scholarly journals Spatial variability of low frequency brain signal differentiates brain states

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242330
Author(s):  
Yifeng Wang ◽  
Yujia Ao ◽  
Qi Yang ◽  
Yang Liu ◽  
Yujie Ouyang ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Neural Activity ◽  
Brain Function ◽  
Spatial Organization ◽  
Low Frequency ◽  
Brain Regions ◽  
Temporal Dimension ◽  
Previous Theory ◽  
Brain Functions ◽  
Signal Variability

Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability.

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 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.

Assessment of Directional Connectivity Between Neural Sources Using Effective Connectivity Measures and Particle Filters

2020 ◽  
pp. 2150149
Author(s):  
Santhosh Kumar Veeramalla ◽  
T. V. K. Hanumantha Rao
Keyword(s):  
Neural Activity ◽  
Effective Connectivity ◽  
Brain Regions ◽  
Current Dipole ◽  
Suggested Approach ◽  
Brain Functions ◽  
Direct Exposure ◽  
Signal Processing Algorithms ◽  
Eeg Connectivity ◽  
Time Courses

Electrical neural activity monitoring and recording will increase our understanding of how the human brain works. Tracking mechanisms of neural activity led to better diagnosis and management of severe neurological conditions such as Parkinson’s disease and epilepsy. More importantly, these approaches were used to distinguish between various types of seizures based on the location and direction of the seizure foci, thereby increasing the outcomes of epilepsy surgery. A detailed study was carried out on the role of neural synchrony in brain functions with Electroencephalography (EEG). Most studies had been conducted on EEG connectivity analysis at sensor level. It is not easy to evaluate the connected networks because the volume conductive effect significantly distorts signals because of the electrical conductiveness of the head and often scalp electrodes derive input from the same sources in the brain. These factors help to estimate the real connectivity between brain regions inaccurately. The suggested approach is referred to as EEG source connectivity. The inverse problem is the estimation of the localized current dipole model from the EEG measurements. In order to solve the inverse EEG problem, advanced signal-processing algorithms such as the efficient implementation of PF have been built to facilitate direct exposure to neural dipole sources in real time and measure the connectivity of neural sources time courses using functional and effective connectivity measures.

scholarly journals P119 Brain function and fatigue in patients with inflammatory bowel disease

2020 ◽  
Vol 14 (Supplement_1) ◽  
pp. S195-S196
Author(s):  
A Thomann ◽  
M Schmitgen ◽  
D Kmuche ◽  
M Griebe ◽  
M Ebert ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Function ◽  
Brain Activity ◽  
Low Frequency ◽  
Peak Level ◽  
Brain Regions ◽  
Fmri Data ◽  
Considerable Proportion ◽  
Functional Studies ◽  
Inflammatory Bowel

Abstract Background Fatigue is common in patients with inflammatory bowel diseases (IBD). It occurs in up to 80% of patients with active disease, but also a considerable proportion of patients in remission, and significantly affects quality of life. The underlying mechanisms are still poorly understood, and it is still unclear which patients will suffer from fatigue even in luminally quiescent disease. Task-based brain functional studies have examined neural correlates of fatigueability and found changes in the orbitofrontal cortex (OFC), among other regions. To the best our knowledge, the relationship between brain function and fatigue in IBD has not been investigated. This study aimed to examine the association between fatigue and resting-state brain function in remitted IBD patients. Methods We obtained resting-state-functional MRI (rs-fMRI) data from 45 IBD patients in stable remission without current steroid or biological therapy and 17 healthy controls (HCs). Fatigue was assessed with Würzburger Erschöpfungsinventar Multiple Sklerose (WEIMuS). Preprocessing of rs-fMRI-data and calculation of amplitude of low frequency fluctuations (ALFF) was performed using the Data Processing Assistant for rs-fMRI. The resulting individual maps were analysed via second-level SPM multiple regression models in patients and HC to test for correlations between ALFF data and WEIMuS scores. Age, gender and mean framewise displacement were included as covariates of no interest and results were displayed at p &lt; 0.001 (peak level) with a threshold of spatial extent (k) according to the expected voxels per cluster estimated by SPM. Results Fatigue scores did not differ significantly between patients and controls (mean WEIMuS-scores 17.9 (SD 13.9) vs. 12.3 (SD 16.5), p = .17). Proportions of participants with fatigue scores above the cutoff (&gt;32P.) were nearly identical in patients and HC (8/45 vs. 3/17). In patients, fatigue scores correlated positively with ALFF in the right central operculum and negatively with ALFF in the left OFC and left cerebellum (all p &lt; .001, Figure 1). Fatigue and ALFF in the left cerebellum were also found to correlate in HC. Conclusion This study shows fatigue-associated changes in brain activity in several brain regions. The negative association between fatigue and ALFF in the left OFC of IBD patients was not seen in HC, indicating that reduced ALFF in the OFC may represent a neural correlate of IBD-related fatigue. The OFC is thought to be involved in decision-making, which is described to be impaired in many fatigued IBD patients. If the association between fatigue and brain function detected in our study is confirmed in longitudinal IBD studies, these regions could serve as biomarkers when targeting fatigue in IBD.

Altered fractional amplitude of low frequency fluctuation in Women with Premenstrual Syndrome Via Acupuncture at Sanyinjiao(SP6)

2020 ◽  
Author(s):  
Gaoxiong Duan ◽  
Ya Chen ◽  
Yong Pang ◽  
Zhuo Feng ◽  
Hai Liao ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Neural Activity ◽  
Premenstrual Syndrome ◽  
Temporal Cortex ◽  
Low Frequency ◽  
Brain Regions ◽  
Inferior Temporal Cortex ◽  
Frequency Fluctuation ◽  
Clinical Trial Registration ◽  
Acupuncture Stimulation

Abstract Background: Premenstrual Syndrome(PMS) is a prevalent gynecological disease and is significantly associated with abnormal neural activity. Acupuncture is an effective treatment on PMS in clinical practice. However, few studies have been performed to investigate whether acupuncture might modulate the abnormal neural activity in patients with PMS. Thereby, the aim of the study was to assess alterations of the brain activity induced by acupuncture stimulation in PMS patients. Methods: 20 PMS patients were enrolled in this study. All patients received a 6-min resting-state functional magnetic resonance imaging(rs-fMRI) scan before and after electro-acupuncturing stimulation (EAS) at Sanyinjiao (SP6) acupoint in the late luteal phase of menstrual. Applied the fractional amplitude of low frequency fluctuation(fALFF) method to examine EAS-related brain changes in PMS patients. Results: Compared with pre-EAS at SP6, increased fALFF value in several brain regions induced by SP6, including brainstem, right thalamus, bilateral insula, right paracentral lobule, bilateral cerebellum, meanwhile, decreased fALFF in the left cuneus, right precuneus, left inferior temporal cortex. Conclusions: Our findings provide imaging evidence to support that SP6-related acupuncture stimulation may modulate the neural activity in patients with PMS. This study may partly interpret the neural mechanisms of acupuncture at SP6 which is used to treat PMS patients in clinical. Trial registration:The study was registered on http://www.chictr.org.cn, the Clinical Trial Registration Number is ChiCTR-OPC-15005918, registry in 29/01/2015.

scholarly journals Altered fractional amplitude of low-frequency fluctuation in women with premenstrual syndrome via acupuncture at Sanyinjiao (SP6)

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Gaoxiong Duan ◽  
Ya Chen ◽  
Yong Pang ◽  
Zhuo Feng ◽  
Hai Liao ◽  
...  
Keyword(s):  
Neural Activity ◽  
Premenstrual Syndrome ◽  
Temporal Cortex ◽  
Low Frequency ◽  
Brain Regions ◽  
Trial Registration ◽  
Inferior Temporal Cortex ◽  
Frequency Fluctuation ◽  
Clinical Trial Registration ◽  
Acupuncture Stimulation

Abstract Background Premenstrual syndrome (PMS) is a prevalent gynecological disease and is significantly associated with abnormal neural activity. Acupuncture is an effective treatment on PMS in clinical practice. However, few studies have been performed to investigate whether acupuncture might modulate the abnormal neural activity in patients with PMS. Thereby, the aim of the study was to assess alterations of the brain activity induced by acupuncture stimulation in PMS patients. Methods Twenty PMS patients were enrolled in this study. All patients received a 6-min resting-state functional magnetic resonance imaging (rs-fMRI) scan before and after electro-acupuncturing stimulation (EAS) at Sanyinjiao (SP6) acupoint in the late luteal phase of menstrual. Fractional amplitude of low-frequency fluctuation (fALFF) method was applied to examine the EAS-related brain changes in PMS patients. Results Compared with pre-EAS at SP6, increased fALFF value in several brain regions induced by SP6, including brainstem, right thalamus, bilateral insula, right paracentral lobule, bilateral cerebellum, meanwhile, decreased fALFF in the left cuneus, right precuneus, left inferior temporal cortex. Conclusions Our findings provide imaging evidence to support that SP6-related acupuncture stimulation may modulate the neural activity in patients with PMS. This study may partly interpret the neural mechanisms of acupuncture at SP6 which is used to treat PMS patients in clinical. Trial registration: The study was registered on http://www.chictr.org.cn. The Clinical Trial Registration Number is ChiCTR-OPC-15005918, registry in 29/01/2015.

scholarly journals BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain

2019 ◽  
Author(s):  
D. Kumral ◽  
F. Şansal ◽  
E. Cesnaite ◽  
K. Mahjoory ◽  
E. Al ◽  
...  
Keyword(s):  
Sex Differences ◽  
Low Frequency ◽  
Brain Regions ◽  
Blood Oxygenation ◽  
Eeg Signal ◽  
Brain Response ◽  
Beta Band ◽  
Band Frequency ◽  
Age Related ◽  
Signal Variability

AbstractVariability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability – identified with either hemodynamic or electrophysiological methods – reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25±3 years, N=135) and older (67±4 years, N=54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1–12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15–25 Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

scholarly journals Pre-stimulus feedback connectivity biases the content of visual experiences

2018 ◽  
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 ◽  
Oscillatory Power ◽  
The Impact ◽  
Stimulus Feedback

AbstractOngoing fluctuations in neural excitability and in network-wide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms, i.e. whether an object is perceived or not. Here, we investigated the impact of pre-stimulus neural fluctuations on the content of perception, i.e. whether one or another object is perceived. We recorded neural activity with magnetoencephalography before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation on each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the post-stimulus period. Applying source localization to the classifier weights suggested early recruitment of V1 and ~160 ms recruitment of category-sensitive FFA. These post-stimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs vase reports. In pre-stimulus intervals, we found no differences in oscillatory power between face vs. vase reports neither in V1 nor in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA prior to face reports for low-frequency oscillations. Specifically, the strength of pre-stimulus feedback connectivity (i.e. Granger causality) from FFA to V1 predicted not only the category of the upcoming percept, but also the strength of post-stimulus neural activity associated with the percept. Our work shows that pre-stimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.

scholarly journals Entropy, complexity, and maturity in children’s neural responses during naturalistic mathematics learning

2020 ◽  
Author(s):  
Marie Amalric ◽  
Jessica F. Cantlon
Keyword(s):  
Real World ◽  
Neural Activity ◽  
Mathematics Learning ◽  
Brain Regions ◽  
Multiscale Entropy ◽  
Neural Responses ◽  
Brain Functions ◽  
Temporal Properties ◽  
Neural Processes ◽  
New Evidence

AbstractA major goal of human neuroscience is to understand how the brain functions in the real world, and to measure neural processes under naturalistic conditions that are more ecologically valid than traditional laboratory tasks. A critical step toward this goal is understanding how neural activity during real world naturalistic tasks relates to neural activity in more traditional laboratory tasks. In the present study, we used intersubject correlations to locate reliable stimulus-driven neural processes among children and adults in naturalistic and laboratory versions of a mathematics task that shared the same content. We show that relative to a control condition with grammatical content, naturalistic and simplified mathematics tasks evoked overlapping activation within brain regions previously associated with math semantics. We further examined the temporal properties of children’s neural responses during the naturalistic and laboratory tasks to determine whether temporal patterns of neural activity change over development, or dissociate based on semantic or task content. We introduce a rather novel measure, not yet used in fMRI studies of child learning: neural multiscale entropy. In addition to showing new evidence of naturalistic mathematics processing in the developing brain, we show that neural maturity and neural entropy are two independent but complementary markers of functional brain development. We discuss the implications of these results for the development of neural complexity in children.

scholarly journals Long-range projections coordinate distributed brain-wide neural activity with a specific spatiotemporal profile

2016 ◽  
Vol 113 (51) ◽  
pp. E8306-E8315 ◽  
Author(s):  
Alex T. L. Leong ◽  
Russell W. Chan ◽  
Patrick P. Gao ◽  
Ying-Shing Chan ◽  
Kevin K. Tsia ◽  
...  
Keyword(s):  
Long Range ◽  
Neural Activity ◽  
Visual Processing ◽  
Large Scale ◽  
Functional Integration ◽  
Low Frequency ◽  
Brain Regions ◽  
Blood Oxygenation ◽  
Neural Basis ◽  
Excitatory Neurons

One challenge in contemporary neuroscience is to achieve an integrated understanding of the large-scale brain-wide interactions, particularly the spatiotemporal patterns of neural activity that give rise to functions and behavior. At present, little is known about the spatiotemporal properties of long-range neuronal networks. We examined brain-wide neural activity patterns elicited by stimulating ventral posteromedial (VPM) thalamo-cortical excitatory neurons through combined optogenetic stimulation and functional MRI (fMRI). We detected robust optogenetically evoked fMRI activation bilaterally in primary visual, somatosensory, and auditory cortices at low (1 Hz) but not high frequencies (5–40 Hz). Subsequent electrophysiological recordings indicated interactions over long temporal windows across thalamo-cortical, cortico-cortical, and interhemispheric callosal projections at low frequencies. We further observed enhanced visually evoked fMRI activation during and after VPM stimulation in the superior colliculus, indicating that visual processing was subcortically modulated by low-frequency activity originating from VPM. Stimulating posteromedial complex thalamo-cortical excitatory neurons also evoked brain-wide blood-oxygenation-level–dependent activation, although with a distinct spatiotemporal profile. Our results directly demonstrate that low-frequency activity governs large-scale, brain-wide connectivity and interactions through long-range excitatory projections to coordinate the functional integration of remote brain regions. This low-frequency phenomenon contributes to the neural basis of long-range functional connectivity as measured by resting-state fMRI.

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