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Xie Y, Oniga S. A Comprehensive Review of Hardware Acceleration Techniques and Convolutional Neural Networks for EEG Signals. SENSORS (BASEL, SWITZERLAND) 2024; 24:5813. [PMID: 39275725 PMCID: PMC11397884 DOI: 10.3390/s24175813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 09/03/2024] [Accepted: 09/04/2024] [Indexed: 09/16/2024]
Abstract
This paper comprehensively reviews hardware acceleration techniques and the deployment of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals across various application areas, including emotion classification, motor imagery, epilepsy detection, and sleep monitoring. Previous reviews on EEG have mainly focused on software solutions. However, these reviews often overlook key challenges associated with hardware implementation, such as scenarios that require a small size, low power, high security, and high accuracy. This paper discusses the challenges and opportunities of hardware acceleration for wearable EEG devices by focusing on these aspects. Specifically, this review classifies EEG signal features into five groups and discusses hardware implementation solutions for each category in detail, providing insights into the most suitable hardware acceleration strategies for various application scenarios. In addition, it explores the complexity of efficient CNN architectures for EEG signals, including techniques such as pruning, quantization, tensor decomposition, knowledge distillation, and neural architecture search. To the best of our knowledge, this is the first systematic review that combines CNN hardware solutions with EEG signal processing. By providing a comprehensive analysis of current challenges and a roadmap for future research, this paper provides a new perspective on the ongoing development of hardware-accelerated EEG systems.
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Affiliation(s)
- Yu Xie
- Faculty of Informatics, University of Debrecen, 4032 Debrecen, Hungary
| | - Stefan Oniga
- Faculty of Informatics, University of Debrecen, 4032 Debrecen, Hungary
- North University Center of Baia Mare, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
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2
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Bowers A, Hudock D. Lower nonword syllable sequence repetition accuracy in adults who stutter is related to differences in audio-motor oscillations. Neuropsychologia 2024; 199:108906. [PMID: 38740180 DOI: 10.1016/j.neuropsychologia.2024.108906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 03/05/2024] [Accepted: 05/06/2024] [Indexed: 05/16/2024]
Abstract
OBJECTIVE The goal of this study was to use independent component analysis (ICA) of high-density electroencephalography (EEG) to investigate whether differences in audio-motor neural oscillations are related to nonword syllable repetition accuracy in a group of adults who stutter compared to typically fluent speakers. METHODS EEG was recorded using 128 channels from 23 typically fluent speakers and 23 adults who stutter matched for age, sex, and handedness. EEG was recorded during delayed, 2 and 4 bilabial nonword syllable repetition conditions. Scalp-topography, dipole source estimates, and power spectral density (PSD) were computed for each independent component (IC) and used to cluster similar ICs across participants. Event-related spectral perturbations (ERSPs) were computed for each IC cluster to examine changes over time in the repetition conditions and to examine how dynamic changes in ERSPs are related to syllable repetition accuracy. RESULTS Findings indicated significantly lower accuracy on a measure of percentage correct trials in the AWS group and for a normalized measure of syllable load performance across conditions. Analysis of ERSPs revealed significantly lower alpha/beta ERD in left and right μ ICs and in left and right posterior temporal lobe α ICs in AWS compared to TFS (CC p < 0.05). Pearson correlations with %CT for frequency across time showed strong relationships with accuracy (FWE<0.05) during maintenance in the TFS group and during execution in the AWS group. CONCLUSIONS Findings implicate lower alpha/beta ERD (8-30 Hz) during syllable encoding over posterior temporal ICs and execution in left temporal/sensorimotor components. Strong correlations with accuracy and interindividual differences in ∼6-8 Hz ERSPs during execution implicate differences in motor and auditory-sensory monitoring during syllable sequence execution in AWS.
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Affiliation(s)
- Andrew Bowers
- University of Arkansas, 275 Epley Center, 606 North Razorback Rd. Fayetteville AR, 72701, United States.
| | - Daniel Hudock
- Idaho State University, 921 S. 8th Ave, Mailstop 8116, Pocatello, ID 83209, United States
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3
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Chizhikova AA. [Electroencephalography: features of the obtained data and its applicability in psychiatry]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:31-39. [PMID: 38884427 DOI: 10.17116/jnevro202412405131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Presently, there is an increased interest in expanding the range of diagnostic and scientific applications of electroencephalography (EEG). The method is attractive due to non-invasiveness, availability of equipment with a wide range of modifications for various purposes, and the ability to track the dynamics of brain electrical activity directly and with high temporal resolution. Spectral, coherency and other types of analysis provide volumetric information about its power, frequency distribution, spatial organization of signal and its self-similarity in dynamics or in different sections at a time. The development of computing technologies provides processing of volumetric data obtained using EEG and a qualitatively new level of their analysis using various mathematical models. This review discusses benefits and limitations of using the EEG in scientific research, currently known interpretation of the obtained data and its physiological and pathological correlates. It is expected to determine the complex relationship between the parameters of brain electrical activity and various functional and pathological conditions. The possibility of using EEG characteristics as biomarkers of various physiological and pathological conditions is being considered. Electronic databases, including MEDLINE (on PubMed), Google Scholar and Russian Scientific Citation Index (RSCI, on elibrary.ru), scientific journals and books were searched to find relevant studies.
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Affiliation(s)
- A A Chizhikova
- Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency, Moscow, Russia
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Caruso VC, Wray AH, Lescht E, Chang SE. Neural oscillatory activity and connectivity in children who stutter during a non-speech motor task. J Neurodev Disord 2023; 15:40. [PMID: 37964200 PMCID: PMC10647051 DOI: 10.1186/s11689-023-09507-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 10/25/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Neural motor control rests on the dynamic interaction of cortical and subcortical regions, which is reflected in the modulation of oscillatory activity and connectivity in multiple frequency bands. Motor control is thought to be compromised in developmental stuttering, particularly involving circuits in the left hemisphere that support speech, movement initiation, and timing control. However, to date, evidence comes from adult studies, with a limited understanding of motor processes in childhood, closer to the onset of stuttering. METHODS We investigated the neural control of movement initiation in children who stutter and children who do not stutter by evaluating transient changes in EEG oscillatory activity (power, phase locking to button press) and connectivity (phase synchronization) during a simple button press motor task. We compared temporal changes in these oscillatory dynamics between the left and right hemispheres and between children who stutter and children who do not stutter, using mixed-model analysis of variance. RESULTS We found reduced modulation of left hemisphere oscillatory power, phase locking to button press and phase connectivity in children who stutter compared to children who do not stutter, consistent with previous findings of dysfunction within the left sensorimotor circuits. Interhemispheric connectivity was weaker at lower frequencies (delta, theta) and stronger in the beta band in children who stutter than in children who do not stutter. CONCLUSIONS Taken together, these findings indicate weaker engagement of the contralateral left motor network in children who stutter even during low-demand non-speech tasks, and suggest that the right hemisphere might be recruited to support sensorimotor processing in childhood stuttering. Differences in oscillatory dynamics occurred despite comparable task performance between groups, indicating that an altered balance of cortical activity might be a core aspect of stuttering, observable during normal motor behavior.
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Affiliation(s)
- Valeria C Caruso
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
| | - Amanda Hampton Wray
- Department of Communication Science & Disorders, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erica Lescht
- Department of Communication Science & Disorders, University of Pittsburgh, Pittsburgh, PA, USA
| | - Soo-Eun Chang
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
- Department of Communication Disorders, Ewha Womans University, Seoul, South Korea
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5
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Sarmukadam K, Behroozmand R. Neural oscillations reveal disrupted functional connectivity associated with impaired speech auditory feedback control in post-stroke aphasia. Cortex 2023; 166:258-274. [PMID: 37437320 PMCID: PMC10527672 DOI: 10.1016/j.cortex.2023.05.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/11/2023] [Accepted: 05/24/2023] [Indexed: 07/14/2023]
Abstract
The oscillatory brain activities reflect neuro-computational processes that are critical for speech production and sensorimotor control. In the present study, we used neural oscillations in left-hemisphere stroke survivors with aphasia as a model to investigate network-level functional connectivity deficits associated with disrupted speech auditory feedback control. Electroencephalography signals were recorded from 40 post-stroke aphasia and 39 neurologically intact control participants while they performed speech vowel production and listening tasks under pitch-shifted altered auditory feedback (AAF) conditions. Using weighted phase-lag index, we calculated broadband (1-70 Hz) functional neural connectivity between electrode pairs covering the frontal, pre- and post-central, and parietal regions. Results revealed reduced fronto-central delta and theta band and centro-parietal low-beta band connectivity in left-hemisphere electrodes associated with diminished speech AAF compensation responses in post-stroke aphasia compared with controls. Lesion-mapping analysis demonstrated that stroke-induced damage to multi-modal brain networks within the inferior frontal gyrus, Rolandic operculum, inferior parietal lobule, angular gyrus, and supramarginal gyrus predicted the reduced functional neural connectivity within the delta and low-beta bands during both tasks in aphasia. These results provide evidence that disrupted neural connectivity due to left-hemisphere brain damage can result in network-wide dysfunctions associated with impaired sensorimotor integration mechanisms for speech auditory feedback control.
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Affiliation(s)
- Kimaya Sarmukadam
- Speech Neuroscience Lab, Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
| | - Roozbeh Behroozmand
- Speech Neuroscience Lab, Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
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Behroozmand R, Sarmukadam K, Fridriksson J. Aberrant modulation of broadband neural oscillations reflects vocal sensorimotor deficits in post-stroke aphasia. Clin Neurophysiol 2023; 149:100-112. [PMID: 36934601 PMCID: PMC10101924 DOI: 10.1016/j.clinph.2023.02.176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/11/2023]
Abstract
OBJECTIVE The present study investigated the neural oscillatory correlates of impaired vocal sensorimotor control in left-hemisphere stroke. METHODS Electroencephalography (EEG) signals were recorded from 34 stroke and 46 control subjects during speech vowel vocalization and listening tasks under normal and pitch-shifted auditory feedback. RESULTS Time-frequency analyses revealed aberrantly decreased theta (4-8 Hz) and increased gamma band (30-80 Hz) power in frontal and posterior parieto-occipital regions as well as reduced alpha (8-13 Hz) and beta (13-30 Hz) desynchronization over sensorimotor areas before speech vowel vocalization in left-hemisphere stroke compared with controls. Subjects with the stroke also presented with aberrant modulation of broadband (4-80 Hz) neural oscillations over sensorimotor regions after speech vowel onset during vocalization and listening under normal and altered auditory feedback. We found that the atypical pattern of broadband neural oscillatory modulation was correlated with diminished vocal feedback error compensation behavior and the severity of co-existing language-related aphasia symptoms associated with left-hemisphere stroke. CONCLUSIONS These findings indicate complex interplays between the underlying mechanisms of speech and language and their deficits in post-stroke aphasia. SIGNIFICANCE Our data motivate the notion of studying neural oscillatory dynamics as a critical component for the examination of speech and language disorders in post-stroke aphasia.
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Affiliation(s)
- Roozbeh Behroozmand
- Speech Neuroscience Lab, Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC 29208, USA.
| | - Kimaya Sarmukadam
- Speech Neuroscience Lab, Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC 29208, USA
| | - Julius Fridriksson
- The Aphasia Lab, Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, 915 Greene St, Columbia, SC 29208, USA; Center for the Study of Aphasia Recovery (C-STAR), Arnold School of Public Health, University of South Carolina, 915 Greene St, Columbia, SC 29208, USA
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Gastaldon S, Busan P, Arcara G, Peressotti F. Inefficient speech-motor control affects predictive speech comprehension: atypical electrophysiological correlates in stuttering. Cereb Cortex 2023:6995383. [PMID: 36682885 DOI: 10.1093/cercor/bhad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/24/2023] Open
Abstract
Listeners predict upcoming information during language comprehension. However, how this ability is implemented is still largely unknown. Here, we tested the hypothesis proposing that language production mechanisms have a role in prediction. We studied 2 electroencephalographic correlates of predictability during speech comprehension-pre-target alpha-beta (8-30 Hz) power decrease and the post-target N400 event-related potential effect-in a population with impaired speech-motor control, i.e. adults who stutter (AWS), compared to typically fluent adults (TFA). Participants listened to sentences that could either constrain towards a target word or not, modulating its predictability. As a complementary task, participants also performed context-driven word production. Compared to TFA, AWS not only displayed atypical neural responses in production, but, critically, they showed a different pattern also in comprehension. Specifically, while TFA showed the expected pre-target power decrease, AWS showed a power increase in frontal regions, associated with speech-motor control. In addition, the post-target N400 effect was reduced for AWS with respect to TFA. Finally, we found that production and comprehension power changes were positively correlated in TFA, but not in AWS. Overall, the results support the idea that processes and neural structures prominently devoted to speech planning also support prediction during speech comprehension.
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Affiliation(s)
- Simone Gastaldon
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Via Venezia 8, Padova (PD) 35131, Italy.,Padova Neuroscience Center (PNC), University of Padova, Via Giuseppe Orus 2/B, Padova (PD) 35131, Italy
| | - Pierpaolo Busan
- IRCCS Ospedale San Camillo, Via Alberoni 70, Lido (VE) 30126, Italy
| | - Giorgio Arcara
- IRCCS Ospedale San Camillo, Via Alberoni 70, Lido (VE) 30126, Italy
| | - Francesca Peressotti
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Via Venezia 8, Padova (PD) 35131, Italy.,Padova Neuroscience Center (PNC), University of Padova, Via Giuseppe Orus 2/B, Padova (PD) 35131, Italy.,Centro Interdipartimentale di Ricerca "I-APPROVE-International Auditory Processing Project in Venice", University of Padova, Via Belzoni 160, Padova (PD) 35121, Italy
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Dynamic auditory contributions to error detection revealed in the discrimination of Same and Different syllable pairs. Neuropsychologia 2022; 176:108388. [PMID: 36183800 DOI: 10.1016/j.neuropsychologia.2022.108388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 09/20/2022] [Accepted: 09/27/2022] [Indexed: 11/22/2022]
Abstract
During speech production auditory regions operate in concert with the anterior dorsal stream to facilitate online error detection. As the dorsal stream also is known to activate in speech perception, the purpose of the current study was to probe the role of auditory regions in error detection during auditory discrimination tasks as stimuli are encoded and maintained in working memory. A priori assumptions are that sensory mismatch (i.e., error) occurs during the discrimination of Different (mismatched) but not Same (matched) syllable pairs. Independent component analysis was applied to raw EEG data recorded from 42 participants to identify bilateral auditory alpha rhythms, which were decomposed across time and frequency to reveal robust patterns of event related synchronization (ERS; inhibition) and desynchronization (ERD; processing) over the time course of discrimination events. Results were characterized by bilateral peri-stimulus alpha ERD transitioning to alpha ERS in the late trial epoch, with ERD interpreted as evidence of working memory encoding via Analysis by Synthesis and ERS considered evidence of speech-induced-suppression arising during covert articulatory rehearsal to facilitate working memory maintenance. The transition from ERD to ERS occurred later in the left hemisphere in Different trials than in Same trials, with ERD and ERS temporally overlapping during the early post-stimulus window. Results were interpreted to suggest that the sensory mismatch (i.e., error) arising from the comparison of the first and second syllable elicits further processing in the left hemisphere to support working memory encoding and maintenance. Results are consistent with auditory contributions to error detection during both encoding and maintenance stages of working memory, with encoding stage error detection associated with stimulus concordance and maintenance stage error detection associated with task-specific retention demands.
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Ross JM, Balasubramaniam R. Time Perception for Musical Rhythms: Sensorimotor Perspectives on Entrainment, Simulation, and Prediction. Front Integr Neurosci 2022; 16:916220. [PMID: 35865808 PMCID: PMC9294366 DOI: 10.3389/fnint.2022.916220] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 06/16/2022] [Indexed: 11/19/2022] Open
Abstract
Neural mechanisms supporting time perception in continuously changing sensory environments may be relevant to a broader understanding of how the human brain utilizes time in cognition and action. In this review, we describe current theories of sensorimotor engagement in the support of subsecond timing. We focus on musical timing due to the extensive literature surrounding movement with and perception of musical rhythms. First, we define commonly used but ambiguous concepts including neural entrainment, simulation, and prediction in the context of musical timing. Next, we summarize the literature on sensorimotor timing during perception and performance and describe current theories of sensorimotor engagement in the support of subsecond timing. We review the evidence supporting that sensorimotor engagement is critical in accurate time perception. Finally, potential clinical implications for a sensorimotor perspective of timing are highlighted.
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Affiliation(s)
- Jessica M. Ross
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, CA, United States
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, United States
- Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Neurology, Harvard Medical School, Boston, MA, United States
- *Correspondence: Jessica M. Ross,
| | - Ramesh Balasubramaniam
- Cognitive and Information Sciences, University of California, Merced, Merced, CA, United States
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Hervault M, Zanone PG, Buisson JC, Huys R. Cortical sensorimotor activity in the execution and suppression of discrete and rhythmic movements. Sci Rep 2021; 11:22364. [PMID: 34785710 PMCID: PMC8595306 DOI: 10.1038/s41598-021-01368-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/20/2021] [Indexed: 11/09/2022] Open
Abstract
Although the engagement of sensorimotor cortices in movement is well documented, the functional relevance of brain activity patterns remains ambiguous. Especially, the cortical engagement specific to the pre-, within-, and post-movement periods is poorly understood. The present study addressed this issue by examining sensorimotor EEG activity during the performance as well as STOP-signal cued suppression of movements pertaining to two distinct classes, namely, discrete vs. ongoing rhythmic movements. Our findings indicate that the lateralized readiness potential (LRP), which is classically used as a marker of pre-movement processing, indexes multiple pre- and in- movement-related brain dynamics in a movement-class dependent fashion. In- and post-movement event-related (de)synchronization (ERD/ERS) observed in the Mu (8-13 Hz) and Beta (15-30 Hz) frequency ranges were associated with estimated brain sources in both motor and somatosensory cortical areas. Notwithstanding, Beta ERS occurred earlier following cancelled than actually performed movements. In contrast, Mu power did not vary. Whereas Beta power may reflect the evaluation of the sensory predicted outcome, Mu power might engage in linking perception to action. Additionally, the rhythmic movement forced stop (only) showed a post-movement Mu/Beta rebound, which might reflect an active "clearing-out" of the motor plan and its feedback-based online control. Overall, the present study supports the notion that sensorimotor EEG modulations are key markers to investigate control or executive processes, here initiation and inhibition, which are exerted when performing distinct movement classes.
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Affiliation(s)
- Mario Hervault
- Centre de Recherche Cerveau et Cognition, UMR 5549, Pavillon Baudot CHU Purpan, CNRS - Université Toulouse 3 Paul Sabatier, Toulouse, France.
| | - Pier-Giorgio Zanone
- Centre de Recherche Cerveau et Cognition, UMR 5549, Pavillon Baudot CHU Purpan, CNRS - Université Toulouse 3 Paul Sabatier, Toulouse, France
| | - Jean-Christophe Buisson
- Institut de Recherche en Informatique de Toulouse - UMR 5505, CNRS - Université Toulouse 3 Paul Sabatier, Toulouse, France
| | - Raoul Huys
- Centre de Recherche Cerveau et Cognition, UMR 5549, Pavillon Baudot CHU Purpan, CNRS - Université Toulouse 3 Paul Sabatier, Toulouse, France
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Jenson D. Audiovisual incongruence differentially impacts left and right hemisphere sensorimotor oscillations: Potential applications to production. PLoS One 2021; 16:e0258335. [PMID: 34618866 PMCID: PMC8496780 DOI: 10.1371/journal.pone.0258335] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 09/26/2021] [Indexed: 11/21/2022] Open
Abstract
Speech production gives rise to distinct auditory and somatosensory feedback signals which are dynamically integrated to enable online monitoring and error correction, though it remains unclear how the sensorimotor system supports the integration of these multimodal signals. Capitalizing on the parity of sensorimotor processes supporting perception and production, the current study employed the McGurk paradigm to induce multimodal sensory congruence/incongruence. EEG data from a cohort of 39 typical speakers were decomposed with independent component analysis to identify bilateral mu rhythms; indices of sensorimotor activity. Subsequent time-frequency analyses revealed bilateral patterns of event related desynchronization (ERD) across alpha and beta frequency ranges over the time course of perceptual events. Right mu activity was characterized by reduced ERD during all cases of audiovisual incongruence, while left mu activity was attenuated and protracted in McGurk trials eliciting sensory fusion. Results were interpreted to suggest distinct hemispheric contributions, with right hemisphere mu activity supporting a coarse incongruence detection process and left hemisphere mu activity reflecting a more granular level of analysis including phonological identification and incongruence resolution. Findings are also considered in regard to incongruence detection and resolution processes during production.
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Affiliation(s)
- David Jenson
- Department of Speech and Hearing Sciences, Washington State University, Spokane, Washington, United States of America
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12
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Jenson D, Saltuklaroglu T. Sensorimotor contributions to working memory differ between the discrimination of Same and Different syllable pairs. Neuropsychologia 2021; 159:107947. [PMID: 34216594 DOI: 10.1016/j.neuropsychologia.2021.107947] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 02/01/2021] [Accepted: 06/27/2021] [Indexed: 10/21/2022]
Abstract
Sensorimotor activity during speech perception is both pervasive and highly variable, changing as a function of the cognitive demands imposed by the task. The purpose of the current study was to evaluate whether the discrimination of Same (matched) and Different (unmatched) syllable pairs elicit different patterns of sensorimotor activity as stimuli are processed in working memory. Raw EEG data recorded from 42 participants were decomposed with independent component analysis to identify bilateral sensorimotor mu rhythms from 36 subjects. Time frequency decomposition of mu rhythms revealed concurrent event related desynchronization (ERD) in alpha and beta frequency bands across the peri- and post-stimulus time periods, which were interpreted as evidence of sensorimotor contributions to working memory encoding and maintenance. Left hemisphere alpha/beta ERD was stronger in Different trials than Same trials during the post-stimulus period, while right hemisphere alpha/beta ERD was stronger in Same trials than Different trials. A between-hemispheres contrast revealed no differences during Same trials, while post-stimulus alpha/beta ERD was stronger in the left hemisphere than the right during Different trials. Results were interpreted to suggest that predictive coding mechanisms lead to repetition suppression effects in Same trials. Mismatches arising from predictive coding mechanisms in Different trials shift subsequent working memory processing to the speech-dominant left hemisphere. Findings clarify how sensorimotor activity differentially supports working memory encoding and maintenance stages during speech discrimination tasks and have potential to inform sensorimotor models of speech perception and working memory.
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Affiliation(s)
- David Jenson
- Washington State University, Elson S. Floyd College of Medicine, Department of Speech and Hearing Sciences, Spokane, WA, USA.
| | - Tim Saltuklaroglu
- University of Tennessee Health Science Center, College of Health Professions, Department of Audiology and Speech-Pathology, Knoxville, TN, USA
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13
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Wisniewski MG, Zakrzewski AC, Bell DR, Wheeler M. EEG power spectral dynamics associated with listening in adverse conditions. Psychophysiology 2021; 58:e13877. [PMID: 34161612 DOI: 10.1111/psyp.13877] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 05/15/2021] [Accepted: 05/17/2021] [Indexed: 01/08/2023]
Abstract
Adverse listening conditions increase the demand on cognitive resources needed for speech comprehension. In an exploratory study, we aimed to identify independent power spectral features in the EEG useful for studying the cognitive processes involved in this effortful listening. Listeners performed the coordinate response measure task with a single-talker masker at a 0-dB signal-to-noise ratio. Sounds were left unfiltered or degraded with low-pass filtering. Independent component analysis (ICA) was used to identify independent components (ICs) in the EEG data, the power spectral dynamics of which were then analyzed. Frontal midline theta, left frontal, right frontal, left mu, right mu, left temporal, parietal, left occipital, central occipital, and right occipital clusters of ICs were identified. All IC clusters showed some significant listening-related changes in their power spectrum. This included sustained theta enhancements, gamma enhancements, alpha enhancements, alpha suppression, beta enhancements, and mu rhythm suppression. Several of these effects were absent or negligible using traditional channel analyses. Comparison of filtered to unfiltered speech revealed a stronger alpha suppression in the parietal and central occipital clusters of ICs for the filtered speech condition. This not only replicates recent findings showing greater alpha suppression as listening difficulty increases but also suggests that such alpha-band effects can stem from multiple cortical sources. We lay out the advantages of the ICA approach over the restrictive analyses that have been used as of late in the study of listening effort. We also make suggestions for moving into hypothesis-driven studies regarding the power spectral features that were revealed.
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Affiliation(s)
- Matthew G Wisniewski
- Department of Psychological Sciences, Kansas State University, Manhattan, KS, USA
| | | | - Destiny R Bell
- Department of Psychological Sciences, Kansas State University, Manhattan, KS, USA
| | - Michelle Wheeler
- Department of Psychological Sciences, Kansas State University, Manhattan, KS, USA
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Gastaldon S, Arcara G, Navarrete E, Peressotti F. Commonalities in alpha and beta neural desynchronizations during prediction in language comprehension and production. Cortex 2020; 133:328-345. [PMID: 33171348 DOI: 10.1016/j.cortex.2020.09.026] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 08/25/2020] [Accepted: 09/29/2020] [Indexed: 01/04/2023]
Abstract
The present study investigates whether predictions during language comprehension are generated by engaging the language production system. Previous studies investigating either prediction or production highlighted M/EEG desynchronization (power decrease) in the alpha (8-10 Hz) and beta (13-30 Hz) frequency bands preceding the target. However, it is unclear whether this electrophysiological modulation underlies common mechanisms. We recorded EEG from participants performing both a comprehension and a production task in two separate blocks. Participants listened to high and low constraint incomplete sentences and were asked either to name a picture to complete them (production) or to simply listen to the final word (comprehension). We found that in a silent gap before the final stimulus, predictable stimuli elicited alpha and beta desynchronization in both tasks, signaling the pre-activation of linguistic information. Source estimation highlighted the involvement of left-lateralized language areas and temporo-parietal areas in the right hemisphere. Furthermore, correlations between the desynchronizations in comprehension and production showed spatiotemporal commonalities in language-relevant areas of the left hemisphere. As proposed by prediction-by-production models, our results suggest that comprehenders engage the production system while predicting upcoming words.
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Affiliation(s)
- Simone Gastaldon
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Padova, Italy.
| | | | - Eduardo Navarrete
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Padova, Italy
| | - Francesca Peressotti
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Padova, Italy.
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15
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Jenson D, Bowers AL, Hudock D, Saltuklaroglu T. The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering. Front Hum Neurosci 2020; 13:458. [PMID: 31998103 PMCID: PMC6965028 DOI: 10.3389/fnhum.2019.00458] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 12/13/2019] [Indexed: 11/29/2022] Open
Abstract
Deficits in basal ganglia-based inhibitory and timing circuits along with sensorimotor internal modeling mechanisms are thought to underlie stuttering. However, much remains to be learned regarding the precise manner how these deficits contribute to disrupting both speech and cognitive functions in those who stutter. Herein, we examine the suitability of electroencephalographic (EEG) mu rhythms for addressing these deficits. We review some previous findings of mu rhythm activity differentiating stuttering from non-stuttering individuals and present some new preliminary findings capturing stuttering-related deficits in working memory. Mu rhythms are characterized by spectral peaks in alpha (8-13 Hz) and beta (14-25 Hz) frequency bands (mu-alpha and mu-beta). They emanate from premotor/motor regions and are influenced by basal ganglia and sensorimotor function. More specifically, alpha peaks (mu-alpha) are sensitive to basal ganglia-based inhibitory signals and sensory-to-motor feedback. Beta peaks (mu-beta) are sensitive to changes in timing and capture motor-to-sensory (i.e., forward model) projections. Observing simultaneous changes in mu-alpha and mu-beta across the time-course of specific events provides a rich window for observing neurophysiological deficits associated with stuttering in both speech and cognitive tasks and can provide a better understanding of the functional relationship between these stuttering symptoms. We review how independent component analysis (ICA) can extract mu rhythms from raw EEG signals in speech production tasks, such that changes in alpha and beta power are mapped to myogenic activity from articulators. We review findings from speech production and auditory discrimination tasks demonstrating that mu-alpha and mu-beta are highly sensitive to capturing sensorimotor and basal ganglia deficits associated with stuttering with high temporal precision. Novel findings from a non-word repetition (working memory) task are also included. They show reduced mu-alpha suppression in a stuttering group compared to a typically fluent group. Finally, we review current limitations and directions for future research.
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Affiliation(s)
- David Jenson
- Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - Andrew L. Bowers
- Epley Center for Health Professions, Communication Sciences and Disorders, University of Arkansas, Fayetteville, AR, United States
| | - Daniel Hudock
- Department of Communication Sciences and Disorders, Idaho State University, Pocatello, ID, United States
| | - Tim Saltuklaroglu
- College of Health Professions, Department of Audiology and Speech-Pathology, University of Tennessee Health Science Center, Knoxville, TN, United States
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16
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Jenson D, Thornton D, Harkrider AW, Saltuklaroglu T. Influences of cognitive load on sensorimotor contributions to working memory: An EEG investigation of mu rhythm activity during speech discrimination. Neurobiol Learn Mem 2019; 166:107098. [DOI: 10.1016/j.nlm.2019.107098] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 09/11/2019] [Accepted: 10/09/2019] [Indexed: 11/16/2022]
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17
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Möttönen R, Adank P, Skipper JI. Sensorimotor Speech Processing: A Brief Introduction to the Special Issue. BRAIN AND LANGUAGE 2018; 187:18. [PMID: 30502818 DOI: 10.1016/j.bandl.2018.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Affiliation(s)
- Riikka Möttönen
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
| | - Patti Adank
- Speech, Hearing and Phonetic Sciences, Division of Psychology and Language Sciences, University College London, London, United Kingdom
| | - Jeremy I Skipper
- Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, United Kingdom
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