Profile analysis compares static spectra while texture change detection needs dynamic statistics

Evidence

The present paradigm builds on research from the spectral and the temporal domain, e.g. profile analysis (Green and Berg 1991 ) or some paradigms in mismatch negativity. For example in profile analysis subjects assess the spectral shape of stimuli. In this context it has also been demonstrated that subjects can compare spectra, however, the results were not interpretable in a statistical sense, due to several reasons. First, the time scale of presentation is much longer in the present paradigm than typically in profile analysis, where the stimulus is presented for multiple seconds rather than subsecond presentations. Second, in the present context the stimulus is composed of randomly timed occurrences of tones in certain frequency bins (which defines the spectral profile over time), rather than static profiles from constantly presented tones or filtered noise. Third, the comparison between different profiles is performed dynamically, rather than in a two stimulus comparison task. — Dijk, Pim van, Physiology, Psychoacoustics and…, 3285

Categorization

• DEFINE: Distinguishes profile analysis from dynamic statistical-integration paradigms by three concrete differences.
• XREF: Ties to classic profile-analysis literature (Green and Berg) familiar from psychoacoustics.