Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions

Part I of this paper describes a model for the parallel development and adult coding of neural feature detectors. It shows how any set of arbitrary spatial patterns can be recoded, or transformed, into any other spatial patterns (universal recoding), if there are sufficiently many cells in the network's cortex. This code is, however, unstable through time if arbitrarily many patterns can perturb a fixed number of cortical cells. This paper shows how to stabilize the code in the general case using feedback between cellular sites. A biochemically defined critical period is not necessary to stabilize the code, nor is it sufficient to ensure useful coding properties.We ask how short term memory can be reset in response to temporal sequences of spatial patterns. This leads to a context-dependent code in which no feature detector need uniquely characterize an input pattern; yet unique classification by the pattern of activity across feature detectors is possible. This property uses learned expectation mechanisms whereby unexpected patterns are temporarily suppressed and/or activate nonspecific arousal. The simplest case describes reciprocal interactions via trainable synaptic pathways (long term memory traces) between two recurrent on-center off-surround networks undergoing mass action (shunting) interactions. This unit can establish an adaptive resonance, or reverberation, between two regions if their coded patterns match, and can suppress the reverberation if their patterns do not match. This concept yields a model of olfactory coding within the olfactory bulb and prepyriform cortex. The resonance idea also includes the establishment of reverberation between conditioned reinforcers and generators of contingent negative variation if presently avialable sensory cues are compatible with the network's drive requirements at that time; and a search and lock mechanism whereby the disparity between two patterns can be minimized and the minimal disparity images locked into position. Stabilizing the code uses attentional mechanisms, in particular nonspecific arousal as a tuning and search device. We suggest that arousal is gated by a chemical transmitter system—for example, norepinephrine—whose relative states of accumulation at antagonistic pairs of on-cells and off-cells through time can shift the spatial pattern of STM activity across a field of feature detectors. For example, a sudden arousal increment in response to an un-expected pattern can reverse, or rebound, these relative activities, thereby suppressing incorrectly classified populations. The rebound mechanism has formal properties analogous to negative afterimages and spatial frequency adaptation.

[1]  G. Fechner.  Ueber die subjectiven Nachbilder und Nebenbilder , 1840 .

[2]  H. von Helmholtz,et al.  Helmholtz's treatise on physiological optics, Vol. 1, Trans. from the 3rd German ed. , 1924 .

[3]  C. Pfaffmann,et al.  Gustatory nerve impulses in rat, cat and rabbit. , 1955, Journal of neurophysiology.

[4]  D. Mackay.  Moving Visual Images Produced by Regular stationary Patterns , 1957, Nature.

[5]  D. Mackay.  Moving Visual Images produced by Regular Stationary Patterns , 1958, Nature.

[6]  W. D. Wright.  Physiological Optics , 1958, Nature.

[7]  D. Hubel,et al.  RECEPTIVE FIELDS OF CELLS IN STRIATE CORTEX OF VERY YOUNG, VISUALLY INEXPERIENCED KITTENS. , 1963, Journal of neurophysiology.

[8]  R. Erickson,et al.  SENSORY NEURAL PATTERNS AND GUSTATION , 1963 .

[9]  A. Hodgkin.  The conduction of the nervous impulse , 1964 .

[10]  C. H. Graham,et al.  Vision and visual perception , 1965 .

[11]  B. Katz.  Nerve, Muscle and Synapse , 1966 .

[12]  M. Low,et al.  Surface‐negative, slow‐potential shift associated with conditioning in man , 1966, Neurology.

[13]  D. Mcadam,et al.  Conative control of the contingent negative variation. , 1966, Electroencephalography and clinical neurophysiology.

[14]  D. Mcadam,et al.  Motivational determinants of the "contingent negative variation". , 1966, Electroencephalography and clinical neurophysiology.

[15]  B. Cant,et al.  The effect of motivation on the contingent negative variation (CNV). , 1967, Electroencephalography and clinical neurophysiology.

[16]  C. Noback.  The Human Nervous System , 1967 .

[17]  Liberson Cw,et al.  Eye movements during the alert state (psychophysiological correlations under resting conditions). , 1967 .

[18]  W. Stell.  The structure and relationships of horizontal cells and photoreceptor-bipolar synaptic complexes in goldfish retina. , 1967, The American journal of anatomy.

[19]  J. R. Hughes,et al.  THE FREQUENCY COMPONENT HYPOTHESIS IN RELATION TO THE CODING MECHANISM IN THE OLFACTORY BULB , 1967 .

[20]  D. Mcadam.  Increases in CNS excitability during negative cortical slow potentials in man. , 1969, Electroencephalography and clinical neurophysiology.

[21]  W. Freeman,et al.  Pattern analysis of cortical evoked potential parameters during attention changes , 1969 .

[22]  J. Cohen.  Very slow brain potentials relating to expectancy - The CNV , 1969 .

[23]  A. Kaneko.  Physiological and morphological identification of horizontal, bipolar and amacrine cells in goldfish retina , 1970, The Journal of physiology.

[24]  T. Hökfelt,et al.  Morphological and Functional Aspects of Central Monoamine Neurons , 1970 .

[25]  S Grossberg,et al.  On the dynamics of operant conditioning. , 1971, Journal of theoretical biology.

[26]  B. Julesz.  Foundations of Cyclopean Perception , 1971 .

[27]  U. Ungerstedt.  Stereotaxic mapping of the monoamine pathways in the rat brain. , 1971, Acta physiologica Scandinavica. Supplementum.

[28]  S. Grossberg.  A neural theory of punishment and avoidance, I: Qualitative theory , 1972 .

[29]  W. Freeman.  Waves, Pulses, and the Theory of Neural Masses , 1972 .

[30]  D. Jacobowitz.  EFFECTS OF 6-HYDROXYDOPA , 1973 .

[31]  L. Stein,et al.  Evidence of -noradrenergic reward receptors and serotonergic punishment receptors in the rat brain. , 1973, Biological psychiatry.

[32]  O. Lindvall,et al.  The organization of the ascending catecholamine neuron systems in the rat brain as revealed by the glyoxylic acid fluorescence method. , 1974, Acta physiologica Scandinavica. Supplementum.

[33]  M. Arbib,et al.  Conceptual models of neural organization. , 1974, Neurosciences Research Program bulletin.

[34]  H R Wilson,et al.  A synaptic model for spatial frequency adaptation. , 1975, Journal of theoretical biology.

[35]  G. Somjen.  Sensory Coding in the Mammalian Nervous System , 1975 .

[36]  S Grossberg,et al.  Some developmental and attentional biases in the contrast enhancement and short term memory of recurrent neural networks. , 1975, Journal of theoretical biology.

[37]  L. Stein.  Norepinephrine reward pathways: role of self-stimulation, memory consolidation, and schizophrenia. , 1975, Nebraska Symposium on Motivation. Nebraska Symposium on Motivation.

[38]  S. Grossberg.  A neural model of attention, reinforcement and discrimination learning. , 1975, International review of neurobiology.

[39]  S. Grossberg,et al.  Visual illusions in neural networks: line neutralization, tilt after effect, and angle expansion. , 1976, Journal of theoretical biology.

[40]  Stephen Grossberg,et al.  Classical and Instrumental Learning by Neural Networks , 1982 .

[41]  J. Staddon,et al.  The dynamics of operant conditioning. , 1999, Psychological review.

[42]  Stephen Grossberg,et al.  A Neural Theory of Punishment and Avoidance , II : Quantitative Theory , 2003 .

[43]  W. Walter.  Slow potential waves in the human brain associated with expectancy, attention and decision , 1964, Archiv für Psychiatrie und Nervenkrankheiten.

[44]  S. Grossberg,et al.  Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors , 1976, Biological Cybernetics.

[45]  S. Grossberg,et al.  Pattern formation, contrast control, and oscillations in the short term memory of shunting on-center off-surround networks , 1975, Biological Cybernetics.

[46]  Stephen Grossberg,et al.  Neural expectation: cerebellar and retinal analogs of cells fired by learnable or unlearned pattern classes , 2004, Kybernetik.

[47]  W. Kilmer,et al.  Model of a plausible learning scheme for CA3 Hippocampus , 1974, Kybernetik.

[48]  S. Grossberg.  On the development of feature detectors in the visual cortex with applications to learning and reaction-diffusion systems , 1976, Biological Cybernetics.

[49]  Ueber das Phänomen der zufälligen Farben , 2006 .