An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

Abstract

The human brain is arguably the most complex “machine” to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain’s structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence frameworks inspired by its logical functioning. In this article, an approach to model some aspects of the brain learning and signal processing is presented, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model to demonstrate how dynamic neuroplasticity, neural inhibition and neuron migration can reshape the brain’s logical connectivity to synchronise signal processing and obtain certain target latencies. This work showcases the importance of dynamic logical and biophysical remodelling in brain plasticity. Combining mathematical (agents, graph theory, topology and backpropagation) and biomedical ingredients (metastability, neuroplasticity and migration), these preliminary results prove complex brain phenomena can be reproduced—under pertinent simplifications—via affordable computations, which can be construed as a starting point for more ambitiously accurate simulations.

Review of the Brain’s Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

“…Neuromorphic hardware (“neuroinformatics”) is the basis of artificial intelligence—albeit with notable simplifications from the real brain’s circuits. Further explanations can be found in [ 360 , 361 ] and Section 4.3 . This is directly related to electrical brain stimulation (EBS), which can alter neural activation thresholds and be measured in diverse ways (evoked potentials) [ 362 ].…”

“…The latter provide a more flexible framework, where an agent (e.g., a migrating neuron) interacts with its environment, reaching equilibrium points (homeostasis) within complex dynamic settings. Since it allows for quick decision making [ 420 ], this technique has been used to simulate different biological aspects: neural community interactions [ 361 , 421 , 422 ] and pathological contagion [ 423 ] and evolution (tumour-induced angiogenesis [ 424 ], glioblastoma multiforme [ 425 ]).…”

“…Although very useful for multiple applications, experts soon pointed out important discrepancies between actual biological neural networks and their intended artificial mock-ups—namely regarding backpropagation—in the way that errors are corrected from the outputs to the inputs to yield an accurate prediction [ 360 ], which constitutes the basis of regression in ML. There are several fundamental differences between artificial (ANNs) and biological neural networks (BNNs), such as the backpropagation procedure (layered vs. nonlayered), neural plasticity (functional vs. structural and functional), and metastability (occasional byproduct vs. biological requirement); see Section 2.5 in [ 361 ] for a more detailed explanation. A simple multilayer perceptron (MLP)—a generalisation of McCulloch–Pitt’s neuron with multiple intermediate layers—will not be enough to mimic the brain.…”

“…This subsection is intended to point out the modelling implications of the diseases summarised in this review in a cognitive agent-based model [ 361 ]. This model is an extension of an ABM model [ 424 , 425 ] of brain cells where the modelled neurons can interact, migrate, connect, and perform plastic remodelling.…”

“…This model is an extension of an ABM model [ 424 , 425 ] of brain cells where the modelled neurons can interact, migrate, connect, and perform plastic remodelling. The details of the model are in Irastorza-Valera et al [ 361 ] (see Figure 2 for a visual diagram of the presented model), and it is a novel treatment of the McCulloch–Pitts neuron as a living cell capable of interacting with its surrounding community. That implies that the neuron may be affected by environmental mechanical abnormalities (brain damage) through a disconnection or reduction in neuronal connections.…”