Wavelet correlations

This module performs correlations on a set of wave pairs. The waves represent instances of stimulus/response pairs, and the result is an estimate of the linear transformation ("kernel") between stimulus and response. Two methods are provided: the conventional way of deriving the kernel, by transforming to the frequency domain, multiplying, normalizing, and inverse transforming; and a novel method that uses the wavelet transform to provide time-frequency representations of stimulus and response, then divides response by stimulus, optionally performs median filtering on the amplitude samples across time at each frequency, and averages over time to derive a kernel estimate.

A demonstration of these correlations is provided, along with a help file and a notebook with instructions.

Comments would be appreciated: Alan Saul .

Project Details

Current Project Release

Wavelet correlations IGOR.6.03.x-1.0

Release File: Wavelet Correlator_0.zip
Version: IGOR.6.03.x-1.0
Version Date: Sun, 11/18/2007 - 04:22 pm
Version Major: 1
OS Compatibility: Mac-Intel Windows
Release Notes: This experiment implements reverse correlation following wavelet transformation of stimulus and response data. It reproduces the model figures from a paper in press in Journal of Neuroscience Methods. The method is simple but effective for certain kinds of problems. In particular, nonstationary systems can be analyzed by extensions of this method. For neuronal data that include limited samples with noise, this method can be quite useful.

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