Brain sciences
May 28, 2023
Peter Grindrod, Martin Brennan
Cognition and internal phenomenological sensations, including emotions, are inseparable. These sensations arise as dynamical "modes" of firing behavior that exist over time across large cortical neuron networks, resulting from network-of-networks architecture, coupling of individual neuronal dynamics, and time delays in neuron-to-neuron transmission. Incoming stimuli create competitive modes that suppress one another, and any present mode acts as a preconditioner for immediate cognitive processing, reducing the decision set and cognitive load. This provides an evolutionary advantage, explaining "thinking fast, thinking slow." The entwinement hypothesis describes how latent conscious phenomena arise from cognitive processing load dynamics and precondition subsequent tasks. These modes, candidates for emotions down to single qualia, can be observed via reverse engineering simulations using supercomputers or generalized Kuramoto models.
Network neuroscience (Cambridge, Mass.)
January 1, 2018
Peter Grindrod
Mathematical modeling of neuron-to-neuron dynamical networks shows that even small-scale strongly connected networks perform nonbinary information processing, enabling multiple-hypothesis decision-making at the brain's lowest architectural level. This framework addresses aspects of the hard problem of consciousness, proposing a dual hierarchy model composed of externally perceived physical elements of increasing complexity and internally experienced mental elements (feelings). The model implies that finite human brains must always be learning and forgetting; any subjective feeling that could be fully idealized with a countable infinity of facets could never be learned completely by automata. Mental elements act like latent variables in processing and decision-making, conferring an evolutionary fast-thinking advantage.
arXiv Preprint Archive
September 11, 2016
Peter Grindrod
Mathematical analysis of small-scale strongly connected neural networks shows they naturally perform non-binary information processing, enabling multiple hypothesis decision-making at the brain's lowest architectural level. Building on this, a proposed "dual hierarchy model"—comprising external physical elements of increasing complexity and internal mental experiences—supports a learning, evolving consciousness. Because the brain can re-conjure subjective feelings at will, these feelings cannot depend on internal noise or instability-driven activity. A consequence is that finite human brains must always be learning or forgetting, and any subjective feeling with a countable infinity of facets can never be learned by zombies or automata, though an evolving brain can experience it increasingly fully, never in totality.