Computational neuroscience

  • Article
    | Open Access

    Autism is characterized by diverse symptoms, including impaired social skills, motor and perceptual atypicalities. Here, using computational modelling, the authors show that impaired synchronization ability in autism stems from reduced error correction, supporting a slow-updating account of autism.

    • Gal Vishne
    • , Nori Jacoby
    •  & Merav Ahissar
  • Article
    | Open Access

    Models of decision making have so far been unable to account for how humans’ choices can be flexible yet efficient. Here the authors present a linear reinforcement learning model which explains both flexibility, and rare limitations such as habits, as arising from efficient approximate computation

    • Payam Piray
    •  & Nathaniel D. Daw
  • Article
    | Open Access

    The relationship between the human structural and functional connectome is still not well established. Here the authors show the interindividual variability that exists in regional coupling of structural and functional connectivity across the brain, and that this is heritable.

    • Zijin Gu
    • , Keith Wakefield Jamison
    •  & Amy Kuceyeski
  • Article
    | Open Access

    Visual processing necessitates both extracting and discarding information. Here, the authors use a specialized set of stimuli and two complementary discrimination tasks to demonstrate the opposing perceptual implications of these two aspects of information processing.

    • Corey M. Ziemba
    •  & Eero P. Simoncelli
  • Article
    | Open Access

    Feedback modulates visual neurons, thought to help achieve flexible task performance. Here, the authors show decision-related feedback is not only relayed to task-relevant neurons, suggesting a broader mechanism and supporting a previously hypothesized link to feature-based attention.

    • Katrina R. Quinn
    • , Lenka Seillier
    •  & Hendrikje Nienborg
  • Article
    | Open Access

    The formation of large-scale brain networks represents crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. Here, the authors use generative network modelling to provide a computational framework for understanding neurodevelopmental diversity.

    • Danyal Akarca
    • , Petra E. Vértes
    •  & Duncan E. Astle
  • Article
    | Open Access

    How genes sculpt the complex architecture of the human connectome remains unclear. Here, the authors show that genes preferentially influence the strength of connectivity between functionally valuable, metabolically costly connections between brain network hubs.

    • Aurina Arnatkeviciute
    • , Ben D. Fulcher
    •  & Alex Fornito
  • Article
    | Open Access

    Recurrent spiking neural networks have garnered interest due to their energy efficiency; however, they suffer from lower accuracy compared to conventional neural networks. Here, the authors present an alternative neuron model and its efficient hardware implementation, demonstrating high classification accuracy across a range of datasets.

    • Ahmed Shaban
    • , Sai Sukruth Bezugam
    •  & Manan Suri
  • Article
    | Open Access

    Working memory is a foundational component of cognition, but its mechanisms are poorly understood. Using a large sample of participants, this study identifies asymmetric dynamic interactions in cognitive control circuits, and their load-dependent network properties including controllability.

    • Weidong Cai
    • , Srikanth Ryali
    •  & Vinod Menon
  • Article
    | Open Access

    Synaptic inputs on neuronal dendrites exhibit remarkable organization at different spatial scales, which emerges during the early postnatal development. Kirchner and Gjorgjieva propose a biophysically motivated computational model to explain the different types of organization in mouse and ferret.

    • Jan H. Kirchner
    •  & Julijana Gjorgjieva
  • Article
    | Open Access

    The superior colliculus (SC) receives diverse cortical inputs to drive many behaviors. Here, based on comprehensive mapping of cortico-tectal projections, the authors refined the superior colliculus into medial, centromedial, centrolateral, and lateral zones, and characterized the input-output connectivity and morphology of neurons in each zone that serve the role of SC in goal-directed behaviors.

    • Nora L. Benavidez
    • , Michael S. Bienkowski
    •  & Hong-Wei Dong
  • Article
    | Open Access

    Surface two-photon imaging of the brain cannot access somatic calcium signals of neurons from deep layers of the macaque cortex. Here, the authors present an implant and imaging system for chronic motion-stabilized two-photon imaging of dendritic calcium signals to drive an optical brain-computer interface in macaques.

    • Eric M. Trautmann
    • , Daniel J. O’Shea
    •  & Krishna V. Shenoy
  • Article
    | Open Access

    The neural sampling theory suggests that neuronal variability encodes the uncertainty of probabilistic inferences. This paper shows that response variability in primary visual cortex reflects the statistical structure of visual inputs, as required for inferences correctly tuned to the statistics of the natural environment.

    • Dylan Festa
    • , Amir Aschner
    •  & Ruben Coen-Cagli
  • Article
    | Open Access

    Voltage-sensitive dye imaging (VSDI) is a powerful technique for measuring membrane potential dynamics of neurons but the effective resolution is limited. Here, the authors developed an in silico model of VSDI to probe activity in a biologically detailed reconstruction of rodent neocortical microcircuits.

    • Taylor H. Newton
    • , Michael W. Reimann
    •  & Henry Markram
  • Article
    | Open Access

    Whether maximizing rewards and minimizing punishments rely on distinct brain learning systems remains debated. Here, using intracerebral recordings in humans, the authors provide evidence for brain regions differentially engaged in signaling reward and punishment prediction errors that prescribe repetition versus avoidance of past choices.

    • Maëlle C. M. Gueguen
    • , Alizée Lopez-Persem
    •  & Julien Bastin
  • Article
    | Open Access

    A major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.

    • Mohammadali Sharifshazileh
    • , Karla Burelo
    •  & Giacomo Indiveri
  • Article
    | Open Access

    Transcranial alternating current stimulation (tACS) can modulate cortical oscillations and associated long-lasting cognitive and behavioral functions in humans. Here, the authors provide in vivo evidence in ferrets on the mechanism of how weak electric fields in tACS can entrain neuronal activity.

    • Wei A. Huang
    • , Iain M. Stitt
    •  & Flavio Fröhlich
  • Article
    | Open Access

    The basolateral amygdala is implicated in several behavior-related states including anxiety, autism, and addiction. The authors apply circuit-level pathway tracing methods combined with computational techniques to provide a comprehensive connectivity atlas of the mouse basolateral amygdala complex.

    • Houri Hintiryan
    • , Ian Bowman
    •  & Hong-Wei Dong
  • Article
    | Open Access

    Large-scale connectomes from the mammalian brain are becoming available, but it remains unclear how informative these are for the distinction of circuit models. Here, the authors use connectome statistics to test competing models of local cortical circuits with approximate Bayesian computation.

    • Emmanuel Klinger
    • , Alessandro Motta
    •  & Moritz Helmstaedter
  • Article
    | Open Access

    New microgrid recordings on the human hippocampal surface reveal that oscillations travel in reversing directions. The route of travel at a given moment was related to behavior and topographic patterns of activity strength, suggesting directions may be biomarkers of hippocampal cognitive processes.

    • Jonathan K. Kleen
    • , Jason E. Chung
    •  & Edward F. Chang
  • Article
    | Open Access

    Identifying enriched gene sets in transcriptomic data is routine analysis. Here, the authors show that conventional gene category enrichment analysis (GCEA) applied to brain-wide atlas data yields biased results and develop a flexible ensemble-based null model framework to enable appropriate inference in GCEA.

    • Ben D. Fulcher
    • , Aurina Arnatkeviciute
    •  & Alex Fornito
  • Article
    | Open Access

    The differentiation of neural stem cells (NSCs) into neurons is a critical part in devising potential cell-based therapeutic strategies for central nervous system diseases but NSCs fate determination and prediction is problematic. Here, the authors present a deep neural network model for predictable reliable identification of NSCs fate.

    • Yanjing Zhu
    • , Ruiqi Huang
    •  & Rongrong Zhu
  • Article
    | Open Access

    Dopamine neurons in the mushroom body help Drosophila learn to approach rewards and avoid punishments. Here, the authors propose a model in which dopaminergic learning signals encode reinforcement prediction errors by utilising feedback reinforcement predictions from mushroom body output neurons.

    • James E. M. Bennett
    • , Andrew Philippides
    •  & Thomas Nowotny
  • Article
    | Open Access

    Deep neural networks usually rapidly forget the previously learned tasks while training new ones. Laborieux et al. propose a method for training binarized neural networks inspired by neuronal metaplasticity that allows to avoid catastrophic forgetting and is relevant for neuromorphic applications.

    • Axel Laborieux
    • , Maxence Ernoult
    •  & Damien Querlioz
  • Article
    | Open Access

    How thalamic sensory relays participate in plasticity upon associative fear learning and stable long-term sensory coding remains unknown. The authors show that auditory thalamus neurons exhibit heterogeneous plasticity patterns after learning while population level encoding of auditory stimuli remains stable across days.

    • James Alexander Taylor
    • , Masashi Hasegawa
    •  & Jan Gründemann
  • Article
    | Open Access

    Neuromorphic devices take inspiration from spiking dynamics of neurons in the brain. Here, the authors demonstrate synchronized spiking dynamics in 240 photonic artificial neurons, each of which is implemented with a pair of antisymmetrically coupled degenerate optical parametric oscillators.

    • Takahiro Inagaki
    • , Kensuke Inaba
    •  & Hiroki Takesue
  • Article
    | Open Access

    Higher-order sequence learning using a structured graph representation - clone-structured cognitive graphs (CSCG) – can explain how the hippocampus learns cognitive maps. CSCG provides novel explanations for transferable schemas and transitive inference in the hippocampus, and for how place cells, splitter cells, lap-cells and a variety of phenomena emerge from the same set of fundamental principles.

    • Dileep George
    • , Rajeev V. Rikhye
    •  & Miguel Lázaro-Gredilla
  • Article
    | Open Access

    A defining human characteristic is the ability to perform diverse cognitively challenging tasks. The authors show that this adaptability relates to a network sampling mechanism, where brain-wide network states transiently blend the unique combinations of neural resources required by different tasks.

    • Eyal Soreq
    • , Ines R. Violante
    •  & Adam Hampshire
  • Article
    | Open Access

    Neural networks trained using predictive models generate representations that recover the underlying low-dimensional latent structure in the data. Here, the authors demonstrate that a network trained on a spatial navigation task generates place-related neural activations similar to those observed in the hippocampus and show that these are related to the latent structure.

    • Stefano Recanatesi
    • , Matthew Farrell
    •  & Eric Shea-Brown
  • Article
    | Open Access

    Attractor networks and drift diffusion models are two approaches to model the perceptual decision making process. Here, the authors identify an intermediate regime only for the attractor model that allows flexible categorization of two choice decisions for long duration and noisy stimuli and validate these model predictions with psychophysical experiments.

    • Genís Prat-Ortega
    • , Klaus Wimmer
    •  & Jaime de la Rocha
  • Article
    | Open Access

    Different languages rely on different vocal sounds to convey meaning. Here the authors show that language-general coding of pitch occurs in the non-primary auditory cortex for both tonal (Mandarin Chinese) and non-tonal (English) languages, with some language specificity on the population level.

    • Yuanning Li
    • , Claire Tang
    •  & Edward F. Chang
  • Article
    | Open Access

    Structures of mu-opioid receptor (mOR) in complex with morphine derivatives have been determined; but the structural basis of mOR activation by fentanyl-like synthetic opioids remains unclear. Here, authors use state-of-the-art simulation techniques and discover a secondary binding mode which is only accessible when the conserved His297 adopts a neutral HID tautomer state.

    • Quynh N. Vo
    • , Paween Mahinthichaichan
    •  & Christopher R. Ellis
  • Article
    | Open Access

    Patch clamp recording of neurons is slow and labor-intensive. Here the authors present a method for automated deep learning driven label-free image guided patch clamp physiology to perform measurements on hundreds of human and rodent neurons.

    • Krisztian Koos
    • , Gáspár Oláh
    •  & Peter Horvath
  • Article
    | Open Access

    Information regarding a sensory stimulus is distributed in activity of neuronal populations. Here the authors show stimulus information scales sub-linearly with the number of neurons in mouse visual cortex due to correlated noise and may saturate in far fewer numbers of neurons than the total in V1.

    • MohammadMehdi Kafashan
    • , Anna W. Jaffe
    •  & Jan Drugowitsch
  • Article
    | Open Access

    Recent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) for brain imaging data analysis. Here, the authors show that if trained following prevalent DL practices, DL methods substantially improve compared to SML methods by encoding robust discriminative brain representations.

    • Anees Abrol
    • , Zening Fu
    •  & Vince Calhoun
  • Article
    | Open Access

    Aberrant synchronous oscillations have been associated with numerous brain disorders, including essential tremor. The authors show that synchronous cerebellar activity can casually affect essential tremor and that its underlying mechanism may be related to the temporal coherence of the tremulous movement.

    • Sebastian R. Schreglmann
    • , David Wang
    •  & Nir Grossman
  • Article
    | Open Access

    Surprisingly, motor cortex becomes less involved in performing skilled motor behaviors as they are practiced. This is addressed by a model of two descending pathways featuring different types of learning: fast learning in a cortical pathway to maximize rewards and slow learning in a subcortical pathway to reinforce behaviors through repetition.

    • James M. Murray
    •  & G. Sean Escola
  • Article
    | Open Access

    Two-photon imaging in macaque V1 captured maps of tuning selectivity for four spatial parameters, all of which correlated with peak spatial frequency. These inter-map relationships reveal a common motif—they are described by uniform spatial pooling from a family of scale invariant Gabor receptive fields.

    • Y. Chen
    • , H. Ko
    •  & I. Nauhaus
  • Article
    | Open Access

    A principle of neuroanatomy, namely diffuse connectivity, is modeled using a large-scale network of corticothalamic neural masses. We demonstrate that increases in diffuse coupling transition the system through a quasi-critical regime, which coincides with known signatures of complex adaptive brain dynamics, and model fits to human imaging data orient task states to higher levels of diffusivity, consistent with the influence of arousal systems.

    • Eli J. Müller
    • , Brandon R. Munn
    •  & James M. Shine