This scientific commentary refers to ‘Decomposing MRI phenotypic heterogeneity in epilepsy: a step towards personalized classification’ by Lee et al. (https://doi.org/10.1093/brain/awab425).
•Network neuroscience combines elements from many disciplines.•We discuss three key areas of inquiry: descriptive, predictive, and perturbative.•Descriptive approaches employ advanced tools from ...graph theory.•Predictive approaches employ machine learning to predict behavior from features.•Perturbative approaches employ network control theory to explain system energetics.
The field of network neuroscience has emerged as a natural framework for the study of the brain and has been increasingly applied across divergent problems in neuroscience. From a disciplinary perspective, network neuroscience originally emerged as a formal integration of graph theory (from mathematics) and neuroscience (from biology). This early integration afforded marked utility in describing the interconnected nature of neural units, both structurally and functionally, and underscored the relevance of that interconnection for cognition and behavior. But since its inception, the field has not remained static in its methodological composition. Instead, it has grown to use increasingly advanced graph-theoretic tools and to bring in several other disciplinary perspectives—including machine learning and systems engineering—that have proven complementary. In doing so, the problem space amenable to the discipline has expanded markedly. In this review, we discuss three distinct flavors of investigation in state-of-the-art network neuroscience: (i) descriptive network neuroscience, (ii) predictive network neuroscience, and (iii) a perturbative network neuroscience that draws on recent advances in network control theory. In considering each area, we provide a brief summary of the approaches, discuss the nature of the insights obtained, and highlight future directions.
A fundamental goal of research in neuroscience is to uncover the causal structure of the brain. This focus on causation makes sense, because causal information can provide explanations of brain ...function and identify reliable targets with which to understand cognitive function and prevent or change neurological conditions and psychiatric disorders. In this research, one of the most frequently used causal concepts is 'mechanism' - this is seen in the literature and language of the field, in grant and funding inquiries that specify what research is supported, and in journal guidelines on which contributions are considered for publication. In these contexts, mechanisms are commonly tied to expressions of the main aims of the field and cited as the 'fundamental', 'foundational' and/or 'basic' unit for understanding the brain. Despite its common usage and perceived importance, mechanism is used in different ways that are rarely distinguished. Given that this concept is defined in different ways throughout the field - and that there is often no clarification of which definition is intended - there remains a marked ambiguity about the fundamental goals, orientation and principles of the field. Here we provide an overview of causation and mechanism from the perspectives of neuroscience and philosophy of science, in order to address these challenges.
Deterministic chaos permits a precise notion of a "perfect measurement" as one that, when obtained repeatedly, captures all of the information created by the system's evolution with minimal ...redundancy. Finding an optimal measurement is challenging and has generally required intimate knowledge of the dynamics in the few cases where it has been done. We establish an equivalence between a perfect measurement and a variant of the information bottleneck. As a consequence, we can employ machine learning to optimize measurement processes that efficiently extract information from trajectory data. We obtain approximately optimal measurements for multiple chaotic maps and lay the necessary groundwork for efficient information extraction from general time series.
Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique to each individual and to the environments we co-create. However, our theoretical and ...methodological toolkits often ignore this reality. There is growing awareness that a shift is needed that allows us to study divergence of brain and behaviour across conventional categorical boundaries. However, we argue that in future our study of divergence must also incorporate the developmental dynamics that capture the emergence of those neurodevelopmental differences. This crucial step will require adjustments in study design and methodology. If our ultimate aim is to incorporate the developmental dynamics that capture how, and ultimately when, divergence takes place then we will need an analytic toolkit equal to these ambitions. We argue that the over reliance on group averages has been a conceptual dead-end with regard to the neurodevelopmental differences. This is in part because any individual differences and developmental dynamics are inevitably lost within the group average. Instead, analytic approaches which are themselves new, or simply newly applied within this context, may allow us to shift our theoretical and methodological frameworks from groups to individuals. Likewise, methods capable of modelling complex dynamic systems may allow us to understand the emergent dynamics only possible at the level of an interacting neural system.
•Efforts to characterise cognition in young people must incorporate the developmental dynamics of how cognitive difficulties emerge.•The interdependence of cognitive processes poses a substantive challenge to characterising divergence between individuals.•The adherence to group-averaging makes it difficult to place difficulties or neural correlates within a developmental context.•Analytic approaches which are themselves new, or simply newly applied, afford a conceptual shift from groups to individuals.•These methods move beyond the model of adult neuropsychology, to foreground emergence across brain networks and across time.
Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a ...substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.
Thermal intolerance may limit activity in hostile environments. After heat illness, two physiologically distinct phenotypes evolve: heat tolerant (HT) and heat intolerant (HI). The recognition that ...heat illness alters gene expression justified revisiting the established physiological concept of HI. We used a DNA microarray to examine the global transcriptional response in peripheral blood mononuclear cells (PMBCs) from HI and HT phenotypes, categorized 2-mo postheat injury using a functional physiological heat-tolerance test (HTT, 40°C)-Recovery (R, 24°C) protocol. The impact of recurrent heat stress was studied in vitro using peripheral blood mononuclear cells (PBMCs) from controls (participants with no history of heat injury), HI, and HT (categorized by functional HTT) with a customized NanoString array. There were significant differences under basal conditions between the HI and HT. HI were more immunological alerted. Almost no shared genes were found between end-HTT and recovery phases, suggesting vast cellular plasticity. In HI, mitochondrial function was dysregulated, canonical pathways associated with exercise endurance-NRF2 and insulin were downregulated, whereas AMPK and peroxisome proliferator-activated receptor (PPAR) were upregulated. HT exhibited reciprocal responses, suggesting that energy dysregulation found in HI interfered with performance in the heat. The endoplasmic-reticulum stress response was also suppressed in HI. In vitro HTT (43°C) abolished differences between HI and HT PBMCs including the HSPs genes, whereas controls showed profound HSPs upregulation.
Mutations in methyl-CpG-binding protein 2 (MeCP2) cause Rett syndrome and related autism spectrum disorders (Amir et al., 1999). MeCP2 is believed to be required for proper regulation of brain gene ...expression, but prior microarray studies in Mecp2 knock-out mice using brain tissue homogenates have revealed only subtle changes in gene expression (Tudor et al., 2002; Nuber et al., 2005; Jordan et al., 2007; Chahrour et al., 2008). Here, by profiling discrete subtypes of neurons we uncovered more dramatic effects of MeCP2 on gene expression, overcoming the "dilution problem" associated with assaying homogenates of complex tissues. The results reveal misregulation of genes involved in neuronal connectivity and communication. Importantly, genes upregulated following loss of MeCP2 are biased toward longer genes but this is not true for downregulated genes, suggesting MeCP2 may selectively repress long genes. Because genes involved in neuronal connectivity and communication, such as cell adhesion and cell-cell signaling genes, are enriched among longer genes, their misregulation following loss of MeCP2 suggests a possible etiology for altered circuit function in Rett syndrome.
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