Computational neuroscience articles within Nature Communications

Featured

  • Article
    | Open Access

    Memories formed around the same time are linked together by a shared temporal context. Here, the authors show that the ability to selectively retrieve distinct episodic memories formed close together in time is related to how quickly neural representations of temporal context change over time during encoding.

    • Mostafa M. El-Kalliny
    • , John H. Wittig Jr
    •  & Kareem A. Zaghloul

  • Article
    | Open Access

    The frontal cortex is involved in cognitive control, e.g. cognitive flexibility and behavioral inhibition, but the roles of frontal subdivisions are unclear. Here, the authors used computational modelling of cognitive control task performance to map lesions responsible for impairments in specific cognitive operations.

    • Jan Gläscher
    • , Ralph Adolphs
    •  & Daniel Tranel

  • Article
    | Open Access

    Molecular circuits implementing fold-change detection (FCD) allow cells to respond to fold-change in signals regardless of absolute levels. Here, the authors find that meaning, attention and saturation similarly form an FCD circuit and produce the observed dynamics of human behavior in creative search.

    • Yuval Hart
    • , Hagar Goldberg
    •  & Uri Alon

  • Article
    | Open Access

    To realize the potential of resistive RAM crossbar arrays as platforms for neuromorphic computing, reduced network-level energy consumption must be achieved. Here, the authors use a hardware/software co-design approach to realize reduced energy consumption during network training for the network.

    • Yuhan Shi
    • , Leon Nguyen
    •  & Duygu Kuzum

  • Article
    | Open Access

    Human eye movements when viewing scenes can reflect overt spatial attention. Here, O’Connell and Chun predict human eye movement patterns from BOLD responses to natural scenes. Linking brain activity, convolutional neural network (CNN) models, and eye movement behavior, they show that brain activity patterns and CNN models share representations that guide eye movements to scenes.

    • Thomas P. O’Connell
    •  & Marvin M. Chun

  • Article
    | Open Access

    While memory is often studied using voluntary recollection, the neural correlates of involuntary memory recall and its effect on cognition are unclear. Here, Ren and colleagues show that the effective connectivity from the anterior hippocampus to the precuneus can predict the strength of involuntary retrieval of episodic memory.

    • Yudan Ren
    • , Vinh T. Nguyen
    •  & Christine C. Guo

  • Article
    | Open Access

    Humans can perform complex motor movements at varying speeds. Here, the authors show that a recurrent neural network can be trained to exhibit temporal scaling obeying Weber’s law as well as validate a prediction of the model of improved precision of movements at faster speeds.

    • Nicholas F. Hardy
    • , Vishwa Goudar
    •  & Dean V. Buonomano

  • Article
    | Open Access

    Humans compensate for sensory noise by biasing sensory estimates toward prior expectations, as predicted by models of Bayesian inference. Here, the authors show that humans perform ‘late inference’ downstream of sensory processing to mitigate the effects of noisy internal mental computations.

    • Evan D. Remington
    • , Tiffany V. Parks
    •  & Mehrdad Jazayeri

  • Article
    | Open Access

    Attention affects stimulus response gain, but its impact without sensory drive is less known. Here, the authors show that attention is coded diversely in a population and is distinct between unstimulated and stimulated contexts, providing a contrast to normalized gain models of attention.

    • Adam C. Snyder
    • , Byron M. Yu
    •  & Matthew A. Smith

  • Article
    | Open Access

    Our brains predict the likely sensory consequences of actions we take; one theory is that these sensory responses are suppressed, but another theory is that they are sharpened. Here, the authors show using fMRI evidence consistent with the sharpening account for sensory consequences of hand movements.

    • Daniel Yon
    • , Sam J. Gilbert
    •  & Clare Press

  • Article
    | Open Access

    In a dynamic environment old evidence could be outdated. Here, the authors investigate the ability of rats to integrate and discount evidence provided by auditory clicks to infer a hidden, dynamic, state of the world and model the consequence of sensory noise to explain the source of errors.

    • Alex T. Piet
    • , Ahmed El Hady
    •  & Carlos D. Brody

  • Article
    | Open Access

    Perceptual learning, the improvement in perceptual abilities with training, is thought to involve changes in neuronal 'tuning'. Here, the authors show that perceptual learning works by making neurons increasingly sensitive to task-relevant differences in stimuli, and by improving population coding mechanisms.

    • Mehdi Sanayei
    • , Xing Chen
    •  & Alexander Thiele

  • Article
    | Open Access

    Functional magnetic resonance imaging (fMRI) is a powerful technique for measuring human brain activity, but the statistical analysis of fMRI data can be difficult. Here, the authors introduce a new fMRI analysis tool, LISA, which provides increased statistical power compared to existing techniques.

    • Gabriele Lohmann
    • , Johannes Stelzer
    •  & Klaus Scheffler

  • Article
    | Open Access

    Attractor dynamics have been discovered in neural circuits, but it is not clear if they exist at the level of whole-brain activity. Here, the authors show that certain brain regions act as nodes in which many activity ‘streams’ converge, regardless of brain state. These regions show distinctive gene expression.

    • Ibai Diez
    •  & Jorge Sepulcre

  • Article
    | Open Access

    Visual search requires recognizing an object “invariantly”, despite changes in its appearance. Here, the authors show that humans can efficiently and invariantly search for objects in complex scenes and introduce a biologically-inspired zero-shot model that captures human eye movements during search.

    • Mengmi Zhang
    • , Jiashi Feng
    •  & Gabriel Kreiman

  • Article
    | Open Access

    Multidimensional stimuli are often represented by neurons encoding only a single dimension and those encoding multiple dimensions. Here, the authors present theoretical and experimental analyses to show that mixed representations are optimal to efficiently encode such stimuli under different behavioral modes.

    • Arseny Finkelstein
    • , Nachum Ulanovsky
    •  & Johnatan Aljadeff

  • Article
    | Open Access

    It is debated whether motor cortical activity reflects plans for multiple potential actions. Here, the authors report that in a delayed response task with two potential reach targets, population activity in the dorsal premotor cortex at any moment in time represents only one of the targets.

    • Brian M. Dekleva
    • , Konrad P. Kording
    •  & Lee E. Miller

  • Article
    | Open Access

    Somatostatin+ (SOM+ ) GABAergic interneurons are known to fine-tune synaptic plasticity as they inhibit dendritic spikes and burst firing. Here, the authors show that both SOM+ and NOS+ interneurons preferentially recruit nonlinear outward-rectifying GABA(A)R with alpha5 subunit, and that this inhibition with slow gating kinetics matches voltage and time-dependent activation of synaptic NMDARs, thereby controlling the generation of dendritic NMDA spikes.

    • Jan M. Schulz
    • , Frederic Knoflach
    •  & Josef Bischofberger

  • Article
    | Open Access

    Astrocytes have gained increasing attention for their roles in regulating neural circuits via neurotransmitter uptake, K + buffering, and ability to signal via Ca2 + transients. Here, the authors develop a computational modelling environment for astrocytes, akin to the NEURON environment, called ASTRO.

    • Leonid P. Savtchenko
    • , Lucie Bard
    •  & Dmitri A. Rusakov

  • Article
    | Open Access

    Working memory (WM) is represented in persistent activity of single neurons as well as a dynamic population code. Here, the authors find that neurons flexibly switch their coding according to current attention while those with stable resting activity maintain WM representations through dynamic activity patterns.

    • Sean E. Cavanagh
    • , John P. Towers
    •  & Steven W. Kennerley

  • Article
    | Open Access

    Reverse correlation is a psychophysics technique used to infer sensory filter properties by measuring how changes in stimuli influence behavior. Here, the authors show that reverse correlation is shaped by both sensory and decision-making processes, and validate a method to partition their contributions.

    • Gouki Okazawa
    • , Long Sha
    •  & Roozbeh Kiani

  • Article
    | Open Access

    Previous work has shown that the neural representation of value adapts to the recent history of rewards. Here, the authors report that a computational model based on divisive normalization over multiple timescales can explain changes in value coding driven by changes in the reward statistics.

    • Jan Zimmermann
    • , Paul W. Glimcher
    •  & Kenway Louie

  • Article
    | Open Access

    Co-morbidity and symptom overlap make it difficult to associate psychiatric disorders with unique neural signatures. Here, the authors use a data-driven approach to show that the symptom dimensions of mood, psychosis, fear and externalizing behavior exhibit unique patterns of functional dysconnectivity.

    • Cedric Huchuan Xia
    • , Zongming Ma
    •  & Theodore D. Satterthwaite

  • Article
    | Open Access

    Saccades have been extensively used to report choices in perceptual decision making studies yet little is known about the influence of covert decision-related processes on saccade metrics. Here, the authors demonstrate that saccade kinematics is a reliable tell about the degree of decision certainty.

    • Joshua A. Seideman
    • , Terrence R. Stanford
    •  & Emilio Salinas

  • Article
    | Open Access

    Decoding or predicting cognitive traits from brain activity is an exciting prospect. Here, the authors show that task-based functional connectivity better predicts intelligence-related measures than rest-based connectivity, suggesting that cognitive tasks amplify individual differences in trait-relevant circuitry.

    • Abigail S. Greene
    • , Siyuan Gao
    •  & R. Todd Constable

  • Article
    | Open Access

    Memristive technology is a promising avenue towards realizing efficient non-von Neumann neuromorphic hardware. Boybat et al. proposes a multi-memristive synaptic architecture with a counter-based global arbitration scheme to address challenges associated with the non-ideal memristive device behavior.

    • Irem Boybat
    • , Manuel Le Gallo
    •  & Evangelos Eleftheriou

  • Article
    | Open Access

    Sensory areas are thought to process stimulus information while higher-order processing occurs in association cortices. Here the authors report that during task engagement population activity in ferret primary auditory cortex shifts away from encoding stimulus features toward detection of the behaviourally relevant targets.

    • Sophie Bagur
    • , Martin Averseng
    •  & Srdjan Ostojic

  • Article
    | Open Access

    Serotonin (5-HT) plays many important roles in reward, punishment, patience and beyond, and optogenetic stimulation of 5-HT neurons has not crisply parsed them. The authors report a novel analysis of a reward-based decision-making experiment, and show that 5-HT stimulation increases the learning rate, but only on a select subset of choices.

    • Kiyohito Iigaya
    • , Madalena S. Fonseca
    •  & Peter Dayan

  • Article
    | Open Access

    From infectious diseases to brain activity, complex systems can be approximated using autoregressive models. Here, the authors show that incomplete sampling can bias estimates of the stability of such systems, and introduce a novel, unbiased metric for use in such situations.

    • Jens Wilting
    •  & Viola Priesemann

  • Article
    | Open Access

    How structure and function coevolve in developing brains is little understood. Here, the authors study a coupled model of network development and memory, and find that due to the feedback networks with some initial memory capacity evolve into heterogeneous structures with high memory performance.

    • Ana P. Millán
    • , J. J. Torres
    •  & J Marro

  • Article
    | Open Access

    Prefrontal cortex is involved in flexibly learning the correct behavioural strategies but the neural correlates of this process are not well understood. Here the authors show that reinforcement for a correct decision at behavioural transitions evokes ensemble firing patterns related to prior events.

    • Silvia Maggi
    • , Adrien Peyrache
    •  & Mark D. Humphries

  • Article
    | Open Access

    Dopamine neurons encode reward prediction errors (RPE) that report the mismatch between expected reward and outcome for a given state. Here the authors report that when there is uncertainty about the current state, RPEs are calculated on the probabilistic representation of the current state or belief state.

    • Benedicte M. Babayan
    • , Naoshige Uchida
    •  & Samuel. J. Gershman

  • Article
    | Open Access

    Movements are continually constrained by the current body position and its relation to the surroundings. Here the authors report that the population activity of monkey dorsal premotor cortex neurons dynamically represents the probability distribution of possible reach directions.

    • Joshua I. Glaser
    • , Matthew G. Perich
    •  & Konrad P. Kording

  • Article
    | Open Access

    Fluctuations in mood are known to affect our decisions. Here the authors propose and validate a model of how mood fluctuations arise through a slow integration of positive and negative feedback and report the resulting key changes in brain activity that modulate our decision making.

    • Fabien Vinckier
    • , Lionel Rigoux
    •  & Mathias Pessiglione

  • Article
    | Open Access

    Perception relies on information integration but it is unclear how the brain decides which information to integrate and which to keep separate. Here, the authors develop and test a biologically inspired model of cue-integration, implicating a key role for GABAergic proscription in robust perception.

    • Reuben Rideaux
    •  & Andrew E. Welchman

  • Article
    | Open Access

    Grouping stimuli into categories often depends on a subjective determination of category boundaries. Here the authors report a neuronal population in pre-supplementary motor area whose peak activity predicts the categorical decision boundary between long and short time intervals on a trial-by-trial basis.

    • Germán Mendoza
    • , Juan Carlos Méndez
    •  & Hugo Merchant

  • Article
    | Open Access

    Previous work decoding linguistic meaning from imaging data has generally been limited to a small number of semantic categories. Here, authors show that a decoder trained on neuroimaging data of single concepts sampling the semantic space can robustly decode meanings of semantically diverse new sentences with topics not encountered during training.

    • Francisco Pereira
    • , Bin Lou
    •  & Evelina Fedorenko

  • Article
    | Open Access

    Human speech and bird song requires the generation of precisely timed motor patterns. The authors show that zebra finches can learn to independently modify the duration of individual song segments and find that synfire chain networks are ideally suited to implement such flexible motor timing.

    • Cengiz Pehlevan
    • , Farhan Ali
    •  & Bence P. Ölveczky

  • Article
    | Open Access

    Neocortical circuits exhibit diverse cell types that can be difficult to build into computational models. Here the authors employ a genetic algorithm-based parameter optimization to generate multi-compartment Hodgkin-Huxley models for diverse cell types in the Allen Cell Types Database.

    • Nathan W. Gouwens
    • , Jim Berg
    •  & Anton Arkhipov

  • Article
    | Open Access

    Simplified neuron models, such as generalized leaky integrate-and-fire (GLIF) models, are extensively used in network modeling. Here the authors systematically generate and compare GLIF models of varying complexity for their ability to classify cell types in the Allen Cell Types Database and faithfully reproduce spike trains.

    • Corinne Teeter
    • , Ramakrishnan Iyer
    •  & Stefan Mihalas

Browse broader subjects

Browse narrower subjects

Browse Computational neuroscience across other nature.com journals