Detection and quantification of a wide range of fMRI temporal responses using a physiologically‐motivated basis set

Abstract

The temporal dynamics of fMRI responses can span a broad range, indicating a rich underlying physiology, but also posing a significant challenge for detection. For instance, in human auditory cortex, prolonged sound stimuli (∼30 sec) can evoke responses ranging from sustained to highly phasic (i.e., characterized by prominent peaks just after sound onset and offset). In the present study, we developed a method capable of detecting a wide variety of responses, while simultaneously extracting information about individual response components, which may have different neurophysiological underpinnings. Specifically, we implemented the general linear model using a novel set of basis functions chosen to reflect temporal features of cortical fMRI responses. This physiologically-motivated basis set (the "OSORU" basis set) was tested against (1) the commonly employed "sustained-only" basis "set" (i.e., a single smoothed "boxcar" function), and (2) a sinusoidal basis set, which is capable of detecting a broad range of responses, but lacks a direct relationship to individual response components. On data that included many different temporal responses, the OSORU basis set performed far better overall than the sustained-only set, and as well or better than the sinusoidal basis set. The OSORU basis set also proved effective in exploring brain physiology. As an example, we demonstrate that the OSORU basis functions can be used to spatially map the relative amount of transient vs. sustained activity within auditory cortex. The OSORU basis set provides a powerful means for response detection and quantification that should be broadly applicable to any brain system and to both human and non-human species.

Human Cortical Activity during Streaming without Spectral Cues Suggests a General Neural Substrate for Auditory Stream Segregation

“…fMRI activation was detected using a multivariate, linear regression analysis and published basis functions (Harms and Melcher, 2003). Activation maps were derived by contrasting the four ⌬f 0 conditions (collectively) with the noise-masker baseline.…”

The role of auditory cortex in the formation of auditory streams

“…Using a generalized linear model, they fitted basis functions to the data (Harms and Melcher, 2003) and quantified the time course of activation using a summary "waveshape index" (Harms and Melcher, 2003) comprised between 0 (indicating highly sustained or "boxcar" activation) and 1 (indicating a completely phasic activation pattern consisting only of peaks following the onset and offset of the sequence, with no sustained activity in-between). They found that as frequency separation increased, the activation generally became more sustained (i.e., less phasic).…”

Effects of sound level on fMRI activation in human brainstem, thalamic and cortical centers

“…Activation was then detected using a general linear model which operated on a set of basis functions designed to reflect different temporal components of fMRI activation in the auditory system (Harms and Melcher, 2003). This approach models the signal vs. time within each voxel as a weighted sum of basis functions, and identifies "active" voxels based on the goodness of fit of this model.…”

“…The WI, calculated from the basis function amplitudes, describes responses on a continuum from completely sustained (WI = 0) to completely phasic (WI = 1) (details in Harms and Melcher, 2003).…”