Journal of Robotics Spectrum


Theoretical Analysis of the Brain and Artificial Intelligence



Journal of Robotics Spectrum

Received On : 23 December 2022

Revised On : 30 January 2023

Accepted On : 02 February 2023

Published On : 18 February 2023

Volume 01, 2023

Pages : 024-035


Abstract


Many articles have expounded on and defended the potential advantages of co-robotics (cobots), robotics, AI, and quantum computers in the domains of research and development, clinics, community health and virology. Numerous trailblazers in the domains of artificial intelligence, robotics, and quantum computing have been recognised for their groundbreaking concepts and principles. Among these luminaries are Richard Feynman, Kurt Godel, John Nash, Norbert Wiener, Alan Turing, John von Neumann, Vannevar Bush, and John McCarthy. Theorems formulated by Kurt Godel were misinterpreted by researchers who erroneously equated computer and brain paradigms. Godel himself had recognised this misinterpretation. The individual's commendation of the brain's supremacy over computational systems was met with disapprobation. This article delineates the diverse array of artificial intelligence techniques, frameworks, and programming languages that are developed by humans and can be employed in tandem with contemporary computational systems. These advancements facilitate advancements in the realm of electrons and quantum mechanics. The process of evolution has resulted in the development of neurons in various animal species, which rely on the flow of electrons to carry out their biological functions. The identification of mirror neurons represented a significant shift in the paradigm of neuroscience. The proposed paradigm shift towards the 'hall of mirror neurons' represents a potentially effective approach to studying, warranting further investigation. The aforementioned concepts are instrumental in advancing the field of artificial intelligence and in furthering research on the intricacies of the human brain.


Keywords


Mirror Neuron System, Mild Cognitive Impairment, Inferior Parietal Lobule, Hall of Mirror Neurons.


  1. H. Li et al., “Primal-dual fixed point algorithms based on adapted metric for distributed optimization,” IEEE Trans. Neural Netw. Learn. Syst., vol. 34, no. 6, pp. 2923–2937, 2023.
  2. F. Schrodt, J. Kneissler, S. Ehrenfeld, and M. V. Butz, “Mario becomes cognitive,” Top. Cogn. Sci., vol. 9, no. 2, pp. 343–373, 2017.
  3. A. Haider, “Super Mario Bros: The ultimate video game icon,” BBC, BBC, 24-Mar-2023.
  4. S. N. L. Schmidt, C. A. Sojer, J. Hass, P. Kirsch, and D. Mier, “fMRI adaptation reveals: The human mirror neuron system discriminates emotional valence,” Cortex, vol. 128, pp. 270–280, 2020.
  5. L. Fogassi and P. F. Ferrari, “Cortical motor organization, mirror neurons, and embodied language: An evolutionary perspective,” Biolinguistics, vol. 6, no. 3–4, pp. 308–337, 2012.
  6. L. Svard, “Seeing sound, hearing movement— music and mirror neurons,” in The Musical Brain, Oxford University PressNew York, 2023, pp. 169-C9P71.
  7. K. S. Wiley et al., “Maternal distress, DNA methylation, and fetal programing of stress physiology in Brazilian mother-infant pairs,” Dev. Psychobiol., vol. 65, no. 1, p. e22352, 2023.
  8. E.-S. H. Ibrahim et al., “Optimized cardiac functional MRI of small-animal models of cancer radiation therapy,” Magn. Reson. Imaging, vol. 73, pp. 130–137, 2020.
  9. J. Costa Pereira et al., “On the role of correlation and abstraction in cross-modal multimedia retrieval,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 3, pp. 521–535, 2014.
  10. M. C. Corballis, The recursive mind: The origins of human language, thought, and civilization. Princeton, NJ: Princeton University Press, 2014.
  11. H. Tomiyama et al., “Functional connectivity between pre-supplementary motor area and inferior parietal lobule associated with impaired motor response inhibition in first-degree relatives of patients with obsessive-compulsive disorder,” Cereb. Cortex, vol. 33, no. 12, pp. 7531–7539, 2023.
  12. O. Karadas et al., “EEG changes in intensive care patients diagnosed with COVID-19: a prospective clinical study,” Neurol. Sci., vol. 43, no. 4, pp. 2277–2283, 2022.
  13. S. de Vidania et al., “Prodromal Alzheimer’s disease: Constitutive upregulation of Neuroglobin prevents the initiation of Alzheimer’s pathology,” Front. Neurosci., vol. 14, p. 562581, 2020.
  14. C. Morrison, M. Dadar, N. Shafiee, D. L. Collins, and For Alzheimer’s Disease Neuroimaging Initiative, “The use of hippocampal grading as a biomarker for preclinical and prodromal Alzheimer’s disease,” Hum. Brain Mapp., vol. 44, no. 8, pp. 3147–3157, 2023.
  15. C. A. Marsden et al., “S3 THE APPLICATION OF fMRI IN RODENTS TO THE STUDY OF PSYCHOACTIVE DRUGS,” Behav. Pharmacol., vol. 16, no. Supplement 1, p. S1, 2005.
  16. G. Antunes, S. F. F. da Silva, and F. M. S. de Souza, “Mirror neurons modeled through spike-timing-dependent plasticity are affected by channelopathies associated with autism spectrum disorder,” Int. J. Neural Syst., vol. 28, no. 5, p. 1750058, 2017.
  17. D. K. Porada, C. Regenbogen, J. Freiherr, J. Seubert, and J. N. Lundström, “Trimodal processing of complex stimuli in inferior parietal cortex is modality-independent,” Cortex, vol. 139, pp. 198–210, 2021.
  18. Z. Zhou et al., “Gene transcriptional expression of cortical thinning during childhood and adolescence,” Hum. Brain Mapp., vol. 44, no. 10, pp. 4040–4051, 2023.
  19. G. Gavazzi et al., “The fMRI correlates of visuo-spatial abilities: sex differences and gender dysphoria,” Brain Imaging Behav., vol. 16, no. 2, pp. 955–964, 2022.
  20. F. A. Raposo, D. Martins de Matos, and R. Ribeiro, “Learning low-dimensional semantics for music and language via multi-subject fMRI,” Neuroinformatics, vol. 20, no. 2, pp. 451–461, 2022.
  21. R. A. Ferreira, S. M. Göbel, M. Hymers, and A. W. Ellis, “The neural correlates of semantic richness: evidence from an fMRI study of word learning,” Brain Lang., vol. 143, pp. 69–80, 2015.
  22. M. Mehrabbeik, A. Ahmadi, F. Bakouie, A. H. Jafari, S. Jafari, and D. Ghosh, “The impact of higher-order interactions on the synchronization of Hindmarsh-Rose neuron maps under different coupling functions,” Preprints, 2023.
  23. S. I. Deutsch, R. B. Rosse, B. L. Schwartz, J. Mastropaolo, J. A. Burket, and A. Weizman, “Regulation of intermittent oscillatory activity of pyramidal cell neurons by GABA inhibitory interneurons is impaired in schizophrenia: rationale for pharmacotherapeutic GABAergic interventions,” Isr. J. Psychiatry Relat. Sci., vol. 47, no. 1, pp. 17–26, 2010.
  24. P. F. Ferrari, C. A. Méndez, and G. Coudé, “Aggression: The dark side of mirror neurons sheds light on their functions,” Curr. Biol., vol. 33, no. 8, pp. R313–R316, 2023.
  25. C. L. Rush et al., “Resilient together-ALS: leveraging the NDD transdiagnostic framework to develop an early dyadic intervention for people with amyotrophic lateral sclerosis and their informal care-partners,” Amyotroph. Lateral Scler. Frontotemporal Degener., pp. 1–8, 2023.
  26. C. A. Findley et al., “Prodromal glutamatergic modulation with riluzole impacts glucose homeostasis and spatial cognition in Alzheimer’s disease mice,” J. Alzheimers. Dis., 2023.
  27. R. D. Lindeman, C. L. Yau, R. N. Baumgartner, J. E. Morley, P. J. Garry, and New Mexico Aging Process Study, “Longitudinal study of fasting serum glucose concentrations in healthy elderly. The New Mexico Aging Process Study,” J. Nutr. Health Aging, vol. 7, no. 3, pp. 172–177, 2003.
  28. J. Kim and J.-H. Lee, “Integration of structural and functional magnetic resonance imaging improves mild cognitive impairment detection,” Magn. Reson. Imaging, vol. 31, no. 5, pp. 718–732, 2013.
  29. B. de Gelder, “Social affordances, mirror neurons, and how to understand the social brain,” Trends Cogn. Sci., vol. 27, no. 3, pp. 218–219, 2023.
  30. J. Ferreira, “Watch and learn: role of hypothalamic neurons in mirroring aggression,” Lab Anim. (NY), vol. 52, no. 4, p. 83, 2023.
  31. A. Abouhussein and Y. T. Peet, “Computational framework for efficient high-fidelity optimization of bio-inspired propulsion and its application to accelerating swimmers,” J. Comput. Phys., vol. 482, no. 112038, p. 112038, 2023.
  32. M. L. Sutter et al., “Corrigendum to ‘The role of cholesterol recognition (CARC/CRAC) mirror codes in the allosterism of the human organic cation transporter 2 (OCT2, SLC22A2)’ [Biochem. Pharmacol. 194 (2021) 114840],” Biochem. Pharmacol., vol. 201, no. 115100, p. 115100, 2022.
  33. P. S. S. Lopes, A. C. P. Campos, E. T. Fonoff, L. R. G. Britto, and R. L. Pagano, “Motor cortex and pain control: exploring the descending relay analgesic pathways and spinal nociceptive neurons in healthy conscious rats,” Behav. Brain Funct., vol. 15, no. 1, p. 5, 2019.
  34. C. Onigata and Y. Bunno, “Unpleasant visual stimuli increase the excitability of spinal motor neurons,” Somatosens. Mot. Res., vol. 37, no. 2, pp. 59–62, 2020.
  35. O. P. O’Sullivan et al., “Facilitator reflections on online delivery of simulation-based mental health education during COVID-19,” J. Ment. Health Train. Educ. Pract., vol. 18, no. 1, pp. 53–59, 2023.
  36. T. P. Bonfiglio, “Language and mirror neurons,” in Linguistics and Psychoanalysis, New York: Routledge, 2023, pp. 136–146.
  37. E. Binder et al., “Lesion evidence for a human mirror neuron system,” Cortex, vol. 90, pp. 125–137, 2017.
  38. J. Chen, J. Gao, Y. Chen, B. M. Oloulade, T. Lyu, and Z. Li, “Auto-GNAS: A parallel graph neural architecture search framework,” IEEE Trans. Parallel Distrib. Syst., vol. 33, no. 11, pp. 3117–3128, 2022.
  39. X. Zhang and B. Hedwig, “Response properties of spiking and non-spiking brain neurons mirror pulse interval selectivity,” Front. Cell. Neurosci., vol. 16, p. 1010740, 2022.
  40. D. K. Mishra, A. Thomas, J. Kuruvilla, P. Kalyanasundaram, K. R. Prasad, and A. Haldorai, “Design of mobile robot navigation controller using neuro-fuzzy logic system,” Computers and Electrical Engineering, vol. 101, p. 108044, Jul. 2022, doi: 10.1016/j.compeleceng.2022.108044.
  41. R. Sankaranarayanan, K. S. Umadevi, N. Bhavani, B. M. Jos, A. Haldorai, and D. V. Babu, “Cluster-based attacks prevention algorithm for autonomous vehicles using machine learning algorithms,” Computers and Electrical Engineering, vol. 101, p. 108088, Jul. 2022, doi: 10.1016/j.compeleceng.2022.108088.
  42. G. S, D. T, and A. Haldorai, “A Supervised Machine Learning Model for Tool Condition Monitoring in Smart Manufacturing,” Defence Science Journal, vol. 72, no. 5, pp. 712–720, Nov. 2022, doi: 10.14429/dsj.72.17533.
  43. R. M. P, S. Ponnan, S. Shelly, Md. Z. Hussain, M. Ashraf, and A. Haldorai, “Autonomous navigation system based on a dynamic access control architecture for the internet of vehicles,” Computers and Electrical Engineering, vol. 101, p. 108037, Jul. 2022, doi: 10.1016/j.compeleceng.2022.108037.

Acknowledgements


Authors thank Reviewers for taking the time and effort necessary to review the manuscript.


Funding


No funding was received to assist with the preparation of this manuscript.


Ethics declarations


Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.


Availability of data and materials


No data available for above study.


Author information


Contributions

All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.


Corresponding author


Rights and permissions


Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/


Cite this article


Francisco Pedro, “Theoretical Analysis of the Brain and Artificial Intelligence”, Journal of Robotics Spectrum, vol.1, pp. 024-035, 2023. doi: 10.53759/9852/JRS202301003.


Copyright


© 2023 Francisco Pedro. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.