TMS-induced phase resets depend on TMS intensity and EEG phase DOI Creative Commons
Brian Erickson, Brian Kim, Philip N. Sabes

et al.

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(5), P. 056035 - 056035

Published: Sept. 25, 2024

Abstract Objective . The phase of the electroencephalographic (EEG) signal predicts performance in motor, somatosensory, and cognitive functions. Studies suggest that brain resets align neural oscillations with external stimuli, or couple across frequency bands regions. Transcranial Magnetic Stimulation (TMS) can cause noninvasively cortex, thus providing potential to control phase-sensitive However, relationship between TMS parameters resetting is not fully understood. This especially true intensity, which may be crucial enabling precise over amount induced. Additionally, interact instantaneous brain. Understanding these relationships development more powerful controllable stimulation protocols. Approach. To test relationships, we conducted a TMS-EEG study. We applied single-pulse at varying degrees intensity motor area an open loop. Offline, used autoregressive algorithm estimate intrinsic µ -Alpha rhythm cortex moment each pulse was delivered. Main results identified post-stimulation epochs where N100 amplitude depend parametrically on are significant versus peripheral auditory sham stimulation. observed inversion after stimulations near peaks but troughs endogenous rhythm. Significance These data low-intensity primarily existing oscillations, while higher intensities activate previously silent neurons, only when peak phase. guide future studies seek induce resetting, point way manipulate effect by timing respect ongoing activity.

Language: Английский

How do online celebrities attract consumers? an EEG study on consumers’ neural engagement in short video advertising DOI
Zhipeng Zhang, Qihua Liu

Electronic Commerce Research, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Language: Английский

Citations

1
Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics DOI Creative Commons
Sneha Shankar, Yuzhang Chen, Spencer Averbeck

et al.

Advanced Healthcare Materials, Journal Year: 2024, Volume and Issue: 14(4)

Published: Sept. 27, 2024

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges developing durable, highly electrodes while maintaining low impedance prioritizing scalable processing fabrication methods. To address these limitations, we introduce artifact-resistant MXene optimized spatiotemporal resolution recording activity. With 60% transmittance at 550 nm, enable simultaneous imaging electrophysiology multimodal mapping. Electrochemical characterization shows 563 ± 99 kΩ 1 kHz charge storage capacity 58 mC cm⁻² chemical doping. In vivo experiments rodent models demonstrate the arrays' functionality performance. model chemically-induced epileptiform activity, tracked ictal wavefronts via calcium simultaneously seizure onset. rat barrel cortex, recorded multi-unit across cortical depths, showing feasibility high-frequency electrophysiological transparency optical absorption properties Ti₃C₂Tx microelectrodes high-quality recordings light-based stimulation contamination from light-induced artifacts.

Language: Английский

Citations

3
Evaluating and benchmarking the EEG signal quality of high-density, dry MXene-based electrode arrays against gelled Ag/AgCl electrodes DOI Creative Commons
Brian Erickson, Ryan Rich, Sneha Shankar

et al.

Journal of Neural Engineering, Journal Year: 2023, Volume and Issue: 21(1), P. 016005 - 016005

Published: Dec. 11, 2023

Abstract Objective. To evaluate the signal quality of dry MXene-based electrode arrays (also termed ‘MXtrodes’) for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard. Approach. We placed 4 × MXtrode and on different scalp locations. The was cleaned with alcohol rewetted saline before application. recorded from both types simultaneously while participants performed vigilance task. Main results. root mean squared amplitude MXtrodes slightly higher than that (.24–1.94 uV). Most pairs had lower broadband spectral coherence (.05 to .1 dB) Delta- Theta-band timeseries correlation units) compared pair ( p < .001). However, magnitude high across types. Beta-band were between neighboring in array (.81 .84 any other (.70 .75 units). This result suggests close spacing nearest (3 mm) more densely sampled spatial-frequency topographies. Event-related potentials similar ρ ⩾ .95) equally spaced ⩽ .77, Dry impedance x̄ = 5.15 KΩ cm 2 ) variable 1.21 , EEG also diverse hair Significance. record at comparable conventional requiring minimal preparation no gel. can independent signals spatial density four times electrodes, including through hair, thus opening novel opportunities research clinical applications could benefit higher-density configurations.

Language: Английский

Citations

4
Decoding Attentional Task Performance Using Electroencephalogram Signals DOI Open Access
Moemi Matsuo

Open access Journal of Neurology & Neurosurgery, Journal Year: 2024, Volume and Issue: 18(5)

Published: March 6, 2024

Background: Electroencephalogram patterns help in evaluating the extent of ischemic brain injury and predicting functional performance. Aim: To determine a possible correlation between attentional task performance electroencephalogram waves. Methods: The cerebral activity 12 healthy young adults was investigated using an while they underwent TrailMaking Test-A B as tasks. Results: A significant observed stronger occipital delta power during rest higher error rates, well weaker temporal central Trail-Making Test-B longer completion times. Delta waves both resting-state conditions correlated with performance, which might be affected by induced lobes. Conclusion: default mode network predict attention deficits. Our findings further our understanding

Language: Английский

Citations

1
TMS-induced phase resets depend on TMS intensity and EEG phase DOI Creative Commons
Brian Erickson, Brian Kim, Philip N. Sabes

et al.

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(5), P. 056035 - 056035

Published: Sept. 25, 2024

Abstract Objective . The phase of the electroencephalographic (EEG) signal predicts performance in motor, somatosensory, and cognitive functions. Studies suggest that brain resets align neural oscillations with external stimuli, or couple across frequency bands regions. Transcranial Magnetic Stimulation (TMS) can cause noninvasively cortex, thus providing potential to control phase-sensitive However, relationship between TMS parameters resetting is not fully understood. This especially true intensity, which may be crucial enabling precise over amount induced. Additionally, interact instantaneous brain. Understanding these relationships development more powerful controllable stimulation protocols. Approach. To test relationships, we conducted a TMS-EEG study. We applied single-pulse at varying degrees intensity motor area an open loop. Offline, used autoregressive algorithm estimate intrinsic µ -Alpha rhythm cortex moment each pulse was delivered. Main results identified post-stimulation epochs where N100 amplitude depend parametrically on are significant versus peripheral auditory sham stimulation. observed inversion after stimulations near peaks but troughs endogenous rhythm. Significance These data low-intensity primarily existing oscillations, while higher intensities activate previously silent neurons, only when peak phase. guide future studies seek induce resetting, point way manipulate effect by timing respect ongoing activity.

Language: Английский

Citations

0