Neurons in different regions within the visual system carry out different aspects of visual pattern analysis needed for visual perception. We are studying how and where the pieces that make up a visually perceived object are brought together. We recorded the activity of single neurons in the primary visual cortex (the first cortical stage of visual processing), and inferior temporal cortex (the last cortical stage) to study the mechanisms underlying visual perception. When we ask how the eye movements that occur on a screenful of images affect the responses of primary visual cortical neurons we find that even though the eyes take 300-400 ms to stabilize completely (including the parts of the message depending on the temporal structure of the response), the amount of stimulus-related information found in these responses is almost as much as that found after they have stabilized. This toleration of instability in the retinal location of a visual stimulus suggests that primary visual cortical neurons react to the overall structure of the features within a stimulus, not the features themselves. The latency before neurons start firing after a pattern appears is one important aspect of the time structure of a neuronal message. We find that the latency indicates how easily the pattern can be seen, and the intensity of the firing, the response strength, is a code indicating what the pattern is. Finding that the latency is related to how easily the pattern can be seen suggests that the features within in a pattern are grouped. We construct a model to show how the neuronal signals entering visual cortex from the lateral geniculate nucleus can be combined to make this feature grouping occur. When inferior temporal cortical neurons respond to a pattern obscured by visual noise, the time it takes for the monkey to respond to the pattern correctly is closely predicted by the time it takes for the neuronal messages to indicate which pattern is present. Our results at both ends of the visual cortical streams suggests there is a template of what constitutes a valid stimulus pattern that gates the neuronal responses. All of these findings taken together suggest that the visual system is sending messages that describe messages that describe stimuli as complex, integrated objects from the earliest cortical stages, and that this integration becomes more general as the signals pass to later stages of visual processing.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Intramural Research (Z01)
Project #
1Z01MH002032-21
Application #
6162853
Study Section
Special Emphasis Panel (LN)
Project Start
Project End
Budget Start
Budget End
Support Year
21
Fiscal Year
1997
Total Cost
Indirect Cost
Name
U.S. National Institute of Mental Health
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Nakahara, Hiroyuki; Amari, Shun-ichi; Richmond, Barry J (2006) A comparison of descriptive models of a single spike train by information-geometric measure. Neural Comput 18:545-68
Shidara, Munetaka; Richmond, Barry J (2005) Effect of visual noise on pattern recognition. Exp Brain Res 163:239-41
Richmond, Barry; Wiener, Matthew (2004) Recruitment order: a powerful neural ensemble code. Nat Neurosci 7:97-8
Wiener, Matthew C; Richmond, Barry J (2003) Decoding spike trains instant by instant using order statistics and the mixture-of-Poissons model. J Neurosci 23:2394-406
Wiener, Matthew C; Richmond, Barry J (2002) Model based decoding of spike trains. Biosystems 67:295-300
Shidara, Munetaka; Richmond, Barry J (2002) Anterior cingulate: single neuronal signals related to degree of reward expectancy. Science 296:1709-11
Richmond, B (2001) Neuroscience. Information coding. Science 294:2493-4
Wiener, M C; Oram, M W; Liu, Z et al. (2001) Consistency of encoding in monkey visual cortex. J Neurosci 21:8210-21
Oram, M W; Hatsopoulos, N G; Richmond, B J et al. (2001) Excess synchrony in motor cortical neurons provides redundant direction information with that from coarse temporal measures. J Neurophysiol 86:1700-16
Liu, Z; Murray, E A; Richmond, B J (2000) Learning motivational significance of visual cues for reward schedules requires rhinal cortex. Nat Neurosci 3:1307-15

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