neurotools.obsolete.opto module

Routines specific to working with Optogenetics datasets from the Donoghue lab. These routines have yet to be ported to make them general. This module refers to and depends on unpublished data.

You’ll need to set the opto_dataset path variable to the location of TOMMY_MI_121101_full_trial_continuous_square_pulse_6mW001.mat.

neurotools.obsolete.opto.opto_get_events_passive(opto_dataset)

neurotools.obsolete.opto.opto_get_all_lfp_quick(opto_dataset)

neurotools.obsolete.opto.opto_get_map(opto_dataset)

neurotools.obsolete.opto.opto_get_laser(opto_dataset)

neurotools.obsolete.opto.opto_get_lfp(opto_dataset, channel)

Retrieves channel or channels from opto LFP dataset Channels are 1-indexed

Parameters:

• opto_dataset (string) – path or string identifier for a dataset

• channel – 1-indexed channel ID or None to return a NTIMES×NCHANNEL array of all LFP data

neurotools.obsolete.opto.opto_get_lfp_filtered(opto_dataset, channel, fa, fb, order=4)

Retrieves channel or channels from opto LFP dataset Channels are 1-indexed

Parameters:

• opto_dataset (string) – path or string identifier for a dataset

• channel – 1-indexed channel ID or None to return a NTimes×NChannel array of all LFP data

• fa – low frequency of band-pass, or ‘None’ to use a low-pass filter. if fb is ‘None’ then this is the cutoff for a high-pass filter.

• fb – high-frequency of band-pass, or ‘None to use a high-pass filter. if fa is ‘None’ then this is the cutoff for a low-pass filter

neurotools.obsolete.opto.opto_get_all_lfp_analytic_quick(opto_dataset, fa, fb)

Parameters:

• opto_dataset (string) – path or string identifier for a dataset

• fa – low frequency of band-pass, or ‘None’ to use a low-pass filter. if fb is ‘None’ then this is the cutoff for a high-pass filter.

• fb – high-frequency of band-pass, or ‘None to use a high-pass filter. if fa is ‘None’ then this is the cutoff for a low-pass filter

neurotools.obsolete.opto.opto_get_all_lfp_analytic_quick_parallel(opto_dataset, fa, fb)

Example:

Fs = 1000.0
order = 4
data = metaloadmat(opto_dataset+'_compact')['lfp']
data = data.transpose((0,2,1))
data = squeeze(parmap(
    __opto_get_all_lfp_analytic_quick_parallel_helper__,
    None)
data = bandfilter(hilbert(data),fa,fb,Fs,order)
return data

neurotools.obsolete.opto.opto_get_lfp_analytic(opto_dataset, channel, fa, fb, order=4)

Retrieves channel or channels from opto LFP dataset Channels are 1-indexed

Parameters:

• opto_dataset (string) – path or string identifier for a dataset

• channel – 1-indexed channel ID or None to return a NTIMES×NCHANNEL array of all LFP data

• fa – low frequency of band-pass, or ‘None’ to use a low-pass filter. if fb is ‘None’ then this is the cutoff for a high-pass filter.

• fb – high-frequency of band-pass, or ‘None to use a high-pass filter. if fa is ‘None’ then this is the cutoff for a low-pass filter

neurotools.obsolete.opto.opto_get_Fs(opto_dataset)