Topic: linear decoders

Learning general principles from single examples is a hallmark of high cognitive functions. This type of learning is computationally challenging for artificial agents, yet many animals such as primates can perform it with ease. To study one-exemplar generalization in the lab, it would be ideal to develop appropriate behavioral tasks in more tractable model organisms, such as rodents. Here we report that mice can perform one-exemplar generalization with difficult texture-based visual stimuli such as “leaves” and “rocks”. We trained mice to discriminate between single images from two texture cat

Intracortical brain-machine interfaces (iBMIs) aim to provide naturalistic communication and movement for those with paralysis by decoding neural spikes into actions 1–10. iBMIs traditionally require closed-loop in vivo experiments to develop, design, optimize, and benchmark decoder algorithms. Although offline evaluation provides insight into what algorithms are promising, the discrepancy between offline and online performance may lead to incorrect conclusions that mislead algorithm design 11–15. We therefore aim to build an emulator that accurately characterizes online decoder performance wi

Real-world decisions often require combining different cognitive computations. Recent findings suggest that, on the one hand, these computations are distributed across the cortex. On the other hand, cortical microcircuits seem to implement them via (near) orthogonal population-activity patterns. But how are these local geometries combined at the level of cortex-wide dynamics? To answer this, we developed a new task for mice navigating in virtual reality (VR) to temporally disentangle different cognitive computations. Mice first accumulate evidence to determine the predominant color of a random

The hippocampal representation of space can change on a time scale of minutes as a result of goal learning. However, the link between behaviour performance and the representation of other variables in the hippocampus is less clear, especially at longer time scales. To investigate this, we recorded the activity of hippocampal CA1 neurons of rats using in vivo electrophysiology, as they learned a space-context association task over the course of 5 days. To assess the representation of different task-related variables such as position, reward, movement direction or context in the population activ