Topic: vision transformer

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