ePoster · Neuroscience
A new approach to inferring the eigenspectra of high-dimensional neural representations
Dean Pospisil,Jonathan Pillow · COSYNE 2022
Thu, Mar 17, 2022
The statistical structure of neural population responses is a topic of intense interest in systems neuroscience. The signal eigenspectrum (eigenvalues ordered from high to low) is a fundamental summary statistic that characterizes the dimensionality and efficiency or redundancy of population tuning curves. However, the problem of characterizing signal eigenvalue spectra from limited, noisy neural response data is complicated by two factors. First, noise in the neural responses (aka ``noise correlations'') can interfere with the estimation of the eigenvalues of the signal distribution. Second,