Studies of large-scale brain organization have revealed interesting relationships between spatial gradients in brain maps across multiple modalities. Evaluating the significance of these findings ...requires establishing statistical expectations under a null hypothesis of interest. Through generative modeling of synthetic data that instantiate a specific null hypothesis, quantitative benchmarks can be derived for arbitrarily complex statistical measures. Here, we present a generative null model, provided as an open-access software platform, that generates surrogate maps with spatial autocorrelation (SA) matched to SA of a target brain map. SA is a prominent and ubiquitous property of brain maps that violates assumptions of independence in conventional statistical tests. Our method can simulate surrogate brain maps, constrained by empirical data, that preserve the SA of cortical, subcortical, parcellated, and dense brain maps. We characterize how SA impacts p-values in pairwise brain map comparisons. Furthermore, we demonstrate how SA-preserving surrogate maps can be used in gene set enrichment analyses to test hypotheses of interest related to brain map topography. Our findings demonstrate the utility of SA-preserving surrogate maps for hypothesis testing in complex statistical analyses, and underscore the need to disambiguate meaningful relationships from chance associations in studies of large-scale brain organization.
•Spatial autocorrelation can dramatically inflate p-values in brain map analyses.•Null model generates surrogate brain maps matched to target spatial autocorrelation.•Spatial autocorrelation drives spurious findings in gene set enrichment analyses.•Surrogate maps can correct statistical analyses including gene set enrichment.•Python-based package implements the generative model with neuroimaging functionality.
Abstract The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, ...symptoms and cognitive impairments arise. This review will consider ways that disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation will be framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It will consider developmental correlates and consequences including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It will also consider the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the “inverted-U” input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, deficits in the temporal tuning of neural activity and its implication for neural codes, and conclude by considering the functional significance of noisy activity for neural network function. This presentation will draw on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving NMDA glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in this review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders.
Multimodal gradients across mouse cortex Fulcher, Ben D.; Murray, John D.; Zerbi, Valerio ...
Proceedings of the National Academy of Sciences,
03/2019, Letnik:
116, Številka:
10
Journal Article
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The primate cerebral cortex displays a hierarchy that extends from primary sensorimotor to association areas, supporting increasingly integrated function underpinned by a gradient of heterogeneity in ...the brain’s microcircuits. The extent to which these hierarchical gradients are unique to primate or may reflect a conserved mammalian principle of brain organization remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1-weighted:T2-weighted (T1w:T2w) magnetic resonance imaging map as a common spatial reference for comparison across species, we report interspecies agreement in a range of large-scale cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex, as well as notable interspecies differences. Our results support the view of systematic structural variation across cortical areas as a core organizational principle that may underlie hierarchical specialization in mammalian brains.
Specialization and hierarchy are organizing principles for primate cortex, yet there is little direct evidence for how cortical areas are specialized in the temporal domain. We measured timescales of ...intrinsic fluctuations in spiking activity across areas and found a hierarchical ordering, with sensory and prefrontal areas exhibiting shorter and longer timescales, respectively. On the basis of our findings, we suggest that intrinsic timescales reflect areal specialization for task-relevant computations over multiple temporal ranges.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Hierarchy provides a unifying principle for the macroscale organization of anatomical and functional properties across primate cortex, yet microscale bases of specialization across human cortex are ...poorly understood. Anatomical hierarchy is conventionally informed by invasive tract-tracing measurements, creating a need for a principled proxy measure in humans. Moreover, cortex exhibits marked interareal variation in gene expression, yet organizing principles of cortical transcription remain unclear. We hypothesized that specialization of cortical microcircuitry involves hierarchical gradients of gene expression. We found that a noninvasive neuroimaging measure-MRI-derived T1-weighted/T2-weighted (T1w/T2w) mapping-reliably indexes anatomical hierarchy, and it captures the dominant pattern of transcriptional variation across human cortex. We found hierarchical gradients in expression profiles of genes related to microcircuit function, consistent with monkey microanatomy, and implicated in neuropsychiatric disorders. Our findings identify a hierarchical axis linking cortical transcription and anatomy, along which gradients of microscale properties may contribute to the macroscale specialization of cortical function.
The large-scale organization of dynamical neural activity across cortex emerges through long-range interactions among local circuits. We hypothesized that large-scale dynamics are also shaped by ...heterogeneity of intrinsic local properties across cortical areas. One key axis along which microcircuit properties are specialized relates to hierarchical levels of cortical organization. We developed a large-scale dynamical circuit model of human cortex that incorporates heterogeneity of local synaptic strengths, following a hierarchical axis inferred from magnetic resonance imaging (MRI)-derived T1- to T2-weighted (T1w/T2w) mapping and fit the model using multimodal neuroimaging data. We found that incorporating hierarchical heterogeneity substantially improves the model fit to functional MRI (fMRI)-measured resting-state functional connectivity and captures sensory-association organization of multiple fMRI features. The model predicts hierarchically organized higher-frequency spectral power, which we tested with resting-state magnetoencephalography. These findings suggest circuit-level mechanisms linking spatiotemporal levels of analysis and highlight the importance of local properties and their hierarchical specialization on the large-scale organization of human cortical dynamics.
•A circuit model with areal heterogeneity across cortex is fit to resting-state fMRI•Hierarchical specialization of microcircuitry follows the MRI-derived T1w/T2w map•T1w/T2w provides a preferential axis of specialization to fit functional connectivity•Hierarchical specialization is an organizing principle for spatiotemporal dynamics
Demirtaş et al. report a large-scale circuit model of human cortex incorporating regional heterogeneity in microcircuit properties using T1w/T2w mapping for parametrization across the cortical hierarchy and fitting models to resting-state functional connectivity. This study shows that hierarchical heterogeneity provides an organizing principle for spatiotemporal dynamics of human cortex.
Abstract Recent theoretical accounts have proposed excitation (E) and inhibition (I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across ...neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. Here we highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with EEG, MEG,1 H-MRS, and fMRI, including effects observed both during task and at rest. Throughout this review we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human non-invasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.
Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of ...thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness.
A considerable body of evidence has accumulated over recent years on the functions of the default-mode network (DMN) – a set of brain regions whose activity is high when the mind is not engaged in ...specific behavioral tasks and low during focused attention on the external environment. In this review, we focus on DMN suppression and its functional role in health and disease, summarizing evidence that spans several disciplines, including cognitive neuroscience, pharmacological neuroimaging, clinical neuroscience, and theoretical neuroscience. Collectively, this research highlights the functional relevance of DMN suppression for goal-directed cognition, possibly by reducing goal-irrelevant functions supported by the DMN (e.g., mind-wandering), and illustrates the functional significance of DMN suppression deficits in severe mental illness.
While reading a book in a noisy café, how does your brain 'gate in' visual information while filtering out auditory stimuli? Here we propose a mechanism for such flexible routing of information flow ...in a complex brain network (pathway-specific gating), tested using a network model of pyramidal neurons and three classes of interneurons with connection probabilities constrained by data. We find that if inputs from different pathways cluster on a pyramidal neuron dendrite, a pathway can be gated-on by a disinhibitory circuit motif. The branch-specific disinhibition can be achieved despite dense interneuronal connectivity, even with random connections. Moreover, clustering of input pathways on dendrites can naturally emerge through synaptic plasticity regulated by dendritic inhibition. This gating mechanism in a neural circuit is further demonstrated by performing a context-dependent decision-making task. The model suggests that cognitive flexibility engages top-down signalling of behavioural rule or context that targets specific classes of inhibitory neurons.
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