Hari M Bharadwaj1, Barbara G Shinn-Cunningham2. 1. Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA 02215, United States; Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States. Electronic address: harimb@bu.edu. 2. Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA 02215, United States; Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States. Electronic address: shinn@cns.bu.edu.
Abstract
OBJECTIVE: Auditory subcortical steady state responses (SSSRs), also known as frequency following responses (FFRs), provide a non-invasive measure of phase-locked neural responses to acoustic and cochlear-induced periodicities. SSSRs have been used both clinically and in basic neurophysiological investigation of auditory function. SSSR data acquisition typically involves thousands of presentations of each stimulus type, sometimes in two polarities, with acquisition times often exceeding an hour per subject. Here, we present a novel approach to reduce the data acquisition times significantly. METHODS: Because the sources of the SSSR are deep compared to the primary noise sources, namely background spontaneous cortical activity, the SSSR varies more smoothly over the scalp than the noise. We exploit this property and extract SSSRs efficiently, using multichannel recordings and an eigendecomposition of the complex cross-channel spectral density matrix. RESULTS: Our proposed method yields SNR improvement exceeding a factor of 3 compared to traditional single-channel methods. CONCLUSIONS: It is possible to reduce data acquisition times for SSSRs significantly with our approach. SIGNIFICANCE: The proposed method allows SSSRs to be recorded for several stimulus conditions within a single session and also makes it possible to acquire both SSSRs and cortical EEG responses without increasing the session length.
OBJECTIVE: Auditory subcortical steady state responses (SSSRs), also known as frequency following responses (FFRs), provide a non-invasive measure of phase-locked neural responses to acoustic and cochlear-induced periodicities. SSSRs have been used both clinically and in basic neurophysiological investigation of auditory function. SSSR data acquisition typically involves thousands of presentations of each stimulus type, sometimes in two polarities, with acquisition times often exceeding an hour per subject. Here, we present a novel approach to reduce the data acquisition times significantly. METHODS: Because the sources of the SSSR are deep compared to the primary noise sources, namely background spontaneous cortical activity, the SSSR varies more smoothly over the scalp than the noise. We exploit this property and extract SSSRs efficiently, using multichannel recordings and an eigendecomposition of the complex cross-channel spectral density matrix. RESULTS: Our proposed method yields SNR improvement exceeding a factor of 3 compared to traditional single-channel methods. CONCLUSIONS: It is possible to reduce data acquisition times for SSSRs significantly with our approach. SIGNIFICANCE: The proposed method allows SSSRs to be recorded for several stimulus conditions within a single session and also makes it possible to acquire both SSSRs and cortical EEG responses without increasing the session length.
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Authors: Hari M Bharadwaj; Salwa Masud; Golbarg Mehraei; Sarah Verhulst; Barbara G Shinn-Cunningham Journal: J Neurosci Date: 2015-02-04 Impact factor: 6.167
Authors: Tiago Zanotelli; Antonio Mauricio Ferreira Leite Miranda de Sá; Eduardo Mazoni Andrade Marçal Mendes; Leonardo Bonato Felix Journal: Med Biol Eng Comput Date: 2019-08-09 Impact factor: 2.602
Authors: Hari M Bharadwaj; Alexandra R Mai; Jennifer M Simpson; Inyong Choi; Michael G Heinz; Barbara G Shinn-Cunningham Journal: Neuroscience Date: 2019-03-08 Impact factor: 3.590
Authors: Hao Lu; Anahita H Mehta; Hari M Bharadwaj; Barbara G Shinn-Cunningham; Andrew J Oxenham Journal: Clin Neurophysiol Date: 2020-06-04 Impact factor: 3.708