Sensory signals in neural populations underlying tactile perception and manipulation

• Published in: Annual review of neuroscience Vol. 27; no. 1; pp. 53 - 77
• Main Authors: GOODWIN, Antony W, WHEAT, Heather E
• Format: Journal Article
• Language: English
• Published: Palo Alto, CA Annual Reviews 01.01.2004; Annual Reviews, Inc
• Subjects: Action Potentials - physiology; Animals; Biological and medical sciences; Brain; Fingers & toes; Fundamental and applied biological sciences. Psychology; Hand - innervation; Hand - physiology; Hand Strength - physiology; Humans; Mechanoreceptors - physiology; Mechanotransduction, Cellular - physiology; Motor ability; Neurons, Afferent - physiology; Sensory perception; Skin; Skin - innervation; Somesthesis and somesthetic pathways (proprioception, exteroception, nociception); interoception; electrolocation. Sensory receptors; Touch - physiology; Vertebrates: nervous system and sense organs; cutaneous; Gripping; Tactile sensitivity; somatosensory; grasp; Mechanoreceptor; Perception; Skin; Review; Motor control; primary afferent
• ISSN: 0147-006X; 1545-4126
• DOI: 10.1146/annurev.neuro.26.041002.131032

For humans to manipulate an object successfully, the motor control system must have accurate information about parameters such as the shape of the stimulus, its position of contact on the skin, and the magnitude and direction of contact force. The same information is required for perception during haptic exploration of an object. Much of these data are relayed by the mechanoreceptive afferents innervating the glabrous skin of the digits. Single afferent responses are modulated by all the relevant stimulus parameters. Thus, only in complete population reconstructions is it clear how each of the parameters can be signaled to the brain independently when many are changing simultaneously, as occurs in most normal movements or haptic exploration. Modeling population responses reveals how resolution is affected by neural noise and intrinsic properties of the population such as the pattern and density of innervation and the covariance of response variability.