Biology subjects

Swann, N. C.

Publications and source records attributed to Swann, N. C..

7 recordsLinked to original sources

bioRxiv2026

EEG Oscillations in Guided Mindfulness versus Mind-Wandering in Young Adults: Effects of Auditory Task Instruction and Naturalistic Video

Alpha and theta band EEG oscillations have been implicated in states of mindfulness meditation. However, results are inconsistent and the influence of testing environment variables is not well-characterized. We used EEG to measure the amplitude of brain oscillations in a mindful-attention versus mind-wandering condition, in which guided auditory instructions were interleaved with periods of silence, with and without accompanying naturalistic video projections. We generated precise measures of alpha and theta in a sample of 20 young-adult non-expert meditators, by identifying each participant's individual alpha peak frequency (IAF) from posterior EEG electrodes and using it to define four individualized frequency bands: two low alpha bands (in 2 Hz increments below the IAF), one upper alpha band (from IAF to 2 Hz above IAF), and one theta band (4 Hz - 6 Hz below IAF). We found that the mindfulness manipulation significantly increased power in alpha ranging between 2 Hz below to 2 Hz above IAF, including peak alpha amplitude, compared with mind-wandering. Meanwhile, central theta amplitude was larger when auditory instructions were on versus off, and naturalistic video did not reliably modulate the EEG effects of mindfulness. We conclude that the acute effects of mindfulness in non-expert meditators are most consistently observed as increases of posterior alpha-band activity, and that auditory task-instructions should be accounted for in studies of guided meditation. Observed alpha increases may reflect induced states of calm or relaxation induced by mindfulness practice, as proposed in previous studies. These results may apply to mindfulness training or biofeedback therapies.

neuroscience↗

bioRxiv2026

Oscillatory activity in rostral middle frontal gyrus and subthalamic nucleus encode proactive inhibition in cortico-subcortical motor control network

The current model of the action inhibition network includes the prefrontal cortex and the subthalamic nucleus (STN) connected via the prefrontal hyperdirect pathway. Proactive inhibition refers to preparatory mechanisms that facilitate action inhibition (i.e. enables a person to act with restraint), while reactive inhibition is a sudden stopping triggered by an external stimulus. Most research has focused on the reactive paradigm, with more limited investigation of proactive inhibition. We studied electrophysiologic activity in multiple cortical and STN regions in 17 patients with Parkinsons disease using high-resolution intracranial electrodes. Subjects performed a Go/NoGo task and a simpler Go task. Proactive inhibition was assessed by contrasting Go trials in the context of two tasks. In the rostral middle frontal gyrus, we found increased beta oscillations during movement preparation in Go trials of the Go/NoGo task compared to the Go task. A similar but weaker, preparatory beta modulation was observed in dorsal STN, while central STN was associated with significant modulation in theta power prior to movement. We interpret this activity as a reflection of the role of these regions in proactively restraining anticipated responses. Conversely, inferior frontal gyrus and ventral STN were primarily engaged during rapid post-cue action control. Specifically, withholding of action after the NoGo signal was accompanied by increased theta activity in these regions. Beta modulation within the STN mirrored those of sensorimotor cortex during successful inhibition and movement execution. In both regions, beta activity decreased during movement and was higher when movement was withheld. We conclude that communication within the hypothesized motor control network is frequency dependent, with key nodes promoting specific functions.

neuroscience↗

bioRxiv2025

"Awe-scillations": EEG spectral and complexity representations of awe

Awe is a positive emotion often accompanied by sensations of vastness and unity, with known benefits for well-being and social behavior. However, its neural underpinnings remain poorly understood. We recorded electroencephalography (EEG) and autonomic physiology in 23 healthy older participants while they watched a nature-based audiovisual film and subjectively rated awe events. Awe was the predominant emotion reported - though other positive emotions (e.g., joy) were also highly rated. Awe events were associated with decreased skin conductance level (SCL), and decreased EEG alpha and theta spectral power - physiological changes associated with low arousal and positively valenced emotional states. Interestingly, awe events exhibited increased Lempel Ziv Complexity (LZC) - indicating heightened neural signal entropy and increased richness of the conscious experience. LZC was also positively associated with the intensity of the awe ratings and negatively associated with SCL. Three additional datasets with separate independent induction methods (video clips and pharmacological induction via N,N-dimethyltryptamine) also showed positive occipital LZC associations with awe - suggesting some generalizability of LZC as a neurophysiological marker of awe. These results suggest that awe evokes neurophysiological states linked to the subjective affective experience. Impact StatementAwe, an emotion of increasing interest, has been studied with fMRI and peripheral physiology - but few studies have used electroencephalography (EEG). In this EEG study, we utilize a movie-watching paradigm to explore potential physiological correlates of awe. The results present EEG-based complexity increases as a potential correlate of awe, though showing limited generalization to independent datasets and limited uniqueness compared to joy, another positive emotion.

neuroscience↗

bioRxiv2022

Classification of Movement-Related Oscillations in sEEG Recordings with Machine Learning

Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement mostly from recordings of primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a broader array of brain areas such as those sampled by stereoelectroencephalography (sEEG). Here we decoded movement using a linear support vector machine (SVM). We were able to accurately classify sEEG spectrograms during a keypress movement in a task versus those during the inter-trial interval. Furthermore, the important time-frequency patterns for this classification recapitulated findings from previous studies that used non-invasive electroencephalography (EEG) and electrocorticography (ECoG) and identified brain regions that were not associated with movement in previous studies. Specifically, we found these previously described patterns: beta (13 - 30 Hz) desynchronization, beta synchronization (rebound), pre-movement alpha (8 - 15 Hz) modulation, a post-movement broadband gamma (60 - 90 Hz) increase and an event-related potential. These oscillatory patterns were newly observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiology recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside primary and secondary motor cortices. We provide evidence for a system of putative motor networks that exhibit unique oscillatory patterns by describing the anatomical extent of the movement-related oscillations that were observed most frequently across all sEEG contacts. Significance StatementSeveral major motor networks have been previously delineated in humans, however, much less is known about the population-level oscillations that coordinate this neural circuitry, especially in cortex. Therapies that modulate brain circuits to treat movement disorders, such as deep brain stimulation (DBS), or use brain signals to control movement, such as brain-computer interfaces (BCIs), rely on our basic scientific understanding of this movement neural circuitry. In order to bridge this gap, we used stereoelectroencephalography (sEEG) collected in human patients being monitored for epilepsy to assess oscillatory patterns during movement.

neuroscience↗

bioRxiv2022

Reduced sensorimotor beta dynamics could represent a "slowed movement state" in healthy individuals

Beta oscillations (~13-30 Hz) recorded from the sensorimotor cortex have canonical amplitude changes during movement. Specifically, a movement-related beta decrease (MRBD) occurs before movement, and a post-movement beta rebound (PMBR) follows. We investigated how the MRBD and PMBR vary with movement speed. Individuals performed a task with blocks that generated longer reaction times (RTs) and shorter RTs (Slow and Fast blocks, respectively) while scalp-electroencephalography (EEG) was recorded. The timing of task events before movement was also modulated to generate blocks with certain and uncertain timing (Fixed and Varied blocks, respectively). Beta modulation was reduced in Slow blocks compared to Fast blocks (i.e., a less negative MRBD and less positive PMBR). For the movement certainty manipulation, we saw mixed behavioral and EEG results. Our primary findings align with previous work which has shown reduced movement-related beta modulation in patients with Parkinsons disease. We propose that a "slowed movement state", whether it is experimentally induced or a manifestation of Parkinsons disease bradykinesia, is represented through reduced beta dynamics. Altogether, the MRBD and PMBR may represent motor speed on a continuum with Parkinsons disease as an extreme example of slowed movement.

neuroscience↗

bioRxiv2021

STOPPING A CONTINUOUS MOVEMENT: A NOVEL APPROACH TO INVESTIGATING MOTOR CONTROL

Flexible, adaptive behavior is critically dependent on inhibitory control. For example, if you suddenly notice you are about to step on a tack and would prefer not to, the ability to halt your ongoing movement is critical. To address limitations in existing approaches for studying your ability to rapidly terminate your movement ("stopping"), we developed a novel stop task. This task requires termination of ongoing motor programs, provides a direct measure of SSRT, and allows for comparison of the same behavior (stopping) in conditions that elicit either prepared or reactive inhibitory control. Here, we present and evaluate our novel Continuous Movement Stop Task (CMST). We examined several versions of the task in a total of 49 participants. Our data reveal that the CMST is effectively able to dissociate stopping behavior between the planned and unplanned conditions. Additionally, within the subset of participants for which we measured speed, we found that participants initiated stopping (with respect to the stop signal) significantly earlier on planned stop compared to unplanned stop trials. Finally, participants took longer to arrive at full motor arrest (i.e. SSRT) following stop initiation on planned than on unplanned stop trials. This novel task design will enable a more precise quantification of stopping behavior and, in conjunction with neuroscientific methods, could provide more rigorous characterization of brain networks underlying stopping.

neuroscience↗

bioRxiv2019

Characteristics of Beta Waveform Shape in Parkinson's Disease Detected with Scalp Electroencephalography

Neural activity in the beta frequency range (13-30 Hz) is excessively synchronized in Parkinsons Disease (PD). Previous work using invasive intracranial recordings and non-invasive scalp electroencephalography (EEG) has shown that correlations between beta phase and broadband gamma amplitude (i.e., phase-amplitude coupling) are elevated in PD, perhaps a reflection of this synchrony. Recently, it has also been shown, in invasive human recordings, that nonsinusoidal features of beta oscillation shape also characterize PD. Here we show that these features of beta waveform shape also distinguish PD patients on and off medication using non-invasive recordings in a dataset of 15 PD patients with resting scalp EEG. Specifically, beta oscillations over sensorimotor electrodes in PD patients off medication had greater sharpness asymmetry and steepness asymmetry than on medication (sign rank, p=0.006, p=0.003 respectively). We also showed that beta oscillations over sensorimotor cortex most often had a canonical shape and that using this prototypical shape as an inclusion criterion increased the effect size of our findings. Together our findings suggest that novel ways of measuring beta synchrony that incorporate waveform shape could improve detection of PD pathophysiology in non-invasive recordings.

neuroscience↗