Feasibility of a Personal Neuromorphic Emulation.

Intelligence arises from patterns of connections among neurons, whether in brains or machines. Brains develop continuously as experience shapes their neural connections. Active inference theory suggests that sentient systems organize themselves by minimizing free energy, a process of informatic self-evidencing. This implies that the mind can be described in information terms independent of its physical substrate. At a certain complexity level, self-evidencing becomes hierarchical and reentrant, leading to consciousness as a good regulator. These principles indicate that adequate reconstruction of an individual human brain's computational dynamics is possible through neuromorphic computational emulation.

Study at a glance

Abstract

The representation of intelligence is achieved by patterns of connections among neurons in brains and machines. Brains grow continuously, such that their patterns of connections develop through activity-dependent specification, with the continuing ontogenesis of individual experience. The theory of active inference proposes that the developmental organization of sentient systems reflects general processes of informatic self-evidencing, through the minimization of free energy. We interpret this theory to imply that the mind may be described in information terms that are not dependent on a specific physical substrate. At a certain level of complexity, self-evidencing of living (self-organizing) information systems becomes hierarchical and reentrant, such that effective consciousness emerges as the consequence of a good regulator. We propose that these principles imply that an adequate reconstruction of the computational dynamics of an individual human brain/mind is possible with sufficient neuromorphic computational emulation.