Regulating the information in spikes: a useful bias

TL;DR

This paper proposes a biologically plausible bias mechanism that promotes cooperative learning, helping the brain handle complex pattern recognition tasks despite the traditional bias-variance tradeoff in machine learning.

Contribution

It introduces a new bias mechanism grounded in biological plausibility that enhances cooperative learning in neural systems.

Findings

The bias mechanism is biologically plausible.

It rigorously justifies the role of this bias in learning.

It supports complex pattern recognition in the brain.

Abstract

The bias/variance tradeoff is fundamental to learning: increasing a model's complexity can improve its fit on training data, but potentially worsens performance on future samples. Remarkably, however, the human brain effortlessly handles a wide-range of complex pattern recognition tasks. On the basis of these conflicting observations, it has been argued that useful biases in the form of "generic mechanisms for representation" must be hardwired into cortex (Geman et al). This note describes a useful bias that encourages cooperative learning which is both biologically plausible and rigorously justified.