Title: Challenges for neuroscience-based computational intelligence

Authors: Jose A. Fernandez-Leon; Gerardo G. Acosta

Addresses: Department of Neuroscience, Baylor College of Medicine, Houston TX77030, USA; CIFICEN (UNCPBA, CICPBA, CONICET), Tandil 7000, Argentina; INTIA Institute, Exact Sciences Faculty-UNCPBA, Tandil 7000, Argentina ' INTELYMEC-CIFICEN (UNCPBA, CICPBA, CONICET), Engineering Faculty-UNCPBA, Olavarría 7400, Argentina

Abstract: We describe some of the major issues concerning the interdisciplinary community that looks for understanding intelligence from the neuroscience and computational perspectives. The challenges outlined focus on the diverse range of theoretical and practical questions that may stimulate not only the study of intelligence in the biological realm but also the practice of research on the theoretical aspects to guide research in neuroscience. Setting the study of computational intelligence from the neuroscience field in a holistic and integrative way is a step toward fostering impactful interactions between distinct perspectives and viewpoints. These ideas might be useful for brain understanding and for constructing new paradigms of machine learning. Rather than proposing a shift on the approach taken in computational intelligence research, discussions in this work suggest approaching the described grand challenges in an integrative manner but guided by theoretical aspects, rather than based mostly on technological developments to study the brain.

Keywords: computational intelligence; cognitive maps; place cells; grid cells; cognition; neuro-inspiration; deep learning.

DOI: 10.1504/IJCISTUDIES.2021.120507

International Journal of Computational Intelligence Studies, 2021 Vol.10 No.4, pp.232 - 238

Received: 04 Jan 2021
Accepted: 18 Jan 2021
Published online: 24 Jan 2022 *

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