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Koorosh Mirpour, James Bisley; Temporal structure in the lateral intraparietal area (LIP) neuronal activity during dynamic visual search. Journal of Vision 2013;13(9):1201. doi: https://doi.org/10.1167/13.9.1201.
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© ARVO (1962-2015); The Authors (2016-present)
The ability to recognize targets from distractors is as crucial as remembering where you have looked when performing dynamic visual search. We have shown that activity in LIP encodes all these elements; the average spiking responses of LIP neurons not only differentiate between targets and distractors, but also keep track of already visited locations during visual search. It has also been shown that the power spectra of LIP activity exhibits a spatially tuned temporal structure in memory guided eye movements. However it has not been shown whether there is temporal structure in LIP activity during dynamic visual search. To address this question, we recorded local field potentials (LFPs) from LIP while two animals performed a visual foraging task. In this task, animals search through an array of 5 task irrelevant distractors and 5 Ts, one of which has a reward linked to it (the target). To obtain the reward, the animal must fixate the target for 500 ms. The stimuli are arranged such that when the animal fixates one stimulus, another is likely to be in the response field of the single neuron being recorded when the LFP was collected. We found that raw LFPs distinguished between the Ts and the irrelevant distractors in addition to new from visited objects. In the spectral analysis of the LFP, we found the temporal structure related to efficient foraging behavior. The spectral power in the mid-gamma band differentiated targets, distractors and visited objects. In addition there was an elevation of power in alpha band which appeared much earlier and was only present when an already visited object was in the receptive filed. We suggest that this signal, which may be a neural correlate of search memory, or inhibition or return, is separate from the feed-forward signal that differentiates between the stimulus classes.
Meeting abstract presented at VSS 2013
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