Unbiased Competition

Unlike Biased Competition, Unbiased Competition is resolved internally, i.e., in the absence of external biases. In Ardid et al. PNAS (2019), I identified how dissimilarities in the physiology of competing neural populations determine the direction of the resulting bias according to the characteristics of unbiased external inputs.

There are three general ways in which Unbiased Competition may occur:

  1. When one competing neural population shows higher excitability for a given unbalanced input strength → higher mean firing rate.
  2. When one competing neural population shows a stronger synchronization with the unbalanced external input → higher instantaneous firing rate.
  3. The third possibility is a combination of the previous two. In this case the two competing neural populations can simultaneously show biases at different timescale → one population shows higher mean firing rate, whereas the other population shows higher instantaneous firing rate.

In Ardid et al. PNAS (2019) I realized a model of corticostriatal processing where these three alternatives naturally emerge out of the physiology of D1 and D2 spiny projection neurons (SPNs). However, according to experimental evidence in prefrontal cortex, only the option 2 above is consistent in biasing action selection (D1 SPNs) vs. inhibitory control (D2 SPNs) in the context of rule-based decisions.

Salva Ardid, PhD
Salva Ardid, PhD
GenT Distinguished Research Group Leader

Research at the Interphase of Computational Neuroscience and AI.