| ObjectiveWorking memory in brain is coded by different modal neural signals and same modal neural signals in different brain areas collaboratively. The study developed and applied time-varying spectrum coherence of LFPs-Spikes based on two types of multi-channel neural singals:local field potentials and discrete spikes, which acquired on prefrontal cortex of rats during working memory task in vivo. The collaborative coding pattern provides neural computation support for analyzing the neural coding mechanisms of working memory.Methods1. Experimental data, which come from our laboratory, were 16-channel neural signals on prefrontal cortex of rats during working memory task based on multi channel recording technology on awake animals in vivo.2. Methods on multi-channel time-varying spectrum coherence:(1) Time-varying spectrum coherence distribution of 16-channel LFPs16-channel LFPs were acquired through lowpass filtering the original data (0-300Hz). Local linear regression based on the weighted least square method was used to remove the baseline drift and power-line interference on LFPs.Power spectral density (PSD) on each channel LFP was performed respectively for characteristic theta band of LFPs. After choosing the reference channel LFP which had the largest PSD value, time-varying spectrum coherence dynamic distribution was available between each channel LFP and reference channel LFP with 50-ms multi-taper window sliding and 25% overlap, and the theta band of LFPs as well.(2) Time varying spectrum coherence of 25-neuron action potential time-space series.16-channel highpass signals were acquired through highpass filtering the original data (≥300Hz). Spikes, or multi-unit, were recognized above -65μV thresholds and 3.0 SNR.25-neuron action potential time-space series were got through sorting the 14-channel valid spikes by Offline Sorter software (Plexon, USA).PSD on each neuron firing rate was performed for characteristic theta band respectively. After choosing the reference neuron which had the largest PSD, time-varying spectrum coherence dynamic distribution was available with 50 ms multi-taper window sliding and 25% overlap.(3) Time-varying spectrum coherence distribution of 14-channel LFPs-Spikes14-channel LFPs-Spikes were matched between 14-channel LFPs and 14-channel spikes. Time-varying spectrum coherence dynamic distribution was available with 50 ms multi-taper window sliding and 25% overlap.PSD on each channel LFP and spike can be obtained through calculating firing rate for charactisric theta band, whose time-varying coherence distribution was computed as above methods.Results1.16-channel LFPs time-varying coherence pattern(1) PSD peak frequency:(8.45±2.46) Hz, occupied for (48.89±3.05) percents among all frequency band (0-120Hz);(2) Average coherence at the onset of working memory event±1s in repeated tests:①Theta band of LFPs:0.2404±0.0102 and 0.7825±0.0104, P<0.05;②All frequency band of LFPs:0.3913±0.0189 and 0.4729±0.0178, P>0.05;③Other band such as delta of LFPs:0.2113±0.0140 and 0.2621±0.0121,P>0.05.2.25-neuron action potential time-space series time-varying coherence pattern(1) PSD peak frequency:(8.25±3.12) Hz, occupied for (60.03±6.98) percents among all frequency band (0-120Hz);(2) Average coherence at the onset of working memory event±1s in repeated tests:①Theta band of series:0.1952±0.0064 and 0.7357±0.0083, P<0.05;②Average firing rate:0.2711±0.0046 and0.3265±0.0038,P>0.05.3.14-channel LFPs-Spikes time-varying coherence pattern(1) PSD peak frequency:(7.86±2.74) Hz for LFPs, (8.26±1.64) Hz for spikes, occupied for (46.21±4.07) percents among all frequency band (0-120Hz);(2) Average coherence at the onset of working memory event±1s in repeated tests:①Theta band of series:0.2222±0.0108 and 0.7786±0.0129, P<0.05;②All frequency band of LFPs-Spikes:0.2987±0.0077 and 0.3332±0.0088,P>0.05. ConclusionsThis paper aimed at time-varying spectrum coherence encoding among 16-channel LFPs,25-neuron action potentials time-space series and 14-channel LFPs-Spikes, and the conclusions as follows:1.16-channel LFPs and its theta band component(1) Theta band of LFPs is the characteristic band during working memory of rats, whose time-varying spectrum coherence encodes the working memory event effectively:the coherence value after event is better to the one before event significantly.(2) All frequency band of LFPs coherence doesn't encode the working memory event, and other band such as delta of LFPs is lower than the former.2.25-neuron action potential time-space series and its theta band component(1) Time-varying spectrum coherence on theta band of action potential time-space series firing rate encodes the working memory event effectively:the coherence value after event is better to the one before event significantly.(2) Average firing rate of series coherence doesn't encode the working memory event.3.14-channel LFPs-Spikes and its theta band component(1) Time-varying spectrum coherence on theta band of LFPs-Spikes encodes the working memory event effectively:the coherence value after event is better to the one before event significantly.(2) All frequency band of LFPs-Spikes coherence doesn't encode the working memory event.
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