International Brain Laboratory

…manifolds and anatomical networks, brain-wide neuronal timescales and collaborative work through the International Brain Laboratory.

Local field potentials (LFPs) of different brain regions are contingent on their individual state and functions. While features of LFPs have been used to distinguish brain regions, no study has attempted to determine the precision with which LFPs can infer the recording positions across the whole brain. To tackle this problem, we hypothesize that tiny differences in LFPs from brain regions and their subregions are separable by using state-of-the-art deep learning methods. We implemented four models to best learn the invariant representations and overcome the predictable noise sources from elec

The goal of behavioral neuroscience is to understand the relationship between neural activity and behavior. One traditional approach for studying this relationship has been to build models that either translate from the neural activity to behavior (decoding) or from behavior to neural activity (encoding). Recent advances in self-supervised learning now allow for modeling both modalities jointly. In this work, we introduce a multimodal masked modeling approach that masks portions of both behavior and neural activity, using the unmasked data to make predictions across both modalities. We evaluat

…In the International Brain Laboratory, over one hundred mice were trained on a visual decision-making task with the explicit goal of establishing a rigorously standardized experimental protocol. This effort led to an automated pipeline that produced trained mice whose behavior was indistinguishable across seven different labs, when considering trial-level descriptors of behavior. Nevertheless, substantial inter-individual

…Neuropixels recordings across the brain from the International Brain Laboratory collaboration. We analyzed 74

…for visual decision-making (The International Brain Laboratory, 2023): mice turned a wheel to indicate whether a visual grating appeared on the left or the right, with prior probabil

Neural decoding is essential for understanding the association between neural activity and behavior. A prerequisite for most decoding methods is spike sorting, the assignment of action potentials (or spikes) to individual neurons. Current spike sorting algorithms, however, can be inaccurate and do not properly model uncertainty of spike assignments, therefore discarding information that could potentially improve decoding performance. Recent advances in high-channel-count probes like Neuropixels (NP) and extracellular analysis pipelines allow for extracting a rich set of spike features to direc

A popular approach to quantifying animal behavior from video data is through behavioral segmentation, wherein video frames are labeled as containing one or more discrete behavior classes, such as grooming or rearing. These behaviors are often manually labeled, which is time consuming and error prone. An alternative approach is to train a sequence model which learns to map behavioral features extracted from video frames to discrete behaviors, although supervised models still require manually labeled examples to learn from. In order to reduce the need for expensive manual labels in this supervis