scholarly journals Spatial Release from Informational Masking: Evidence from Functional Near Infrared Spectroscopy

2018 ◽  
Author(s):  
Min Zhang ◽  
Antje Ihlefeld

ABSTRACTInformational masking (IM) can greatly reduce speech intelligibility, but the neural mechanisms underlying IM are not understood. Binaural differences between target and masker can improve speech perception. In general, improvement in masked speech intelligibility due to provision of spatial cues is called spatial release from masking. Here, we focused on an aspect of spatial release from masking, specifically, the role of spatial attention. We hypothesized that in a situation with IM background sound 1) attention to speech recruits lateral frontal cortex (LFCx), and 2) LFCx activity varies with direction of spatial attention. Using functional near infrared spectroscopy (fNIRS), we assessed LFCx activity bilaterally in normal-hearing listeners. In experiment 1, two talkers were simultaneously presented. Listeners either attended to the target talker (speech task) or they listened passively to an unintelligible, scrambled version of the acoustic mixture (control task). Target and masker differed in pitch and interaural time difference (ITD). Relative to the passive control, LFCx activity increased during attentive listening. Experiment 2 measured how LFCx activity varied with ITD, by testing listeners on the speech task in experiment 1, except that talkers either were spatially separated by ITD or co-located. Results show that directing of auditory attention activates LFCx bilaterally. Moreover, right LFCx is recruited more strongly in the spatially separated as compared with co-located configurations. Findings hint that LFCx function contributes to spatial release from masking in situations with IM.

2018 ◽  
Vol 370 ◽  
pp. 53-64 ◽  
Author(s):  
Rachael J. Lawrence ◽  
Ian M. Wiggins ◽  
Carly A. Anderson ◽  
Jodie Davies-Thompson ◽  
Douglas E.H. Hartley

Author(s):  
Faizah Mushtaq ◽  
Ian M. Wiggins ◽  
Pádraig T. Kitterick ◽  
Carly A. Anderson ◽  
Douglas E. H. Hartley

AbstractWhilst functional neuroimaging has been used to investigate cortical processing of degraded speech in adults, much less is known about how these signals are processed in children. An enhanced understanding of cortical correlates of poor speech perception in children would be highly valuable to oral communication applications, including hearing devices. We utilised vocoded speech stimuli to investigate brain responses to degraded speech in 29 normally hearing children aged 6–12 years. Intelligibility of the speech stimuli was altered in two ways by (i) reducing the number of spectral channels and (ii) reducing the amplitude modulation depth of the signal. A total of five different noise-vocoded conditions (with zero, partial or high intelligibility) were presented in an event-related format whilst participants underwent functional near-infrared spectroscopy (fNIRS) neuroimaging. Participants completed a word recognition task during imaging, as well as a separate behavioural speech perception assessment. fNIRS recordings revealed statistically significant sensitivity to stimulus intelligibility across several brain regions. More intelligible stimuli elicited stronger responses in temporal regions, predominantly within the left hemisphere, while right inferior parietal regions showed an opposite, negative relationship. Although there was some evidence that partially intelligible stimuli elicited the strongest responses in the left inferior frontal cortex, a region previous studies have suggested is associated with effortful listening in adults, this effect did not reach statistical significance. These results further our understanding of cortical mechanisms underlying successful speech perception in children. Furthermore, fNIRS holds promise as a clinical technique to help assess speech intelligibility in paediatric populations.


Author(s):  
S. Srilekha ◽  
B. Vanathi

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 61-LB
Author(s):  
LISA R. LETOURNEAU-FREIBERG ◽  
KIMBERLY L. MEIDENBAUER ◽  
ANNA M. DENSON ◽  
PERSEPHONE TIAN ◽  
KYOUNG WHAN CHOE ◽  
...  

2019 ◽  
Author(s):  
Shannon Burns ◽  
Matthew D. Lieberman

Social and affective neuroscience studies the neurophysiological underpinnings of psychological experience and behavior as it relates to the world around us. Yet, most neuroimaging methods require the removal of participants from their rich environment and the restriction of meaningful interaction with stimuli. In this Tools of the Trade article, we explain functional near infrared spectroscopy (fNIRS) as a neuroimaging method that can address these concerns. First, we provide an overview of how fNIRS works and how it compares to other neuroimaging methods common in social and affective neuroscience. Next, we describe fNIRS research that highlights its usefulness to the field – when rich stimuli engagement or environment embedding is needed, studies of social interaction, and examples of how it can help the field become more diverse and generalizable across participant populations. Lastly, this article describes how to use fNIRS for neuroimaging research with points of advice that are particularly relevant to social and affective neuroscience studies.


2021 ◽  
Vol 18 ◽  
pp. 100272
Author(s):  
Alexander von Lühmann ◽  
Yilei Zheng ◽  
Antonio Ortega-Martinez ◽  
Swathi Kiran ◽  
David C. Somers ◽  
...  

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