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Prefrontal firing rates reflect the number of stimuli processed for visual short-term memory

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84293

Natora M, Waizel,  M
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84098

Munk,  MHJ
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Franke, F., Natora M, Waizel, M., Muckli LF, Pipa, G., & Munk, M. (2009). Prefrontal firing rates reflect the number of stimuli processed for visual short-term memory. Poster presented at Bernstein Conference on Computational Neuroscience (BCCN 2009), Frankfurt a.M., Germany.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-C2B8-A
Abstract
The way a system reacts to increased task demands can reveal information about its functional mechanism. We therefore assessed the question how non human primates process information about visual stimuli by driving two rhesus monkeys to their cognitive limits in a visual memory task. The monkeys were first trained to successfully perform the visual memory task (> 80 correct responses). Then the number of stimuli shown to the monkey (load) was increased to up to 4. The stimulus presentation period (SP) was 900 milliseconds long. Thus, in the load 4 condition each single stimulus was only shown for less than 225ms. After a three second delay period, a test stimulus was shown. The task of the monkey was then to decide via differential button press, whether the test stimulus matched any of the previously shown stimuli. Neuronal firing rates were recorded using up to 16 multi electrodes placed in the prefrontal cortex. For every trial in which the monkey responded correctly, the average multi unit rate during the SP was estimated. We then assessed the question whether the firing rates in the SP during the distinct load conditions were significantly different. To minimize the effect of non-stationarities present in the data, we paired the data so that the trials of one pair were maximally 2.5 minutes apart. We tested against the null-hypothesis that the firing rates during the SP did not differ significantly among the load conditions using the nonparametric Friedman-test for paired data. For every recording site where we could reject the null-hypothesis (p<0.05), we investigated in which direction the rates of the different load conditions differed, correcting for multiple tests using the Tukey-Kramer-correction. A total of 12681 correct trials were recorded with a total of 160 recording positions (6 to 16 per session). In total, 23 positions showed significant effects from which 20 were consistent. The firing rate differences were called consistent if the difference compared to load 1 were stronger the higher the load. Out of these 20 consistent recording sites 14 showed a firing rate which monotonically increased with the load, 6 showed a monotonous decrease. This means that 12 of the recording sites in prefrontal cortex show a significant modulation of firing rates with respect to the load condition during a delayed match to sample task. However this modulation is not necessarily excitatory. Interestingly, it seems that the majority of sites showed a load-consistent modulation i.e. the higher the load, the stronger the modulation. This could be a possible mechanism to code the number of stimuli or their sequence.