Measuring the Frequency-Specific Functional Connectivity Using Wavelet Coherence Analysis in Stroke Rats Based on Intrinsic Signals.
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ABSTRACT:
SUBMITTER: Mohammadzadeh L
PROVIDER: S-EPMC7286921 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The present study aimed to evaluate the functional connectivity (FC) in relevant cortex areas during simulated driving with distraction based on functional near-infrared spectroscopy (fNIRS) method. Twelve subjects were recruited to perform three types of driving tasks, namely, straight driving, straight driving with secondary auditory task, and straight driving with secondary visual vigilance task, on a driving simulator. The wavelet amplitude (WA) and wavelet phase coherence (WPCO) of the fNIRS signals were calculated in six frequency intervals: I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; IV, 0.021-0.052 Hz; and V, 0.0095-0.021 Hz, VI, 0.005-0.0095Hz. Results showed that secondary tasks during driving led to worse driving performance, brain activity changes, and dynamic configuration of the connectivity. The significantly lower WA value in the right motor cortex in interval IV, and higher WPCO values in intervals II, V, and VI were found with additional auditory task. Significant standard deviation of speed and lower WA values in the left prefrontal cortex and right prefrontal cortex in interval VI, and lower WPCO values in intervals I, IV, V, and VI were found under the additional visual vigilance task. The results suggest that the changed FC levels in intervals IV, V, and VI were more likely to reflect the driver's distraction condition. The present study provides new insights into the relationship between distracted driving behavior and brain activity. The method may be used for the evaluation of drivers' attention level.
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Project description:UnlabelledBackgroundAutism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.MethodsWe analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.ResultsResults demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.ConclusionsInterhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.
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Project description:Several neuroimaging studies have examined cerebral function in patients who suffer from aphasia, but the mechanism underlying this disorder remains poorly understood. In this study, we examined alterations in the local regional and remote interregional network cerebral functions in aphasia combined with amplitude of low-frequency fluctuations and interregional functional connectivity (FC) using resting-state functional magnetic resonance imaging. A total of 17 post-stroke aphasic patients, all having suffered a stroke in the left hemisphere, as well as 20 age- and sex-matched healthy controls, were enrolled in this study. The aphasic patients showed significantly increased intrinsic regional activity mainly in the contralesional mesial temporal (hippocampus/parahippocampus, [HIP/ParaHIP]) and lateral temporal cortices. In addition, intrinsic regional activity in the contralesional HIP/ParaHIP was negatively correlated with construction score. Aphasic patients showed increased remote interregional FC between the contralesional HIP/ParaHIP and fusiform gyrus, but reduced FC in the ipsilesional occipital and parietal cortices. These findings suggested that the intrinsic regional brain dysfunctions in aphasia were related to interregional functional connectivity. Changes in the intrinsic regional brain activity and associated remote functional connectivity pattern would provide valuable information to enhance the understanding of the pathophysiological mechanisms of aphasia.
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Project description:The aim of this study was to investigate if discrete wavelet decomposition provides additional insight into resting-state processes through the analysis of functional connectivity within specific frequency ranges within the default mode network (DMN) that may be affected by mild traumatic brain injury (mTBI). Participants included 32 mTBI patients (15 with postconcussive syndrome [PCS+] and 17 without [PCS-]). mTBI patients received resting-state functional magnetic resonance imaging (rs-fMRI) at acute (within 10 days of injury) and chronic (6 months postinjury) time points and were compared with 31 controls (healthy control [HC]). The wavelet decomposition divides the time series into multiple frequency ranges based on four scaling factors (SF1: 0.125-0.250?Hz, SF2: 0.060-0.125?Hz, SF3: 0.030-0.060?Hz, SF4: 0.015-0.030?Hz). Within each SF, wavelet connectivity matrices for nodes of the DMN were created for each group (HC, PCS+, PCS-), and bivariate measures of strength and diversity were calculated. The results demonstrate reduced strength of connectivity in PCS+ patients compared with PCS- patients within SF1 during both the acute and chronic stages of injury, as well as recovery of connectivity within SF1 across the two time points. Furthermore, the PCS- group demonstrated greater network strength compared with controls at both time points, suggesting a potential compensatory or protective mechanism in these patients. These findings stress the importance of investigating resting-state connectivity within multiple frequency ranges; however, many of our findings are within SF1, which may overlap with frequencies associated with cardiac and respiratory activities.
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Project description:Optically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that provide improved data quality, accommodate any subject group, allow data capture during movement and potentially reduce cost. However, OPM-MEG is a nascent technology and, to realise its potential, it must be shown to facilitate key neuroscientific measurements, such as the characterisation of brain networks. Networks, and the connectivities that underlie them, have become a core area of neuroscientific investigation, and their importance is underscored by many demonstrations of their disruption in brain disorders. Consequently, a demonstration of network measurements using OPM-MEG would be a significant step forward. Here, we aimed to show that a wearable 50-channel OPM-MEG system enables characterisation of the electrophysiological connectome. To this end, we measured connectivity in the resting state and during a visuo-motor task, using both OPM-MEG and a state-of-the-art 275-channel cryogenic MEG device. Our results show that resting-state connectome matrices from OPM and cryogenic systems exhibit a high degree of similarity, with correlation values >70%. In addition, in task data, similar differences in connectivity between individuals (scanned multiple times) were observed in cryogenic and OPM-MEG data, again demonstrating the fidelity of the OPM-MEG device. This is the first demonstration of network connectivity measured using OPM-MEG, and results add weight to the argument that OPMs will ultimately supersede cryogenic sensors for MEG measurement.
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Project description:Research has shown that inflammatory processes affect brain function and behavior through several neuroimmune pathways. However, high order brain functions affected by inflammation largely remain to be defined. Resting state functional connectivity of synchronized oscillatory activity is a valid approach to understand network processing and high order brain function under different experimental conditions. In the present study multi-electrode EEG recording in awake, freely moving rats was used to study resting state connectivity after administration of lipopolysaccharides (LPS). Male Wistar rats were implanted with 10 cortical surface electrodes and administered with LPS (2 mg/kg) and monitored for symptoms of sickness at 3, 6 and 24 h. Resting state connectivity and power were computed at baseline, 6 and 24 h. Three prominent connectivity bands were identified using a method resistant to spurious correlation: alpha (5-15 Hz), beta-gamma (20-80 Hz), and high frequency oscillation (150-200 Hz). The most prominent connectivity band, alpha, was strongly reduced 6 h after LPS administration, and returned to baseline at 24 h. Beta-gamma connectivity was also reduced at 6 h and remained reduced at 24 h. Interestingly, high frequency oscillation connectivity remained unchanged at 6 h and was impaired 24 h after LPS challenge. Expected elevations in delta and theta power were observed at 6 h after LPS administration, when behavioral symptoms of sickness were maximal. Notably, gamma and high frequency power were reduced 6 h after LPS and returned to baseline by 24 h, when the effects on connectivity were more evident. Finally, increases in cross-frequency coupling elicited by LPS were detected at 6 h for theta-gamma and at 24 h for theta-high frequency oscillations. These studies show that LPS challenge profoundly affects EEG connectivity across all identified bands in a time-dependent manner indicating that inflammatory processes disrupt both bottom-up and top-down communication across the cortex during the peak and resolution of inflammation.
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Project description:Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with altered brain connectivity. Previous neuroimaging research demonstrates inconsistent results, particularly in studies of functional connectivity in ASD. Typically, these inconsistent findings are results of studies using static measures of resting-state functional connectivity. Recent work has demonstrated that functional brain connections are dynamic, suggesting that static connectivity metrics fail to capture nuanced time-varying properties of functional connections in the brain. Here we used a dynamic functional connectivity approach to examine the differences in the strength and variance of dynamic functional connections between individuals with ASD and healthy controls (HCs). The variance of dynamic functional connections was defined as the respective standard deviations of the dynamic functional connectivity strength across time. We utilized a large multicenter dataset of 507 male subjects (209 with ASD and 298 HC, from 6 to 36 years old) from the Autism Brain Imaging Data Exchange (ABIDE) to identify six distinct whole-brain dynamic functional connectivity states. Analyses demonstrated greater variance of widespread long-range dynamic functional connections in ASD (P < 0.05, NBS method) and weaker dynamic functional connections in ASD (P < 0.05, NBS method) within specific whole-brain connectivity states. Hypervariant dynamic connections were also characterized by weaker connectivity strength in ASD compared with HC. Increased variance of dynamic functional connections was also related to ASD symptom severity (ADOS total score) (P < 0.05), and was most prominent in connections related to the medial superior frontal gyrus and temporal pole. These results demonstrate that greater intraindividual dynamic variance is a potential biomarker of ASD. Hum Brain Mapp 38:5740-5755, 2017. © 2017 Wiley Periodicals, Inc.
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Project description:PurposeTo reveal the physiological mechanism of the decline in cognitive function after sleep deprivation, a within-subject study was performed to assess sleep deprivation effects on phase synchronization, as revealed by wavelet phase coherence (WPCO) analysis of prefrontal tissue oxyhemoglobin signals.Materials and methodsTwenty subjects (10 male and 10 female, 25.5 ± 3.5 years old) were recruited to participate in two tests: one without sleep deprivation (group A) and the other with 24 h of sleep deprivation (group B). Before the test, each subject underwent a subjective evaluation using visual analog scales. A cognitive task was performed by judging three random numbers. Continuous recordings of the near-infrared spectroscopy (NIRS) signals were obtained from both the left and right prefrontal lobes during rest, task, and post-task periods. The WPCO of cerebral Delta [HbO2] signals were analyzed for these three periods for both groups A and B.ResultsSix frequency intervals were defined: I: 0.6-2 Hz (cardiac activity), II: 0.145-0.6 Hz (respiratory activity), III: 0.052-0.145 Hz (myogenic activity), IV: 0.021-0.052 Hz (neurogenic activity), V: 0.0095-0.021 Hz (nitric oxide related endothelial activity) and VI: 0.005-0.0095 Hz (non-nitric oxide related endothelial activity). WPCO in intervals III (F = 5.955, p = 0.02) and V (F = 4.7, p = 0.037) was significantly lower in group B than in group A at rest. During the task period, WPCO in intervals III (F = 5.175, p = 0.029) and IV (F = 4.585, p = 0.039) was significantly lower in group B compared with group A. In the post-task recovery period, the WPCO in interval III (F = 6.125, p = 0.02) was significantly lower in group B compared with group A. Reaction time was significantly prolonged, and the accuracy rate and F1 score both declined after sleep deprivation.ConclusionsThe decline in WPCO after sleep deprivation indicates reduced phase synchronization between left and right prefrontal oxyhemoglobin oscillations, which may contribute to the diminished cognitive function.
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Project description:Intrinsic optical signals constitute a noninvasive biomarker promising the objective assessment of retinal photoreceptor function. We employed a commercial optical coherence tomography (OCT) system and an OCT signal model for evaluation of optical path length (OPL) changes in the temporal outer retina of five healthy subjects during light adaptation. Data were acquired at 30 time points, in ambient light and during long duration stimulation with white light, and analyzed, employing a signal model based on the sum of seven Gaussian curves corresponding to all relevant anatomical structures of the outer retina. During light stimulation, mean OPL between rod outer segment tips (ROST) and the retinal pigment epithelium (RPE) decreased by 21.4 ± 3.5%. Further, OPL between the external-limiting membrane (ELM) and the RPE decreased by 5.2 ± 0.9% versus baseline, while OPL between ELM and ROST showed an initial decrease by 2.1 ± 1.6% versus baseline and, thereafter, increased by 2.8 ± 2.1% versus baseline. Thus, the presented approach allowed for assess to dynamic changes in the outer retina in response to light. The change in the subretinal space occurring in the context of light adaptation could be measured using a standard OCT platform and a dedicated signal model.
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