There is a newer version of the record available.

Published March 23, 2025 | Version 1.0
Publication Restricted

Neurodynamic Cognitive Systems Model: A Mesoscopic Architecture for Real-Time Cognitive Transitions and Regulation

Description

This research introduces the Neurodynamic Cognitive Systems Model (NCSM) — a mesoscopic, biologically grounded architecture for modeling real-time cognitive state transitions. NCSM integrates predictive processing, oscillatory control, and cognitive mode arbitration into a recursive control framework, explaining how the brain preserves coherence under uncertainty.

 

The model formalizes a three-layer system:

  • NPPE (Neurocognitive Predictive Processing Engine) handles generative modeling and error detection
  • DCSM (Dynamic Cognitive Systems Model) organizes cognition into five quasi-stable modes
  • CSTP (Cognitive Synchronization and Transition Protocol) regulates transitions via oscillatory gating and precision-weighted arbitration

NCSM produces testable predictions involving theta–gamma coupling, mode transition dynamics, and system breakdown under overload. This architecture serves as a bridge between cognitive neuroscience, clinical modeling (e.g., ADHD, PTSD), and next-generation AI systems, offering both falsifiability and simulation scaffolding.

 

This upload includes the full manuscript, validation logic, simulation pseudocode, and empirical protocols. It is intended as the foundation for an open, collaborative, and self-funded PhD research initiative.

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Additional details

References

  • 1. Ashby, W. R. (1956). An Introduction to Cybernetics. London: Chapman & Hall.
  • 2. Baars, B. J. (1988). A Cognitive Theory of Consciousness. Cambridge University Press.
  • 3. Badre, D., & Nee, D. E. (2018). Frontal cortex and the hierarchical control of behavior. Trends in Cognitive Sciences, 22(2), 170–188.
  • 4. Bar, M. (2007). The proactive brain: Using analogies and associations to generate predictions. Trends in Cognitive Sciences, 11(7), 280–289.
  • 5. Barrett, L. F. (2017). How Emotions Are Made: The Secret Life of the Brain. Houghton Mifflin Harcourt.
  • 6. Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2015). Canonical microcircuits for predictive coding. Neuron, 76(4), 695–711.
  • 7. Beaty, R. E., Benedek, M., Silvia, P. J., & Schacter, D. L. (2016). Creative cognition and brain network dynamics. Trends in Cognitive Sciences, 20(2), 87–95.
  • 8. Bechara, A., Damasio, H., & Damasio, A. R. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex, 10(3), 295–307.
  • 9. Behrens, T. E., Hunt, L. T., Woolrich, M. W., & Rushworth, M. F. (2008). Associative learning of social value. Nature, 456(7219), 245–249.
  • 10. Blanchard, R. J., Blanchard, D. C., & Rodgers, J. (2001). Risk assessment and animal models of anxiety. Neuroscience & Biobehavioral Reviews, 25(7-8), 597–604.
  • 11. Botvinick, M. M., & Cohen, J. D. (2014). The computational and neural basis of cognitive control. Cognitive Science, 38(6), 1249–1285.
  • 12. Brown, A. S. (2004). The déjà vu experience. Psychological Bulletin, 130(3), 493–508.
  • 13. Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414–421.
  • 14. Chartrand, T. L., & Bargh, J. A. (1999). The chameleon effect. Journal of Personality and Social Psychology, 76(6), 893–910.
  • 15. Clark, A. (2016). Surfing Uncertainty: Prediction, Action, and the Embodied Mind. Oxford University Press.
  • 16. Collins, A. G. E., & Frank, M. J. (2013). Cognitive control over learning. Cognitive, Affective, & Behavioral Neuroscience, 13(2), 467–486.
  • 17. Damasio, A. R. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness. Harcourt.
  • 18. Diekelmann, S., & Born, J. (2010). The memory function of sleep. Nature Reviews Neuroscience, 11(2), 114–126.
  • 19. Dunbar, R. I. M., & Shultz, S. (2007). Understanding primate brain evolution. Philosophical Transactions of the Royal Society B, 362(1480), 649–658.
  • 20. Eichenbaum, H. (2012). The cognitive neuroscience of memory: An introduction. Oxford University Press.
  • 21. Feldman, H., & Friston, K. J. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4, 215.
  • 22. Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2016). Statistically optimal perception and learning. Trends in Cognitive Sciences, 14(3), 119–130.
  • 23. Fleming, S. M., Huijgen, J., & Dolan, R. J. (2012). Prefrontal contributions to metacognition in perceptual decision making. Journal of Neuroscience, 32(18), 6117–6125.
  • 24. Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138.
  • 25. Frith, C. D., & Frith, U. (2007). Social cognition in humans. Current Biology, 17(16), R724–R732.
  • 26. Gershman, S. J., & Daw, N. D. (2017). Reinforcement learning and episodic memory. Current Opinion in Behavioral Sciences, 17, 110–116.
  • 27. Hassabis, D., & Maguire, E. A. (2007). Deconstructing episodic memory. Trends in Cognitive Sciences, 11(7), 299–306.
  • 28. Hohwy, J. (2013). The Predictive Mind. Oxford University Press.
  • 29. Holroyd, C. B., & Coles, M. G. (2002). The neural basis of human error processing. Psychological Review, 109(4), 679–709.
  • 30. Kauffman, S. A. (1993). The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press.
  • 31. Kiebel, S. J., Daunizeau, J., & Friston, K. J. (2008). A hierarchy of time-scales and the brain. PLoS Computational Biology, 4(11), e1000209.
  • 32. LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of Neuroscience, 23(1), 155–184.
  • 33. Lupyan, G., & Clark, A. (2015). Words and the world. Current Directions in Psychological Science, 24(4), 279–284.
  • 34. Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. MIT Press.
  • 35. McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995). Why there are complementary learning systems. Psychological Review, 102(3), 419–457.
  • 36. Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24(1), 167–202.
  • 37. Nadel, L., & Moscovitch, M. (1997). Memory consolidation, retrograde amnesia and the hippocampal complex. Current Opinion in Neurobiology, 7(2), 217–227.
  • 38. Niv, Y., Edlund, J. A., Dayan, P., & O'Doherty, J. P. (2012). Neural prediction errors reveal a risk-sensitive reinforcement-learning process. Nature Neuroscience, 15(5), 719–725.
  • 39. Norman, D. A., & Shallice, T. (1986). Attention to action. In Consciousness and Self-Regulation (pp. 1–18). Springer.
  • 40. O'Reilly, R. C. (2006). Biologically based computational models of high-level cognition. Science, 314(5796), 91–94.
  • 41. Panksepp, J. (1998). Affective Neuroscience: The Foundations of Human and Animal Emotions. Oxford University Press.
  • 42. Pezzulo, G., & Cisek, P. (2016). Navigating the affordance landscape. Trends in Cognitive Sciences, 20(6), 414–424.
  • 43. Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning. Classical Conditioning II: Current Research and Theory, 2, 64–99.
  • 44. Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593–1599.
  • 45. Shenhav, A., Botvinick, M. M., & Cohen, J. D. (2013). The expected value of control. Neuron, 79(2), 217–240.
  • 46. Summerfield, C., & de Lange, F. P. (2014). Expectation in perceptual decision making. Nature Reviews Neuroscience, 15(11), 745–756.
  • 47. Tulving, E. (2002). Episodic memory. Annual Review of Psychology, 53(1), 1–25.
  • 48. Van der Kolk, B. (2014). The Body Keeps the Score. Viking.
  • 49. Zurek, W. H. (1989). Thermodynamic cost of computation, algorithmic complexity and the information metric. Nature, 341(6241), 119–124.
  • 50. Yonelinas, A. P. (2013). The hippocampus supports high-resolution binding in the service of perception, working memory and long-term memory. Behavioral Brain Research, 254, 34–44.
  • 51. Anderson, M. C., & Hulbert, J. C. (2021). Active forgetting: Adaptation of memory by prefrontal control. Annual Review of Psychology, 72, 1–28.
  • 52. Aron, A. R., Robbins, T. W., & Poldrack, R. A. (2014). Inhibition and the right inferior frontal cortex. Trends in Cognitive Sciences, 8(4), 170–177.
  • 53. Apps, M. A., Rushworth, M. F., & Chang, S. W. (2016). The anterior cingulate gyrus and social cognition. Neuron, 90(4), 692–707.
  • 54. Bartlett, F. C. (1932). Remembering: A Study in Experimental and Social Psychology. Cambridge University Press.
  • 55. Bechara, A., Damasio, A. R., & Damasio, H. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex, 10(3), 295–307.
  • 56. Bjork, R. A., & Bjork, E. L. (1992). A new theory of disuse and an old theory of stimulus fluctuation. From Learning Processes to Cognitive Processes, 2, 35–67.
  • 57. Chun, M. M., & Turk-Browne, N. B. (2007). Interactions between attention and memory. Current Opinion in Neurobiology, 17(2), 177–184.
  • 58. Dunbar, R. I. M. (1998). The social brain hypothesis. Evolutionary Anthropology: Issues, News, and Reviews, 6(5), 178–190.
  • 59. Dunbar, R. I., & Shultz, S. (2007). Understanding primate brain evolution. Philosophical Transactions of the Royal Society B, 362(1480), 649–658.
  • 60. Hassabis, D., & Maguire, E. A. (2007). Deconstructing episodic memory with construction. Trends in Cognitive Sciences, 11(7), 299–306.
  • 61. Jack, R. E., Caldara, R., & Schyns, P. G. (2012). Internal representations reveal cultural diversity in expectations of facial expressions of emotion. Journal of Experimental Psychology: General, 141(1), 19.
  • 62. Jung, R. E., Mead, B. S., Carrasco, J., & Flores, R. A. (2013). The structure of creative cognition in the human brain. Frontiers in Human Neuroscience, 7, 330.
  • 63. Klein, S. B., Loftus, J., & Kihlstrom, J. F. (2010). Memory and temporal experience. Social Cognition, 28(5), 638–654.
  • 64. Koechlin, E., Ody, C., & Kouneiher, F. (2003). The architecture of cognitive control in the human prefrontal cortex. Science, 302(5648), 1181–1185.
  • 65. Kumaran, D., Banino, A., Blundell, C., Hassabis, D., & Dayan, P. (2016). Computations underlying social hierarchy learning. Neuron, 92(5), 1135–1147.
  • 66. LeDoux, J. (2015). Anxious: Using the Brain to Understand and Treat Fear and Anxiety. Viking.
  • 67. Macrae, C. N., Milne, A. B., & Bodenhausen, G. V. (1994). Stereotypes as energy-saving devices. Journal of Personality and Social Psychology, 66(1), 37.
  • 68. Mazur, A., & Booth, A. (1998). Testosterone and dominance in men. Behavioral and Brain Sciences, 21(3), 353–363.
  • 69. McClelland, J. L., & Rumelhart, D. E. (1986). Parallel Distributed Processing. MIT Press.
  • 70. McGaugh, J. L. (2004). The amygdala modulates the consolidation of emotionally arousing experiences. Annual Review of Neuroscience, 27, 1–28.
  • 71. McGaugh, J. L. (2015). Consolidating memories. Annual Review of Psychology, 66, 1–24.
  • 72. Nadel, L., & Hardt, O. (2011). Update on memory reconsolidation. Trends in Cognitive Sciences, 15(10), 504–510.
  • 73. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175.
  • 74. Nowak, M. A., & Sigmund, K. (2005). Evolution of indirect reciprocity. Nature, 437(7063), 1291–1298.
  • 75. Öhman, A., & Mineka, S. (2001). Fears, phobias, and preparedness. Perspectives on Psychological Science, 6(2), 142–152.
  • 76. Phelps, E. A., & LeDoux, J. E. (2005). Contributions of the amygdala to emotion processing. The Journal of Neuroscience, 25(41), 10347–10350.
  • 77. Post, R. M. (1992). Transduction of psychosocial stress into the neurobiology of recurrent affective disorder. American Journal of Psychiatry, 149(8), 999–1010.
  • 78. Raichle, M. E., et al. (2001). A default mode of brain function. PNAS, 98(2), 676–682.
  • 79. Sapolsky, R. M. (2004). Why Zebras Don't Get Ulcers. Holt Paperbacks.
  • 80. Sapolsky, R. M. (2005). The influence of social hierarchy on primate health. Science, 308(5722), 648–652.
  • 81. Schultz, W. (2016). Reward functions of the basal ganglia. Journal of Neural Transmission, 123(7), 679–693.
  • 82. Seligman, M. E. (1972). Learned helplessness. Annual Review of Medicine, 23(1), 407–412.
  • 83. Seghier, M. L. (2013). The angular gyrus: Multiple functions and multiple subdivisions. The Neuroscientist, 19(1), 43–61.
  • 84. Shenhav, A., Cohen, J. D., & Botvinick, M. M. (2016). Dorsal anterior cingulate cortex and the value of control. Nature Neuroscience, 19(10), 1286–1291.
  • 85. Squire, L. R., & Wixted, J. T. (2011). The cognitive neuroscience of human memory since HM. Annual Review of Neuroscience, 34, 259–288.
  • 86. Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In The Social Psychology of Intergroup Relations, 33–47.
  • 87. Teicher, M. H., et al. (2016). Childhood maltreatment and memory bias. Neuropsychopharmacology, 41(1), 232–245.
  • 88. Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005). Understanding and sharing intentions. Behavioral and Brain Sciences, 28(5), 675–691.
  • 89. Trivers, R. (1971). The evolution of reciprocal altruism. The Quarterly Review of Biology, 46(1), 35–57.
  • 90. Van der Kolk, B. A. (2014). The Body Keeps the Score. Viking.
  • 91. Wegner, D. M. (2003). The illusion of conscious will. MIT Press.
  • 92. Weber, M. (1947). The Theory of Social and Economic Organization. Oxford University Press.
  • 93. Weiskopf, D. A. (2011). Models and mechanisms in psychological explanation. Synthese, 183(3), 313–338.
  • 94. Wixted, J. T. (2004). The psychology and neuroscience of forgetting. Annual Review of Psychology, 55, 235–269.
  • 95. Yonelinas, A. P. (2002). The nature of recollection and familiarity. Journal of Memory and Language, 46(3), 441–517.
  • 96. Yu, A. J., & Dayan, P. (2005). Uncertainty, neuromodulation, and attention. Neuron, 46(4), 681–692.
  • 97. Zald, D. H. (2003). The human amygdala and the emotional evaluation of sensory stimuli. Brain Research Reviews, 41(1), 88–123.
  • 98. Zeki, S. (2004). The disunity of consciousness. Trends in Cognitive Sciences, 7(5), 214–218.
  • 99. Zhang, J. (2003). The nature of external representations in problem solving. Cognitive Science, 27(4), 587–625.
  • 100. Zylberberg, J., & DeWeese, M. R. (2013). Neurons learn by predicting future activity. Nature Neuroscience, 16(12), 1783–1789.