed with subscores of the Beck Depression Inventory (BDI) and/or the Scale for the Assessment of Negative Symptoms (SANS). Voxel-based morphometry (VBM) was conducted for identifying dimensional symptom-structure associations using region of interest (ROI, dorsal and ventral striatum) and whole-brain analyses, as well as for group comparisons of striatal volume.

ROI analyses revealed significant negative relationships between putamen volume and BDI and SANS anhedonia scores across OUD, MDD, BPD, CUD and SZ patients (n = 175) and MDD, FEP and SZ patients (n = 114), respectively. Whole-brain VBM analyses confirmed these associations and further showed negative relationships between anhedonia severity and volume of the bilateral cerebellum. There were group differences in right accumbens volume, which however were not related to anhedonia expression across the different diagnoses.

Our findings indicate volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

Aerobic exercise alters brain function and structure in Parkinson's disease a randomized controlled trial

Objective

Randomized clinical trials have shown that aerobic exercise attenuates motor symptom progression in Parkinson's disease, but the underlying neural mechanisms are unclear. Here, we investigated how aerobic exercise influences disease‐related functional and structural changes in the corticostriatal sensorimotor network, which is involved in the emergence of motor deficits in Parkinson's disease. Additionally, we explored effects of aerobic exercise on tissue integrity of the substantia nigra, and on behavioral and cerebral indices of cognitive control.

Methods

The Park‐in‐Shape trial is a single‐center, double‐blind randomized controlled trial in 130 Parkinson's disease patients who were randomly assigned (1:1 ratio) to aerobic exercise (stationary home trainer) or stretching (active control) interventions (duration = 6 months). An unselected subset from this trial (exercise, n = 25; stretching, n = 31) underwent resting‐state functional and structural magnetic resonance imaging (MRI), and an oculomotor cognitive control task (pro‐ and antisaccades), at baseline and at 6‐month follow‐up.

Results

Aerobic exercise, but not stretching, led to increased functional connectivity of the anterior putamen with the sensorimotor cortex relative to the posterior putamen. Behaviorally, aerobic exercise also improved cognitive control. Furthermore, aerobic exercise increased functional connectivity in the right frontoparietal network, proportionally to fitness improvements, and it reduced global brain atrophy.

Interpretation

MRI, clinical, and behavioral results converge toward the conclusion that aerobic exercise stabilizes disease progression in the corticostriatal sensorimotor network and enhances cognitive performance. ANN NEUROL 2022;91:203–216