scholarly journals The Effect of GABAA Receptor on Information Capacity of Cultured Hippocampal Neurons

2021 ◽  
Vol 271 ◽  
pp. 03007
Author(s):  
Geng Zhu ◽  
Xiangning Li ◽  
Hui Gong ◽  
Yan Zhu ◽  
Xiaoou Li

Neural information is encoded by action potentials delivered by neurons. Which component of neural activity constitutes the basic unit carrying information is still a controversial issue. In this paper, stimulation experiments using a network of hippocampal neurons cultured on a multi-electrode array are used to investigate this issue. The results show that for a set of pulse stimuli with varying voltage amplitude, the neuronal response to the fronto-potential sequence encodes more information through the moment of fronto-potential delivery than the number of fronto-potential deliveries, and that neurons at each locus are encoded independently of each other. After the addition of bicuculline inhibited the GABAA receptors, the information capacity decreased and the temporal resolution decreased, but the neurons at each site were still encoded independently. The results suggest that the encoding of stimulus amplitude in the cultured hippocampal neuronal network is better with spike timing than with count, and the effect of timing encoding is dependent on GABAA receptors.

2002 ◽  
Vol 87 (4) ◽  
pp. 1749-1762 ◽  
Author(s):  
Shigeto Furukawa ◽  
John C. Middlebrooks

Previous studies have demonstrated that the spike patterns of cortical neurons vary systematically as a function of sound-source location such that the response of a single neuron can signal the location of a sound source throughout 360° of azimuth. The present study examined specific features of spike patterns that might transmit information related to sound-source location. Analysis was based on responses of well-isolated single units recorded from cortical area A2 in α-chloralose-anesthetized cats. Stimuli were 80-ms noise bursts presented from loudspeakers in the horizontal plane; source azimuths ranged through 360° in 20° steps. Spike patterns were averaged across samples of eight trials. A competitive artificial neural network (ANN) identified sound-source locations by recognizing spike patterns; the ANN was trained using the learning vector quantization learning rule. The information about stimulus location that was transmitted by spike patterns was computed from joint stimulus-response probability matrices. Spike patterns were manipulated in various ways to isolate particular features. Full-spike patterns, which contained all spike-count information and spike timing with 100-μs precision, transmitted the most stimulus-related information. Transmitted information was sensitive to disruption of spike timing on a scale of more than ∼4 ms and was reduced by an average of ∼35% when spike-timing information was obliterated entirely. In a condition in which all but the first spike in each pattern were eliminated, transmitted information decreased by an average of only ∼11%. In many cases, that condition showed essentially no loss of transmitted information. Three unidimensional features were extracted from spike patterns. Of those features, spike latency transmitted ∼60% more information than that transmitted either by spike count or by a measure of latency dispersion. Information transmission by spike patterns recorded on single trials was substantially reduced compared with the information transmitted by averages of eight trials. In a comparison of averaged and nonaveraged responses, however, the information transmitted by latencies was reduced by only ∼29%, whereas information transmitted by spike counts was reduced by 79%. Spike counts clearly are sensitive to sound-source location and could transmit information about sound-source locations. Nevertheless, the present results demonstrate that the timing of the first poststimulus spike carries a substantial amount, probably the majority, of the location-related information present in spike patterns. The results indicate that any complete model of the cortical representation of auditory space must incorporate the temporal characteristics of neuronal response patterns.


1994 ◽  
Vol 14 (12) ◽  
pp. 7747-7760 ◽  
Author(s):  
BA Orser ◽  
LY Wang ◽  
PS Pennefather ◽  
JF MacDonald

2011 ◽  
Vol 20 (4) ◽  
pp. 343-350 ◽  
Author(s):  
Yushan Wang ◽  
Lidong Liu ◽  
Tracy Weiss ◽  
Christine Stewart ◽  
John Mikler

2012 ◽  
Vol 108 (8) ◽  
pp. 2101-2114 ◽  
Author(s):  
P. Christiaan Klink ◽  
Anna Oleksiak ◽  
Martin J. M. Lankheet ◽  
Richard J. A. van Wezel

Repeated stimulation impacts neuronal responses. Here we show how response characteristics of sensory neurons in macaque visual cortex are influenced by the duration of the interruptions during intermittent stimulus presentation. Besides effects on response magnitude consistent with neuronal adaptation, the response variability was also systematically influenced. Spike rate variability in motion-sensitive area MT decreased when interruption durations were systematically increased from 250 to 2,000 ms. Activity fluctuations between subsequent trials and Fano factors over full response sequences were both lower with longer interruptions, while spike timing patterns became more regular. These variability changes partially depended on the response magnitude, but another significant effect that was uncorrelated with adaptation-induced changes in response magnitude was also present. Reduced response variability was furthermore accompanied by changes in spike-field coherence, pointing to the possibility that reduced spiking variability results from interactions in the local cortical network. While neuronal response stabilization may be a general effect of repeated sensory stimulation, we discuss its potential link with the phenomenon of perceptual stabilization of ambiguous stimuli as a result of interrupted presentation.


Neuron ◽  
2017 ◽  
Vol 94 (5) ◽  
pp. 954-960 ◽  
Author(s):  
Tatyana O. Sharpee

Author(s):  
I. Khalilov ◽  
X. Leinekugel ◽  
M. Mukhtarov ◽  
R. Khazipov

2003 ◽  
Vol 63 (1) ◽  
pp. 2-8 ◽  
Author(s):  
Jacky Y. T. Yeung ◽  
Kevin J. Canning ◽  
Guoyun Zhu ◽  
Peter Pennefather ◽  
John F. MacDonald ◽  
...  

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