Differentiation of speech-induced artifacts from physiological high gamma activity in intracranial recordings

Bush, Alan; Chrabaszcz, Anna; Peterson, Victoria; Saravanan, Varun; Dastolfo-Hromack, Christina; Lipski, Witold; Richardson, R. Mark

doi:10.1016/j.neuroimage.2022.118962

Cited by 14 publications

(22 citation statements)

References 40 publications

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“…Moreover, the HI-DGD model revealed that the power of the gamma band in mPFC is a significant contributor to decoding conflict and non-conflict trials. Gamma activities are mostly associated with contralateral movement such as hand movements Kondylis et al (2016), or speech production Bush et al (2022). Speech production, in a verbal Stroop task, is an inevitable part of the task and its onset is marked as the response time.…”

Section: Discussionmentioning

confidence: 99%

Inferring Cognitive State Underlying Conflict Choices in Verbal Stroop Task Using Heterogeneous Input Discriminative-Generative Decoder Model

Rezaei

Jeoung

Gharamani

et al. 2022

Preprint

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The subthalamic nucleus (STN) of the basal ganglia interacts with the medial prefrontal cortex (mPFC) and shapes a control loop, specifically when the brain receives contradictory information from either different sensory systems or conflicting information from sensory inputs and prior knowledge that developed in the brain. Experimental studies demonstrated that significant increases in theta activities (2-8 Hz) in both the STN and mPFC as well as increased phase synchronization between mPFC and STN are prominent features of conflict processing. While these neural features reflect the importance of STN-mPFC circuitry in conflict processing, a low-dimensional representation of the mPFC-STN interaction referred to as a cognitive state, that links neural activities generated by these sub-regions to behavioral signals (e.g., the response time), remains to be identified. Here, we propose a new model, namely, the heterogeneous input discriminative-generative decoder (HI-DGD) model, to infer a cognitive state underlying decision-making based on neural activities (STN and mPFC) and behavioral signals (individuals' response time) recorded in 10 Parkinson's disease patients while they performed a Stroop task. PD patients may have conflict processing which is quantitatively (may be qualitative in some) different from healthy population. Using extensive synthetic and experimental data, we showed that the HI-DGD model can diffuse information from neural- and behavioral data simultaneously and estimate cognitive states underlying conflict and non-conflict trials significantly better than traditional methods. Additionally, the HI-DGD model identified which neural features made significant contributions to conflict and non-conflict choices. Interestingly, the estimated features match well with those reported in experimental studies. Finally, we highlight the capability of the HI-DGD model in estimating a cognitive state from a single trial of observation, which makes it appropriate to be utilized in closed-loop neuromodulation systems.

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Section: Discussionmentioning

confidence: 99%

Inferring Cognitive State Underlying Conflict Choices in Verbal Stroop Task Using Heterogeneous Input Discriminative-Generative Decoder Model

Rezaei

Jeoung

Gharamani

et al. 2022

Preprint

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“…Participants. Movement disorder patients undergoing intracranial electrode implantation for deep brain stimulation therapy participated in a speech production task (Bush et al, 2021), for which the baseline periods were analyzed in this study. One or two high-density subdural electrocorticography (ECoG) strips were temporary placed through the standard burr hole, targeting the left superior temporal gyrus (covering also the ventral sensorimotor cortex) and left inferior frontal gyrus.…”

Section: Methodsmentioning

confidence: 99%

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Bush

Zou

Lipski

et al. 2023

Preprint

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Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/fχbroadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinson's disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent (χSTN=1.3±0.2, χVIM=1.4±0.1, χGPi=1.4±0.1) that differed markedly from cortical values (χCortex=3.2±0.4, fk,Cortex=17±5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex.

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“…These findings establish a basis for continued investigation of subcortical participation in speech planning and modulation, including the integration of information from sensory cortical areas participating in both feed-forward and feedback processes. Important additional factors for the future of this field will be the detection of speech artifacts in gamma frequencies and the need to engage patients proactively in intracranial human neuroscience experiments ( Montreuil et al, 2019 ; Bush et al, 2022 ).…”

Section: Transforming the Or Into The Laboratorymentioning

confidence: 99%

Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation

Wong

Mayberg

Wang

et al. 2023

Front. Hum. Neurosci.

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The deep brain stimulation (DBS) Think Tank X was held on August 17–19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the “trough of disillusionment.” DBS for depression was considered as “re-emerging” and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year’s meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.

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Differentiation of speech-induced artifacts from physiological high gamma activity in intracranial recordings

Cited by 14 publications

References 40 publications

Inferring Cognitive State Underlying Conflict Choices in Verbal Stroop Task Using Heterogeneous Input Discriminative-Generative Decoder Model

Inferring Cognitive State Underlying Conflict Choices in Verbal Stroop Task Using Heterogeneous Input Discriminative-Generative Decoder Model

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation

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