Computational neuroscience articles within Nature Communications

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  • Article
    | Open Access

    The extent to which brain structure and function are coupled remains a complex question. Here, the authors show that coupling strength between structural connectivity and functional activity can be quantified and reveals a cortical gradient spanning from lower-level sensory areas to high-level cognitive ones.

    • Maria Giulia Preti
    •  & Dimitri Van De Ville

  • Article
    | Open Access

    Current techniques have enabled the simultaneous collection of spike train data from large numbers of neurons. Here, the authors report a method to infer the underlying neural circuit connectivity diagram based on a generalized linear model applied to spike cross-correlations between neurons.

    • Ryota Kobayashi
    • , Shuhei Kurita
    •  & Shigeru Shinomoto

  • Article
    | Open Access

    How are stable memories maintained in the brain despite significant ongoing fluctuations in synaptic strengths? Here, the authors show that a model consistent with fluctuations, homeostasis and biologically plausible learning rules, naturally leads to memories implemented as dynamic attractors.

    • Lee Susman
    • , Naama Brenner
    •  & Omri Barak

  • Article
    | Open Access

    Neural signalling is directional, but non-invasive neuroimaging methods are unable to map directed connections between brain regions. Here, the authors show how network communication measures can be used to infer signalling directionality from the undirected topology of brain structural connectomes.

    • Caio Seguin
    • , Adeel Razi
    •  & Andrew Zalesky

  • Article
    | Open Access

    Sense of agency (SoA) refers to the experience that one's own actions caused an external event. Here, the authors present a model of SoA in terms of optimal Bayesian cue integration taking into account reliability of action and outcome sensory signals and judging if the action caused the outcome.

    • Roberto Legaspi
    •  & Taro Toyoizumi

  • Article
    | Open Access

    Light intensity on the retina can fluctuate rapidly during natural vision, posing a challenge for encoding visual information. Here, the authors report that mechanisms of sensitization/facilitation maintain the sensitivity of the numerically dominant neural pathway in the primate retina during dynamic vision.

    • Todd R. Appleby
    •  & Michael B. Manookin

  • Article
    | Open Access

    The nature of the signals that propagate through feedforward networks is not well understood. Here, the authors combine microfabrication, multilayer cortical cultures, and optogenetic stimulation to show that NMDA-mediated synaptic current generates a sustained phase of activity that propagates firing rate signals.

    • Jérémie Barral
    • , Xiao-Jing Wang
    •  & Alex D. Reyes

  • Article
    | Open Access

    The effect of spontaneous variations in prestimulus neural activity on subsequent perception is incompletely understood. Here, using MEG, the authors identify two distinct neural processes that can influence object recognition in different ways.

    • Ella Podvalny
    • , Matthew W. Flounders
    •  & Biyu J. He

  • Article
    | Open Access

    The authors show that areas of the auditory cortex differ in the extent to which their responses to sounds are altered by the presence of background noise. Cortical responses to sounds in primary areas are more affected by background noise than are those in non-primary areas.

    • Alexander J. E. Kell
    •  & Josh H. McDermott

  • Article
    | Open Access

    A combination of large-scale connectomics with cellular and synapse data to generate a first draft statistical model of the neuron-to-neuron micro-connectome of a whole mouse neocortex. This micro-connectome recreates biological trends of targeting on the macro-, meso-, and micro-scale.

    • Michael W. Reimann
    • , Michael Gevaert
    •  & Eilif Muller

  • Article
    | Open Access

    Whether cortical neurons can fire reliable spikes amid cellular noise and chaotic network dynamics remains debated. Here the authors simulate a detailed neocortical microcircuit model and show that noisy and chaotic cortical network dynamics are compatible with stimulus-evoked, millisecond spike-time reliability.

    • Max Nolte
    • , Michael W. Reimann
    •  & Eilif B. Muller

  • Perspective
    | Open Access

    Recent gains in artificial neural networks rely heavily on large amounts of training data. Here, the author suggests that for AI to learn from animal brains, it is important to consider that animal behaviour results from brain connectivity specified in the genome through evolution, and not due to unique learning algorithms.

    • Anthony M. Zador

  • Article
    | Open Access

    Recent experimental work has revealed non-linear dendritic integration in interneurons. Here, the authors show, through detailed biophysical modeling, that fast spiking interneurons are better described with a 2-stage artificial neural network model calling into question the use of point neuron models.

    • Alexandra Tzilivaki
    • , George Kastellakis
    •  & Panayiota Poirazi

  • Article
    | Open Access

    By examining the organization of bird song and human speech, the authors show that the two types of communication signals have similar sequential structures, following both hierarchical and Markovian organization.

    • Tim Sainburg
    • , Brad Theilman
    •  & Timothy Q. Gentner

  • Article
    | Open Access

    It is known that attention can modify the brain's representations of sensory stimuli to enhance features of importance. Here, the authors show that flexible readout of cortical representations is also required to explain the behavioral effects of attention.

    • Daniel Birman
    •  & Justin L. Gardner

  • Article
    | Open Access

    Neural representations in working memory are susceptible to internal noise, which scales with memory load. Here, the authors show that attractor dynamics mitigate the influence of internal noise by pulling memories towards a few stable representations.

    • Matthew F. Panichello
    • , Brian DePasquale
    •  & Timothy J. Buschman

  • Article
    | Open Access

    It is thought that higher cortical areas are more plastic than lower ones, but there is little direct evidence for this. Here, the authors show that plasticity (defined as lower heritability) of functional connectivity decreases from early to mid-level visual cortex, and then increases further up the visual hierarchy.

    • Koen V. Haak
    •  & Christian F. Beckmann

  • Article
    | Open Access

    The praying mantis, a predatory insect, estimates depth via binocular vision. In this way, the animal decides whether prey is within reach. Here, the authors explore the neural correlates of binocular distance estimation and report that individual neurons are tuned to specific locations in 3D space.

    • Ronny Rosner
    • , Joss von Hadeln
    •  & Jenny C. A. Read

  • Comment
    | Open Access

    Qualitative psychological principles are commonly utilized to influence the choices that people make. Can this goal be achieved more efficiently by using quantitative models of choice? Here, we launch an academic competition to compare the effectiveness of these two approaches.

    • Ohad Dan
    •  & Yonatan Loewenstein

  • Article
    | Open Access

    Motor preparation processes guide movement. Here, by recording neural activity in monkeys reaching toward targets that can change location, the authors provide evidence that changing a prepared movement midway through completion reengages motor preparation.

    • K. Cora Ames
    • , Stephen I. Ryu
    •  & Krishna V. Shenoy

  • Article
    | Open Access

    The brain stores memories through a set of neurons known as engram cells. Here, the authors show that engram cells in the mouse hippocampus are organized into sub-ensembles representing distinct pieces of information, which are then orchestrated to constitute an entire memory.

    • Khaled Ghandour
    • , Noriaki Ohkawa
    •  & Kaoru Inokuchi

  • Article
    | Open Access

    Transcranial alternating current stimulation (TACS) of the brain is widely used in neuroscience, but the electric fields produced when multiple stimulation electrodes are used are not well understood. Here, the authors directly record electric fields in primate brains during multi-electrode TACS.

    • Ivan Alekseichuk
    • , Arnaud Y. Falchier
    •  & Alexander Opitz

  • Article
    | Open Access

    In order to make optimal choices, it is adaptive for the brain to build a model of the world to enable predictions about likely later events. Here, the authors show that activity across learning in the orbitofrontal cortex comes to represent expected states, up to 30 s in the future.

    • G. Elliott Wimmer
    •  & Christian Büchel

  • Article
    | Open Access

    Despite the known role of midbrain dopaminergic (mDA) signaling in the homeostatic control of mood and motor functions, little is known about how gene expression in these neurons is regulated. Here, authors develop an in vivo nuclear tagging and capture technique for low-input chromatin accessibility and transcriptome profiling of genetically-defined neuron populations to identify Gmeb1 as a novel transcriptional regulator of mDA neurons, whose loss of function impairs motor control in mice.

    • Luis M. Tuesta
    • , Mohamed N. Djekidel
    •  & Yi Zhang

  • Article
    | Open Access

    NREM sleep in rodents is characterized by internal dynamics in the form of UP/DOWN states in the neocortex and SWRs in the hippocampus. Here, the authors report that a mean field model with excitable dynamics captures the transition probabilities between these states from rodent sleep data.

    • Daniel Levenstein
    • , György Buzsáki
    •  & John Rinzel

  • Article
    | Open Access

    Place cells are neurons in the hippocampus which encode an animal’s location in space. Here, in mice, the authors show that place cell activity is also modulated by the heading-direction of the animal relative to a particular “reference point” that can be either within or outside their enclosure.

    • P. E. Jercog
    • , Y. Ahmadian
    •  & E. R. Kandel

  • Article
    | Open Access

    An individual’s pattern of resting state brain connectivity, as measured with fMRI, has been shown to predict cognitive and behavioral traits. Here, the authors show that different traits are predicted by different time-scales of resting state activity (dynamic vs. static).

    • Raphaël Liégeois
    • , Jingwei Li
    •  & B. T. Thomas Yeo

  • Article
    | Open Access

    We make decisions with varying degrees of confidence and, if our confidence in a decision falls, we may change our mind. Here, the authors present a neuronal circuit model to account for how change of mind occurs under particular low-confidence conditions.

    • Nadim A. A. Atiya
    • , Iñaki Rañó
    •  & KongFatt Wong-Lin

  • Article
    | Open Access

    People differ in their current levels of understanding of many complex concepts. Here, the authors show using fMRI that brain activity during a task that requires concept knowledge can be used to compute a ‘neural score’ of the participant’s understanding.

    • Joshua S. Cetron
    • , Andrew C. Connolly
    •  & David J. M. Kraemer

  • Article
    | Open Access

    Game theory typically models strategic human behavior using scenarios with decision constraints that poorly represent real-world social interactions. Here, the authors show it is possible to model dynamic, real-world strategic interactions using Bayesian and reinforcement learning principles.

    • Kelsey R. McDonald
    • , William F. Broderick
    •  & John M. Pearson

  • Article
    | Open Access

    Santiago Herce Castañón and colleagues show that people are blind to mental errors that arise when combining multiple pieces of discordant information. This blindness helps explain why cognitive judgements often are suboptimal.

    • Santiago Herce Castañón
    • , Rani Moran
    •  & Christopher Summerfield

  • Article
    | Open Access

    Most neuronal reconstruction software can automatically trace single neuronal morphologies but tracing multiple, densely interwoven neurons is much more challenging. Here the authors develop G-Cut, a computational approach for accurate segmentation of densely interconnected neuron clusters.

    • Rui Li
    • , Muye Zhu
    •  & Hong-Wei Dong

  • Article
    | Open Access

    There has been recent controversy over the validity of commonly-used software packages for functional MRI (fMRI) data analysis. Here, the authors compare the performance of three leading packages (AFNI, FSL, SPM) in terms of temporal autocorrelation modeling, a key statistical step in fMRI analysis.

    • Wiktor Olszowy
    • , John Aston
    •  & Guy B. Williams

  • Article
    | Open Access

    Large-scale brain activity arises from inter-areal interactions determined by the underlying connectivity. Here, the authors develop a whole-brain model based on connectivity data that captures activity patterns such as cortical waves and metastability, relating these to underlying brain anatomy.

    • James A. Roberts
    • , Leonardo L. Gollo
    •  & Michael Breakspear

  • Article
    | Open Access

    Autism spectrum disorder (ASD) is associated with symptoms ranging from sensory hypersensitivity to social difficulties. Here, the authors provide evidence of atypical connectivity transitions between sensory and higher-order cortical areas in people with ASD, which could underlie the diverse symptoms.

    • Seok-Jun Hong
    • , Reinder Vos de Wael
    •  & Boris C. Bernhardt

  • Article
    | Open Access

    Sensory systems produce stable stimulus representations despite constant changes across multiple stimulus dimensions. Here, the authors reveal dynamic neural coding mechanisms by testing how coding of one dimension (orientation) changes with adaptations to other dimensions (luminance and contrast).

    • Masoud Ghodrati
    • , Elizabeth Zavitz
    •  & Nicholas S. C. Price

  • Article
    | Open Access

    Early neuropsychological studies suggested that different aspects of working memory (WM) are exclusively associated with specific brain areas. Here, the authors show, using machine-learning analysis of fMRI, how WM processes are dynamically coded by large-scale overlapping networks in the human brain.

    • Eyal Soreq
    • , Robert Leech
    •  & Adam Hampshire

  • Article
    | Open Access

    We can recognize an object from one of its features, e.g. hearing a bark leads us to think of a dog. Here, the authors show using fMRI that the brain combines bits of information into object representations, and that presenting a few features of an object activates representations of its other attributes.

    • Sasa L. Kivisaari
    • , Marijn van Vliet
    •  & Riitta Salmelin

  • Article
    | Open Access

    The reinforcement learning literature suggests decisions are based on a model-free system, operating retrospectively, and a model-based system, operating prospectively. Here, the authors show that a model-based retrospective inference of a reward’s cause, guides model-free credit-assignment.

    • Rani Moran
    • , Mehdi Keramati
    •  & Raymond J. Dolan

  • Article
    | Open Access

    An unresolved problem in neuroscience is to determine the relevant timescale for understanding spatiotemporal dynamics of the brain. Here, the authors introduce a new framework to study the different timescales through binning the output of a generative model of neural activity.

    • Gustavo Deco
    • , Josephine Cruzat
    •  & Morten L. Kringelbach

  • Article
    | Open Access

    To explain the neural correlates of behavior and its variability, one must analyze single-trial population dynamics. Here, the authors develop a statistical method that extracts low-dimensional dynamics that explain behavior better than high-dimensional neural activity revealing unexpected structure.

    • Ziqiang Wei
    • , Hidehiko Inagaki
    •  & Shaul Druckmann

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