Unsupervised neuron spike decoding for macaque's finger position via EM algorithm

Author(s):  
Minglong Xue ◽  
Haifeng Wu ◽  
Yu Zeng ◽  
Yan Li
2011 ◽  
Vol E94-B (2) ◽  
pp. 533-545 ◽  
Author(s):  
Kazushi MURAOKA ◽  
Kazuhiko FUKAWA ◽  
Hiroshi SUZUKI ◽  
Satoshi SUYAMA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jermyn Z. See ◽  
Natsumi Y. Homma ◽  
Craig A. Atencio ◽  
Vikaas S. Sohal ◽  
Christoph E. Schreiner

AbstractNeuronal activity in auditory cortex is often highly synchronous between neighboring neurons. Such coordinated activity is thought to be crucial for information processing. We determined the functional properties of coordinated neuronal ensembles (cNEs) within primary auditory cortical (AI) columns relative to the contributing neurons. Nearly half of AI cNEs showed robust spectro-temporal receptive fields whereas the remaining cNEs showed little or no acoustic feature selectivity. cNEs can therefore capture either specific, time-locked information of spectro-temporal stimulus features or reflect stimulus-unspecific, less-time specific processing aspects. By contrast, we show that individual neurons can represent both of those aspects through membership in multiple cNEs with either high or absent feature selectivity. These associations produce functionally heterogeneous spikes identifiable by instantaneous association with different cNEs. This demonstrates that single neuron spike trains can sequentially convey multiple aspects that contribute to cortical processing, including stimulus-specific and unspecific information.


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