Seven Properties of Self-Organization in the Human Brain

Abstract

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: (1) modular connectivity, (2) unsupervised learning, (3) adaptive ability, (4) functional resiliency, (5) functional plasticity, (6) from-local-to-global functional organization, and (7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward.

Correlating Grip Force Signals from Multiple Sensors Highlights Prehensile Control Strategies in a Complex Task-User System

“…Here, we provide step-by-step statistics which show that different levels of proficiency in performing the highly complex precision grip task are reflected by skill-specific, distinct co-variation patterns in locally produced grip force signals from the most task-relevant sensor locations in the middle, ring and small fingers and in the palm of the preferred hand. These co-variation patterns are presumed to reflect individual grip force strategies, governed by prehensile synergies at the central control levels in the neural networks of a somatotopically organized cortical brain map [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. With grip forces being both locally and globally mapped in the somatosensory brain [ 21 , 22 ], it is shown here that variations in task-skill result in distinctive from-global-to-local grip force co-variation patterns across fingers and hands.…”

“…This is shown and discussed in the context of a complex task-device-user system with tightly limited degrees of freedom for hand and finger movement. Illustrates how locally generated grip-force data may be encoded in a fixed-size neural network in the somatosensory brain [14][15][16][17][18][19][20][21][22]. Local effectors/mechanoreceptors on the middle phalanxes of the small (1)…”

“…The S1 cortical area is conceptualized in current state of the art [ 16 , 17 ] as containing a single map of the receptor periphery. The somatosensory cortical network has a modular functional architecture and connectivity, with highly specific connectivity patterns [ 16 , 17 , 18 , 19 , 20 ], binding functionally distinct neuronal subpopulations from other cortical areas into motor circuit modules at several hierarchical levels [ 17 ]. The functional modules display a hierarchy of interleaved circuits connecting via inter-neurons in the spinal cord, in visual sensory areas, and in motor cortex with feed-back loops, and bilateral communication with supraspinal centers [ 17 , 18 ].…”

“…The from-local-to-global functional organization ( Figure 1 ) of the somatosensory neural circuits relates to precise connectivity patterns, and these patterns frequently correlate with specific behavioral functions or motor output. Current state of the art suggests that developmental specification, where neuronal subpopulations are specified in the process of a precisely timed neurogenesis [ 17 , 18 ], determines the self-organizing nature of this connectivity for motor control and, in particular, limb movement control [ 20 ]. The functional plasticity of the somatosensory cortical network is revealed by neuroscience research on the human primate [ 19 ] showing that somatosensory representations of fingers left intact after amputation of others on the same hand become expanded in less than ten days after amputation, when compared with representations in the intact hand of the same patient, or to representations in either hand of controls.…”

“…The functional plasticity of the somatosensory cortical network is revealed by neuroscience research on the human primate [ 19 ] showing that somatosensory representations of fingers left intact after amputation of others on the same hand become expanded in less than ten days after amputation, when compared with representations in the intact hand of the same patient, or to representations in either hand of controls. Such a network expansion reflects the functional resiliency of the self-organized somatosensory system, which has evolved as a function of active constraints [ 20 ], and in harmony with other sensory systems such as the visual and auditory brain. Grip force profiles are a direct reflection of the complex low-level, cognitive, and behavioral synergies this evolution has produced.…”