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Hambrook DA, Tata MS. The effects of distractor set-size on neural tracking of attended speech. BRAIN AND LANGUAGE 2019; 190:1-9. [PMID: 30616147 DOI: 10.1016/j.bandl.2018.12.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 11/19/2018] [Accepted: 12/19/2018] [Indexed: 06/09/2023]
Abstract
Attention is crucial to speech comprehension in real-world, noisy environments. Selective phase-tracking between low-frequency brain dynamics and the envelope of target speech is a proposed mechanism to reject competing distractors. Studies have supported this theory in the case of a single distractor, but have not considered how tracking is systematically affected by varying distractor set sizes. We recorded electroencephalography (EEG) during selective listening to both natural and vocoded speech as distractor set-size varied from two to six voices. Increasing set-size reduced performance and attenuated EEG tracking of target speech. Further, we found that intrusions of distractor speech into perception were not accompanied by sustained tracking of the distractor stream. Our results support the theory that tracking of speech dynamics is a mechanism for selective attention, and that the mechanism of distraction is not simple stimulus-driven capture of sustained entrainment of auditory mechanisms by the acoustics of distracting speech.
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Affiliation(s)
- Dillon A Hambrook
- The University of Lethbridge, 4401 University Drive, Lethbridge, Alberta T1K 3M4, Canada.
| | - Matthew S Tata
- The University of Lethbridge, 4401 University Drive, Lethbridge, Alberta T1K 3M4, Canada
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Analysis of slow (theta) oscillations as a potential temporal reference frame for information coding in sensory cortices. PLoS Comput Biol 2012; 8:e1002717. [PMID: 23071429 PMCID: PMC3469413 DOI: 10.1371/journal.pcbi.1002717] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2012] [Accepted: 08/12/2012] [Indexed: 11/19/2022] Open
Abstract
While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
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Maddox RK, Billimoria CP, Perrone BP, Shinn-Cunningham BG, Sen K. Competing sound sources reveal spatial effects in cortical processing. PLoS Biol 2012; 10:e1001319. [PMID: 22563301 PMCID: PMC3341327 DOI: 10.1371/journal.pbio.1001319] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2011] [Accepted: 03/20/2012] [Indexed: 11/18/2022] Open
Abstract
Why is spatial tuning in auditory cortex weak, even though location is important to object recognition in natural settings? This question continues to vex neuroscientists focused on linking physiological results to auditory perception. Here we show that the spatial locations of simultaneous, competing sound sources dramatically influence how well neural spike trains recorded from the zebra finch field L (an analog of mammalian primary auditory cortex) encode source identity. We find that the location of a birdsong played in quiet has little effect on the fidelity of the neural encoding of the song. However, when the song is presented along with a masker, spatial effects are pronounced. For each spatial configuration, a subset of neurons encodes song identity more robustly than others. As a result, competing sources from different locations dominate responses of different neural subpopulations, helping to separate neural responses into independent representations. These results help elucidate how cortical processing exploits spatial information to provide a substrate for selective spatial auditory attention.
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Affiliation(s)
- Ross K. Maddox
- Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Biodynamics, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
| | - Cyrus P. Billimoria
- Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Biodynamics, Boston University, Boston, Massachusetts, United States of America
| | - Ben P. Perrone
- Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Biodynamics, Boston University, Boston, Massachusetts, United States of America
| | - Barbara G. Shinn-Cunningham
- Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Computational Neuroscience and Neural Technology, Boston University, Boston, Massachusetts, United States of America
| | - Kamal Sen
- Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Biodynamics, Boston University, Boston, Massachusetts, United States of America
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