Selective attention increases both gain and feature selectivity of the human auditory cortex.
BACKGROUND
An experienced car mechanic can often deduce what's wrong with a car by carefully listening to the sound of the ailing engine, despite the presence of multiple sources of noise. Indeed, the ability to select task-relevant sounds for awareness, whilst ignoring irrelevant ones, constitutes one of the most fundamental of human faculties, but the underlying neural mechanisms have remained elusive. While most of the literature explains the neural basis of selective attention by means of an increase in neural gain, a number of papers propose enhancement in neural selectivity as an alternative or a complementary mechanism.


RESULTS
Here, to address the question whether pure gain increase alone can explain auditory selective attention in humans, we quantified the auditory cortex frequency selectivity in 20 healthy subjects by masking 1000-Hz tones by continuous noise masker with parametrically varying frequency notches around the tone frequency (i.e., a notched-noise masker). The task of the subjects was, in different conditions, to selectively attend to either occasionally occurring slight increments in tone frequency (1020 Hz), tones of slightly longer duration, or ignore the sounds. In line with previous studies, in the ignore condition, the global field power (GFP) of event-related brain responses at 100 ms from the stimulus onset to the 1000-Hz tones was suppressed as a function of the narrowing of the notch width. During the selective attention conditions, the suppressant effect of the noise notch width on GFP was decreased, but as a function significantly different from a multiplicative one expected on the basis of simple gain model of selective attention.


CONCLUSIONS
Our results suggest that auditory selective attention in humans cannot be explained by a gain model, where only the neural activity level is increased, but rather that selective attention additionally enhances auditory cortex frequency selectivity.
Kauramäki
Jaakko
J
Laboratory of Computational Engineering, Helsinki University of Technology, Espoo, Finland. Jaakko.Kauramaki@tkk.fi
Jääskeläinen
Iiro P
IP
Sams
Mikko
M
D001288:Attention; D001303:Auditory Cortex / Q000502:physiology*; D005071:Evoked Potentials; D006801:Humans