Computational neuroscience articles from across Nature Portfolio

Computational neuroscience is the field of study in which mathematical tools and theories are used to investigate brain function. It can also incorporate diverse approaches from electrical engineering, computer science and physics in order to understand how the nervous system processes information.

Featured

News & Views | 22 May 2023

Chronic brain recordings reveal objective biomarkers of chronic pain

Nature Neuroscience 26, 928-929
News & Views | 15 May 2023

A machine learning-based model for the quantification of mental conflict

Nature Computational Science 3, 370-371

Latest Research and Reviews

Research
07 June 2023 | Open Access

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations

Whether or not deep neural networks require hierarchical representations to predict brain activity is not known. Here, the authors show that a multi-branch deep neural network can predict neural activity independently in visual areas in the absence of hierarchical representations.
- Ghislain St-Yves
- , Emily J. Allen
- & Thomas Naselaris
Nature Communications 14, 3329
Research
06 June 2023 | Open Access

Perivascular network segmentations derived from high-field MRI and their implications for perivascular and parenchymal mass transport in the rat brain
- Julian A. Rey
- , Uzair M. Farid
- & Malisa Sarntinoranont
Scientific Reports 13, 9205
Research
05 June 2023 | Open Access

Multiple visual objects are represented differently in the human brain and convolutional neural networks
- Viola Mocz
- , Su Keun Jeong
- & Yaoda Xu
Scientific Reports 13, 9088
Research
31 May 2023 | Open Access

Geometric constraints on human brain function

Cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain’s geometry rather than from modes of complex interregional connectivity.
- James C. Pang
- , Kevin M. Aquino
- & Alex Fornito
Nature, 1-9
Reviews | 30 May 2023

The neuroconnectionist research programme

Artificial neural networks are being widely used to model behavioural and neural data. In this Perspective article, Doerig et al. present neuroconnectionism as a Lakatosian research programme using artificial neural networks as a computational language for expressing falsifiable theories and hypotheses about the brain computations underlying cognition.
- Adrien Doerig
- , Rowan P. Sommers
- & Tim C. Kietzmann
Nature Reviews Neuroscience, 1-20
Research
29 May 2023 | Open Access

The effect of prediction error on episodic memory encoding is modulated by the outcome of the predictions
- Francesco Pupillo
- , Javier Ortiz-Tudela
- & Yee Lee Shing
npj Science of Learning 8, 18

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News and Comment

Research Highlights | 30 May 2023

Non-invasive continuous language decoding

A brain–computer interface can decode semantic representations of perceived and imagined stimuli at the level of words and phrases from functional MRI recordings of brain activity.
- Jake Rogers
Nature Reviews Neuroscience, 1
News & Views | 22 May 2023

Chronic brain recordings reveal objective biomarkers of chronic pain

Using long-term brain recordings in patients with chronic pain, we identified objective biomarkers of real-world subjective pain intensity over many months. Spontaneous chronic pain states were predicted most reliably by sustained changes in the activity of the orbitofrontal cortex, whereas acute pain was most associated with signals from the anterior cingulate cortex.

Nature Neuroscience 26, 928-929
News & Views | 15 May 2023

A machine learning-based model for the quantification of mental conflict

We often encounter mental conflict in our lives. Such mental conflict has long been regarded as subjective. However, a machine learning method can be used to quantify the temporal dynamics of conflict between reward and curiosity from behavioral time-series.

Nature Computational Science 3, 370-371
Research Highlights | 02 May 2023

Parallel processing of alternative approaches

Neuronal activity in the secondary motor cortex of mice engaged in a foraging task simultaneously represents multiple alternative decision-making strategies.
- Katherine Whalley
Nature Reviews Neuroscience 24, 331
News & Views | 24 April 2023

Complex topology meets simple statistics

In this issue, Shinn et al. demonstrate a close relationship between complex brain network topology and lower-level statistical properties of neuroimaging data. They also highlight the potential of these statistical measures, which capture similarity in space and time, to provide imaging-based markers of aging and pharmacological states.
- Shiyu Wang
- & Catie Chang
Nature Neuroscience 26, 732-734
News & Views | 27 March 2023

Revealing trajectories of the mind via non-linear manifolds of brain activity

This work involved the design of a multi-view manifold learning algorithm that capitalizes on various types of structure in high-dimensional time-series data to model dynamic signals in low dimensions. The resulting embeddings of human functional brain imaging data unveil trajectories through brain states that predict cognitive processing during diverse experimental tasks.

Nature Computational Science 3, 192-193

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Computational neuroscience articles from across Nature Portfolio

Featured

Chronic brain recordings reveal objective biomarkers of chronic pain

A machine learning-based model for the quantification of mental conflict

Latest Research and Reviews

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations

Perivascular network segmentations derived from high-field MRI and their implications for perivascular and parenchymal mass transport in the rat brain

Multiple visual objects are represented differently in the human brain and convolutional neural networks

Geometric constraints on human brain function

The neuroconnectionist research programme

The effect of prediction error on episodic memory encoding is modulated by the outcome of the predictions

News and Comment

Non-invasive continuous language decoding

Chronic brain recordings reveal objective biomarkers of chronic pain

A machine learning-based model for the quantification of mental conflict

Parallel processing of alternative approaches

Complex topology meets simple statistics

Revealing trajectories of the mind via non-linear manifolds of brain activity

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Computational neuroscience articles from across Nature Portfolio

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