Publication

Artificial intelligence is reshaping neuroscience across scales

2026

Abstract

Across every scale at which we study the brain, from folded proteins and single neurons to cortical populations and the moving body, artificial intelligence (AI) has shifted from a bespoke tool into a driver of measurement and, increasingly, a generative engine for hypotheses. Here, I review recent progress (and open challenges) in applying AI for neuroscience along this scale axis: structure prediction for proteins, simulation-based inference for biophysical neurons, latent and dynamical models for neural populations, task-trained networks as minimal models of circuit computation, computer vision for animal behavior, neuromusculoskeletal modeling for biomechanics, and the multimodal, agentic systems now promising to automate discovery itself.

Official source

https://infoscience.epfl.ch/entities/publication/d501930f-65a9-4fc4-a570-618497a33b90

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2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d501930f-65a9-4fc4-a570-618497a33b90

About this result

Related concepts (32)

Computational neuroscience

Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.

Neuroscience

Neuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions and disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, psychology, physics, computer science, chemistry, medicine, statistics, and mathematical modeling to understand the fundamental and emergent properties of neurons, glia and neural circuits.

Biological neuron model

Biological neuron models, also known as a spiking neuron models, are mathematical descriptions of the properties of certain cells in the nervous system that generate sharp electrical potentials across their cell membrane, roughly one millisecond in duration, called action potentials or spikes (Fig. 2). Since spikes are transmitted along the axon and synapses from the sending neuron to many other neurons, spiking neurons are considered to be a major information processing unit of the nervous system.

Related publications (32)

Artificial intelligence is reshaping neuroscience across scales

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