The Neuroscience Chronicles

This paper presents a mathematical proof of the equivalence between the Human Language-based Consciousness (HLbC) model and Bayesian inference, exploring their connection within neural information processing. The HLbC model posits that consciousness emerges through a process involving the observation of external events, the matching of those events to past memories, unconscious action selection, and post-hoc recognition of actions as conscious decisions.

This paper presents a novel framework for measuring consciousness strength based on the Human Language-based Consciousness (HLbC) model. While Integrated Information Theory (IIT) quantifies consciousness via integrated information, the HLbC model views consciousness as a post-hoc process, emphasizing language and probabilistic decision-making.

A systematic analysis of Global Burden of Diseases (GBD) documented by the World Health Organization (WHO) now includes alarming prevalence of neurological diseases (NDs) as the foremost leading cause of death and disability worldwide. Given limited effectiveness of current symptomatic management of NDs, clinical implementation of alternative therapies is gaining increasing recognition as the viable option(s) for treating NDs.

Alzheimer’s disease (AD) is the leading cause of dementia, defined by amyloid plaques and neurofibrillary tangles. Yet, variability in disease onset and progression cannot be explained solely by pathology. Neuroplasticity, the brain’s ability to reorganize and adapt, is increasingly recognized as central to resilience in AD, with compelling evidence that it differs between sexes.

We establish a rigorous mathematical framework for the spontaneous formation of stable structures through the universal principle of energy minimization in multi-interaction systems. Within this formulation, each subsystem contributes to a collective energy function E(x) composed of bounded, weakly nonlinear interaction terms. 

Autism spectrum disorder is a multifactorial neurodevelopmental disorder with increasing prevalence worldwide. Given the heterogeneity of autism, it is highly unlikely to have a single effective therapy for autism. Adversities associated with current pharma-therapies in treating autism have prompted the emergence of alternative therapies including variety of behavioral and music interventions. Autistic children, who tend to show a strong preference for music, makes music therapy a promising intervention for autism. 

The challenge of developing a unified, mathematically rigorous framework for consciousness remains central to neuroscience. Hereby two recent papers are discussed that advance the Human Language-based Consciousness (HLbC) model as a novel, testable alternative to existing theories. 

Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are increasingly prevalent in children globally, including Cameroon. Emerging evidence suggests that early-life exposure to environmental neurotoxins, particularly mycotoxins, may disrupt brain development and contribute to these disorders.

Emotion has traditionally been understood as a subjective experience intrinsic to individual agents. However, the emergence of multi-agent systems, including artificial intelligence, calls for a reconceptualization of emotion as a dynamic process grounded in interaction. This paper proposes the Interacting Processual Information-based Emotive Model (IPIEM), a formal framework that defines emotion not as an intrinsic qualia within a single agent—which is philosophically treated here as an empty set—but as a set-theoretic phenomenon emergent through inter-agent information exchange and social realization.