skip to main content


Title: Neural silences can be localized rapidly using noninvasive scalp EEG
A rapid and cost-effective noninvasive tool to detect and characterize neural silences can be of important benefit in diagnosing and treating many disorders. We propose an algorithm, SilenceMap, for uncovering the absence of electrophysiological signals, or neural silences, using noninvasive scalp electroencephalography (EEG) signals. By accounting for the contributions of different sources to the power of the recorded signals, and using a hemispheric baseline approach and a convex spectral clustering framework, SilenceMap permits rapid detection and localization of regions of silence in the brain using a relatively small amount of EEG data. SilenceMap substantially outperformed existing source localization algorithms in estimating the center-of-mass of the silence for three pediatric cortical resection patients, using fewer than 3 minutes of EEG recordings (13, 2, and 11mm vs. 25, 62, and 53 mm), as well for 100 different simulated regions of silence based on a real human head model (12 ± 0.7 mm vs. 54 ± 2.2 mm). SilenceMap paves the way towards accessible early diagnosis and continuous monitoring of altered physiological properties of human cortical function.  more » « less
Award ID(s):
1763561
PAR ID:
10252508
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Nature communications biology selections
ISSN:
2188-5028
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. There is a rise in the study of functional connectivity among various cortical regions and investigations to uncover causal links between a stimulus and the corresponding neural dynamics through electrophysiological imaging of the human brain. Animal model that exhibit simplistic representations of such networks open a doorway for such investigations and are gaining rapid popularity. In this study, we investigate and compare resting state network and auditory stimulus related activity with minimal invasive technology along computational spectral analysis on a C57/BL6 based mouse model. Somatosensory, motor and visual cortex are observed to be highly active and significantly correlated (p-value<0.05). Moreover, given the spatial limitation due to small size of the mouse head, we also describe a low-cost and effective fabrication process for the mouse EEG Polyimide Based Microelectrodes (PBM) array. The easy-to-implement fabrication process involves transfer of the pattern on a copper layer of the Kapton film followed by gold electroplating and application of insulation paint. Acoustic stimulation is done by using tube extensions for avoiding electrical coupling to EEG signals. Unlike multi-electrode array type of invasive methods that are local to a cortical region, the methods established in this study can be used for examining functional connectivity analysis, neural dynamics and cortical response at a global level. 
    more » « less
  2. Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation method that modulates brain activity by inducing electric fields in the brain. Real-time, state-dependent stimulation with TMS has shown that neural oscillation phase modulates corticospinal excitability. However, such motor evoked potentials (MEPs) only indirectly reflect motor cortex activation and are unavailable at other brain regions of interest. The direct and secondary cortical effects of phase-dependent brain stimulation remain an open question. In this study, we recorded the cortical responses during single-pulse TMS using electroencephalography (EEG) concurrently with the MEP measurements in 20 healthy human volunteers (11 female). TMS was delivered at peak, rising, trough, and falling phases of mu (8–13 Hz) and beta (14–30 Hz) oscillations in the motor cortex. The cortical responses were quantified through TMS evoked potential components N15, P50, and N100 as peak-to-peak amplitudes (P50-N15 and P50-N100). We further analyzed whether the prestimulus frequency band power was predictive of the cortical responses. We demonstrated that phase-specific targeting modulates cortical responses. The phase relationship between cortical responses was different for early and late responses. In addition, pre-TMS mu oscillatory power and phase significantly predicted both early and late cortical EEG responses in mu-specific targeting, indicating the independent causal effects of phase and power. However, only pre-TMS beta power significantly predicted the early and late TEP components during beta-specific targeting. Further analyses indicated distinct roles of mu and beta power on cortical responses. These findings provide insight to mechanistic understanding of neural oscillation states in cortical and corticospinal activation in humans.

     
    more » « less
  3. Abstract

    Objective.Reorienting is central to how humans direct attention to different stimuli in their environment. Previous studies typically employ well-controlled paradigms with limited eye and head movements to study the neural and physiological processes underlying attention reorienting. Here, we aim to better understand the relationship between gaze and attention reorienting using a naturalistic virtual reality (VR)-based target detection paradigm.Approach.Subjects were navigated through a city and instructed to count the number of targets that appeared on the street. Subjects performed the task in a fixed condition with no head movement and in a free condition where head movements were allowed. Electroencephalography (EEG), gaze and pupil data were collected. To investigate how neural and physiological reorienting signals are distributed across different gaze events, we used hierarchical discriminant component analysis (HDCA) to identify EEG and pupil-based discriminating components. Mixed-effects general linear models (GLM) were used to determine the correlation between these discriminating components and the different gaze events time. HDCA was also used to combine EEG, pupil and dwell time signals to classify reorienting events.Main results.In both EEG and pupil, dwell time contributes most significantly to the reorienting signals. However, when dwell times were orthogonalized against other gaze events, the distributions of the reorienting signals were different across the two modalities, with EEG reorienting signals leading that of the pupil reorienting signals. We also found that the hybrid classifier that integrates EEG, pupil and dwell time features detects the reorienting signals in both the fixed (AUC = 0.79) and the free (AUC = 0.77) condition.Significance.We show that the neural and ocular reorienting signals are distributed differently across gaze events when a subject is immersed in VR, but nevertheless can be captured and integrated to classify target vs. distractor objects to which the human subject orients.

     
    more » « less
  4. During music listening, humans routinely acquire the regularities of the acoustic sequences and use them to anticipate and interpret the ongoing melody. Specifically, in line with this predictive framework, it is thought that brain responses during such listening reflect a comparison between the bottom-up sensory responses and top-down prediction signals generated by an internal model that embodies the music exposure and expectations of the listener. To attain a clear view of these predictive responses, previous work has eliminated the sensory inputs by inserting artificial silences (or sound omissions) that leave behind only the corresponding predictions of the thwarted expectations. Here, we demonstrate a new alternate approach in which we decode the predictive electroencephalography (EEG) responses to the silent intervals that are naturally interspersed within the music. We did this as participants (experiment 1, 20 participants, 10 female; experiment 2, 21 participants, 6 female) listened or imagined Bach piano melodies. Prediction signals were quantified and assessed via a computational model of the melodic structure of the music and were shown to exhibit the same response characteristics when measured during listening or imagining. These include an inverted polarity for both silence and imagined responses relative to listening, as well as response magnitude modulations that precisely reflect the expectations of notes and silences in both listening and imagery conditions. These findings therefore provide a unifying view that links results from many previous paradigms, including omission reactions and the expectation modulation of sensory responses, all in the context of naturalistic music listening. 
    more » « less
  5. Studying electroencephalography (EEG) in response to transcranial magnetic stimulation (TMS) is gaining popularity for investigating the dynamics of complex neural architecture in the brain. For example, the primary motor cortex (M1) executes voluntary movements by complex connections with other associated subnetworks. To understand these connections better, we analyzed EEG signal response to TMS at left M1 from schizophrenia patients and healthy controls and in contrast with resting state EEG recording. After removing artifacts from EEG, we conducted 2D to 3D sLORETA conversion, a well-established source localization method, for estimating signal strength of 68 source dipoles or cortical regions inside the brain. Next, we studied dynamic connectivity by computing time-evolving spatial coherence of 2278 (=68*(68-1)/2) pairs of cortical regions, with sliding window technique of 200ms window size and 20ms shift over 1sec long data. Pairs with consistent coherence (coherence>0.8 during 200+ sliding windows of patients and controls combined) were chosen for identifying stable networks. For example, we found that during the resting state, precuneus was steadily coherent with middle and superior temporal gyrus in the left hemisphere in both patient and controls. Their connectivity pattern over the sliding windows significantly differed between patients and controls (pvalue<0.05). Whereas for M1, the same was true for two other coherent pairs namely, superamarginal gyrus with lateral occipital gyrus in right hemisphere and medial orbitofrontal gyrus with fusiform in left hemisphere. The TMS-EEG dynamic connectivity results can help to differentiate patient and normal subjects and also help to better understand the brain architecture and mechanisms. 
    more » « less