Do Neurochemicals Reflect Psychophysiological Dimensions in Behaviors? A Transdisciplinary Perspective Based on Analogy with Maslow’s Needs Pyramid

• Published in: ACS chemical neuroscience Vol. 16; no. 5; pp. 753 - 760
• Main Author: Parrot, Sandrine
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 05.03.2025; American Chemical Society (ACS)
• Series: ACS Chemical Neuroscience special issue “Monitoring Molecules in Neuroscience 2024”
• Subjects: Animals; Behavior - physiology; Brain - metabolism; Brain - physiology; Humans; Life Sciences; Motivation - physiology; Neurobiology; Neurochemistry; Neurons and Cognition; Neurotransmitter Agents - metabolism; Psychology and behavior; Psychophysiology; psychometry; amino acids; Maslow’s pyramid model; neurochemistry; big data; behavior; multivariate analysis; latent dimensions; monoamines; Neurochemistry; Neurochemistry amino acids monoamines big data multivariate analysis behavior psychometry latent dimensions Maslow's pyramid model; Maslow's pyramid model
• ISSN: 1948-7193; 1948-7193
• DOI: 10.1021/acschemneuro.4c00566

All behaviors, including motivated behaviors, result from integration of information in the brain via nerve impulses, with two main means of communication: electrical gap-junctions and chemical signaling. The latter enables information transfer between brain cells through release of biochemical messengers, such as neurotransmitters. Neurochemical studies generate plentiful biochemical data, with many variables per individual, since there are many methods to quantify neurotransmitters, precursors and metabolites. The number of variables can be far higher using other concomitant techniques to monitor behavioral parameters on the same subject of study. Surprisingly, while many quantitative variables are obtained, data analysis and discussion focus on just a few or only on the neurotransmitter known to be involved in the behavior, and the other biochemical data are, at best, regarded as less important for scientific interpretation. The present article aims to provide novel transdisciplinary arguments that all neurochemical data can be regarded as items of psychophysiological dimensions, just as questionnaire items identify modified behaviors or disorders using latent classes. A first proof of concept on nonmotivated and motivated behaviors using a multivariate data-mining approach is presented.