The widespread adoption of deep learning to model neural activity often relies on "black-box" approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for in...
In this NeuroView, we discuss challenges and best practices when dealing with disease-detection AI models that are trained on heterogeneous clinical data, focusing on the interrelated problems of model bias, causality, and rare diseases.
To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these function...
The EU AI Act, the first comprehensive regulation of AI, came into effect in August. Here, we provide an overview of the provisions that apply to the field of neurotechnology with respect to research and development and neuroscience practice and disc...
A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly un...
In a recent issue of Cell, Vargas and colleagues demonstrate that task-driven neural network models are superior at predicting proprioceptive activity in the primate cuneate nucleus and sensorimotor cortex compared with other models. This provides va...
Human brains and bodies are not hardware running software: the hardware is the software. We reason that because the physics of artificial intelligence hardware and of human biological "hardware" is distinct, neuromorphic engineers need to be selectiv...
Human understanding of the world can change rapidly when new information comes to light, such as when a plot twist occurs in a work of fiction. This flexible "knowledge assembly" requires few-shot reorganization of neural codes for relations among ob...
Biological brains possess an unparalleled ability to adapt behavioral responses to changing stimuli and environments. How neural processes enable this capacity is a fundamental open question. Previous works have identified two candidate mechanisms: a...
Neural activity is often described in terms of population-level factors extracted from the responses of many neurons. Factors provide a lower-dimensional description with the aim of shedding light on network computations. Yet, mechanistically, comput...