Command: correlospinmatrix_detector

Description

The correlospinmatrix_detector is a recording device. It is used to record

correlations

from binary neurons from several binary sources and calculates the raw auto and cross correlation

binned to bins of duration delta_tau.

The result can be obtained via GetStatus under the key /count_covariance.

The result is a tensor of rank 3 of size N_channels x N_channels with each entry C_ij being a

vector of

size 2*tau_max/delta_tau + 1 containing the histogram for the different time lags.

The bins are centered around the time difference they represent and are left-closed

and right-open in the lower triangular part of the matrix. On the diagonal and in the upper

triangular part the intervals are left-open and right-closed. This ensures proper counting

of events at the border of bins.

The correlospinmatrix_detector has a variable number of inputs which can be set via SetStatus

under the key N_channels. All incoming connections to a specified receptor will be pooled.

Tstart double - Time when to start counting events. This time should be set to at least

start + tau_max in order to avoid edge effects of the correlation counts.

Tstop double - Time when to stop counting events. This time should be set to at most

Tsim - tau_max where Tsim is the duration of simulation

in order to avoid edge effects of the correlation counts.

delta_tau double - bin width in ms. This has to be a multiple of the resolution.

tau_max double - one-sided width in ms. In the lower triangular part events with

differences in

[0 tau_max+delta_tau/2) are counted. On the diagonal and in

the upper triangular part events with differences in (0

tau_max+delta_tau/2]

N_channels long - The number of inputs to correlate. This defines the range of

receptor_type. Default is

1.

count_covariance matrix of long vectors read-only - raw auto/cross correlation counts

correlations

from binary neurons from several binary sources and calculates the raw auto and cross correlation

binned to bins of duration delta_tau.

The result can be obtained via GetStatus under the key /count_covariance.

The result is a tensor of rank 3 of size N_channels x N_channels with each entry C_ij being a

vector of

size 2*tau_max/delta_tau + 1 containing the histogram for the different time lags.

The bins are centered around the time difference they represent and are left-closed

and right-open in the lower triangular part of the matrix. On the diagonal and in the upper

triangular part the intervals are left-open and right-closed. This ensures proper counting

of events at the border of bins.

The correlospinmatrix_detector has a variable number of inputs which can be set via SetStatus

under the key N_channels. All incoming connections to a specified receptor will be pooled.

Parameters

Tstart double - Time when to start counting events. This time should be set to at least

start + tau_max in order to avoid edge effects of the correlation counts.

Tstop double - Time when to stop counting events. This time should be set to at most

Tsim - tau_max where Tsim is the duration of simulation

in order to avoid edge effects of the correlation counts.

delta_tau double - bin width in ms. This has to be a multiple of the resolution.

tau_max double - one-sided width in ms. In the lower triangular part events with

differences in

[0 tau_max+delta_tau/2) are counted. On the diagonal and in

the upper triangular part events with differences in (0

tau_max+delta_tau/2]

N_channels long - The number of inputs to correlate. This defines the range of

receptor_type. Default is

1.

count_covariance matrix of long vectors read-only - raw auto/cross correlation counts

Author

Moritz Helias

Receives

SpikeEvent

File

models/correlospinmatrix_detector.h

Remarks

This recorder does not record to file
screen or memory in the usual sense. The result

must be obtained by a call to GetStatus. Setting either N_channels Tstart Tstop tau_max or

delta_tau clears count_covariance.

Example:

See also pynest/examples/correlospinmatrix_detector_two_neuron.py

for a script reproducing a setting studied in Fig 1 of Grinzburg & Sompolinsky (1994) PRE 50(4)

p. 3171.

See also examples/nest/correlospinmatrix_detector.sli for a basic

example in sli.

/sg1 /spike_generator Create def

/sg2 /spike_generator Create def

/sg3 /spike_generator Create def

/csd /correlospinmatrix_detector Create def

csd << /N_channels 3 /tau_max 10. /delta_tau 1.0 >> SetStatus

sg1 << /spike_times [10. 10. 16.] >> SetStatus

sg2 << /spike_times [15. 15. 20.] >> SetStatus

% one final event needed so that last down transition will be detected

sg3 << /spike_times [25.] >> SetStatus

sg1 csd << /receptor_type 0 >> Connect

sg2 csd << /receptor_type 1 >> Connect

sg3 csd << /receptor_type 2 >> Connect

100. Simulate

must be obtained by a call to GetStatus. Setting either N_channels Tstart Tstop tau_max or

delta_tau clears count_covariance.

Example:

See also pynest/examples/correlospinmatrix_detector_two_neuron.py

for a script reproducing a setting studied in Fig 1 of Grinzburg & Sompolinsky (1994) PRE 50(4)

p. 3171.

See also examples/nest/correlospinmatrix_detector.sli for a basic

example in sli.

/sg1 /spike_generator Create def

/sg2 /spike_generator Create def

/sg3 /spike_generator Create def

/csd /correlospinmatrix_detector Create def

csd << /N_channels 3 /tau_max 10. /delta_tau 1.0 >> SetStatus

sg1 << /spike_times [10. 10. 16.] >> SetStatus

sg2 << /spike_times [15. 15. 20.] >> SetStatus

% one final event needed so that last down transition will be detected

sg3 << /spike_times [25.] >> SetStatus

sg1 csd << /receptor_type 0 >> Connect

sg2 csd << /receptor_type 1 >> Connect

sg3 csd << /receptor_type 2 >> Connect

100. Simulate

FirstVersion

2015/08/25

Availability