Characterizing the neural correlates of reasoning

TL;DR

This paper explores how the complex properties of spontaneous brain activity underpin reasoning processes, emphasizing the need for new analytical tools and experimental approaches in cognitive neuroscience.

Contribution

It proposes that neural correlates of reasoning are rooted in spontaneous activity properties, challenging traditional event-related analysis methods.

Findings

Spontaneous brain activity exhibits complex properties relevant to reasoning.

Reasoning involves long time-scale neural dynamics driven by internal processes.

Standard methods may overlook the neural correlates of reasoning.

Abstract

The brain did not develop a dedicated device for reasoning. This fact bears dramatic consequences. While for perceptuo-motor functions neural activity is shaped by the input's statistical properties, and processing is carried out at high speed in hardwired spatially segregated modules, in reasoning, neural activity is driven by internal dynamics, and processing times, stages, and functional brain geometry are largely unconstrained a priori. Here, it is shown that the complex properties of spontaneous activity, which can be ignored in a short-lived event-related world, become prominent at the long time scales of certain forms of reasoning which stretch over sufficiently long periods of time. It is argued that the neural correlates of reasoning should in fact be defined in terms of non-trivial generic properties of spontaneous brain activity, and that this implies resorting to concepts, analytical tools, and ways of designing experiments that are as yet non-standard in cognitive neuroscience. The implications in terms of models of brain activity, shape of the neural correlates, methods of data analysis, observability of the phenomenon and experimental designs are discussed.