Theoretical neuroscience
Recent articles
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.
How energy determines where proteins are produced in neurons
Tatjana Tchumatchenko explains how mathematical modeling elucidates whether ion-channel proteins are produced locally in the soma or in the dendrites.
How energy determines where proteins are produced in neurons
Tatjana Tchumatchenko explains how mathematical modeling elucidates whether ion-channel proteins are produced locally in the soma or in the dendrites.
Five new neuroscience books, and other notable titles from 2026
The Transmitter’s summer reading list includes an autopsy of the Human Brain Project, an overview of the neuroscience of motherhood and a memoir from a pioneer in Huntington’s disease research.
Five new neuroscience books, and other notable titles from 2026
The Transmitter’s summer reading list includes an autopsy of the Human Brain Project, an overview of the neuroscience of motherhood and a memoir from a pioneer in Huntington’s disease research.
Marco Facchin explores the ever-shifting landscape of neuroscience theory and philosophy
Computational explanations of cognition, though powerful, aren't the only game in town.
Marco Facchin explores the ever-shifting landscape of neuroscience theory and philosophy
Computational explanations of cognition, though powerful, aren't the only game in town.
Reverse engineering neural circuits; success stories from computational neuroscience
Kevin Mitchell talks with Timothy Behrens about ring attractors, the role of innate structure, and an expanded view of cognitive maps.
Reverse engineering neural circuits; success stories from computational neuroscience
Kevin Mitchell talks with Timothy Behrens about ring attractors, the role of innate structure, and an expanded view of cognitive maps.
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
What a bird’s-eye view of half a million papers reveals about neuroscience
New research uses artificial-intellligence-driven bibliometrics to map the structural organization of neuroscience across 25 years. The field it reveals is at once thriving and theoretically adrift.
What a bird’s-eye view of half a million papers reveals about neuroscience
New research uses artificial-intellligence-driven bibliometrics to map the structural organization of neuroscience across 25 years. The field it reveals is at once thriving and theoretically adrift.
Explore more from The Transmitter
Highly cited autism paper earns expression of concern over data duplications
The notice, published in Nature last week, also addressed an image duplication identified by a prominent research-integrity sleuth.
Highly cited autism paper earns expression of concern over data duplications
The notice, published in Nature last week, also addressed an image duplication identified by a prominent research-integrity sleuth.
Govern neurodata by how it’s used, not where it’s from
New neurodata laws will shape how researchers gather, share and reuse brain data. A use-based governance protects basic researchers and those whose data are being used, without freezing science.
Govern neurodata by how it’s used, not where it’s from
New neurodata laws will shape how researchers gather, share and reuse brain data. A use-based governance protects basic researchers and those whose data are being used, without freezing science.
How new technologies can bring primatologists and systems neuroscientists together
The two groups study the same behavioral phenomena yet rarely interact or read each other's work—a mutual blind spot that weakens both fields. New technologies offer a chance to bring them together.
How new technologies can bring primatologists and systems neuroscientists together
The two groups study the same behavioral phenomena yet rarely interact or read each other's work—a mutual blind spot that weakens both fields. New technologies offer a chance to bring them together.