DocumentCode :
1390723
Title :
Understanding Perception Through Neural “Codes”
Author :
Freeman, Walter J.
Author_Institution :
Dept. of Mol. & Cell Biol., Univ. of California, Berkeley, CA, USA
Volume :
58
Issue :
7
fYear :
2011
fDate :
7/1/2011 12:00:00 AM
Firstpage :
1884
Lastpage :
1890
Abstract :
A major challenge for cognitive scientists is to deduce and explain the neural mechanisms of the rapid transposition between stimulus energy and recalled memory-between the specific (sensation) and the generic (perception)-in both material and mental aspects. Researchers are attempting three explanations in terms of neural codes. The microscopic code: cellular neurobiologists correlate stimulus properties with the rates and frequencies of trains of action potentials induced by stimuli and carried by topologically organized axons. The mesoscopic code: cognitive scientists formulate symbolic codes in trains of action potentials from feature-detector neurons of phonemes, lines, odorants, vibrations, faces, etc., that object-detector neurons bind into representations of stimuli. The macroscopic code: neurodynamicists extract neural correlates of stimuli and associated behaviors in spatial patterns of oscillatory fields of dendritic activity, which self-organize and evolve on trajectories through high-dimensional brain state space. This multivariate code is expressed in landscapes of chaotic attractors. Unlike other scientific codes, such as DNA and the periodic table, these neural codes have no alphabet or syntax. They are epistemological metaphors that experimentalists need to measure neural activity and engineers need to model brain functions. My aim is to describe the main properties of the macroscopic code and the grand challenge it poses: how do very large patterns of textured synchronized oscillations form in cortex so quickly?
Keywords :
DNA; bioelectric potentials; brain; cellular biophysics; codes; cognition; molecular biophysics; neurophysiology; DNA; action potentials; axons; cellular neurobiologists; chaotic attractors; cognition; dendritic activity; epistemological metaphors; feature-detector neurons; high-dimensional brain state space; neural codes; neurodynamics; object-detector neurons; perception; recalled memory; self-organization; sensation; stimuli; stimulus energy; Arrays; Assembly; Correlation; Frequency modulation; Microscopy; Neurons; Oscillators; Amplitude (AM) pattern; Hebbian assembly; correlation length; electrocorticogram (ECoG); neocortical population; Animals; Cats; Cerebral Cortex; Cognitive Science; Computer Simulation; Electroencephalography; Humans; Multivariate Analysis; Neurons; Perception; Rabbits; Sensation; Signal Processing, Computer-Assisted; Smell;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2010.2095854
Filename :
5648451
Link To Document :
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