Analyses

Some of the major analysis types are documented below. For more information about these or other analyses, contact Wyeth Bair. Analysis types are listed beneath the command (nda or nda_corr) that implements the analysis.

nda
barnoise     White-noise analysis for 1D array of random bars.
bar1ran     Analysis for sparse random bar stimulus.
char_01     Characterize tuning curves: spline fit, peak height and width, and direction and orientation indices.
characterize_lms_sf Compute cone weights from cone-isolating SF tuning curves.
characterize_plaid Characterize responses to a joint plaid and grating stimulus.
choice_prob     Choice probability; computing a decision variable from spike channels.
coverage     Stimulus-response coverage and related maps.
event_interval     Compute the distribution of time between specific events.
event_stat     Compute simple statistical summaries of event times.
f1     F1 (F2, etc.) analysis for temporally periodic signals (spikes and continuous)
fn     compute amplitude and phase at multiple frequencies, for sum-of-sine stimuli.
grid_sta     spike-triggered average for spatial grid white-noise
isi     inter-spike interval
percent_plot     probabilities - e.g. for percent correct curves, psychophysics
plot     plot continuous signals
psth     peri-stimulus time histogram (PSTH), and power spectrum thereof
psth_trig     peri-stimulus time histogram (PSTH) relative to triggers within random stimulus sequences (e.g., 'gabor_britt' stimuli)
param     examine and print trial parameter values
pta     stimulus pattern-triggered average response
pwr     power spectrum
raster     spike times, spike train plots
sc_var     spike count mean and variance
sr     spike rate (and continuous data, partially impl'd)
sta     spike-triggered average
sta_multi     spike-triggered average
tref     analyze trial start time sequence
write_stim_seq write values of a random stimulus sequence to a text file

nda_corr
rsc     spike count correlation coefficient
sr_corr     r_signal for a pair of neurons, i.e., correlation of tuning curves
tcorr     spike count cross-correlation, TAC and TCC
transmit     spike transmission statistics for a pair of neurons
xcorr     cross-correlation, auto-correlation for spikes and continuous data
xcorr_pta     cross-correlation of pattern-triggered responses