Local Brain Activity Research Articles

Altered spontaneous activity of posterior cingulate cortex and superior temporal gyrus are associated with a smoking cessation treatment outcome using varenicline revealed by regional homogeneity

Compared to nonsmokers, smokers exhibit a number of potentially important differences in regional brain function. However, little is known about the associations between the local spontaneous brain activity and smoking cessation treatment outcomes. In the present analysis, we aimed to evaluate whether the local features of spontaneous brain activity prior to the target quit date was associated with the smoking cessation outcomes. All the participants underwent magnetic resonance imaging scans and smoking-related behavioral assessments. After a 12-week treatment with varenicline, 23 smokers succeeded in quitting smoking and 32 failed. Smokers underwent functional magnetic resonance imaging (fMRI) scanning prior to an open label smoking cessation treatment trial. Regional homogeneity (ReHo) was used to measure spontaneous brain activity, and whole-brain voxel-wise comparisons of ReHo were performed to detect brain regions with altered spontaneous brain activity between relapser and quitter groups. After controlling for potentially confounding factors including years of education, years smoked, cigarettes smoked per day and FTND score as covariates, compared to quitters, relapsers displayed significantly decreased ReHo in bilateral posterior cingulate cortex (PCC), as well as increased ReHo in left superior temporal gyrus (STG). These preliminary results suggest that regional brain function variables may be promising predictors of smoking relapse. This study provided novel insights into the neurobiological mechanisms underlying smoking relapse. A deeper understanding of the neurobiological mechanisms associated with relapse may result in novel pharmacological and behavioral interventions.

Dynamic coupling of complex brain networks and dual-task behavior

Multi-tasking is a familiar situation where behavioral performance is often challenged. To date, fMRI studies investigating the neural underpinning of dual-task interference have mostly relied on local brain activation maps or static brain connectivity networks. Here, based on task fMRI we explored how fluctuations in behavior during concurrent performance of a visuospatial and a speech task relate to alternations in the topology of dynamic brain connectivity networks. We combined a time-resolved functional connectivity and complex network analysis with a sliding window approach applied to the trial by trial behavioral responses to investigate the coupling between dynamic brain networks and dual-task behavior at close temporal proximity. Participants showed fluctuations in their dual-task behavior over time, with the accuracy in the component tasks being statistically independent from one another. On the global level of brain networks we found that dynamic changes of network topology were differentially coupled with the behavior in each component task during the course of dual-tasking. While momentary decrease in the global efficiency of dynamic brain networks correlated with subsequent increase in visuospatial accuracy, better speech performance was preceded by higher global network efficiency and was followed by an increase in between-module connectivity over time. Additionally, dynamic alternations in the modular organization of brain networks at the posterior cingulate cortex were differentially predictive for the visuospatial as compared to the speech accuracy over time. Our results provide the first evidence that, during the course of dual-tasking, each component task is supported by a distinct topological configuration of brain connectivity networks. This finding suggests that the failure of functional brain connectivity networks to adapt to an optimal topology supporting the performance in both component tasks at the same time contributes to the moment to moment fluctuations in dual-task behavior.

Cingulo-opercular network activity maintains alertness

Previous investigations of alertness have confounded it with selective attention because targets were highly predictable. To truly isolate alertness we devised a sparse event-related design with many different randomly appearing and interleaved auditory and visual targets, thereby rendering prediction inefficient. Using functional magnetic resonance imaging, we then analyzed the influence of local brain activity variations prior to task appearance on reaction times, thus avoiding signal contributions from stimulus-driven attention. Higher pre-stimulus activity in a cingulo-opercular network, and the default mode network, resulted in faster response speed but only the former network showed task-positive responses. Conversely, dorsal attention network pre-stimulus activity was overall irrelevant and on auditory trials even detrimental to performance. Thus, in a paradigm where no information predicted timing, modality or properties of a subsequent stimulus, our results dissociate alertness, both anatomically and functionally, from attention and establish the central role of the cingulo-opercular network for sustaining alertness.

Sensorimotor modulation by botulinum toxin A in post-stroke arm spasticity: Passive hand movement

IntroductionIn post-stroke spasticity, functional imaging may uncover modulation in the central sensorimotor networks associated with botulinum toxin type A (BoNT) therapy. Investigations were performed to localize brain activation changes in stroke patients treated with BoNT for upper limb spasticity using functional magnetic resonance imaging (fMRI). MethodsSeven ischemic stroke patients (4 females; mean age 58.86) with severe hand paralysis and notable spasticity were studied. Spasticity was scored according to the modified Ashworth scale (MAS). fMRI examination was performed 3 times: before (W0) and 4 (W4) and 11weeks (W11) after BoNT. The whole-brain fMRI data were acquired during paced repetitive passive movements of the plegic hand (flexion/extension at the wrist) alternating with rest. Voxel-by-voxel statistical analysis using the General Linear Model (GLM) implemented in FSL (v6.00)/FEAT yielded group session-wise statistical maps and paired between-session contrasts, thresholded at the corrected cluster-wise significance level of p<0.05. ResultsAs expected, BoNT transiently lowered MAS scores at W4. Across all the sessions, fMRI activation of the ipsilesional sensorimotor cortex (M1, S1, and SMA) dominated. At W4, additional clusters transiently emerged bilaterally in the cerebellum, in the contralesional sensorimotor cortex, and in the contralesional occipital cortex. Paired contrasts demonstrated significant differences W4>W0 (bilateral cerebellum and contralesional occipital cortex) and W4>W11 (ipsilesional cerebellum and SMA). The remaining paired contrast (W0>W11) showed activation decreases mainly in the ipsilesional sensorimotor cortex (M1, S1, and SMA). ConclusionsThe present study confirms the feasibility of using passive hand movements to map the cerebral sensorimotor networks in patients with post-stroke arm spasticity and demonstrates that BoNT-induced spasticity relief is associated with changes in task-induced central sensorimotor activation, likely mediated by an altered afferent drive from the spasticity-affected muscles.

Altered Local Spontaneous Brain Activity in Juvenile Myoclonic Epilepsy: A Preliminary Resting-State fMRI Study.

Purpose. The purpose of this study was to evaluate the regional synchronization of brain in patients with juvenile myoclonic epilepsy (JME). Methods. Resting-state fMRI data were acquired from twenty-one patients with JME and twenty-two healthy subjects. Regional homogeneity (ReHo) was used to analyze the spontaneous activity in whole brain. Two-sample t-test was performed to detect the ReHo difference between two groups. Correlations between the ReHo values and features of seizures were calculated further. Key Findings. Compared with healthy controls, patients showed significantly increased ReHo in bilateral thalami and motor-related cortex regions and a substantial reduction of ReHo in cerebellum and occipitoparietal lobe. In addition, greater ReHo value in the left paracentral lobule was linked to the older age of onset in patients. Significance. These findings implicated the abnormality of thalamomotor cortical network in JME which were associated with the genesis and propagation of epileptiform activity. Moreover, our study supported that the local brain spontaneous activity is a potential tool to investigate the epileptic activity and provided important insights into understanding the pathophysiological mechanisms of JME.

Optimized parallel transmit and receive radiofrequency coil for ultrahigh-field MRI of monkeys

Monkeys are a valuable model for investigating the structure and function of the brain. To attain the requisite resolution to resolve fine anatomical detail and map localized brain activation requires radiofrequency (RF) coils that produce high signal-to-noise ratios (SNRs) both spatially (image SNR) and temporally. Increasing the strength of the static magnetic field is an effective method to improve SNR, yet this comes with commensurate challenges in RF coil design. First, at ultrahigh field strengths, the magnetic field produced by a surface coil in a dielectric medium is asymmetric. In neuroimaging of rhesus macaques, this complex field pattern is compounded by the heterogeneous structure of the head. The confluence of these effects results in a non-uniform flip angle, but more markedly, a suboptimal circularly polarized mode with reduced transmit efficiency. Secondly, susceptibility-induced geometric distortions are exacerbated when performing echo-planar imaging (EPI), which is a standard technique in functional studies. This requires receive coils capable of parallel imaging with low noise amplification during image reconstruction. To address these challenges at 7T, this study presents a parallel (8-channel) transmit coil developed for monkey imaging, along with a highly parallel (24-channel) receive coil. RF shimming with the parallel-transmit coil produced significant advantages—the transmit field was 38% more uniform than a traditional circularly polarized mode and 54% more power-efficient, demonstrating that parallel-transmit coils should be used for monkey imaging at ultrahigh field strengths. The receive coil had the ability to accelerate along an arbitrary axis with at least a three-fold reduction factor, thereby reducing geometric distortions in whole-brain EPI.

Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data.

A new method for the analysis and localization of brain activity has been developed, based on multichannel magnetic field recordings, over minutes, superimposed on the MRI of the individual. Here, a high resolution Fourier Transform is obtained over the entire recording period, leading to a detailed multi-frequency spectrum. Further analysis implements a total decomposition of the frequency components into functionally invariant entities, each having an invariant field pattern localizable in recording space. The method, addressed as functional tomography, makes it possible to find the distribution of magnetic field sources in space. Here, the method is applied to the analysis of simulated data, to oscillating signals activating a physical current dipoles phantom, and to recordings of spontaneous brain activity in 10 healthy adults. In the analysis of simulated data, 61 dipoles are localized with 0.7 mm precision. Concerning the physical phantom the method is able to localize three simultaneously activated current dipoles with 1 mm precision. Spatial resolution 3 mm was attained when localizing spontaneous alpha rhythm activity in 10 healthy adults, where the alpha peak was specified for each subject individually. Co-registration of the functional tomograms with each subject's head MRI localized alpha range activity to the occipital and/or posterior parietal brain region. This is the first application of this new functional tomography to human brain activity. The method successfully provides an overall view of brain electrical activity, a detailed spectral description and, combined with MRI, the localization of sources in anatomical brain space.

Decreased Regional Homogeneity in Patients With Acute Mild Traumatic Brain Injury: A Resting-State fMRI Study.

Mild traumatic brain injury (mTBI) is characterized by structural disconnection and large-scale neural network dysfunction in the resting state. However, little is known concerning the intrinsic changes in local spontaneous brain activity in patients with mTBI. The aim of the current study was to assess regional synchronization in acute mTBI patients. Fifteen acute mTBI patients and 15 sex-, age-, and education-matched healthy controls (HCs) were studied. We used the regional homogeneity (ReHo) method to map local connectivity across the whole brain and performed a two-sample t-test between the two groups. Compared with HCs, patients with acute mTBI showed significantly decreased ReHo in the left insula, left precentral/postcentral gyrus, and left supramarginal gyrus (p < 0.05, AlphaSim corrected). The ReHo index of the left insula showed a positive correlation with the Mini-Mental State Examination (MMSE) scores across all acute mTBI patients (p < 0.05, uncorrected). The ReHo method may provide an objective biomarker for evaluating the functional abnormity of mTBI in the acute setting.

Altered regional homogeneity of spontaneous brain activity in idiopathic trigeminal neuralgia.

The pathophysiology of idiopathic trigeminal neuralgia (ITN) has conventionally been thought to be induced by neurovascular compression theory. Recent structural brain imaging evidence has suggested an additional central component for ITN pathophysiology. However, far less attention has been given to investigations of the basis of abnormal resting-state brain activity in these patients. The objective of this study was to investigate local brain activity in patients with ITN and its correlation with clinical variables of pain. Resting-state functional magnetic resonance imaging data from 17 patients with ITN and 19 age- and sex-matched healthy controls were analyzed using regional homogeneity (ReHo) analysis, which is a data-driven approach used to measure the regional synchronization of spontaneous brain activity. Patients with ITN had decreased ReHo in the left amygdala, right parahippocampal gyrus, and left cerebellum and increased ReHo in the right inferior temporal gyrus, right thalamus, right inferior parietal lobule, and left postcentral gyrus (corrected). Furthermore, the increase in ReHo in the left precentral gyrus was positively correlated with visual analog scale (r=0.54; P=0.002). Our study found abnormal functional homogeneity of intrinsic brain activity in several regions in ITN, suggesting the maladaptivity of the process of daily pain attacks and a central role for the pathophysiology of ITN.

Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks

Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual’s cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

Localization of brain activities using multiway analysis of EEG tensor via EMD and reassigned TF representation.

Electroencephalogram (EEG) is widely used for monitoring, diagnosis purposes and also for study of brain's physiological, mental and functional abnormalities. Processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. EEG signal processing tends to describe and quantify these variations in such a way that they are localized in temporal, spectral and spatial domain. Here we use multi-way (Tensor) analysis for localizing the EEG events. We used EMD process for decomposing EEG into distinct oscillatory modes, which are then mapped to TF plane using the near optimal Reassigned Spectrogram. Temporal, Spatial and Spectral information of the Multichannel EEG are then used to generate a three-way Frequency-Time-Space EEG tensor. Exploiting EMD also enables us to detrend the EEG recordings. Simulation results on both synthetic and real EEG data show that tensor analysis greatly improve separation and localization of overlapping events in EEG and it could be effectively exploited for detecting and characterizing the evoked potentials.

Feature analysis for correlation studies of simultaneous EEG-fMRI data: A proof of concept for neurofeedback approaches.

The identification and interpretation of facial expressions is an important feature of social cognition. This characteristic is often impaired in various neurodevelopmental disorders. Recent therapeutic approaches to intervene in social communication impairments include neurofeedback (NF). In this study, we present a NF real-time functional Magnetic Resonance Imaging (rt-fMRI), combined with electroencephalography (EEG) to train social communication skills. In this sense, we defined the right Superior Temporal Sulcus as our target region-of-interest. To analyze the correlation between the fMRI regions of interest and the EEG data, we transposed the sources located at the nearest cortical location to the target region. We extracted a set of 75 features from EEG segments and performed a correlation analysis with the brain activations extracted from rt-fMRI in the right pSTS region. The finding of significant correlations of simultaneously measured signals in distinct modalities (EEG and fMRI) is promising. Future studies should address whether the observed correlation levels between local brain activity and scalp measures are sufficient to implement NF approaches.

Cognitive and neural strategies during control of the anterior cingulate cortex by fMRI neurofeedback in patients with schizophrenia.

Cognitive functioning is impaired in patients with schizophrenia, leading to significant disabilities in everyday functioning. Its improvement is an important treatment target. Neurofeedback (NF) seems a promising method to address the neural dysfunctions underlying those cognitive impairments. The anterior cingulate cortex (ACC), a central hub for cognitive processing, is one of the brain regions known to be dysfunctional in schizophrenia. Here we conducted NF training based on real-time functional magnetic resonance imaging (fMRI) in patients with schizophrenia to enable them to control their ACC activity. Training was performed over 3 days in a group of 11 patients with schizophrenia and 11 healthy controls. Social feedback was provided in accordance with the evoked activity in the selected region of interest (ROI). Neural and cognitive strategies were examined off-line. Both groups learned to control the activity of their ACC but used different neural strategies: patients activated the dorsal and healthy controls the rostral subdivision. Patients mainly used imagination of music to elicit activity and the control group imagination of sports. In a stepwise regression analysis, the difference in neural control did not result from the differences in cognitive strategies but from diagnosis alone. Based on social reinforcers, patients with schizophrenia can learn to regulate localized brain activity. However, cognitive strategies and neural network location differ from healthy controls. These data emphasize that for therapeutic interventions in patients with schizophrenia compensatory strategies may emerge. Specific cognitive skills or specific dysfunctional networks should be addressed to train impaired skills. Social NF based on fMRI may be one method to accomplish precise learning targets.

Dynamic brain architectures in local brain activity and functional network efficiency associate with efficient reading in bilinguals

The human brain is organized as a dynamic network, in which both regional brain activity and inter-regional connectivity support high-level cognitive processes, such as reading. However, it is still largely unknown how the functional brain network organizes to enable fast and effortless reading processing in the native language (L1) but not in a non-proficient second language (L2), and whether the mechanisms underlying local activity are associated with connectivity dynamics in large-scale brain networks. In the present study, we combined activation-based and multivariate graph-theory analysis with functional magnetic resonance imaging data to address these questions. Chinese–English unbalanced bilinguals read narratives for comprehension in Chinese (L1) and in English (L2). Compared with L2, reading in L1 evoked greater brain activation and recruited a more globally efficient but less clustered network organization. Regions with both increased network efficiency and enhanced brain activation in L1 reading were mostly located in the fronto-temporal reading-related network (RN), whereas regions with decreased global network efficiency, increased clustering, and more deactivation in L2 reading were identified in the default mode network (DMN). Moreover, functional network efficiency was closely associated with local brain activation, and such associations were also modulated by reading efficiency in the two languages. Our results demonstrate that an economical and integrative brain network topology is associated with efficient reading, and further reveal a dynamic association between network efficiency and local activation for both RN and DMN. These findings underscore the importance of considering interregional connectivity when interpreting local BOLD signal changes in bilingual reading.

A novel fMRI paradigm suggests that pedaling-related brain activation is altered after stroke.

The purpose of this study was to examine the feasibility of using functional magnetic resonance imaging (fMRI) to measure pedaling-related brain activation in individuals with stroke and age-matched controls. We also sought to identify stroke-related changes in brain activation associated with pedaling. Fourteen stroke and 12 control subjects were asked to pedal a custom, MRI-compatible device during fMRI. Subjects also performed lower limb tapping to localize brain regions involved in lower limb movement. All stroke and control subjects were able to pedal while positioned for fMRI. Two control subjects were withdrawn due to claustrophobia, and one control data set was excluded from analysis due to an incidental finding. In the stroke group, one subject was unable to enter the gantry due to excess adiposity, and one stroke data set was excluded from analysis due to excessive head motion. Consequently, 81% of subjects (12/14 stroke, 9/12 control) completed all procedures and provided valid pedaling-related fMRI data. In these subjects, head motion was ≤3 mm. In both groups, brain activation localized to the medial aspect of M1, S1, and Brodmann’s area 6 (BA6) and to the cerebellum (vermis, lobules IV, V, VIII). The location of brain activation was consistent with leg areas. Pedaling-related brain activation was apparent on both sides of the brain, with values for laterality index (LI) of –0.06 (0.20) in the stroke cortex, 0.05 (±0.06) in the control cortex, 0.29 (0.33) in the stroke cerebellum, and 0.04 (0.15) in the control cerebellum. In the stroke group, activation in the cerebellum – but not cortex – was significantly lateralized toward the damaged side of the brain (p = 0.01). The volume of pedaling-related brain activation was smaller in stroke as compared to control subjects. Differences reached statistical significance when all active regions were examined together [p = 0.03; 27,694 (9,608) μL stroke; 37,819 (9,169) μL control]. When individual regions were examined separately, reduced brain activation volume reached statistical significance in BA6 [p = 0.04; 4,350 (2,347) μL stroke; 6,938 (3,134) μL control] and cerebellum [p = 0.001; 4,591 (1,757) μL stroke; 8,381 (2,835) μL control]. Regardless of whether activated regions were examined together or separately, there were no significant between-group differences in brain activation intensity [p = 0.17; 1.30 (0.25)% stroke; 1.16 (0.20)% control]. Reduced volume in the stroke group was not observed during lower limb tapping and could not be fully attributed to differences in head motion or movement rate. There was a tendency for pedaling-related brain activation volume to increase with increasing work performed by the paretic limb during pedaling (p = 0.08, r = 0.525). Hence, the results of this study provide two original and important contributions. First, we demonstrated that pedaling can be used with fMRI to examine brain activation associated with lower limb movement in people with stroke. Unlike previous lower limb movements examined with fMRI, pedaling involves continuous, reciprocal, multijoint movement of both limbs. In this respect, pedaling has many characteristics of functional lower limb movements, such as walking. Thus, the importance of our contribution lies in the establishment of a novel paradigm that can be used to understand how the brain adapts to stroke to produce functional lower limb movements. Second, preliminary observations suggest that brain activation volume is reduced during pedaling post-stroke. Reduced brain activation volume may be due to anatomic, physiology, and/or behavioral differences between groups, but methodological issues cannot be excluded. Importantly, brain action volume post-stroke was both task-dependent and mutable, which suggests that it could be modified through rehabilitation. Future work will explore these possibilities.

Social reward improves the voluntary control over localized brain activity in fMRI-based neurofeedback training.

Neurofeedback (NF) based on real-time functional magnetic resonance imaging (rt-fMRI) allows voluntary regulation of the activity in a selected brain region. For the training of this regulation, a well-designed feedback system is required. Social reward may serve as an effective incentive in NF paradigms, but its efficiency has not yet been tested. Therefore, we developed a social reward NF paradigm and assessed it in comparison with a typical visual NF paradigm (moving bar). We trained twenty-four healthy participants, on three consecutive days, to control activation in dorsal anterior cingulate cortex (ACC) with fMRI-based NF. In the social feedback group, an avatar gradually smiled when ACC activity increased, whereas in the standard feedback group, a moving bar indicated the activation level. In order to assess a transfer of the NF training both groups were asked to up-regulate their brain activity without receiving feedback immediately before and after the NF training (pre- and post-test). Finally, the effect of the acquired NF training on ACC function was evaluated in a cognitive interference task (Simon task) during the pre- and post-test. Social reward led to stronger activity in the ACC and reward-related areas during the NF training when compared to standard feedback. After the training, both groups were able to regulate ACC without receiving feedback, with a trend for stronger responses in the social feedback group. Moreover, despite a lack of behavioral differences, significant higher ACC activations emerged in the cognitive interference task, reflecting a stronger generalization of the NF training on cognitive interference processing after social feedback. Social reward can increase self-regulation in fMRI-based NF and strengthen its effects on neural processing in related tasks, such as cognitive interference. A particular advantage of social feedback is that a direct external reward is provided as in natural social interactions, opening perspectives for implicit learning paradigms.

Alterations of local spontaneous brain activity and connectivity in adults with high-functioning autism spectrum disorder.

BackgroundPrevious autism research has hypothesized that abnormalities of functional connectivity in autism spectrum disorder (ASD) may vary with the spatial distance between two brain regions. Although several resting-state functional magnetic resonance imaging (rsfMRI) studies have extensively examined long-range (or distant) connectivity in the adult ASD brain, short-range (or local) connectivity has been investigated in less depth. Furthermore, the possible relationship between functional connectivity and brain activity level during the resting state remains unclear.MethodsWe acquired rsfMRI data from 50 adults with high-functioning ASD and 50 matched controls to examine the properties of spontaneous brain activity using measures of local and distant connectivity together with a measure of the amplitude of brain activity, known as fractional amplitude of low-frequency fluctuation (fALFF). The two connectivity measures were calculated using a common graph-theoretic framework. We also examined the spatial overlaps between these measures and possible relationships of these disrupted functional measures with autistic traits assessed by the Autism-Spectrum Quotient (AQ).ResultsCompared to the controls, participants with ASD exhibited local over-connectivity in the right superior frontal gyrus and middle frontal gyrus, accompanied by local under-connectivity in the bilateral fusiform gyri (FG) and right middle temporal gyrus (MTG). On the other hand, we did not find any significant alterations in distant connectivity. Participants with ASD also exhibited reduced fALFF in the right middle occipital gyrus, lingual gyrus, and FG. Further conjunction and spatial overlap analyses confirmed that the spatial pattern of reduced fALFF substantially overlapped with that of local under-connectivity, demonstrating the co-occurrence of disrupted connectivity and spontaneous activity level in the right inferior occipital gyrus, posterior MTG (pMTG), and FG. Finally, within the ASD group, disrupted local connectivity in the right pMTG significantly correlated with the “social interaction” subscale score of the AQ.ConclusionsThese findings revealed local functional disruptions in the occipital and temporal regions, especially the right FG and pMTG, in the form of co-occurrence of spontaneous brain activity level and local connectivity, which may underline social and communicative dysfunctions in adult ASD.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-015-0026-z) contains supplementary material, which is available to authorized users.

Dynamic adjustment of stimuli in real time functional magnetic resonance imaging.

The conventional fMRI image analysis approach to associating stimuli to brain activation is performed by carrying out a massive number of parallel univariate regression analyses. fMRI blood-oxygen-level dependent (BOLD) signal, the basis of these analyses, is known for its low signal-noise-ratio and high spatial and temporal signal correlation. In order to ensure accurate localization of brain activity, stimulus administration in an fMRI session is often lengthy and repetitive. Real-time fMRI BOLD signal analysis is carried out as the signal is observed. This method allows for dynamic, real-time adjustment of stimuli through sequential experimental designs. We have developed a voxel-wise sequential probability ratio test (SPRT) approach for dynamically determining localization, as well as decision rules for stopping stimulus administration. SPRT methods and general linear model (GLM) approaches are combined to identify brain regions that are activated by specific elements of stimuli. Stimulus administration is dynamically stopped when sufficient statistical evidence is collected to determine activation status across regions of interest, following predetermined statistical error thresholds. Simulation experiments and an example based on real fMRI data show that scan volumes can be substantially reduced when compared with pre-determined, fixed designs while achieving similar or better accuracy in detecting activated voxels. Moreover, the proposed approach is also able to accurately detect differentially activated areas, and other comparisons between task-related GLM parameters that can be formulated in a hypothesis-testing framework. Finally, we give a demonstration of SPRT being employed in conjunction with a halving algorithm to dynamically adjust stimuli.

Local brain activity in different motor subtypes of Parkinson's disease with fMRI

To explore the changes of local brain activity in motor subtypes of Parkinson's disease (PD) with functional magnetic resonance imaging (fMRI). A total of 60 idiopathic PD and 30 age- and gender-matched normal controls were examined with resting-state fMRI from January 2013 to March 2014. All subjects gave their written informed consent for the study. The amplitude of low-frequency fluctuation (ALFF) was calculated to measure local brain activity. The PD patients were divided into two groups of tremor dominant (TD) and postural instability/gait difficulty (PIGD) (n = 30 each). All subjects gave their written in formed consent for the study.One-way ANOVA and post-hoc t-test were performed to detect the differences of local brain activity between PD and normal subjects. And the correlations were examined between ALFF, scores and levodopa dose. Compared with normal subjects, the TD group showed increased activity in bilateral cerebellums (-37, -47, -38), thalamus (-18, -17,0), pons (-3, -23, -37) and left precentral gyrus (-41, -30, 46) versus decreased activity in bilateral frontal lobes (-13, 69, 6), temporal lobes (-42, 18, -21), left insula (-32, 22, 2) and left anterior cingulated (-7, 32, -5). The PIGD group showed increased activity in right postcentral gyrus (63, -18, 39) and decreased activity in bilateral putamens (-24, 12, 3), pre-supplementary motor area (10, 10, 58), frontal lobes (15, -15, 57), temporal lobes (-39, 18, -3) and left insula (-29, 20, 11). Compared with PIGD, the TD group showed increased activity in temporal lobes, but decreased activity in frontal lobes. Additionally, ALFF in bilateral cerebellums and frontal lobes was positively correlated with TD scores while ALFF in left precentral gyrus, bilateral putamens and temporal lobes negatively correlated with TD scores. ALFF in bilateral frontal lobes and left temporal lobe was positively correlated with PIGD scores.However, in right postcentral gyrus and bilateral putamens, ALFF was negatively correlated with PIGD scores. The levodopa dose was positively correlated with frontal lobes and temporal lobe in TD and cerebellums and inferior parietal lobule in PIGD. A specific pattern of intrinsic activity in TD and PIGD may provide insights into neurophysiological mechanisms of PD motor subtypes. The changes of brain activity in TD are caused by the interaction between cerebello-thalamo-cortical circuit and basal ganglia loop while the changes in PIGD result largely from damaged basal ganglia loop.

EEG-based local brain activity feedback training—tomographic neurofeedback

Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback (NF) have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on “EEG-based LBA-feedback training” developed by Bauer et al. (2011). Local brain activity-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, five experimental subjects increased significantly the feedback rate whereas five controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the Anterior Cingulate Cortex (ACC) and Dorso-Lateral Prefrontal Cortex (DLPFC) by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014).