Using OPM-MEG in contrasting magnetic environments

2021 ◽  
Author(s):  
Ryan M Hill ◽  
Jasen Devasagayam ◽  
Niall Holmes ◽  
Elena Boto ◽  
Vishal Shah ◽  
...  
Keyword(s):  
Quantum Interference ◽  
Motor Task ◽  
Low Frequency ◽  
Background Field ◽  
Brain Regions ◽  
City Centre ◽  
Similar Data ◽  
Temporal Correlations ◽  
Custom Made ◽  
Cross Site

Magnetoencephalography (MEG) has been revolutionised in recent years by optically pumped magnetometers (OPMs). OPM-MEG offers higher sensitivity, better spatial resolution and lower cost than conventional instrumentation based on superconducting quantum interference devices (SQUIDS). Moreover, OPMs offer the possibility of motion robustness and lifespan compliance, dramatically expanding the range of MEG applications. However, OPM-MEG remains nascent technology; it places stringent requirements on magnetic shielding, and whilst a number of viable systems exist, most are custom made and there have been no cross-site investigations showing the reliability of data. In this paper, we undertake the first cross-site OPM-MEG comparison, using near identical commercial systems scanning the same participant. The two sites are deliberately contrasting, with different magnetic environments: a green field campus university site with an OPM-optimised shielded room (low interference) and a city centre hospital site with a standard (non-optimised) MSR (high interference). We show that despite a 25-fold difference in background field, and a 30-fold difference in low frequency interference, using dynamic field control and software-based suppression of interference we can generate comparable noise floors at both sites. In human data recorded during a visuo-motor task and a face processing paradigm, we were able to generate similar data, with source localisation showing that brain regions could be pinpointed with just ~10 mm spatial discrepancy and temporal correlations of > 80%. Overall, our study demonstrates that plug-and-play OPM-MEG systems exist and can be sited even in challenging magnetic environments.

scholarly journals Dissociable oscillatory networks support gain and loss processing in human orbitofrontal cortex

2021 ◽  
Author(s):  
Ignacio Saez ◽  
Jack Lin ◽  
Edward Chang ◽  
Josef Parvizi ◽  
Robert T. Knight ◽  
...  
Keyword(s):  
Neural Activity ◽  
Orbitofrontal Cortex ◽  
Low Frequency ◽  
Brain Regions ◽  
Reward Processing ◽  
Neural Oscillations ◽  
Beta Band ◽  
Neuronal Ensembles ◽  
Gain And Loss

AbstractHuman neuroimaging and animal studies have linked neural activity in orbitofrontal cortex (OFC) to valuation of positive and negative outcomes. Additional evidence shows that neural oscillations, representing the coordinated activity of neuronal ensembles, support information processing in both animal and human prefrontal regions. However, the role of OFC neural oscillations in reward-processing in humans remains unknown, partly due to the difficulty of recording oscillatory neural activity from deep brain regions. Here, we examined the role of OFC neural oscillations (<30Hz) in reward processing by combining intracranial OFC recordings with a gambling task in which patients made economic decisions under uncertainty. Our results show that power in different oscillatory bands are associated with distinct components of reward evaluation. Specifically, we observed a double dissociation, with a selective theta band oscillation increase in response to monetary gains and a beta band increase in response to losses. These effects were interleaved across OFC in overlapping networks and were accompanied by increases in oscillatory coherence between OFC electrode sites in theta and beta band during gain and loss processing, respectively. These results provide evidence that gain and loss processing in human OFC are supported by distinct low-frequency oscillations in networks, and provide evidence that participating neuronal ensembles are organized functionally through oscillatory coherence, rather than local anatomical segregation.

scholarly journals Neuronal Substrates Underlying Performance Variability in Well-Trained Skillful Motor Task in Humans

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Nobuaki Mizuguchi ◽  
Shintaro Uehara ◽  
Satoshi Hirose ◽  
Shinji Yamamoto ◽  
Eiichi Naito
Keyword(s):  
Task Performance ◽  
Motor Skill ◽  
Brain Activity ◽  
Motor Task ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Cerebellar Hemisphere ◽  
Intensive Training ◽  
Performance Variability ◽  
The Right

Motor performance fluctuates trial by trial even in a well-trained motor skill. Here we show neural substrates underlying such behavioral fluctuation in humans. We first scanned brain activity with functional magnetic resonance imaging while healthy participants repeatedly performed a 10 s skillful sequential finger-tapping task. Before starting the experiment, the participants had completed intensive training. We evaluated task performance per trial (number of correct sequences in 10 s) and depicted brain regions where the activity changes in association with the fluctuation of the task performance across trials. We found that the activity in a broader range of frontoparietocerebellar network, including the bilateral dorsolateral prefrontal cortex (DLPFC), anterior cingulate and anterior insular cortices, and left cerebellar hemisphere, was negatively correlated with the task performance. We further showed in another transcranial direct current stimulation (tDCS) experiment that task performance deteriorated, when we applied anodal tDCS to the right DLPFC. These results indicate that fluctuation of brain activity in the nonmotor frontoparietocerebellar network may underlie trial-by-trial performance variability even in a well-trained motor skill, and its neuromodulation with tDCS may affect the task performance.

scholarly journals Causal connectivity abnormalities of regional homogeneity in children with attention deficit hyperactivity disorder: a rest-state fMRI study

ADMET & DMPK ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 242-252 ◽  
Author(s):  
Dechun Zhao ◽  
Shuxing Zheng ◽  
Li Yang ◽  
Yin Tian
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Low Frequency ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Support Vector ◽  
Attention And Memory ◽  
Causality Analysis ◽  
Hyperactivity Disorder ◽  
Significant Difference

The present study aimed to investigate individual differences of causal connectivity between brain regions in attention deficit hyperactivity disorder (ADHD) which was a psychiatric disorder. Resting-state functional magnetic resonance imaging (R-fMRI) data of typically-developing controls (TDC) children group and combined ADHD (ADHD-C) children group were distinguished by the support vector machine (SVM) with linear kernel function, based on regional homogeneity (ReHo), amplitude of low frequency fluctuation (ALFF) and fractional ALFF (FALFF). The highest classification accuracy yielded by ReHo was 90.91 %. Furthermore, the granger causality analysis (GCA) method based on the classified weight map of regions of interesting (ROIs) showed that five causal flows existed significant difference between TDC and ADHD-C. That is, the averaged GCA values of three causal connections (i.e. left VLPFC à left CC1, right PoCG à left CC1, and right PoCG à right CC2) for ADHD-C were separately stronger than those for TDC. And the other two connections (i.e. right FEF à right SOG and right CC1 à right SOG) were weaker for ADHD-C than those for TDC. In addition, only two causality flows (i.e. left VLPFC à left CC1 and right PoCG à right CC2) presented that their GCA values were positively correlation with ADHD index scores, respectively. Our findings revealed that ADHD children represented widespread abnormalities in the causality connectivity, especially involved in the attention and memory related regions. And further provided evidence that the potential neural causality flows could play a key role in characterizing individual’s ADHD.

Topographic Correction for the Data of SQUID-based TEM Using a Ground Loop

2019 ◽  
Vol 24 (1) ◽  
pp. 111-117
Author(s):  
Yanju Ji ◽  
Yi Zhao ◽  
Shangyu Du ◽  
Dongsheng Li ◽  
Yi Zhang ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Quantum Interference ◽  
Low Frequency ◽  
High Sensitivity ◽  
Absolute Error ◽  
Correction Method ◽  
Topographic Effects ◽  
Topographic Correction ◽  
Transient Electromagnetic ◽  
Ground Loop

Superconducting quantum interference device (SQUID) can be used to detect the signal of transient electromagnetic method (TEM) due to its superiority of high sensitivity in the low frequency range. However, the measuring direction of SQUID is hardly consistent with the normal direction of the transmitting coil of a TEM system because of the undulating topography in the field. In this case, the central magnetic field measured by SQUID is only a component of the theoretical central magnetic field. There will be larger errors if we directly use the measured central magnetic field for geological interpretation. To solve this problem, we propose a topographic correction method for the data of SQUID-based TEM using ground loop. The theoretical central magnetic field of the ground loop is calculated after the trapezoidal transmitting current wave is turned off. Then, we use the theoretical central magnetic field of the ground loop as the reference to correct the measured central magnetic field of SQUID-based on the trigonometric function relation between the measuring direction of SQUID and the topographic inclination. The experiment of SQUID-based TEM using a ground loop was carried out in the field. The result shows that at the measurement point with larger topographic inclination, the average absolute error of the measured central magnetic field reduces significantly with the proposed correction method. This method can also be applied to the correction of complex topographic effects when using SQUID to measure three components of magnetic field.

scholarly journals Prestimulus feedback connectivity biases the content of visual experiences

2019 ◽  
Vol 116 (32) ◽  
pp. 16056-16061 ◽  
Author(s):  
Elie Rassi ◽  
Andreas Wutz ◽  
Nadia Müller-Voggel ◽  
Nathan Weisz
Keyword(s):  
Neural Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Brain Regions ◽  
Stimulus Onset ◽  
Neural Excitability ◽  
Gamma Frequency ◽  
Face Area ◽  
Oscillatory Power ◽  
The Impact

Ongoing fluctuations in neural excitability and in networkwide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms—that is, whether or not an object is perceived. Here, we investigated the impact of prestimulus neural fluctuations on the content of perception—that is, whether one or another object is perceived. We recorded neural activity with magnetoencephalography (MEG) before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation in each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the poststimulus period. Applying source localization to the classifier weights suggested early recruitment of primary visual cortex (V1) and ∼160-ms recruitment of the category-sensitive fusiform face area (FFA). These poststimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs. vase reports. In prestimulus intervals, we found no differences in oscillatory power between face vs. vase reports in V1 or in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA before face reports for low-frequency oscillations. Specifically, the strength of prestimulus feedback connectivity (i.e., Granger causality) from FFA to V1 predicted not only the category of the upcoming percept but also the strength of poststimulus neural activity associated with the percept. Our work shows that prestimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.

Temporal correlations in low frequency BOLD fluctuations reveal functional networks

NeuroImage ◽  
2000 ◽  
Vol 11 (5) ◽  
pp. S510
Author(s):  
Mark J. Lowe ◽  
Mario Dzemidzic ◽  
Joseph T. Lurito ◽  
Vincent P. Mathews ◽  
Micheal D. Phillips
Keyword(s):  
Low Frequency ◽  
Functional Networks ◽  
Temporal Correlations

scholarly journals On the role of the corpus callosum in interhemispheric functional connectivity in humans

2017 ◽  
Vol 114 (50) ◽  
pp. 13278-13283 ◽  
Author(s):  
Jarod L. Roland ◽  
Abraham Z. Snyder ◽  
Carl D. Hacker ◽  
Anish Mitra ◽  
Joshua S. Shimony ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Corpus Callosum ◽  
Parietal Lobe ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Limited Sample ◽  
Temporal Correlations ◽  
Before And After

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

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