ArticleFrontiers in human neuroscience2015
How can we study reasoning in the brain?
Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- The time scales of irreversibility in spontaneous brain activity are altered in obsessive compulsive disorder.Frontiers in psychiatry · 2023Article
- Editorial: Advances in brain dynamics in the healthy and psychiatric disorders.Frontiers in psychiatry · 2023Article
- Attaining the recesses of the cognitive space.Cognitive neurodynamics · 2022Article
- Principles and open questions in functional brain network reconstruction.Human brain mapping · 2021Review
- Emotions as Abstract Evaluation Criteria in Biological and Artificial Intelligences.Frontiers in computational neuroscience · 2021Article
- Gauging Functional Brain Activity: From Distinguishability to Accessibility.Frontiers in physiology · 2019Article
- A universal mechanism of extreme events and critical phenomena.Scientific reports · 2016Article
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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. 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.
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