Network models articles within Nature Communications

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  • Article
    | Open Access

    How the dauer, an alternative developmental stage in nematodes, exhibits distinct behavioral traits remains unclear. Here, the authors reveal the neural circuitry underlying these distinctions by reconstructing the dauer connectome and comparing it with other stages.

    • Hyunsoo Yim
    • , Daniel T. Choe
    •  & Junho Lee

  • Article
    | Open Access

    The neural mechanisms that give rise to aperiodic EEG signals remains unclear. Here the authors characterize EEG signals generated by neural processes other than brain rhythms, demonstrating that certain drugs alter EEG signals in ways that confound traditional interpretation.

    • Niklas Brake
    • , Flavie Duc
    •  & Gilles Plourde

  • Article
    | Open Access

    Neonatal brain dynamics are not well understood. Here, the authors characterise brain transient states in neonates, and show that preterm infants display altered whole brain dynamics and an atypical repertoire of regional transient states, which are associated with behavioural outcomes at 18 months of age.

    • Lucas G. S. França
    • , Judit Ciarrusta
    •  & Dafnis Batalle

  • Article
    | Open Access

    The developmental trajectory of hippocampal ripples, the electrical signature of long term memory storage, is poorly understood. Here, the authors show that their delayed appearance is mechanistically linked to the maturation of inhibition.

    • Irina Pochinok
    • , Tristan M. Stöber
    •  & Ileana L. Hanganu-Opatz

  • Article
    | Open Access

    Brain connectivity patterns shape computational capacity of biological neural networks, however mapping empirically measured connectivity to artificial networks remains challenging. The authors present a toolbox for implementing biological neural networks as artificial reservoir networks. The toolbox allows for a variety of empirical/measured connectomes and is equipped with various dynamical systems, and cognitive tasks.

    • Laura E. Suárez
    • , Agoston Mihalik
    •  & Bratislav Misic

  • Article
    | Open Access

    Differences in information transmission in the brain network between humans and other species are not well understood. Here, the authors apply an information theory approach to structural connectomes and functional MRI and report that human brain networks display more evidence of parallel information transmission compared to macaques and mice.

    • Alessandra Griffa
    • , Mathieu Mach
    •  & Enrico Amico

  • Article
    | Open Access

    Animals respond rapidly and precisely to a variety of sensory stimuli, but the neural mechanisms supporting this flexibility are not fully understood. Here the authors describe a model of adaptive sensory processing based on functionally-targeted stochastic modulation, and find evidence for this co-variability in macaque V1 and middle temporal area.

    • Caroline Haimerl
    • , Douglas A. Ruff
    •  & Eero P. Simoncelli

  • Article
    | Open Access

    How learning refines the coordinated activitity of neurons across multiple regions of the mouse cortex remains unclear. Here, the authors identified the emergence of cortical subnetworks during learning of a sensorimotor task.

    • Xin Wei Chia
    • , Jian Kwang Tan
    •  & Hiroshi Makino

  • Article
    | Open Access

    How the brain selects relevant information in complex and dynamic environments remains poorly understood. Here, the authors reveal that distinct neural populations in rat auditory cortex gate stimuli based on context, which could be facilitated by top-down signals from the prefrontal cortex.

    • Joao Barbosa
    • , Rémi Proville
    •  & Yves Boubenec

  • Article
    | Open Access

    Recent research sheds light on sex-specific molecular changes in the brains of MDD patients, but their association with specific symptoms is still uncertain. Here, the authors revealed the existence of gene signatures underlying the expression of distinct symptom domains in the brain of men and women with depression.

    • Samaneh Mansouri
    • , André M. Pessoni
    •  & Benoit Labonté

  • Article
    | Open Access

    How neurophysiological dynamics are organized across the cortex and their relationship with cortical micro-architecture is not well understood. Here, the authors find the dominant axis of neurophysiological dynamics reflects characteristics of the power spectrum and the linear correlation structure of the signal, and that spatial variation in neurophysiological dynamics is colocalized with multiple micro-architectural features.

    • Golia Shafiei
    • , Ben D. Fulcher
    •  & Bratislav Misic

  • Article
    | Open Access

    Network controllability represents the ease with which the brain switches between mental states and can be inferred from white matter connectivity. Here, the authors show network controllability emerges in infants as early as the third trimester, and that preterm birth disrupts the energy required to drive state transitions.

    • Huili Sun
    • , Rongtao Jiang
    •  & Dustin Scheinost

  • Comment
    | Open Access

    The current gap between computing algorithms and neuromorphic hardware to emulate brains is an outstanding bottleneck in developing neural computing technologies. Aimone and Parekh discuss the possibility of bridging this gap using theoretical computing frameworks from a neuroscience perspective.

    • James B. Aimone
    •  & Ojas Parekh

  • Article
    | Open Access

    Human decision confidence displays a number of biases and has been shown to dissociate from decision accuracy. Here, by using neural network and Bayesian models, the authors show that these effects can be explained by the statistics of sensory inputs.

    • Taylor W. Webb
    • , Kiyofumi Miyoshi
    •  & Hakwan Lau

  • Article
    | Open Access

    Rumination, which is the tendency to dwell on negative internal states repetitively, is a well-known cognitive style associated with depression. The authors developed a predictive model of rumination and observed that the dorsomedial prefrontal cortex plays an important role in rumination.

    • Jungwoo Kim
    • , Jessica R. Andrews-Hanna
    •  & Choong-Wan Woo

  • Article
    | Open Access

    Better understanding of a trade-off between the speed and accuracy of decision-making is relevant for mapping biological intelligence to machines. The authors introduce a brain-inspired learning algorithm to uncover dependencies in individual fMRI networks with features of neural activity and predict inter-individual differences in decision-making.

    • Michael Schirner
    • , Gustavo Deco
    •  & Petra Ritter

  • Article
    | Open Access

    How macroscale connectivity relates to regional micro-architecture is poorly understood. Here, the authors annotate brain networks with microarchitectural attributes, finding that the interplay between connection patterns and biological annotations shape regional functional specialization.

    • Vincent Bazinet
    • , Justine Y. Hansen
    •  & Bratislav Misic

  • Article
    | Open Access

    Not much is known about how intrinsic timescales, which characterize the dynamics of endogenous fluctuations in neural activity, change during cognitive tasks. Here, the authors show that intrinsic timescales of neural activity in the primate visual cortex change during spatial attention. Experimental data were best explained by a network model in which timescales arise from spatially arranged connectivity.

    • Roxana Zeraati
    • , Yan-Liang Shi
    •  & Tatiana A. Engel

  • Article
    | Open Access

    In the posterior cortex, which is involved in decision making, the strength and area specificity of choice signals are highly variable. Here the authors show that the representation of choice in the posterior area of the mouse brain is orthogonal to that of sensory and movement-related signals, with modulations determined by task features and cognitive demands.

    • Javier G. Orlandi
    • , Mohammad Abdolrahmani
    •  & Andrea Benucci

  • Article
    | Open Access

    In animals, sensory systems appear optimized for the statistics of the external world. Here the authors take an artificial psychophysics approach, analysing sensory responses in artificial neural networks, and show why these demonstrate the same phenomenon as natural sensory systems.

    • Ari S. Benjamin
    • , Ling-Qi Zhang
    •  & Konrad P. Kording

  • Article
    | Open Access

    Neural circuit dynamics are thought to drive temporally precise actions. Here, the authors used a theoretical approach to show that synapses endowed with diverse short-term plasticity can act as tunable timers sufficient to generate rich neural dynamics.

    • A. Barri
    • , M. T. Wiechert
    •  & D. A. DiGregorio

  • Article
    | Open Access

    How the human visual system leverages the rich structure in object motion for perception remains unclear. Here, Bill et al. propose a theory of how the brain could infer motion relations in real time and offer a unifying explanation for various perceptual phenomena.

    • Johannes Bill
    • , Samuel J. Gershman
    •  & Jan Drugowitsch

  • Article
    | Open Access

    The sensory cortices of many mammals consist of modules in the form of cortical columns. By analyzing functional connectivity and neural responses to visual stimuli, the authors show that this organization may extend to the human temporal lobe.

    • Julio I. Chapeton
    • , John H. Wittig Jr
    •  & Kareem A. Zaghloul

  • Article
    | Open Access

    There are several models of how serotonergic psychedelic drugs affect brain activity. Here the authors use network control theory and functional MRI data to provide evidence that serotonin receptor agonists LSD and psilocybin flatten the brain’s dynamic landscape, allowing for facile state transitions and more temporally diverse brain activity.

    • S. Parker Singleton
    • , Andrea I. Luppi
    •  & Amy Kuceyeski

  • Article
    | Open Access

    Although spontaneous brain activity is complex and clinically relevant, it is still unclear whether transitions in resting brain activity follow an underlying arrangement or whether they are unpredictable. In this work, the authors revealed a transition state of the brain that acts like a switch between states and forms the basis for the continuous evolution of brain activity patterns at rest.

    • Manish Saggar
    • , James M. Shine
    •  & Damien Fair

  • Article
    | Open Access

    Memory formation and recall are complementary processes within the hippocampus. Here the authors demonstrate a synaptic signal of novelty in the hippocampus and provide a computational framework for how such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

    • Ruy Gómez-Ocádiz
    • , Massimiliano Trippa
    •  & Christoph Schmidt-Hieber

  • Article
    | Open Access

    The intrinsic dynamics of neurons, in particular the generation action potentials, can impact neural network states and processes of encoding information. The authors demonstrate how the elevation of temperature induces a type of action potential dynamics that favors synchronization patterns in neural networks.

    • Janina Hesse
    • , Jan-Hendrik Schleimer
    •  & Susanne Schreiber

  • Article
    | Open Access

    The authors investigate the influence of brain injury (strokes) on the criticality of neural dynamics using directly measured connectomes and whole-brain models. They show that lesions engender a sub-critical state that recovers over time in parallel with behavior.

    • Rodrigo P. Rocha
    • , Loren Koçillari
    •  & Maurizio Corbetta

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