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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 11255
School of Cognitive Sciences
  Title:   State-dependent effects of stimulus presentation duration on the temporal dynamics of neural responses in the inferotemporal cortex of macaque monkeys
  Author(s): 
1.  Koorosh Mirpour
2.  Hossein Esteky
  Status:   Published
  Journal: Neurophysiology
  Vol.:  102
  Year:  2009
  Pages:   1790-1800
  Supported by:  IPM
  Abstract:
During natural vision, stimuli are viewed for different durations as the state of brain activity changes over time. Here, we studied the effects of stimulus presentation duration on cell responses (n=259) in three subdivisions of the inferotemporal (IT) cortex of fixating macaque monkeys as neural baseline firing rates varied over the course of recording. First, cell responses to the presentation of 120 images were tested and four images that elicited significant responses with various degrees of effectiveness were selected for further study. Then, the four selected images were presented to the monkeys for five different presentation durations (18, 70, 140, 210 and 350 ms). We found that, depending on the magnitude of neural baseline activity, stimulus presentation duration affected the response properties and efficiency of neural information processing in the IT cortex. Short stimulus presentation durations elicited phasic responses consisting of rhythmic activation and inactivation, which conveyed a lower amount of stimulus information, particularly following higher baseline firing rates. Longer presentation durations elicited a sustained pattern of response and carried a greater amount of information, particularly at lower baseline firing rates. Finally, a significantly higher proportion of cells in the posterior IT compared to the anterior IT had a tendency to have high baseline activity, recruit stronger phasic responses and convey less information. It is plausible that during natural vision, as stimuli with various exposure durations affect the visual system, top-down influence or competition within local neural networks differentially influences the function of IT cells by changing their baseline activity.

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