Phase-Amplitude Coupling (PAC) in electrophysiological signals refers to the transient interplay ... more Phase-Amplitude Coupling (PAC) in electrophysiological signals refers to the transient interplay of activities in different frequency ranges, wherein phase in a low-frequency band and amplitude in a high-frequency band are in some way dependent. PAC phenomena have received increasing interest in neuroscience given the growing evidence of their apparent role in both normal and pathological brain processes. This interest has resulted in publication of a wave of methods for PAC estimation, each with its own advantages and drawbacks relative to others. Motivated by the widespread study of this phenomenon, most academic open source software environments for analyzing electrophysiological signals (e.g., Fieldtrip, Brainstorm, MNE) have implemented at least one method of PAC estimation. Here we describe an EEGLAB plug-in release, PACTools for MATLAB (The Mathworks, Inc.), that computes PAC in either continuous or event-related data using any of five methods for PAC estimation: Mean Vector Length Modulation Index, Kullback- Leibler Modulation Index, Phase-Locking Value, General Linear Model Modulation Index and Mutual Information PAC (MIPAC). PACTools uses parallelized code for efficient performance and offers built-in direct access to online high-performance computing resources made freely available for nonprofit research by the Neurosciences Gateway (nsgportal.org). PACTools features intuitive graphic user interfaces and equivalent command line calls that make its use straightforward and seamless in the EEGLAB environment. We discuss toolbox implementation, architecture, dependencies, and the implemented methods of PAC computation and visualization.
Several studies have suggested that the auditory mismatch-response (MMR) elicited in infants is a... more Several studies have suggested that the auditory mismatch-response (MMR) elicited in infants is a predictor of later language skills (Choudhury & Benasich, 2011;van Zuijen et al. 2013). However, there is little knowledge of what brain source activities the infant MMR reflects (Näätänen et al., 2014) and Independent Component Analysis (ICA) has not been used to address this issue. Scalpchannel averaged EEG and MMRs may sum volume-conducted contributions from many cortical source areas. ICA applied to the unaveraged EEG data can be used to identify the complex spatiotemporal dynamics underlying the MMR, allowing identification of the contributions of the cortical generators that contribute to the scalp averages (Rissling et al., 2014). We recorded 60channel EEG data in 34 typically developing six-month-old infants during a passive acoustic oddball paradigm involving ‘standard’ interspersed with occasional pitchor duration-deviant tonepairs. Adaptive-Mixture-ICA (Palmer et al., 2006, 2...
There is a dearth of studies examining the underlying mechanisms of blink suppression and the eff... more There is a dearth of studies examining the underlying mechanisms of blink suppression and the effects of urge and reward, particularly those measuring subsecond electroencephalogram (EEG) brain dynamics. To address these issues, we designed an EEG study to ask 3 questions: 1) How does urge develop? 2) What are EEG-correlates of blink suppression? 3) How does reward change brain dynamics related to urge suppression? This study examined healthy children (N = 26, age 8–12 years) during blink suppression under 3 conditions: blink freely (i.e., no suppression), blink suppressed, and blink suppressed for reward. During suppression conditions, children used a joystick to indicate their subjective urge to blink. Results showed that 1) half of the trials were associated with clearly defined urge time course of ~7 s, which was accompanied by EEG delta (1–4 Hz) power reduction localized at anterior cingulate cortex (ACC); 2) the EEG correlates of blink suppression were found in left prefrontal...
Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cog... more Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control paradigms. In addition to these top down attentional control regions, widespread alterations in brain activity across multiple neural networks have been reported. There is a dearth, however, of studies examining event-related connectivity during cognitive inhibitory paradigms among affected individuals. The goal of this study was to characterize neural oscillatory activity and effective connectivity, using a case–control design, among children with and without chronic tic disorder during perfor...
Here we assume that emotional states correspond to functional dynamic states of brain and body, a... more Here we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for ...
<p>ERSPs and associated scalp maps for the (A) left temporal and (B) the right temporal ind... more <p>ERSPs and associated scalp maps for the (A) left temporal and (B) the right temporal independent component cluster. The frames immediately to the left of the ERSP images show the average baseline log power spectrum (−200–0 ms, blue trace) that was subtracted from individual component activities to generate ERSPs. The red and green traces in these frames show the average upper and lower significance threshold (p<.001) across individuals. The ERSP images on the right were created by averaging component ERSP images from individual participants after masking non-significant perturbations from baseline (p<.001). Vertical blue lines in the ERSP image indicate speech delivery onsets, and pink dashed lines indicate motor responses. Colors in the images indicate the relative log power (in dB) at that frequency and latency (normalized) relative to the power at that frequency during the baseline period.</p
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 17, 2016
Everyday locomotion and obstacle avoidance requires effective gait adaptation in response to sens... more Everyday locomotion and obstacle avoidance requires effective gait adaptation in response to sensory cues. Many studies have shown that efficient motor actions are associated with μ rhythm (8-13 Hz) and β band (13-35 Hz) local field desynchronizations in sensorimotor and parietal cortex, whereas a number of cognitive task studies have reported higher behavioral accuracy to be associated with increases in β band power in prefrontal and sensory cortex. How these two distinct patterns of β band oscillations interplay during gait adaptation, however, has not been established. Here we recorded 108 channel EEG activity from 18 participants (10 males, 22-35 years old) attempting to walk on a treadmill in synchrony with a series of pacing cue tones, and quickly adapting their step rate and length to sudden shifts in pacing cue tempo. Independent component analysis parsed each participant's EEG data into maximally independent component (IC) source processes, which were then grouped acros...
Phase-Amplitude Coupling (PAC) in electrophysiological signals refers to the transient interplay ... more Phase-Amplitude Coupling (PAC) in electrophysiological signals refers to the transient interplay of activities in different frequency ranges, wherein phase in a low-frequency band and amplitude in a high-frequency band are in some way dependent. PAC phenomena have received increasing interest in neuroscience given the growing evidence of their apparent role in both normal and pathological brain processes. This interest has resulted in publication of a wave of methods for PAC estimation, each with its own advantages and drawbacks relative to others. Motivated by the widespread study of this phenomenon, most academic open source software environments for analyzing electrophysiological signals (e.g., Fieldtrip, Brainstorm, MNE) have implemented at least one method of PAC estimation. Here we describe an EEGLAB plug-in release, PACTools for MATLAB (The Mathworks, Inc.), that computes PAC in either continuous or event-related data using any of five methods for PAC estimation: Mean Vector Length Modulation Index, Kullback- Leibler Modulation Index, Phase-Locking Value, General Linear Model Modulation Index and Mutual Information PAC (MIPAC). PACTools uses parallelized code for efficient performance and offers built-in direct access to online high-performance computing resources made freely available for nonprofit research by the Neurosciences Gateway (nsgportal.org). PACTools features intuitive graphic user interfaces and equivalent command line calls that make its use straightforward and seamless in the EEGLAB environment. We discuss toolbox implementation, architecture, dependencies, and the implemented methods of PAC computation and visualization.
Several studies have suggested that the auditory mismatch-response (MMR) elicited in infants is a... more Several studies have suggested that the auditory mismatch-response (MMR) elicited in infants is a predictor of later language skills (Choudhury & Benasich, 2011;van Zuijen et al. 2013). However, there is little knowledge of what brain source activities the infant MMR reflects (Näätänen et al., 2014) and Independent Component Analysis (ICA) has not been used to address this issue. Scalpchannel averaged EEG and MMRs may sum volume-conducted contributions from many cortical source areas. ICA applied to the unaveraged EEG data can be used to identify the complex spatiotemporal dynamics underlying the MMR, allowing identification of the contributions of the cortical generators that contribute to the scalp averages (Rissling et al., 2014). We recorded 60channel EEG data in 34 typically developing six-month-old infants during a passive acoustic oddball paradigm involving ‘standard’ interspersed with occasional pitchor duration-deviant tonepairs. Adaptive-Mixture-ICA (Palmer et al., 2006, 2...
There is a dearth of studies examining the underlying mechanisms of blink suppression and the eff... more There is a dearth of studies examining the underlying mechanisms of blink suppression and the effects of urge and reward, particularly those measuring subsecond electroencephalogram (EEG) brain dynamics. To address these issues, we designed an EEG study to ask 3 questions: 1) How does urge develop? 2) What are EEG-correlates of blink suppression? 3) How does reward change brain dynamics related to urge suppression? This study examined healthy children (N = 26, age 8–12 years) during blink suppression under 3 conditions: blink freely (i.e., no suppression), blink suppressed, and blink suppressed for reward. During suppression conditions, children used a joystick to indicate their subjective urge to blink. Results showed that 1) half of the trials were associated with clearly defined urge time course of ~7 s, which was accompanied by EEG delta (1–4 Hz) power reduction localized at anterior cingulate cortex (ACC); 2) the EEG correlates of blink suppression were found in left prefrontal...
Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cog... more Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control paradigms. In addition to these top down attentional control regions, widespread alterations in brain activity across multiple neural networks have been reported. There is a dearth, however, of studies examining event-related connectivity during cognitive inhibitory paradigms among affected individuals. The goal of this study was to characterize neural oscillatory activity and effective connectivity, using a case–control design, among children with and without chronic tic disorder during perfor...
Here we assume that emotional states correspond to functional dynamic states of brain and body, a... more Here we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for ...
<p>ERSPs and associated scalp maps for the (A) left temporal and (B) the right temporal ind... more <p>ERSPs and associated scalp maps for the (A) left temporal and (B) the right temporal independent component cluster. The frames immediately to the left of the ERSP images show the average baseline log power spectrum (−200–0 ms, blue trace) that was subtracted from individual component activities to generate ERSPs. The red and green traces in these frames show the average upper and lower significance threshold (p<.001) across individuals. The ERSP images on the right were created by averaging component ERSP images from individual participants after masking non-significant perturbations from baseline (p<.001). Vertical blue lines in the ERSP image indicate speech delivery onsets, and pink dashed lines indicate motor responses. Colors in the images indicate the relative log power (in dB) at that frequency and latency (normalized) relative to the power at that frequency during the baseline period.</p
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 17, 2016
Everyday locomotion and obstacle avoidance requires effective gait adaptation in response to sens... more Everyday locomotion and obstacle avoidance requires effective gait adaptation in response to sensory cues. Many studies have shown that efficient motor actions are associated with μ rhythm (8-13 Hz) and β band (13-35 Hz) local field desynchronizations in sensorimotor and parietal cortex, whereas a number of cognitive task studies have reported higher behavioral accuracy to be associated with increases in β band power in prefrontal and sensory cortex. How these two distinct patterns of β band oscillations interplay during gait adaptation, however, has not been established. Here we recorded 108 channel EEG activity from 18 participants (10 males, 22-35 years old) attempting to walk on a treadmill in synchrony with a series of pacing cue tones, and quickly adapting their step rate and length to sudden shifts in pacing cue tempo. Independent component analysis parsed each participant's EEG data into maximally independent component (IC) source processes, which were then grouped acros...
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