Neural Reshaping: the Plasticity of Human Brain and Artificial Intelligence in the Learning Process

Overview

Journal Am J Neurodegener Dis

Date 2025 Jan 24

PMID 39850545

Authors

Seyed-Ali Sadegh-Zadeh

Mahboobe Bahrami

Ommolbanin Soleimani

Sahar Ahmadi

Affiliations

Soon will be listed here.

Abstract

Objectives: To investigate the parallels and distinctions between human brain plasticity and artificial neural network plasticity, with a focus on their learning processes.

Methods: A comparative analysis was conducted using literature reviews and machine learning experiments, specifically employing a multi-layer perceptron neural network to examine regression and classification problems.

Results: Experimental findings demonstrate that machine learning models, similar to human neuroplasticity, enhance performance through iterative learning and optimization, drawing parallels in strengthening and adjusting connections.

Conclusions: Understanding the shared principles and limitations of neural and artificial plasticity can drive advancements in AI design and cognitive neuroscience, paving the way for future interdisciplinary innovations.

References

Peng S, Wuu J, Mufson E, Fahnestock M . Precursor form of brain-derived neurotrophic factor and mature brain-derived neurotrophic factor are decreased in the pre-clinical stages of Alzheimer's disease. J Neurochem. 2005; 93(6):1412-21. DOI: 10.1111/j.1471-4159.2005.03135.x. View

HUTTENLOCHER P, Dabholkar A . Regional differences in synaptogenesis in human cerebral cortex. J Comp Neurol. 1997; 387(2):167-78. DOI: 10.1002/(sici)1096-9861(19971020)387:2<167::aid-cne1>3.0.co;2-z. View

Gray J, Chabris C, Braver T . Neural mechanisms of general fluid intelligence. Nat Neurosci. 2003; 6(3):316-22. DOI: 10.1038/nn1014. View

Kuperberg G . Neural mechanisms of language comprehension: challenges to syntax. Brain Res. 2007; 1146:23-49. DOI: 10.1016/j.brainres.2006.12.063. View

Pourtois G, de Gelder B, Bol A, Crommelinck M . Perception of facial expressions and voices and of their combination in the human brain. Cortex. 2005; 41(1):49-59. DOI: 10.1016/s0010-9452(08)70177-1. View

Zenke F, Ganguli S . SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks. Neural Comput. 2018; 30(6):1514-1541. PMC: 6118408. DOI: 10.1162/neco_a_01086. View

Rice M, Russo-Menna I . Differential compartmentalization of brain ascorbate and glutathione between neurons and glia. Neuroscience. 1998; 82(4):1213-23. DOI: 10.1016/s0306-4522(97)00347-3. View

Papale A, Hooks B . Circuit changes in motor cortex during motor skill learning. Neuroscience. 2017; 368:283-297. PMC: 5762136. DOI: 10.1016/j.neuroscience.2017.09.010. View

Sadegh-Zadeh S, Fakhri E, Bahrami M, Bagheri E, Khamsehashari R, Noroozian M . An Approach toward Artificial Intelligence Alzheimer's Disease Diagnosis Using Brain Signals. Diagnostics (Basel). 2023; 13(3). PMC: 9913919. DOI: 10.3390/diagnostics13030477. View

10.

Yoo Y, Tang L, Brosch T, Li D, Kolind S, Vavasour I . Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls. Neuroimage Clin. 2017; 17:169-178. PMC: 5651626. DOI: 10.1016/j.nicl.2017.10.015. View

11.

Kaiser J, Mostafa H, Neftci E . Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE). Front Neurosci. 2020; 14:424. PMC: 7235446. DOI: 10.3389/fnins.2020.00424. View

12.

Johansson B . Brain plasticity in health and disease. Keio J Med. 2005; 53(4):231-46. DOI: 10.2302/kjm.53.231. View

13.

Caroni P, Donato F, Muller D . Structural plasticity upon learning: regulation and functions. Nat Rev Neurosci. 2012; 13(7):478-90. DOI: 10.1038/nrn3258. View

14.

Fields R . White matter in learning, cognition and psychiatric disorders. Trends Neurosci. 2008; 31(7):361-70. PMC: 2486416. DOI: 10.1016/j.tins.2008.04.001. View

15.

Moreno S, Bidelman G . Examining neural plasticity and cognitive benefit through the unique lens of musical training. Hear Res. 2013; 308:84-97. DOI: 10.1016/j.heares.2013.09.012. View

16.

Sohrabi M, Zare-Mirakabad F, Ghidary S, Saadat M, Sadegh-Zadeh S . A novel data augmentation approach for influenza A subtype prediction based on HA proteins. Comput Biol Med. 2024; 172:108316. DOI: 10.1016/j.compbiomed.2024.108316. View

17.

Muller F, ORAHILLY R . The development of the human brain, including the longitudinal zoning in the diencephalon at stage 15. Anat Embryol (Berl). 1988; 179(1):55-71. DOI: 10.1007/BF00305100. View

18.

Nazari M, Shalbafan M, Eissazade N, Khalilian E, Vahabi Z, Masjedi N . A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities. PLoS One. 2024; 19(6):e0303699. PMC: 11192371. DOI: 10.1371/journal.pone.0303699. View

19.

Lenroot R, Giedd J . Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev. 2006; 30(6):718-29. DOI: 10.1016/j.neubiorev.2006.06.001. View

20.

Fletcher P, Zafiris O, Frith C, Honey R, Corlett P, Zilles K . On the benefits of not trying: brain activity and connectivity reflecting the interactions of explicit and implicit sequence learning. Cereb Cortex. 2004; 15(7):1002-15. PMC: 3838938. DOI: 10.1093/cercor/bhh201. View