Spatial and Temporal Organization of the Individual Human Cerebellum

A Functional Atlas of the Cerebellum Based on NeuroSynth Task Coordinates

Although the human cerebellum has a surface that is about 80% of that of the cerebral cortex and has about four times as many neurons, its functional organization is still very much uncharted. Despite recent attempts to provide resting-state and task-based parcellations of the cerebellum, these two approaches lead to large discrepancies. This article describes a comprehensive task-based functional parcellation of the human cerebellum based on a large-scale functional database, NeuroSynth, involving an unprecedented diversity of tasks, which were reliably associated with ontological key terms referring to psychological functions. Involving over 44,500 participants from this database, we present a parcellation that exhibits replicability with earlier resting-state parcellations across cerebellar and neocortical structures. The functional parcellation of the cerebellum confirms the major networks revealed in prior work, including sensorimotor, directed (dorsal) attention, divided (ventral) attention, executive control, mentalizing (default mode) networks, tiny patches of a limbic network, and also a unilateral language network (but not the visual network), and the association of these networks with underlying ontological key terms confirms their major functionality. The networks are revealed at locations that are roughly similar to prior resting-state cerebellar parcellations, although they are less symmetric and more fragmented across the two hemispheres. This functional parcellation of the human cerebellum and associated key terms can provide a useful guide in designing studies to test specific functional hypotheses and provide a reference for interpreting the results.

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.

Postoperative cerebellar mutism syndrome is an acquired autism-like network disturbance

BACKGROUND

Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumor surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates.

METHODS

In this study, we analyzed postoperative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and pediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n = 427).

RESULTS

Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the pediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to the prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviors.

CONCLUSIONS

Our findings indicate that CMS-associated lesions may result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

The Evolution of the Optimization of Cognitive and Social Functions in the Cerebellum and Thereby the Rise of Homo sapiens Through Cumulative Culture

The evolution of the prominent role of the cerebellum in the development of composite tools, and cumulative culture, leading to the rise of Homo sapiens is examined. Following Stout and Hecht's (2017) detailed description of stone-tool making, eight key repetitive involvements of the cerebellum are highlighted. These key cerebellar learning involvements include the following: (1) optimization of cognitive-social control, (2) prediction (3) focus of attention, (4) automaticity of smoothness, appropriateness, and speed of movement and cognition, (5) refined movement and social cognition, (6) learns models of extended practice, (7) learns models of Theory of Mind (ToM) of teachers, (8) is predominant in acquisition of novel behavior and cognition that accrues from the blending of cerebellar models sent to conscious working memory in the cerebral cortex. Within this context, the evolution of generalization and blending of cerebellar internal models toward optimization of social-cognitive learning is described. It is concluded that (1) repetition of movement and social cognition involving the optimization of internal models in the cerebellum during stone-tool making was the key selection factor toward social-cognitive and technological advancement, (2) observational learning during stone-tool making was the basis for both technological and social-cognitive evolution and, through an optimizing positive feedback loop between the cerebellum and cerebral cortex, the development of cumulative culture occurred, and (3) the generalization and blending of cerebellar internal models related to the unconscious forward control of the optimization of imagined future states in working memory was the most important brain adaptation leading to intertwined advances in stone-tool technology, cognitive-social processes behind cumulative culture (including the emergence of language and art) and, thereby, with the rise of Homo sapiens.

Fetal brain MRI atlases and datasets: A review

Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., "brain template" and "brain atlas"), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging.

The pathobiology of psychomotor slowing in psychosis: altered cortical excitability and connectivity

Psychomotor slowing is a frequent symptom of schizophrenia. Short-interval intracortical inhibition assessed by transcranial magnetic stimulation demonstrated inhibitory dysfunction in schizophrenia. The inhibitory deficit results from additional noise during information processing in the motor system in psychosis. Here, we tested whether cortical inhibitory dysfunction was linked to psychomotor slowing and motor network alterations. In this cross-sectional study, we included 60 patients with schizophrenia and psychomotor slowing determined by the Salpêtrière Retardation Rating Scale, 23 patients without slowing and 40 healthy control participants. We acquired single and double-pulse transcranial magnetic stimulation effects from the left primary motor cortex, resting-state functional connectivity and diffusion imaging on the same day. Groups were compared on resting motor threshold, amplitude of the motor evoked potentials, as well as short-interval intracortical inhibition. Regression analyses calculated the association between motor evoked potential amplitudes or cortical inhibition with seed-based resting-state functional connectivity from the left primary motor cortex and fractional anisotropy at whole brain level and within major motor tracts. In patients with schizophrenia and psychomotor slowing, we observed lower amplitudes of motor evoked potentials, while the short-interval intracortical inhibition/motor evoked potentials amplitude ratio was higher than in healthy controls, suggesting lower cortical inhibition in these patients. Patients without slowing also had lower amplitudes of motor evoked potentials. Across the combined patient sample, cortical inhibition deficits were linked to more motor coordination impairments. In patients with schizophrenia and psychomotor slowing, lower amplitudes of motor evoked potentials were associated with lower fractional anisotropy in motor tracts. Moreover, resting-state functional connectivity between the primary motor cortex, the anterior cingulate cortex and the cerebellum increased with stronger cortical inhibition. In contrast, in healthy controls and patients without slowing, stronger cortical inhibition was linked to lower resting-state functional connectivity between the left primary motor cortex and premotor or parietal cortices. Psychomotor slowing in psychosis is linked to less cortical inhibition and aberrant functional connectivity of the primary motor cortex. Higher neural noise in the motor system may drive psychomotor slowing and thus may become a treatment target.

Behaviour-correlated profiles of cerebellar-cerebral functional connectivity observed in independent neurodevelopmental disorder cohorts

The cerebellum, through its connectivity with the cerebral cortex, plays an integral role in regulating cognitive and affective processes, and its dysregulation can result in neurodevelopmental disorder (NDD)-related behavioural deficits. Identifying cerebellar-cerebral functional connectivity (FC) profiles in children with NDDs can provide insight into common connectivity profiles and their correlation to NDD-related behaviours. 479 participants from the Province of Ontario Neurodevelopmental Disorders (POND) network (typically developing = 93, Autism Spectrum Disorder = 172, Attention Deficit/Hyperactivity Disorder = 161, Obsessive-Compulsive Disorder = 53, mean age = 12.2) underwent resting-state functional magnetic resonance imaging and behaviour testing (Social Communication Questionnaire, Toronto Obsessive-Compulsive Scale, and Child Behaviour Checklist - Attentional Problems Subscale). FC components maximally correlated to behaviour were identified using canonical correlation analysis. Results were then validated by repeating the investigation in 556 participants from an independent NDD cohort provided from a separate consortium (Healthy Brain Network (HBN)). Replication of canonical components was quantified by correlating the feature vectors between the two cohorts. The two cerebellar-cerebral FC components that replicated to the greatest extent were correlated to, respectively, obsessive-compulsive behaviour (behaviour feature vectors, rPOND-HBN = -0.97; FC feature vectors, rPOND-HBN = -0.68) and social communication deficit contrasted against attention deficit behaviour (behaviour feature vectors, rPOND-HBN = -0.99; FC feature vectors, rPOND-HBN = -0.78). The statistically stable (|z| > 1.96) features of the FC feature vectors, measured via bootstrap re-sampling, predominantly comprised of correlations between cerebellar attentional and control network regions and cerebral attentional, default mode, and control network regions. In both cohorts, spectral clustering on FC loading values resulted in subject clusters mixed across diagnostic categories, but no cluster was significantly enriched for any given diagnosis as measured via chi-squared test (p > 0.05). Overall, two behaviour-correlated components of cerebellar-cerebral functional connectivity were observed in two independent cohorts. This suggests the existence of generalizable cerebellar network differences that span across NDD diagnostic boundaries.

The Role of the Human Cerebellum for Learning from and Processing of External Feedback in Non-Motor Learning: A Systematic Review

This review aimed to systematically identify and comprehensively review the role of the cerebellum in performance monitoring, focusing on learning from and on processing of external feedback in non-motor learning. While 1078 articles were screened for eligibility, ultimately 36 studies were included in which external feedback was delivered in cognitive tasks and which referenced the cerebellum. These included studies in patient populations with cerebellar damage and studies in healthy subjects applying neuroimaging. Learning performance in patients with different cerebellar diseases was heterogeneous, with only about half of all patients showing alterations. One patient study using EEG demonstrated that damage to the cerebellum was associated with altered neural processing of external feedback. Studies assessing brain activity with task-based fMRI or PET and one resting-state functional imaging study that investigated connectivity changes following feedback-based learning in healthy participants revealed involvement particularly of lateral and posterior cerebellar regions in processing of and learning from external feedback. Cerebellar involvement was found at different stages, e.g., during feedback anticipation and following the onset of the feedback stimuli, substantiating the cerebellum's relevance for different aspects of performance monitoring such as feedback prediction. Future research will need to further elucidate precisely how, where, and when the cerebellum modulates the prediction and processing of external feedback information, which cerebellar subregions are particularly relevant, and to what extent cerebellar diseases alter these processes.

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Transcranial Direct Current Stimulation (tDCS) has demonstrated its potential in enhancing surgical training and performance compared to sham tDCS. However, optimizing its efficacy requires the selection of appropriate brain targets informed by neuroimaging and mechanistic understanding. Previous studies have established the feasibility of using portable brain imaging, combining functional near-infrared spectroscopy (fNIRS) with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks. This allows concurrent monitoring of cortical activations. Building on these foundations, our study aimed to explore the multi-modal imaging of the brain response using fNIRS and electroencephalogram (EEG) to tDCS targeting the right cerebellar (CER) and left ventrolateral prefrontal cortex (PFC) during a challenging FLS suturing with intracorporeal knot tying task. Involving twelve novices with a medical/premedical background (age: 22-28 years, two males, 10 females with one female with left-hand dominance), our investigation sought mechanistic insights into tDCS effects on brain areas related to error-based learning, a fundamental skill acquisition mechanism. The results revealed that right CER tDCS applied to the posterior lobe elicited a statistically significant (q < 0.05) brain response in bilateral prefrontal areas at the onset of the FLS task, surpassing the response seen with sham tDCS. Additionally, right CER tDCS led to a significant (p < 0.05) improvement in FLS scores compared to sham tDCS. Conversely, the left PFC tDCS did not yield a statistically significant brain response or improvement in FLS performance. In conclusion, right CER tDCS demonstrated the activation of bilateral prefrontal brain areas, providing valuable mechanistic insights into the effects of CER tDCS on FLS peformance. These insights motivate future investigations into the effects of CER tDCS on error-related perception-action coupling through directed functional connectivity studies.

Human cerebellar organoids with functional Purkinje cells

Research on human cerebellar development and disease has been hampered by the need for a human cell-based system that recapitulates the human cerebellum's cellular diversity and functional features. Here, we report a human organoid model (human cerebellar organoids [hCerOs]) capable of developing the complex cellular diversity of the fetal cerebellum, including a human-specific rhombic lip progenitor population that have never been generated in vitro prior to this study. 2-month-old hCerOs form distinct cytoarchitectural features, including laminar organized layering, and create functional connections between inhibitory and excitatory neurons that display coordinated network activity. Long-term culture of hCerOs allows healthy survival and maturation of Purkinje cells that display molecular and electrophysiological hallmarks of their in vivo counterparts, addressing a long-standing challenge in the field. This study therefore provides a physiologically relevant, all-human model system to elucidate the cell-type-specific mechanisms governing cerebellar development and disease.

A Comparative Perspective on the Cerebello-Cerebral System and Its Link to Cognition

The longstanding idea that the cerebral cortex is the main neural correlate of human cognition can be elaborated by comparative analyses along the vertebrate phylogenetic tree that support the view that the cerebello-cerebral system is suited to support non-motor functions more generally. In humans, diverse accounts have illustrated cerebellar involvement in cognitive functions. Although the neocortex, and its transmodal association cortices such as the prefrontal cortex, have become disproportionately large over primate evolution specifically, human neocortical volume does not appear to be exceptional relative to the variability within primates. Rather, several lines of evidence indicate that the exceptional volumetric increase of the lateral cerebellum in conjunction with its connectivity with the cerebral cortical system may be linked to non-motor functions and mental operation in primates. This idea is supported by diverging cerebello-cerebral adaptations that potentially coevolve with cognitive abilities across other vertebrates such as dolphins, parrots, and elephants. Modular adaptations upon the vertebrate cerebello-cerebral system may thus help better understand the neuroevolutionary trajectory of the primate brain and its relation to cognition in humans. Lateral cerebellar lobules crura I-II and their reciprocal connections to the cerebral cortical association areas appear to have substantially expanded in great apes, and humans. This, along with the notable increase in the ventral portions of the dentate nucleus and a shift to increased relative prefrontal-cerebellar connectivity, suggests that modular cerebellar adaptations support cognitive functions in humans. In sum, we show how comparative neuroscience provides new avenues to broaden our understanding of cerebellar and cerebello-cerebral functions in the context of cognition.

Deep topographic proteomics of a human brain tumour

The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular level.

Phylogenetic comparative analysis of the cerebello-cerebral system in 34 species highlights primate-general expansion of cerebellar crura I-II

The reciprocal connections between the cerebellum and the cerebrum have been suggested to simultaneously play a role in brain size increase and to support a broad array of brain functions in primates. The cerebello-cerebral system has undergone marked functionally relevant reorganization. In particular, the lateral cerebellar lobules crura I-II (the ansiform) have been suggested to be expanded in hominoids. Here, we manually segmented 63 cerebella (34 primate species; 9 infraorders) and 30 ansiforms (13 species; 8 infraorders) to understand how their volumes have evolved over the primate lineage. Together, our analyses support proportional cerebellar-cerebral scaling, whereas ansiforms have expanded faster than the cerebellum and cerebrum. We did not find different scaling between strepsirrhines and haplorhines, nor between apes and non-apes. In sum, our study shows primate-general structural reorganization of the ansiform, relative to the cerebello-cerebral system, which is relevant for specialized brain functions in an evolutionary context.

Cerebellar transcranial magnetic stimulation in psychotic disorders: intermittent, continuous, and sham theta-burst stimulation on time perception and symptom severity

Background

The cerebellum contributes to the precise timing of non-motor and motor functions, and cerebellum abnormalities have been implicated in psychosis pathophysiology. In this study, we explored the effects of cerebellar theta burst stimulation (TBS), an efficient transcranial magnetic stimulation protocol, on temporal discrimination and self-reported mood and psychotic symptoms.

Methods

We conducted a case-crossover study in which patients with psychosis (schizophrenias, schizoaffective disorders, or bipolar disorders with psychotic features) were assigned to three sessions of TBS to the cerebellar vermis: one session each of intermittent (iTBS), continuous (cTBS), and sham TBS. Of 28 enrolled patients, 26 underwent at least one TBS session, and 20 completed all three. Before and immediately following TBS, participants rated their mood and psychotic symptoms and performed a time interval discrimination task (IDT). We hypothesized that cerebellar iTBS and cTBS would modulate these measures in opposing directions, with iTBS being adaptive and cTBS maladaptive.

Results

Reaction time (RT) in the IDT decreased significantly after iTBS vs. Sham (LS-mean difference = -73.3, p = 0.0001, Cohen's d = 1.62), after iTBS vs. cTBS (LS-mean difference = -137.6, p < 0.0001, d = 2.03), and after Sham vs. cTBS (LS-mean difference = -64.4, p < 0.0001, d = 1.33). We found no effect on IDT accuracy. We did not observe any effects on symptom severity after correcting for multiple comparisons.

Conclusion

We observed a frequency-dependent dissociation between the effects of iTBS vs. cTBS to the cerebellar midline on the reaction time of interval discrimination in patients with psychosis. iTBS showed improved (adaptive) while cTBS led to worsening (maladaptive) speed of response. These results demonstrate behavioral target engagement in a cognitive dimension of relevance to patients with psychosis and generate testable hypotheses about the potential therapeutic role of cerebellar iTBS in this clinical population.

Clinical Trial Registration

clinicaltrials.gov, identifier NCT02642029.

Predicting an individual's cerebellar activity from functional connectivity fingerprints

The cerebellum is gaining scientific attention as a key neural substrate of cognitive function; however, individual differences in the cerebellar organization have not yet been well studied. Individual differences in functional brain organization can be closely tied to individual differences in brain connectivity. 'Connectome Fingerprinting' is a modeling approach that predicts an individual's brain activity from their connectome. Here, we extend 'Connectome Fingerprinting' (CF) to the cerebellum. We examined functional MRI data from 160 subjects (98 females) of the Human Connectome Project young adult dataset. For each of seven cognitive task paradigms, we constructed CF models from task activation maps and resting-state cortico-cerebellar functional connectomes, using a set of training subjects. For each model, we then predicted task activation in novel individual subjects, using their resting-state functional connectomes. In each cognitive paradigm, the CF models predicted individual subject cerebellar activity patterns with significantly greater precision than did predictions from the group average task activation. Examination of the CF models revealed that the cortico-cerebellar connections that carried the most information were those made with the non-motor portions of the cerebral cortex. These results demonstrate that the fine-scale functional connectivity between the cerebral cortex and cerebellum carries important information about individual differences in cerebellar functional organization. Additionally, CF modeling may be useful in the examination of patients with cerebellar dysfunction, since model predictions require only resting-state fMRI data which is more easily obtained than task fMRI.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Explicit and Implicit Emotion Processing in the Cerebellum: A Meta-analysis and Systematic Review

The cerebellum's role in affective processing is increasingly recognized in the literature, but remains poorly understood, despite abundant clinical evidence for affective disruptions following cerebellar damage. To improve the characterization of emotion processing and investigate how attention allocation impacts this processing, we conducted a meta-analysis on task activation foci using GingerALE software. Eighty human neuroimaging studies of emotion including 2761 participants identified through Web of Science and ProQuest databases were analyzed collectively and then divided into two categories based on the focus of attention during the task: explicit or implicit emotion processing. The results examining the explicit emotion tasks identified clusters within the posterior cerebellar hemispheres (bilateral lobule VI/Crus I/II), the vermis, and left lobule V/VI that were likely to be activated across studies, while implicit tasks activated clusters including bilateral lobules VI/Crus I/II, right Crus II/lobule VIII, anterior lobule VI, and lobules I-IV/V. A direct comparison between these categories revealed five overlapping clusters in right lobules VI/Crus I/Crus II and left lobules V/VI/Crus I of the cerebellum common to both the explicit and implicit task contrasts. There were also three clusters activated significantly more for explicit emotion tasks compared to implicit tasks (right lobule VI, left lobule VI/vermis), and one cluster activated more for implicit than explicit tasks (left lobule VI). These findings support previous studies indicating affective processing activates both the lateral hemispheric lobules and the vermis of the cerebellum. The common and distinct activation of posterior cerebellar regions by tasks with explicit and implicit attention demonstrates the supportive role of this structure in recognizing, appraising, and reacting to emotional stimuli.

Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability

A rapidly emerging application of network neuroscience in neuroimaging studies has provided useful tools to understand individual differences in intrinsic brain function by mapping spontaneous brain activity, namely intrinsic functional network neuroscience (ifNN). However, the variability of methodologies applied across the ifNN studies-with respect to node definition, edge construction, and graph measurements-makes it difficult to directly compare findings and also challenging for end users to select the optimal strategies for mapping individual differences in brain networks. Here, we aim to provide a benchmark for best ifNN practices by systematically comparing the measurement reliability of individual differences under different ifNN analytical strategies using the test-retest design of the Human Connectome Project. The results uncovered four essential principles to guide ifNN studies: (1) use a whole brain parcellation to define network nodes, including subcortical and cerebellar regions; (2) construct functional networks using spontaneous brain activity in multiple slow bands; and (3) optimize topological economy of networks at individual level; and (4) characterize information flow with specific metrics of integration and segregation. We built an interactive online resource of reliability assessments for future ifNN (https://ibraindata.com/research/ifNN).

Dissociating distinct cortical networks associated with subregions of the human medial temporal lobe using precision neuroimaging

Tract-tracing studies in primates indicate that different subregions of the medial temporal lobe (MTL) are connected with multiple brain regions. However, no clear framework defining the distributed anatomy associated with the human MTL exists. This gap in knowledge originates in notoriously low MRI data quality in the anterior human MTL and in group-level blurring of idiosyncratic anatomy between adjacent brain regions, such as entorhinal and perirhinal cortices, and parahippocampal areas TH/TF. Using MRI, we intensively scanned four human individuals and collected whole-brain data with unprecedented MTL signal quality. Following detailed exploration of cortical networks associated with MTL subregions within each individual, we discovered three biologically meaningful networks associated with the entorhinal cortex, perirhinal cortex, and parahippocampal area TH, respectively. Our findings define the anatomical constraints within which human mnemonic functions must operate and are insightful for examining the evolutionary trajectory of the MTL connectivity across species.

Insights from personalized models of brain and behavior for identifying biomarkers in psychiatry

A main goal in translational neuroscience is to identify neural correlates of psychopathology ("biomarkers") that can be used to facilitate diagnosis, prognosis, and treatment. This goal has led to substantial research into how psychopathology symptoms relate to large-scale brain systems. However, these efforts have not yet resulted in practical biomarkers used in clinical practice. One reason for this underwhelming progress may be that many study designs focus on increasing sample size instead of collecting additional data within each individual. This focus limits the reliability and predictive validity of brain and behavioral measures in any one person. As biomarkers exist at the level of individuals, an increased focus on validating them within individuals is warranted. We argue that personalized models, estimated from extensive data collection within individuals, can address these concerns. We review evidence from two, thus far separate, lines of research on personalized models of (1) psychopathology symptoms and (2) fMRI measures of brain networks. We close by proposing approaches uniting personalized models across both domains to improve biomarker research.

Psilocybin desynchronizes brain networks

1The relationship between the acute effects of psychedelics and their persisting neurobiological and psychological effects is poorly understood. Here, we tracked brain changes with longitudinal precision functional mapping in healthy adults before, during, and for up to 3 weeks after oral psilocybin and methylphenidate (17 MRI visits per participant) and again 6+ months later. Psilocybin disrupted connectivity across cortical networks and subcortical structures, producing more than 3-fold greater acute changes in functional networks than methylphenidate. These changes were driven by desynchronization of brain activity across spatial scales (area, network, whole brain). Psilocybin-driven desynchronization was observed across association cortex but strongest in the default mode network (DMN), which is connected to the anterior hippocampus and thought to create our sense of self. Performing a perceptual task reduced psilocybin-induced network changes, suggesting a neurobiological basis for grounding, connecting with physical reality during psychedelic therapy. The acute brain effects of psilocybin are consistent with distortions of space-time and the self. Psilocybin induced persistent decrease in functional connectivity between the anterior hippocampus and cortex (and DMN in particular), lasting for weeks but normalizing after 6 months. Persistent suppression of hippocampal-DMN connectivity represents a candidate neuroanatomical and mechanistic correlate for psilocybin's pro-plasticity and anti-depressant effects.

A review of brain regions and associated post-concussion symptoms

The human brain is an exceptionally complex organ that is comprised of billions of neurons. Therefore, when a traumatic event such as a concussion occurs, somatic, cognitive, behavioral, and sleep impairments are the common outcome. Each concussion is unique in the sense that the magnitude of biomechanical forces and the direction, rotation, and source of those forces are different for each concussive event. This helps to explain the unpredictable nature of post-concussion symptoms that can arise and resolve. The purpose of this narrative review is to connect the anatomical location, healthy function, and associated post-concussion symptoms of some major cerebral gray and white matter brain regions and the cerebellum. As a non-exhaustive description of post-concussion symptoms nor comprehensive inclusion of all brain regions, we have aimed to amalgamate the research performed for specific brain regions into a single article to clarify and enhance clinical and research concussion assessment. The current status of concussion diagnosis is highly subjective and primarily based on self-report of symptoms, so this review may be able to provide a connection between brain anatomy and the clinical presentation of concussions to enhance medical imaging assessments. By explaining anatomical relevance in terms of clinical concussion symptom presentation, an increased understanding of concussions may also be achieved to improve concussion recognition and diagnosis.

A triple distinction of cerebellar function for oculomotor learning and fatigue compensation

The cerebellum implements error-based motor learning via synaptic gain adaptation of an inverse model, i.e. the mapping of a spatial movement goal onto a motor command. Recently, we modeled the motor and perceptual changes during learning of saccadic eye movements, showing that learning is actually a threefold process. Besides motor recalibration of (1) the inverse model, learning also comprises perceptual recalibration of (2) the visuospatial target map and (3) of a forward dynamics model that estimates the saccade size from corollary discharge. Yet, the site of perceptual recalibration remains unclear. Here we dissociate cerebellar contributions to the three stages of learning by modeling the learning data of eight cerebellar patients and eight healthy controls. Results showed that cerebellar pathology restrains short-term recalibration of the inverse model while the forward dynamics model is well informed about the reduced saccade change. Adaptation of the visuospatial target map trended in learning direction only in control subjects, yet without reaching significance. Moreover, some patients showed a tendency for uncompensated oculomotor fatigue caused by insufficient upregulation of saccade duration. According to our model, this could induce long-term perceptual compensation, consistent with the overestimation of target eccentricity found in the patients' baseline data. We conclude that the cerebellum mediates short-term adaptation of the inverse model, especially by control of saccade duration, while the forward dynamics model was not affected by cerebellar pathology.

Thalamo-cortical and cerebello-cortical functional connectivity in development

The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.

Cerebellar connectome alterations and associated genetic signatures in multiple sclerosis and neuromyelitis optica spectrum disorder

BACKGROUND

The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown.

METHODS

Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles.

RESULTS

Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained > 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases.

CONCLUSIONS

We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases.

A somato-cognitive action network alternates with effector regions in motor cortex

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.

A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum

While resting-state fMRI studies have provided a broad picture of the connectivity between human neocortex and cerebellum, the degree of convergence of cortical inputs onto cerebellar circuits remains unknown. Does each cerebellar region receive input from a single cortical area or convergent inputs from multiple cortical areas? Here, we use task-based fMRI data to build a range of cortico-cerebellar connectivity models, each allowing for a different degree of convergence. We compared these models by their ability to predict cerebellar activity patterns for novel Task Sets. Models that allow some degree of convergence provided the best predictions, arguing for convergence of multiple cortical inputs onto single cerebellar voxels. Importantly, the degree of convergence varied across the cerebellum with the highest convergence observed in areas linked to language, working memory, and social cognition. These findings suggest important differences in the way that functional subdivisions of the cerebellum support motor and cognitive function.

Gray matter differences in adults and children with posttraumatic stress disorder: A systematic review and meta-analysis of 113 studies and 11 meta-analyses

BACKGROUND

In this systematic review and meta-analysis, we aimed to provide a comprehensive overview of gray matter alterations of adult- and underage patients with posttraumatic stress disorder (PTSD) in comparison to healthy trauma-exposed (TC) and non-exposed (HC) individuals.

METHODS

We subdivided our groups into patients with PTSD after trauma exposure in adulthood (aa) or childhood (ac) as well as children with PTSD (cc). We identified 113 studies, including 6.800 participants in our review, which we divided into studies focusing on whole-brain and region-of-interest (ROI) analysis. We performed a coordinate-based meta-analysis on 14 studies in the group of aa-PTSD.

RESULTS

We and found lower gray matter volume in patients with PTSD (aa) in the medial frontal gyrus (PTSD<HC/TC) and Culmen/posterior cingulate cortex (PTSD<TC). Results from ROI-based studies mainly show alterations for patients with PTSD in the prefrontal cortex, hippocampus, anterior cingulate cortex, insula, corpus callosum, and amygdala.

LIMITATIONS

Due to a limited number of studies reporting whole-brain results, the meta-analyses could only be performed in one subgroup and within this subgroup for a limited number of studies.

CONCLUSIONS

Our results are in line with psychobiological models of PTSD that associate the identified regions with brain circuits involved in context processing, threat detection and emotion regulation.

A framework for focal and connectomic mapping of transiently disrupted brain function

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective anatomical information with focal disruption of function are needed to disambiguate local from global neural dependence, and critical from merely coincidental activity. Here we present a comprehensive framework for focal and connective spatial inference based on sparse disruptive data, and demonstrate its application in the context of transient direct electrical stimulation of the human medial frontal wall during the pre-surgical evaluation of patients with focal epilepsy. Our framework formalizes voxel-wise mass-univariate inference on sparsely sampled data within the statistical parametric mapping framework, encompassing the analysis of distributed maps defined by any criterion of connectivity. Applied to the medial frontal wall, this transient dysconnectome approach reveals marked discrepancies between local and distributed associations of major categories of motor and sensory behaviour, revealing differentiation by remote connectivity to which purely local analysis is blind. Our framework enables disruptive mapping of the human brain based on sparsely sampled data with minimal spatial assumptions, good statistical efficiency, flexible model formulation, and explicit comparison of local and distributed effects.

Whole-brain dynamics of human sensorimotor adaptation

Humans vary greatly in their motor learning abilities, yet little is known about the neural processes that underlie this variability. We identified distinct profiles of human sensorimotor adaptation that emerged across 2 days of learning, linking these profiles to the dynamics of whole-brain functional networks early on the first day when cognitive strategies toward sensorimotor adaptation are believed to be most prominent. During early learning, greater recruitment of a network of higher-order brain regions, involving prefrontal and anterior temporal cortex, was associated with faster learning. At the same time, greater integration of this "cognitive network" with a sensorimotor network was associated with slower learning, consistent with the notion that cognitive strategies toward adaptation operate in parallel with implicit learning processes of the sensorimotor system. On the second day, greater recruitment of a network that included the hippocampus was associated with faster learning, consistent with the notion that declarative memory systems are involved with fast relearning of sensorimotor mappings. Together, these findings provide novel evidence for the role of higher-order brain systems in driving variability in adaptation.

Using synthetic MR images for distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

Resting state network mapping in individuals using deep learning

Introduction

Resting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases to individual network mapping for pre-surgical planning of tumor resections. Reproducibility of these results has been shown to require a substantial amount of high-quality data, which is not often available in clinical or research settings.

Methods

In this work, we report voxelwise mapping of a standard set of RSNs using a novel deep 3D convolutional neural network (3DCNN). The 3DCNN was trained on publicly available functional MRI data acquired in n = 2010 healthy participants. After training, maps that represent the probability of a voxel belonging to a particular RSN were generated for each participant, and then used to calculate mean and standard deviation (STD) probability maps, which are made publicly available. Further, we compared our results to previously published resting state and task-based functional mappings.

Results

Our results indicate this method can be applied in individual subjects and is highly resistant to both noisy data and fewer RS-fMRI time points than are typically acquired. Further, our results show core regions within each network that exhibit high average probability and low STD.

Discussion

The 3DCNN algorithm can generate individual RSN localization maps, which are necessary for clinical applications. The similarity between 3DCNN mapping results and task-based fMRI responses supports the association of specific functional tasks with RSNs.

Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments

Vocal emotion recognition, a key determinant to analyzing a speaker's emotional state, is known to be impaired following cerebellar dysfunctions. Nevertheless, its possible functional integration in the large-scale brain network subtending emotional prosody recognition has yet to be explored. We administered an emotional prosody recognition task to patients with right versus left-hemispheric cerebellar lesions and a group of matched controls. We explored the lesional correlates of vocal emotion recognition in patients through a network-based analysis by combining a neuropsychological approach for lesion mapping with normative brain connectome data. Results revealed impaired recognition among patients for neutral or negative prosody, with poorer sadness recognition performances by patients with right cerebellar lesion. Network-based lesion-symptom mapping revealed that sadness recognition performances were linked to a network connecting the cerebellum with left frontal, temporal, and parietal cortices. Moreover, when focusing solely on a subgroup of patients with right cerebellar damage, sadness recognition performances were associated with a more restricted network connecting the cerebellum to the left parietal lobe. As the left hemisphere is known to be crucial for the processing of short segmental information, these results suggest that a corticocerebellar network operates on a fine temporal scale during vocal emotion decoding.

Individual-level functional connectomes predict the motor symptoms of Parkinson's disease

Abnormalities in functional connectivity networks are associated with sensorimotor networks in Parkinson's disease (PD) based on group-level mapping studies, but these results are controversial. Using individual-level cortical segmentation to construct individual brain atlases can supplement the individual information covered by group-level cortical segmentation. Functional connectivity analyses at the individual level are helpful for obtaining clinically useful markers and predicting treatment response. Based on the functional connectivity of individualized regions of interest, a support vector regression model was trained to estimate the severity of motor symptoms for each subject, and a correlation analysis between the estimated scores and clinical symptom scores was performed. Forty-six PD patients aged 50-75 years were included from the Parkinson's Progression Markers Initiative database, and 63 PD patients were included from the Beijing Rehabilitation Hospital database. Only patients below Hoehn and Yahr stage III were included. The analysis showed that the severity of motor symptoms could be estimated by the individualized functional connectivity between the visual network and sensorimotor network in early-stage disease. The results reveal individual-level connectivity biomarkers related to motor symptoms and emphasize the importance of individual differences in the prediction of the treatment response of PD.

A Prospective Evaluation of Infant Cerebellar-Cerebral Functional Connectivity in Relation to Behavioral Development in Autism Spectrum Disorder

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection.

Methods

Data from the Infant Brain Imaging Study (n = 94, 68 male) were used to examine 6-month cerebellar functional connectivity magnetic resonance imaging in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning-based predictive tests examined cerebellar-frontoparietal network (FPN; subserves error signaling in support of EBL) and cerebellar-default mode network (DMN; broadly implicated in ASD) connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven functional connectivity magnetic resonance imaging enrichment examined brain-wide behavioral associations, with post hoc tests of cerebellar connections.

Results

Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. Functional connectivity magnetic resonance imaging enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post hoc tests did not suggest a role for cerebellar connections.

Conclusions

We failed to identify cerebellar functional connectivity-based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities.

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene silencing trial has recently started, there is an urgent need for quantitative, sensitive imaging markers at pre-symptomatic stages for stratification and treatment assessment. This work introduces CerebNet, a fully automated, extensively validated, deep learning method for the lobular segmentation of the cerebellum, including the separation of gray and white matter. For training, validation, and testing, T1-weighted images from 30 participants were manually annotated into cerebellar lobules and vermal sub-segments, as well as cerebellar white matter. CerebNet combines FastSurferCNN, a UNet-based 2.5D segmentation network, with extensive data augmentation, e.g. realistic non-linear deformations to increase the anatomical variety, eliminating additional preprocessing steps, such as spatial normalization or bias field correction. CerebNet demonstrates a high accuracy (on average 0.87 Dice and 1.742mm Robust Hausdorff Distance across all structures) outperforming state-of-the-art approaches. Furthermore, it shows high test-retest reliability (average ICC >0.97 on OASIS and Kirby) as well as high sensitivity to disease effects, including the pre-ataxic stage of spinocerebellar ataxia type 3 (SCA3). CerebNet is compatible with FreeSurfer and FastSurfer and can analyze a 3D volume within seconds on a consumer GPU in an end-to-end fashion, thus providing an efficient and validated solution for assessing cerebellum sub-structure volumes. We make CerebNet available as source-code (https://github.com/Deep-MI/FastSurfer).

Cognitive control training enhances the integration of intrinsic functional networks in adolescents

Introduction

We have demonstrated that intensive cognitive training can produce sustained improvements in cognitive performance in adolescents. Few studies, however, have investigated the neural basis of these training effects, leaving the underlying mechanism of cognitive plasticity during this period unexplained.

Methods

In this study, we trained 51 typically developing adolescents on cognitive control tasks and examined how their intrinsic brain networks changed by applying graph theoretical analysis. We hypothesized that the training would accelerate the process of network integration, which is a key feature of network development throughout adolescence.

Results

We found that the cognitive control training enhanced the integration of functional networks, particularly the cross-network integration of the cingulo-opercular network. Moreover, the analysis of additional data from older adolescents revealed that the cingulo-opercular network was more integrated with other networks in older adolescents than in young adolescents.

Discussion

These findings are consistent with the hypothesis that cognitive control training may speed up network development, such that brain networks exhibit more mature patterns after training.

The underpinnings of cerebellar ataxias

The human cerebellum contains more than 60% of all neurons of the brain. Anatomically, the cerebellum is divided into 10 lobules (I-X). The cerebellar cortex is arranged into three layers: the molecular layer (external), the Purkinje cell layer and the granular layer (internal). Purkinje neurons and interneurons are inhibitory, except for granule cells. The layer of Purkinje neurons inhibit cerebellar nuclei, the sole output of the cerebellar circuitry, as well as vestibular nuclei. The cerebellum is arranged into a series of olivo-cortico-nuclear modules arranged longitudinally in the rostro-caudal plane. The cerebro-cerebellar connectivity is organized into multiple loops running in parallel. From the clinical standpoint, it is now considered that cerebellar symptoms can be gathered into 3 cerebellar syndromes: a cerebellar motor syndrome (CMS), a vestibulocerebellar syndrome (VCS) and a cerebellar cognitive affective syndrome/Schmahmann syndrome (CCAS/SS). CMS remains a cornerstone of modern clinical ataxiology, and relevant lesions involve lobules I-V, VI and VIII. The core feature of cerebellar symptoms is dysmetria, covering motor dysmetria (errors in the metrics of motion) and dysmetria of thought. The cerebellar circuitry plays a key-role in the generation and maintenance of internal models which correspond to neural representations reproducing the dynamic properties of the body. These models allow predictive computations for motor, cognitive, social, and affective operations. Cerebellar circuitry is endowed with noticeable plasticity properties.

The complexity of the stream of consciousness

Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.

Automated optimization of TMS coil placement for personalized functional network engagement

Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.

Cerebellum lineage allocation, morphogenesis and repair: impact of interplay amongst cells

The cerebellum has a simple cytoarchitecture consisting of a folded cortex with three cell layers that surrounds a nuclear structure housing the output neurons. The excitatory neurons are generated from a unique progenitor zone, the rhombic lip, whereas the inhibitory neurons and astrocytes are generated from the ventricular zone. The growth phase of the cerebellum is driven by lineage-restricted progenitor populations derived from each zone. Research during the past decade has uncovered the importance of cell-to-cell communication between the lineages through largely unknown signaling mechanisms for regulating the scaling of cell numbers and cell plasticity during mouse development and following injury in the neonatal (P0-P14) cerebellum. This Review focuses on how the interplay between cell types is key to morphogenesis, production of robust neural circuits and replenishment of cells after injury, and ends with a discussion of the implications of the greater complexity of the human cerebellar progenitor zones for development and disease.

Person-specific and precision neuroimaging: Current methods and future directions

Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat interindividual differences in brain organization as noise, but this approach can obscure important information about the brain's functional architecture. Recently, a number of studies have adopted a person-specific approach that aims to characterize these individual differences and explore their reliability and implications for behavior. A subset of these studies has taken a precision imaging approach that collects multiple hours of data from each participant to map brain function on a finer scale. In this review, we provide a broad overview of how person-specific and precision imaging techniques have used resting-state measures to examine individual differences in the brain's organization and their impact on behavior, followed by how task-based activity continues to add detail to these discoveries. We argue that person-specific and precision approaches demonstrate substantial promise in uncovering new details of the brain's functional organization and its relationship to behavior in many areas of cognitive neuroscience. We also discuss some current limitations in this new field and some new directions it may take.

Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

OBJECTIVE

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

METHOD

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer's type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

RESULTS

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive-behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

CONCLUSION

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

Human Cerebellar Development and Transcriptomics: Implications for Neurodevelopmental Disorders

Developmental abnormalities of the cerebellum are among the most recognized structural brain malformations in human prenatal imaging. Yet reliable information regarding their cause in humans is sparse, and few outcome studies are available to inform prognosis. We know very little about human cerebellar development, in stark contrast to the wealth of knowledge from decades of research on cerebellar developmental biology of model organisms, especially mice. Recent studies show that multiple aspects of human cerebellar development significantly differ from mice and even rhesus macaques, a nonhuman primate. These discoveries challenge many current mouse-centric models of normal human cerebellar development and models regarding the pathogenesis of several neurodevelopmental phenotypes affecting the cerebellum, including Dandy-Walker malformation and medulloblastoma. Since we cannot model what we do not know, additional normative and pathological human developmental data are essential, and new models are needed.

Accuracy and reliability of diffusion imaging models

Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.

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.