Spontaneous Brain Activity Patterns Research Articles

Attentional bias modification (ABM) training induces spontaneous brain activity changes in young women with subthreshold depression: a randomized controlled trial.

Attention bias modification (ABM) training has been suggested to effectively reduce depressive symptoms, and may be useful in the prevention of the illness in individuals with subthreshold symptoms, yet little is known about the spontaneous brain activity changes associated with ABM training. Resting-state functional MRI was used to explore the effects of ABM training on subthreshold depression (SubD) and corresponding spontaneous brain activity changes. Participants were 41 young women with SubD and 26 matched non-depressed controls. Participants with SubD were randomized to receive either ABM or placebo training during 28 sessions across 4 weeks. Non-depressed controls were assessed before training only. Attentional bias, depressive severity, and spontaneous brain activity before and after training were assessed in both training groups. Findings revealed that compared to active control training, ABM training significantly decreased depression symptoms, and increased attention for positive stimuli. Resting-state data found that ABM training significantly reduced amplitude of low-frequency fluctuations (ALFF) of the right anterior insula (AI) and right middle frontal gyrus which showed greater ALFF than non-depressed controls before training; Functional connectivity strength between right AI and the right frontoinsular and right supramarginal gyrus were significantly decreased after training within the ABM group; moreover, the improvement of depression symptoms following ABM significantly correlated with the connectivity strength reductions between right AI and right frontoinsular and right supramarginal gyrus. These results suggest that ABM has the potential to reshape the abnormal patterns of spontaneous brain activity in relevant neural circuits associated with depression.

Distinct patterns of spontaneous brain activity between children and adults with anisometropic amblyopia: a resting-state fMRI study.

To detect the altered spontaneous brain activity patterns in children and adults with anisometropic amblyopia using resting-state functional magnetic resonance imaging (rs-fMRI) technique combined with the amplitude of low-frequency fluctuation (ALFF) method. Thirty-two monocular anisometropic amblyopia and 34 normal-sight controls were divided into child group and adult group. Rs-fMRI was performed in all participants and analysis of ALFF value within the whole brain was conducted in each subject. ALFF value differences between the patients and controls in the two groups were compared via an independent two-sample t test. The amblyopic children mainly exhibited increased ALFF in part of the bilateral calcarine (BA17), the left middle occipital gyrus (BA18/19), and the left postcentral gyrus (BA2). By contrast, the amblyopic adults showed decreased ALFF in the bilateral precuneus cortex (part of BA7), and the standardized ALFF value of bilateral precuneus were correlated with the amount of anisometropia of the amblyopic adults. Rs-fMRI is an effective noninvasive technique for exploring brain activity of the anisometropic amblyopia. Our findings demonstrated that brain activity changed both in amblyopic children and adults under the resting state, and revealed the differences in spontaneous activity patterns between the amblyopic children and adults.

Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study.

ObjectiveThe aim of this study is to use amplitude of low-frequency fluctuation (ALFF) as a method to explore the local features of spontaneous brain activity in patients with primary angle -closure glaucoma (PACG) and ALFFs relationship with the behavioral performances.MethodsA total of twenty one patients with PACG (eight males and 13 females), and twenty one healthy subjects (nine males and twelve females) closely matched in age, sex, and education, each underwent a resting-state functional magnetic resonance imaging scan. The ALFF method was used to assess the local features of spontaneous brain activity. The correlation analysis was used to explore the relationships between the observed mean ALFF signal values of the different areas in PACG patients and the thickness of the retinal nerve fiber layer (RNFL).ResultsCompared with the healthy subjects, patients with PACG had significant lower ALFF areas in the left precentral gyrus, bilateral middle frontal gyrus, bilateral superior frontal gyrus, right precuneus, and right angular gyrus, and higher areas in the right precentral gyrus. In the PACG group, there were significant negative correlations between the mean ALFF signal value of the right middle frontal gyrus and the left mean RNFL thickness (r=−0.487, P=0.033), and between the mean ALFF signal value of the left middle frontal gyrus and the right mean RNFL thickness (r=−0.504, P=0.020).ConclusionPACG mainly involved in the dysfunction in the frontal lobe, which may reflect the underlying pathologic mechanism of PACG.

Abnormal Intrinsic Brain Activity Patterns in Patients with End-Stage Renal Disease Undergoing Peritoneal Dialysis: A Resting-State Functional MR Imaging Study.

To analyze the spontaneous brain activity patterns in patients with end-stage renal disease (ESRD) undergoing peritoneal dialysis (PD) by using resting-state functional magnetic resonance (MR) imaging with an amplitude of low-frequency fluctuations (ALFF) algorithm. This study received institutional review board approval, and all subjects gave informed consent. Forty-four patients with ESRD, 24 of whom were undergoing PD (PD group; eight women; mean age, 34 years ± 8) and 20 who were not undergoing PD or hemodialysis (nondialysis group; six women; mean age, 37 years ± 9) and 24 healthy control subjects (eight women; mean age, 32 years ± 9 years) were included. All subjects underwent neuropsychologic tests, and patients with ESRD underwent laboratory testing. ALFF values were compared among the three groups. The relationship between ALFF values and clinical markers was investigated by using multiple regression analysis. Patients in both the PD and nondialysis groups showed lower ALFF values in default mode network regions than did healthy control subjects (P < .01, false discovery rate corrected). Patients in the PD group showed lower ALFF values than did those in the nondialysis group in the left superior parietal lobe (1.51 ± 0.21 vs 2.01 ± 0.40), left inferior parietal lobe (0.99 ± 0.16 vs 1.13 ± 0.22) and left precuneus (1.45 ± 0.39 vs 1.77 ± 0.41) (P < .01, corrected with simulation software). In patients in the PD group, neuropsychologic test scores correlated with ALFF values of the middle temporal gyrus and the parietal and occipital lobe, serum urea and creatinine levels negatively correlated with ALFF in some default mode network regions, and hemoglobin positively correlated with ALFF in the bilateral precuneus, precentral, and supplementary motor areas (P < .01 corrected). Patients with ESRD who were undergoing PD showed more severe spontaneous brain activity abnormalities that correlate with cognitive impairments than did patients who were not undergoing dialysis. Elevated serum urea, creatinine, and lowered hemoglobin levels affect spontaneous brain activity in patients with ESRD.

Widespread increase of functional connectivity in Parkinson's disease with tremor: a resting-state FMRI study.

Parkinson’s disease (PD) is a clinically heterogeneous disease in the symptomatology dominated by tremor, akinesia, or rigidity. Focusing on PD patients with tremor, this study investigated their discoordination patterns of spontaneous brain activity by combining voxel-wise centrality, seed-based functional connectivity, and network efficiency methods. Sixteen patients and 20 matched healthy controls (HCs) were recruited and underwent structural and resting-state functional MRI scan. Compared with the HCs, the patients exhibited increased centrality in the frontal, parietal, and occipital regions while decreased centrality in the cerebellum anterior lobe and thalamus. Seeded at these regions, a distributed network was further identified that encompassed cortical (default mode network, sensorimotor cortex, prefrontal and occipital areas) and subcortical (thalamus and basal ganglia) regions and the cerebellum and brainstem. Graph-based analyses of this network revealed increased information transformation efficiency in the patients. Moreover, the identified network correlated with clinical manifestations in the patients and could distinguish the patients from HCs. Morphometric analyses revealed decreased gray matter volume in multiple regions that largely accounted for the observed functional abnormalities. Together, these findings provide a comprehensive view of network disorganization in PD with tremor and have important implications for understanding neural substrates underlying this specific type of PD.

Altered Amplitude of Low-frequency Fluctuations in Early and Late Mild Cognitive Impairment and Alzheimer's Disease

Previous studies have shown that the strength of the low frequency fluctuation in the medial-line brain areas are abnormally reduced in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. The purpose of this study was to explore the functional brain changes in early MCI (EMCI) and late MCI (LMCI) patients by measuring the amplitude of the blood oxygenation level dependent (BOLD) functional MRI (fMRI) signals at rest. 35 elderly normal controls (NC), 24 EMCI, 29 LMCI, and 14 AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI2) were included in this study. Resting state fMRI and 3D structural MRI data were acquired. The spatial patterns of spontaneous brain activity were measured by examining the amplitude of low-frequency fluctuations (ALFF) of BOLD signal during rest. A one-way analysis of variance (ANOVA) was then performed on ALFF maps, with age, sex and regional atrophy as covariates. There were widespread ALFF differences among the four groups. As compared with controls, AD, LMCI and EMCI patients showed decreased ALFF mainly in the posterior cingulate cortex, precuneus, right lingual gyrus and thalamus (with a linear trend: NC>EMCI>LMCI>AD), while there was increased activity in the right parahippocampal gyrus (with a linear trend: NC<EMCI<LMCI<AD). Additionally, we also showed that many regions with ALFF changes had significant correlations with the cognitive performance as measured by mini-mental state examination scores (MMSE) and the emotion states as measured by Geriatric Depression Scale (GD scale) for EMCI, LMCI and AD patients, but not for controls. Our results indicated that the significantly altered ALFF activities can be detected at EMCI stage, independent of age, sex and regional atrophy. The present study thus suggests ALFF abnormalities as a potential biomarker for the early diagnosis of AD and further provides insights into biological mechanisms of the diseases.

Altered Pattern of Spontaneous Brain Activity in the Patients with End-Stage Renal Disease: A Resting-State Functional MRI Study with Regional Homogeneity Analysis

PurposeTo investigate the pattern of spontaneous neural activity in patients with end-stage renal disease (ESRD) with and without neurocognitive dysfunction using resting-state functional magnetic resonance imaging (rs-fMRI) with a regional homogeneity (ReHo) algorithm.Materials and Methodsrs-fMRI data were acquired in 36 ESRD patients (minimal nephro-encephalopathy [MNE], n = 19, 13 male, 37±12.07 years; non-nephro-encephalopathy [non-NE], n = 17, 11 male, 38±12.13 years) and 20 healthy controls (13 male, 7 female, 36±10.27 years). Neuropsychological (number connection test type A [NCT-A], digit symbol test [DST]) and laboratory tests were performed in all patients. The Kendall's coefficient of concordance (KCC) was used to measure the regional homogeneity for each subject. The regional homogeneity maps were compared using ANOVA tests among MNE, non-NE, and healthy control groups and post hoc t -tests between each pair in a voxel-wise way. A multiple regression analysis was performed to evaluate the relationships between ReHo index and NCT-A, DST scores, serum creatinine and urea levels, disease and dialysis duration.ResultsCompared with healthy controls, both MNE and non-NE patients showed decreased ReHo in the multiple areas of bilateral frontal, parietal and temporal lobes. Compared with the non-NE, MNE patients showed decreased ReHo in the right inferior parietal lobe (IPL), medial frontal cortex (MFC) and left precuneus (PCu). The NCT-A scores and serum urea levels of ESRD patients negatively correlated with ReHo values in the frontal and parietal lobes, while DST scores positively correlated with ReHo values in the bilateral PCC/precuneus, MFC and inferior parietal lobe (IPL) (all P<0.05, AlphaSim corrected). No significant correlations were found between any regional ReHo values and disease duration, dialysis duration and serum creatinine values in ESRD patients (all P>0.05, AlphaSim corrected).ConclusionDiffused decreased ReHo values were found in both MNE and non-NE patients. The progressively decreased ReHo in the default mode network (DMN), frontal and parietal lobes might be trait-related in MNE. The ReHo analysis may be potentially valuable for elucidating neurocognitive abnormalities of ESRD patients and detecting the development from non-NE to MNE.

Patterns of Spontaneous Brain Activity in Amyotrophic Lateral Sclerosis: A Resting-State fMRI Study

By detecting spontaneous low-frequency fluctuations (LFF) of blood oxygen level–dependent (BOLD) signals, resting-state functional magnetic resonance imaging (rfMRI) measurements are believed to reflect spontaneous cerebral neural activity. Previous fMRI studies were focused on the examination of motor-related areas and little is known about the functional changes in the extra-motor areas in amyotrophic lateral sclerosis (ALS) patients. The aim of this study is to investigate functional cerebral abnormalities in ALS patients on a whole brain scale. Twenty ALS patients and twenty age- and sex-matched healthy volunteers were enrolled. Voxel-based analysis was used to characterize the alteration of amplitude of low frequency fluctuation (ALFF). Compared with the controls, the ALS patients showed significantly decreased ALFF in the visual cortex, fusiform gyri and right postcentral gyrus; and significantly increased ALFF in the left medial frontal gyrus, and in right inferior frontal areas after grey matter (GM) correction. Taking GM volume as covariates, the ALFF results were approximately consistent with those without GM correction. In addition, ALFF value in left medial frontal gyrus was negatively correlated with the rate of disease progression and duration. Decreased functional activity observed in the present study indicates the underlying deficits of the sensory processing system in ALS. Increased functional activity points to a compensatory mechanism. Our findings suggest that ALS is a multisystem disease other than merely motor dysfunction and provide evidence that alterations of ALFF in the frontal areas may be a special marker of ALS.

Spatial patterns of intrinsic neural activity in depressed patients with vascular risk factors as revealed by the amplitude of low-frequency fluctuation

To investigate spatial patterns of intrinsic neural activity of depressed patients with vascular risk factors using resting-state functional magnetic resonance imaging (fMRI) and to examine the relationship between regional activity abnormalities and symptom severity factor, we analyzed spatial patterns of spontaneous brain activity in 19 depressed patients with vascular risk factors and 18 healthy subjects. Intrinsic brain activity was measured by the amplitude of low-frequency fluctuations (ALFF) of the resting-state blood oxygen level dependent signal. Depressed patients with vascular risk factors showed decrease in ALFF in the limbic-cortical-striatal-pallidal-thalamic circuit. Specifically, the altered ALFF values (i.e., left insula and right superior frontal gyrus) were significantly correlated with depression severity in the depressed group. In addition, higher ALFF values in the right middle temporal gyrus and right superior temporal gyrus were observed in depressed patients with vascular risk factors. Our findings reveal distinct functional patterns of abnormal brain activity in depressed patients with vascular risk factors and have implications for the understanding of the pathophysiology of this understudied population.

Early Development of Spatial Patterns of Power-Law Frequency Scaling in fMRI Resting-State and EEG Data in the Newborn Brain

Recent studies have revealed spatial and functional relations in the temporal dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) or electroencephalography (EEG) signals recorded in the adult brain. By modeling the frequency power spectrum of resting-state brain signals with a power-law function 0(f)α1/fα, the power-law exponent α has been shown to relate to the connectivity patterns of spontaneous brain activity that forms so-called rs-fMRI networks in the human adult brain. Here, we present an analysis of the dynamic properties of rs-fMRI and EEG signals acquired both in the newborn and adult brain, and we demonstrate frequency scaling of a power-law kind for orders of magnitude in the hemodynamic (0.01-0.15 Hz) and the electrical (0.2-30 Hz) domain. We show that the spatial segregation of resting-state dynamics of intrinsic fMRI signals in terms of the power-law exponent α is closely related to previously delineated resting-state neuronal architecture that encompasses primary sensory cortices and associate cortex in newborns. Moreover, the spatial profiles of differences in temporal dynamics for rs-fMRI signals could also be observed in EEG measurements in the newborn brain, albeit at a coarser spatial scale, with larger power-law exponents in occipital and parietal cortices compared with signals from the frontal brain.

Spatial patterns of intrinsic brain activity in mild cognitive impairment and alzheimer's disease: A resting‐state functional MRI study

We used resting-state functional MRI to investigate spatial patterns of spontaneous brain activity in 22 healthy elderly subjects, as well as 16 mild cognitive impairment (MCI) and 16 Alzheimer's disease (AD) patients. The pattern of intrinsic brain activity was measured by examining the amplitude of low-frequency fluctuations (ALFF) of blood oxygen level dependent signal during rest. There were widespread ALFF differences among the three groups throughout the frontal, temporal, and parietal cortices. Both AD and MCI patients showed decreased activity mainly in the medial parietal lobe region and lentiform nucleus, while there was increased activity in the lateral temporal regions and superior frontal and parietal regions as compared with controls. Compared with MCI, the AD patients showed decreased activity in the medial prefrontal cortex and increased activity in the superior frontal gyrus and inferior and superior temporal gyri. Specifically, the most significant ALFF differences among the groups appeared in the posterior cingulate cortex, with a reduced pattern of activity when comparing healthy controls, MCI, and AD patients. Additionally, we also showed that the regions with ALFF changes had significant correlations with the cognitive performance of patients as measured by mini-mental state examination scores. Finally, while taking gray matter volume as covariates, the ALFF results were approximately consistent with those without gray matter correction, implying that the functional analysis could not be explained by regional atrophy. Together, our results demonstrate that there is a specific pattern of ALFF in AD and MCI, thus providing insights into biological mechanisms of the diseases.

Transient reduction of tinnitus intensity is marked by concomitant reductions of delta band power

BackgroundTinnitus is an auditory phantom phenomenon characterized by the sensation of sounds without objectively identifiable sound sources. To date, its causes are not well understood. Previous research found altered patterns of spontaneous brain activity in chronic tinnitus sufferers compared to healthy controls, yet it is unknown whether these abnormal oscillatory patterns are causally related to the tinnitus sensation. Partial support for this notion comes from a neurofeedback approach developed by our group, in which significant reductions in tinnitus loudness could be achieved in patients who successfully normalized their patterns of spontaneous brain activity. The current work attempts to complement these studies by scrutinizing how modulations of tinnitus intensity alter ongoing oscillatory activity.ResultsIn the present study the relation between tinnitus sensation and spontaneous brain activity was investigated using residual inhibition (RI) to reduce tinnitus intensity and source-space projected magnetencephalographic (MEG) data to index brain activity. RI is the sustained reduction (criteria: 50% for at least 30 s) in tinnitus loudness after cessation of a tonal tinnitus masker. A pilot study (n = 38) identified 10 patients who showed RI. A significant reduction of power in the delta (1.3–4.0 Hz) frequency band was observed in temporal regions during RI (p ≤ 0.001).ConclusionThe current results suggest that changes of tinnitus intensity induced by RI are mediated by alterations in the pathological patterns of spontaneous brain activity, specifically a reduction of delta activity. Delta activity is a characteristic oscillatory activity generated by deafferented/deprived neuronal networks. This implies that RI effects might reflect the transient reestablishment of balance between excitatory and inhibitory neuronal assemblies, via reafferentation, that have been perturbed (in most tinnitus individuals) by hearing damage. As enhancements have been reported in the delta frequency band for tinnitus at rest, this result conforms to our assumption that a normalization of oscillatory properties of cortical networks is a prerequisite for attenuating the tinnitus sensation. For RI to have therapeutic significance however, this normalization would have to be stabilized.

Independent component analysis of interictal fMRI in focal epilepsy: Comparison with general linear model-based EEG-correlated fMRI

The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG–fMRI data in which abnormalities are not apparent on scalp EEG.

Gap junctions mediate large-scale Turing structures in a mean-field cortex driven by subcortical noise

One of the grand puzzles in neuroscience is establishing the link between cognition and the disparate patterns of spontaneous and task-induced brain activity that can be measured clinically using a wide range of detection modalities such as scalp electrodes and imaging tomography. High-level brain function is not a single-neuron property, yet emerges as a cooperative phenomenon of multiply-interacting populations of neurons. Therefore a fruitful modeling approach is to picture the cerebral cortex as a continuum characterized by parameters that have been averaged over a small volume of cortical tissue. Such mean-field cortical models have been used to investigate gross patterns of brain behavior such as anesthesia, the cycles of natural sleep, memory and erasure in slow-wave sleep, and epilepsy. There is persuasive and accumulating evidence that direct gap-junction connections between inhibitory neurons promote synchronous oscillatory behavior both locally and across distances of some centimeters, but, to date, continuum models have ignored gap-junction connectivity. In this paper we employ simple mean-field arguments to derive an expression for D2, the diffusive coupling strength arising from gap-junction connections between inhibitory neurons. Using recent neurophysiological measurements reported by Fukuda [J. Neurosci. 26, 3434 (2006)], we estimate an upper limit of D2 approximately 0.6cm2. We apply a linear stability analysis to a standard mean-field cortical model, augmented with gap-junction diffusion, and find this value for the diffusive coupling strength to be close to the critical value required to destabilize the homogeneous steady state. Computer simulations demonstrate that larger values of D2 cause the noise-driven model cortex to spontaneously crystalize into random mazelike Turing structures: centimeter-scale spatial patterns in which regions of high-firing activity are intermixed with regions of low-firing activity. These structures are consistent with the spatial variations in brain activity patterns detected with the BOLD (blood oxygen-level-dependent) signal detected with magnetic resonance imaging, and may provide a natural substrate for synchronous gamma-band rhythms observed across separated EEG (electroencephalogram) electrodes.

Neuronal Computations with Stochastic Network States

Neuronal networks in vivo are characterized by considerable spontaneous activity, which is highly complex and intrinsically generated by a combination of single-cell electrophysiological properties and recurrent circuits. As seen, for example, during waking compared with being asleep or under anesthesia, neuronal responsiveness differs, concomitant with the pattern of spontaneous brain activity. This pattern, which defines the state of the network, has a dramatic influence on how local networks are engaged by inputs and, therefore, on how information is represented. We review here experimental and theoretical evidence of the decisive role played by stochastic network states in sensory responsiveness with emphasis on activated states such as waking. From single cells to networks, experiments and computational models have addressed the relation between neuronal responsiveness and the complex spatiotemporal patterns of network activity. The understanding of the relation between network state dynamics and information representation is a major challenge that will require developing, in conjunction, specific experimental paradigms and theoretical frameworks.