We study the synthesis of neural coding, selective attention and perceptual decision making. We build a hierarchical neural architecture that implements Bayesian integration of no...
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer f...
We search for assignments of numbers to the amino acids (property codes) that maximize the autocorrelation function signal in given protein sequence data by an iterative method. Ou...
Recent advances in the technology of multi-unit recordings make it possible to test Hebb's hypothesis that neurons do not function in isolation but are organized in assemblie...
Laura Martignon, Gustavo Deco, Kathryn B. Laskey, ...
We address the problem of distributed source coding, i.e. compression of correlated sources that are not co-located and/or cannot communicatewith each other to minimize their join...