Journal: eLife
Article Title: Hierarchy between forelimb premotor and primary motor cortices and its manifestation in their firing patterns
doi: 10.7554/eLife.103069
Figure Lengend Snippet: ( A ), ( B ) Histograms of waveform widths for recorded neurons in CFA ( A ) and RFA ( B ), showing the bimodal distribution of narrow and wide waveforms. Dotted line shows the threshold above which neurons were considered wide waveform. ( C )-( F ) Histograms of p-values from our modified version of SALT for narrow-waveform neurons recorded in one session ( C,E ) or all sessions ( D,F ) in either CFA ( C,D ) or RFA ( E,F ) while inactivating the other region. The uniformity of these distributions indicates an absence of appreciable violation of the null hypotheses that neurons are not directly activated by light. ( G )-( N ) Mean firing rate ± SEM for wide-waveform ( G–J ) or narrow-waveform ( K–N ) neurons for one animal ( G,I,K,M ) or three animals ( H,J,L,N ) recorded in CFA ( G,H,K,L ) or RFA ( I,J,M,N ) while inactivating the other region. Averages combining cells from multiple animals used the same number of cells from each animal. The cyan rectangle indicates when the light was applied. ( O )-( R ) Mean absolute firing rate change ± SEM between control and inactivation trials ( O,Q ) and mean absolute firing rate difference between control and inactivation trials averaged from 10ms after light/trial onset to 25, 50, or 100ms afterwards ( P,R ) for wide- and narrow-waveform neurons recorded in CFA ( O,P ) or RFA ( Q,R ) during inactivation of the other region. Black bars show mean across animals. ( T )-(AA) Mean firing rate ± SEM for all three animals recorded in CFA ( T,U,X,Y ) or RFA ( V,W,Z,AA ) while inactivating the other region, either for two separate sessions ( T–W ) or the first and second half of trials from all sessions ( X–AA ). The cyan rectangle indicates when the light was applied. Average inactivation effects show remarkable consistency, both within and across sessions.
Article Snippet: From distributions of p-values calculated as described below for each metric, we estimated the fraction of false null hypotheses as one minus an estimate of the a prior i fraction of true null hypotheses ( ) (MATLAB function ‘mafdr’).
Techniques: Modification, Control
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