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Abstract
Various spike patterns from sensory/motor neurons provide information about the dynamic sensory stimuli. Based on the information theory, neuroscientists have revealed the influence of spike variables on information transmission. Among diverse spike variables, inter-trial heterogeneity, known as jitter, has been observed in physiological neuron activity and responses to artificial stimuli, and it is recognized to contribute to information transmission. However, the relationship between inter-trial heterogeneity and information remains unexplored. Therefore, understanding how jitter impacts the heterogeneity of spiking activities and information encoding is crucial, as it offers insights into stimulus conditions and the efficiency of neural systems. Here, we systematically explored how neural information is altered by number of neurons as well as by each of three fundamental spiking characteristics: mean firing rate (MFR), duration, and cross-correlation (spike time tiling coefficient; STTC). First, we generated groups of spike trains to have specific average values for those characteristics. Second, we quantified the transmitted information rate as a function of each parameter. As population size, MFR, and duration increased, the information rate was enhanced but gradually saturated with further increments in number of cells and MFR. Regarding the cross-correlation level, homogeneous and heterogeneous spike trains (STTCAVG = 0.9 and 0.1) showed the lowest and highest information transmission, respectively. Interestingly however, when jitters were added to mimic physiological noisy environment, the information was reduced by ~ 46% for the spike trains with STTCAVG = 0.1 but rather substantially increased by ~ 63% for the spike trains with STTCAVG = 0.9. Our study suggests that optimizing various spiking characteristics may enhance the robustness and amount of neural information transmitted.
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1 Korea University, School of Electrical Engineering, Seoul, South Korea (GRID:grid.222754.4) (ISNI:0000 0001 0840 2678); Korea Institute of Science and Technology (KIST), Brain Science Institute, Seoul, South Korea (GRID:grid.496416.8) (ISNI:0000 0004 5934 6655)
2 Korea University, School of Electrical Engineering, Seoul, South Korea (GRID:grid.222754.4) (ISNI:0000 0001 0840 2678)
3 Korea Institute of Science and Technology (KIST), Brain Science Institute, Seoul, South Korea (GRID:grid.496416.8) (ISNI:0000 0004 5934 6655); University of Science & Technology (UST), Division of Bio-Medical Science & Technology, KIST School, Seoul, South Korea (GRID:grid.412786.e) (ISNI:0000 0004 1791 8264); KHU-KIST, Kyung Hee University, Department of Converging Science and Technology, Seoul, South Korea (GRID:grid.289247.2) (ISNI:0000 0001 2171 7818)