Differences in Spiking Patterns Among Cortical Neurons

• Published in: Neural computation Vol. 15; no. 12; pp. 2823 - 2842
• Main Authors: Shinomoto, Shigeru, Shima, Keisetsu, Tanji, Jun
• Format: Journal Article
• Language: English
• Published: One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.12.2003
• Subjects: Action Potentials - physiology; Animals; Biological and medical sciences; Cerebral Cortex - cytology; Cerebral Cortex - physiology; Evoked Potentials - physiology; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Models. Methods; Genetic Variation - physiology; Haplorhini; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Neurons - classification; Neurons - physiology; Reaction Time - physiology; Statistical Distributions; Synaptic Transmission - physiology; Time Factors; Vertebrates: nervous system and sense organs; Wakefulness - physiology; Correlation; Monkey; Stochastic process; Properties; Poisson process; Classification; Primates; Corticalneuron; Spike; Stimulus; Supplementary motor area; Characteristic; Cingulate motor area; Neural network; Sequence; Statistics; Functional; Response; Vertebrata; Area; Mammalia; Neuron; Interspike interval; Distribution; Ensemble; Ornstein Uhlenbeck process; Interval
• ISSN: 0899-7667; 1530-888X
• DOI: 10.1162/089976603322518759

Spike sequences recorded from four cortical areas of an awake behaving monkey were examined to explore characteristics that vary among neurons. We found that a measure of the local variation of interspike intervals, , is nearly the same for every spike sequence for any given neuron, while it varies significantly among neurons. The distributions of values for neuron ensembles in three of the four areas were found to be distinctly bimodal. Two groups of neurons classified according to the spiking irregularity exhibit different responses to the same stimulus. This suggests that neurons in each area can be classified into different groups possessing unique spiking statistics and corresponding functional properties.