scholarly journals Decision letter: The human auditory brainstem response to running speech reveals a subcortical mechanism for selective attention

2017 ◽  
eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Antonio Elia Forte ◽  
Octave Etard ◽  
Tobias Reichenbach

Humans excel at selectively listening to a target speaker in background noise such as competing voices. While the encoding of speech in the auditory cortex is modulated by selective attention, it remains debated whether such modulation occurs already in subcortical auditory structures. Investigating the contribution of the human brainstem to attention has, in particular, been hindered by the tiny amplitude of the brainstem response. Its measurement normally requires a large number of repetitions of the same short sound stimuli, which may lead to a loss of attention and to neural adaptation. Here we develop a mathematical method to measure the auditory brainstem response to running speech, an acoustic stimulus that does not repeat and that has a high ecological validity. We employ this method to assess the brainstem's activity when a subject listens to one of two competing speakers, and show that the brainstem response is consistently modulated by attention.


NeuroImage ◽  
2019 ◽  
Vol 200 ◽  
pp. 1-11 ◽  
Author(s):  
Octave Etard ◽  
Mikolaj Kegler ◽  
Chananel Braiman ◽  
Antonio Elia Forte ◽  
Tobias Reichenbach

2018 ◽  
Author(s):  
Octave Etard ◽  
Mikolaj Kegler ◽  
Chananel Braiman ◽  
Antonio Elia Forte ◽  
Tobias Reichenbach

AbstractHumans are highly skilled at analysing complex acoustic scenes. The segregation of different acoustic streams and the formation of corresponding neural representations is mostly attributed to the auditory cortex. Decoding of selective attention from neuroimaging has therefore focussed on cortical responses to sound. However, the auditory brainstem response to speech is modulated by selective attention as well, as recently shown through measuring the brainstem’s response to running speech. Although the response of the auditory brainstem has a smaller magnitude than that of the auditory cortex, it occurs at much higher frequencies and therefore has a higher information rate. Here we develop statistical models for extracting the brainstem response from multi-channel scalp recordings and for analysing the attentional modulation according to the focus of attention. We demonstrate that the attentional modulation of the brainstem response to speech can be employed to decode the attentional focus of a listener from short measurements of ten seconds or less in duration. The decoding remains accurate when obtained from three EEG channels only. We further show how out-of-the-box decoding that employs subject-independent models, as well as decoding that is independent of the specific attended speaker is capable of achieving similar accuracy. These results open up new avenues for investigating the neural mechanisms for selective attention in the brainstem and for developing efficient auditory brain-computer interfaces.


2017 ◽  
Author(s):  
Antonio Elia Forte ◽  
Octave Etard ◽  
Tobias Reichenbach

AbstractHumans excel at selectively listening to a target speaker in background noise such as competing voices. While the encoding of speech in the auditory cortex is modulated by selective attention, it remains debated whether such modulation occurs already in subcortical auditory structures. Investigating the contribution of the human brainstem to attention has, in particular, been hindered by the tiny amplitude of the brainstem response. Its measurement normally requires a large number of repetitions of the same short sound stimuli, which may lead to a loss of attention and to neural adaptation. Here we develop a mathematical method to measure the auditory brainstem response to running speech, an acoustic stimulus that does not repeat and that has a high ecological validity. We employ this method to assess the brainstem’s activity when a subject listens to one of two competing speakers, and show that the brainstem response is consistently modulated by attention.


2010 ◽  
Author(s):  
Sara C. Therrien ◽  
Catherine E. Carr ◽  
Elizabeth F. Brittan-Powell ◽  
Alicia M. Wells-Berlin

Sign in / Sign up

Export Citation Format

Share Document