Insights into déjà vu: Associations between the frequency of experience and amplitudes of low-frequency oscillations in resting-state functional magnetic resonance imaging.

The phenomenon of déjà vu (DV) has intrigued scientists for decades, yet its neurophysiological underpinnings remain elusive. Brain regions have been identified in which morphometry differs between healthy individuals according to the frequency of their DV experiences. This study built upon these findings by assessing if and how neural activity in these and other brain regions also differ with respect to DV experience. Resting-state fMRI was performed on 68 healthy volunteers, 44 of whom reported DV experiences (DV group) and 24 who did not (NDV group). Using multivariate analyses, we then assessed the (fractional) amplitude of low-frequency fluctuations (fALFF/ALFF), a metric that is believed to index brain tissue excitability, for five discrete frequency bands within sets of brain regions implicated in DV and those comprising the default mode network (DMN). Analyses revealed significantly lower values of fALFF/ALFF for specific frequency bands in the DV relative to the NDV group, particularly within mesiotemporal structures, bilateral putamina, right caudatum, bilateral superior frontal cortices, left lateral parietal cortex, dorsal and ventral medial prefrontal cortex, and the posterior cingulate cortex. The pattern of differences in fALFF/ALFF measures between the brains of individuals who have experienced DV and those who have not provides new neurophysiological insights into this phenomenon, including the potential role of the DMN. We suggest that the erroneous feeling of familiarity arises from a temporary disruption of cortico-subcortical circuitry together with the upregulation of cortical excitability.

Contribution of the multi-echo approach in accelerated functional magnetic resonance imaging multiband acquisition.

We wanted to verify the effect of combining multi-echo (ME) functional magnetic resonance imaging (fMRI) with slice acceleration in simultaneous multi-slice acquisition. The aim was to shed light on the benefits of multiple echoes for various acquisition settings, especially for levels of slice acceleration and flip angle. Whole-brain ME fMRI data were obtained from 26 healthy volunteers (using three echoes; seven runs with slice acceleration 1, 4, 6, and 8; and two different flip angles for each of the first three acceleration factors) and processed as single-echo (SE) data and ME data based on optimal combinations weighted by the contrast-to-noise ratio. Global metrics (temporal signal-to-noise ratio, signal-to-noise separation, number of active voxels, etc.) and local characteristics in regions of interest were used to evaluate SE and ME data. ME results outperformed SE results in all runs; the differences became more apparent for higher acceleration, where a significant decrease in data quality is observed. ME fMRI can improve the observed data quality metrics over SE fMRI for a wide range of accelerated fMRI acquisitions.

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging.

Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand-alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR-negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel-wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion-weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR-negative epilepsy patients.

The role of the striatum in visuomotor integration during handwriting: an fMRI study.

This study investigates the role of the dorsal/sensorimotor striatum in visuomotor integration (i.e., the transformation of internal visual information about letter shapes into motor output) during handwriting. Twenty healthy participants underwent fMRI scanning with tasks consisting of self-paced handwriting of alphabetically ordered single letters and simple dots, with both tasks performed without visual feedback. Functional connectivity (FC) from these two tasks was compared to demonstrate the difference between coordinated activity arising during handwriting and the activity during a simpler motor condition. Our study focused upon the writing-specific cortico-striatal network of preselected regions of interest consisting of the visual word form area (VWFA), anterior intraparietal sulcus/superior parietal lobule, striatum, premotor cortex/Exner's area, and primary and supplementary motor regions. We observed systematically increased task-induced cortico-striatal and cortico-cortical FC. This increased synchronization of neural activity between the VWFA, i.e., the visual cortical area containing information about letter shapes, and the frontoparietal motor regions is mediated by the striatum. These findings suggest the involvement of the striatum in integrating stored letter-shape information with motor planning and execution during handwriting.

Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation.

This study examines the impact of using different cerebrospinal fluid (CSF) and white matter (WM) nuisance signals for data-driven filtering of functional magnetic resonance imaging (fMRI) data as a cleanup method before analyzing intrinsic brain fluctuations. The routinely used temporal signal-to-noise ratio metric is inappropriate for assessing fMRI filtering suitability, as it evaluates only the reduction of data variability and does not assess the preservation of signals of interest. We defined a new metric that evaluates the preservation of selected neural signal correlates, and we compared its performance with a recently published signal-noise separation metric. These two methods provided converging evidence of the unfavorable impact of commonly used filtering approaches that exploit higher numbers of principal components from CSF and WM compartments (typically 5 + 5 for CSF and WM, respectively). When using only the principal components as nuisance signals, using a lower number of signals results in a better performance (i.e., 1 + 1 performed best). However, there was evidence that this routinely used approach consisting of 1 + 1 principal components may not be optimal for filtering resting-state (RS) fMRI data, especially when RETROICOR filtering is applied during the data preprocessing. The evaluation of task data indicated the appropriateness of 1 + 1 principal components, but when RETROICOR was applied, there was a change in the optimal filtering strategy. The suggested change for extracting WM (and also CSF in RETROICOR-corrected RS data) is using local signals instead of extracting signals from a large mask using principal component analysis.

Robustness of Representative Signals Relative to Data Loss Using Atlas-Based Parcellations.

Parcellation-based approaches are an important part of functional magnetic resonance imaging data analysis. They are a necessary processing step for sorting data in structurally or functionally homogenous regions. Real functional magnetic resonance imaging datasets usually do not cover the atlas template completely; they are often spatially constrained due to the physical limitations of MR sequence settings, the inter-individual variability in brain shape, etc. When using a parcellation template, many regions are not completely covered by actual data. This paper addresses the issue of the area coverage required in real data in order to reliably estimate the representative signal and the influence of this kind of data loss on network analysis metrics. We demonstrate this issue on four datasets using four different widely used parcellation templates. We used two erosion approaches to simulate data loss on the whole-brain level and the ROI-specific level. Our results show that changes in ROI coverage have a systematic influence on network measures. Based on the results of our analysis, we recommend controlling the ROI coverage and retaining at least 60% of the area in order to ensure at least 80% of explained variance of the original signal.

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks.

Multiway array decomposition methods have been shown to be promising statistical tools for identifying neural activity in the EEG spectrum. They blindly decompose the EEG spectrum into spatial-temporal-spectral patterns by taking into account inherent relationships among signals acquired at different frequencies and sensors. Our study evaluates the stability of spatial-temporal-spectral patterns derived by one particular method, parallel factor analysis (PARAFAC). We focused on patterns' stability over time and in population and divided the complete data set containing data from 50 healthy subjects into several subsets. Our results suggest that the patterns are highly stable in time, as well as among different subgroups of subjects. Further, we show with simultaneously acquired fMRI data that power fluctuations of some patterns have stable correspondence to hemodynamic fluctuations in large-scale brain networks. We did not find such correspondence for power fluctuations in standard frequency bands, the common way of dealing with EEG data. Altogether, our results suggest that PARAFAC is a suitable method for research in the field of large-scale brain networks and their manifestation in EEG signal.

Changes in connectivity of the posterior default network node during visual processing in mild cognitive impairment: staged decline between normal aging and Alzheimer's disease.

Visual processing difficulties are often present in Alzheimer's disease (AD), even in its pre-dementia phase (i.e. in mild cognitive impairment, MCI). The default mode network (DMN) modulates the brain connectivity depending on the specific cognitive demand, including visual processes. The aim of the present study was to analyze specific changes in connectivity of the posterior DMN node (i.e. the posterior cingulate cortex and precuneus, PCC/P) associated with visual processing in 17 MCI patients and 15 AD patients as compared to 18 healthy controls (HC) using functional magnetic resonance imaging. We used psychophysiological interaction (PPI) analysis to detect specific alterations in PCC connectivity associated with visual processing while controlling for brain atrophy. In the HC group, we observed physiological changes in PCC connectivity in ventral visual stream areas and with PCC/P during the visual task, reflecting the successful involvement of these regions in visual processing. In the MCI group, the PCC connectivity changes were disturbed and remained significant only with the anterior precuneus. In between-group comparison, we observed significant PPI effects in the right superior temporal gyrus in both MCI and AD as compared to HC. This change in connectivity may reflect ineffective "compensatory" mechanism present in the early pre-dementia stages of AD or abnormal modulation of brain connectivity due to the disease pathology. With the disease progression, these changes become more evident but less efficient in terms of compensation. This approach can separate the MCI from HC with 77% sensitivity and 89% specificity.

An evaluation of traffic-awareness campaign videos: empathy induction is associated with brain function within superior temporal sulcus.

Acting appropriately within social contexts requires an ability to appreciate others' mental and emotional states. Indeed, some campaign programs designed to reduce anti-social behaviour seek to elicit empathy for the victims. The effectiveness of these campaigns can be evaluated according to the degree to which they induce such responses, but by applying neuroscientific techniques this can be done at the behavioural and neurophysiological level. Neuroimaging studies aimed at identifying the neural mechanisms behind such socio-cognitive and -emotional processes frequently reveal the role of the superior temporal sulcus (STS). We applied this knowledge to assess the effectiveness of traffic-awareness campaign adverts to induce empathic expression. Functional magnetic resonance imaging (fMRI) data were acquired from 20 healthy male volunteers as they watched these campaign videos consisting of a dramatic sequence of events and catastrophic endings, and control videos without such dramatic endings. Among other structures, a significantly greater neural response was observed within bilateral STS, particularly within the right hemisphere, during the observation of campaign relative to control videos. Furthermore, activation in these brain regions correlated with the subjects' empathic expression. Our results develop our understanding of the role of STS in social cognition. Moreover, our data demonstrate the utility of neuroscientific methods when evaluating the effectiveness of campaign videos in terms of their ability to elicit empathic responses. Our study also demonstrates the utility of these specific stimuli for future neuroscientific research.

Disruption of resting functional connectivity in Alzheimer's patients and at-risk subjects.

The resting brain exhibits continuous intrinsic activity, which is correlated between groups of regions forming resting state networks. Evaluating resting connectivity is a popular approach for studying brain diseases. Several hundred studies are now available that address integrity of resting connectivity in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI), as well as preclinical at-risk subjects. Most studies focus on the default mode network, a system of specific brain areas showing strong connected resting activity that attenuates during goal-directed behavior. The extent of intrinsic brain activity tends to be strongly correlated with cognitive processes and is specifically disrupted in AD and MCI patients and at-risk subjects, with changes seeming to evolve during the transition between the disease stages. In this study, we review the current findings in default mode network and other resting state network studies in AD and MCI patients and at-risk subjects as assessed by resting state functional magnetic resonance imaging.

Superior temporal sulcus and social cognition in dangerous drivers.

Understanding the neural systems underpinning social cognition is a primary focus of contemporary social neuroscience. Using functional magnetic resonance imaging (fMRI), the present study asked if brain activity reflecting socio-cognitive processes differs between individuals according to their social behavior; namely, between a group of drivers with frequent traffic offenses and a group with none. Socio-cognitive processing was elicited by employing videos from a traffic awareness campaign, consisting of reckless and anti-social driving behavior ending in tragic consequences, and control videos with analogous driving themes but without such catastrophic endings. We investigated whether relative increases in brain function during the observation of these campaign stimuli compared with control videos differed between these two groups. To develop the results of our previous study we focused our analyses on superior temporal sulcus/gyrus (STS/STG). This revealed a bigger increase in brain activity within this region during the campaign stimuli in safe compared with dangerous drivers. Furthermore, by thematically coding drivers' verbal descriptions of the stimuli, we also demonstrate differences in STS reactivity according to drivers' scores on two indices of socio-cognitive processing: subjects' perceived consequences of actors' actions, and their affective evaluation of the clips. Our results demonstrate the influence of social behavior and socio-cognitive processing on STS reactivity to social stimuli, developing considerably our understanding of the role of this region in social cognition.

Brain functional connectivity of male patients in remission after the first episode of schizophrenia.

OBJECTIVES: Abnormal task-related activation and connectivity is present in schizophrenia. The aim of this study was the analysis of functional networks in schizophrenia patients in remission after the first episode. EXPERIMENTAL DESIGN: Twenty-nine male patients in remission after the first episode of schizophrenia and 22 healthy controls underwent examination by functional magnetic resonance during verbal fluency tasks (VFT). The functional connectivity of brain networks was analyzed using independent component analysis. RESULTS: The patients showed lower activation of the salience network during VFT. They also showed lower deactivation of the default mode network (DMN) during VFT processing. Spectral analysis of the component time courses showed decreased power in slow frequencies of signal fluctuations in the salience and DMNs and increased power in higher frequencies in the left frontoparietal cortex reflecting higher fluctuations of the network activity. Moreover, there was decreased similarity of component time courses in schizophrenia­the patients had smaller negative correlation between VFT activated and deactivated networks, and smaller positive correlations between DMN subcomponents. CONCLUSIONS: There is still an abnormal functional connectivity of several brain networks in remission after the first episode of schizophrenia. The effect of different treatment modalities on brain connectivity, together with temporal dynamics of this functional abnormality should be the objective of further studies to assess its potential as a marker of disease stabilization.

Association between the basal ganglia and large-scale brain networks in epilepsy.

Epilepsy may affect connectivity between the putamen and cortex even during the resting state. Putamen is part of the basal ganglia resting state network (BG-RSN) which is anti-correlated with the default mode network (DMN) in healthy subjects. Therefore, we aimed at studying the functional brain connectivity (FC) of the putamen with the cortical areas engaged in the DMN as well as with the primary somatomotor cortex which is a cortical region engaged in the BG-RSN. We compared the data obtained in patients with epilepsy with that in healthy controls (HC). Functional magnetic resonance imaging (fMRI) was performed in 10 HC and 24 patients with epilepsy: 14 patients with extratemporal epilepsy (PE) and 10 patients with temporal epilepsy (PT). Resting state fMRI data was obtained using the 1.5 T Siemens Symphony scanner. The Group ICA of fMRI Toolbox (GIFT) program was used for independent component analysis. The component representing the DMN was chosen according to a spatial correlation with a mask typical for DMN. The FC between the putamen and the primary somatomotor cortex was studied to assess the connectivity of the putamen within the BG-RSN. A second-level analysis was calculated to evaluate differences among the groups using SPM software. In patients with epilepsy as compared to HC, the magnitude of anti-correlation between the putamen and brain regions engaged in the DMN was significantly lower. In fact, the correlation changed the connectivity direction from negative in HC to positive in PE and PT. The disturbed FC of the BG in patients with epilepsy as compared with HC was further illustrated by a significant decrease in connectivity between the left/right putamen and the left/right somatomotor cortex, i.e. between regions that are engaged in the BG-RSN. The FC between the putamen and the cortex is disturbed in patients with epilepsy. This may reflect an altered function of the BG in epilepsy.

Functional anatomy of outcome evaluation during Iowa Gambling Task performance in patients with Parkinson's disease: an fMRI study.

The aim of this study was to investigate the functional anatomy of decision-making during the Iowa Gambling Task in patients with Parkinson's disease. We used event-related functional magnetic resonance imaging (fMRI) during a computerized version of IGT to compare 18 PD patients on dopaminergic medication in the ON state and 18 healthy control subjects. Our analyses focused on outcome evaluation following card selection, because we expected this aspect of decision-making to be impaired in PD patients. The PD patients exhibited lower activation of the left putamen than the control group as a reaction to penalty. Using psychophysiological interaction analysis, we identified decreased functional connectivity between the right globus pallidus internus and the left anterior cingulate gyrus in the PD group. In contrast, increased connectivity between these structures was observed after penalty in the control group. Our results suggest altered functioning of the basal ganglia and their connections with the cortical structures involved in the limbic loop (e.g., the limbic fronto-striatal circuit of the basal ganglia) during decision-making in PD patients. Differences in the response to loss could be associated with insufficient negative reinforcement after a loss in PD patients in the ON state in comparison to a healthy population.

Cortico-cerebellar functional connectivity and sequencing of movements in schizophrenia.

BACKGROUND: Abnormal execution of several movements in a sequence is a frequent finding in schizophrenia. Successful performance of such motor acts requires correct integration of cortico-subcortical processes, particularly those related to cerebellar functions. Abnormal connectivity between cortical and cerebellar regions with resulting cognitive dysmetria has been proposed as the core dysfunction behind many signs and symptoms of schizophrenia. The aim of the present study was to assess if these proposed abnormalities in connectivity are a unifying feature of schizophrenia, or, rather, reflect a specific symptom domain of a heterogeneous disease. We predicted that abnormal functional connectivity between the motor cortex and cerebellum would be linked with abnormal performance of movement sequencing. METHODS: We examined 24 schizophrenia patients (SCH) and 24 age-, sex-, and handedness-matched healthy controls (HC) using fMRI during a modified finger-tapping task. The ability to perform movement sequencing was tested using the Neurological Evaluation Scale (NES). The subjects were categorized into two groups, with (SQ+) and without (SQ-) movement sequencing abnormalities, according to the NES-SQ score. The effects of diagnosis and movement sequencing abnormalities on the functional connectivity parameters between the motor cortex and cerebellum (MC-CRBL) and the supplementary motor cortex and cerebellum (SMA-CRBL) activated during the motor task were analyzed. RESULTS: We found no effect of diagnosis on the functional connectivity measures. There was, however, a significant effect on the SQ group: SQ + patients showed a lower level of MC-CRBL connectivity than SQ- patients and healthy controls. Moreover, the level of MC-CRBL and SMA-CRBL negatively correlated with the magnitude of NES-SQ abnormalities, but with no other NES domain. CONCLUSIONS: Abnormal cortico-cerebellar functional connectivity during the execution of a motor task is linked with movement sequencing abnormalities in schizophrenia, but not with the diagnosis of schizophrenia per se. It seems that specific patterns of inter-regional connectivity are linked with corresponding signs and symptoms of clinically heterogeneous conditions such as schizophrenia.

Iowa Gambling Task in patients with early-onset Parkinson's disease: strategy analysis.

The aim of our study was to analyse decision making in early-onset Parkinson's disease (PD) patients performing the Iowa Gambling Task (IGT). We compared 19 patients with early-onset PD (≤ 45 years) on dopaminergic medication (no evidence of depression, dementia, executive dysfunction according to the Tower of London test and the Stroop test, or pathological gambling) with 20 age-matched controls. A computer version of the IGT was employed. The PD patients achieved slightly lower IGT scores than the control group. A detailed analysis based on 'shift frequencies' between the individual decks showed that the patients tended to change their preferences for the decks more frequently, with a higher preference for the 'disadvantageous' deck B. Control subjects seemed to develop a more effective strategy. These differences could be caused by the poorer ability of the patients to develop any strategy at all. We observed changes in decision making during IGT performance in patients with early-onset PD, although they had no executive dysfunction as measured by established neuropsychological tests. The more detailed analysis employed in the present study could lead to a more accurate study of IGT performance and application of IGT in clinical practice.

Does repetitive transcranial magnetic stimulation have a positive effect on working memory and neuronal activation in treatment of negative symptoms of schizophrenia?

OBJECTIVE: The objective of the study was to find out whether, under the conditions of a double-blind, placebo coil controlled study, high-frequency repetitive transcranial magnetic stimulation (TMS) over the left prefrontal cortex will show positive effects on working memory with simultaneous assessment of respective changes in neuronal activation. RESULTS: Stimulation treatment led to a reduction of seriousness of negative schizophrenia symptoms in both comparative groups. However, mutual comparison of real (n=19) and sham (n=11) rTMS, respectively, has shown that the effect of real rTMS was statistically significantly higher compared with placebo stimulation. During stimulation treatment an improvement in working memory performance was also found. No statistically significant difference between the real and placebo sham rTMS, respectively, was established. The rate of neuronal activation did not change at all during rTMS treatment. CONCLUSIONS: From clinical point of view rTMS seems to be a well-tolerated neurostimulation method for treatment of negative schizophrenia symptoms with favourable of impact on cognitive functions.

Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy.

The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.

Source-based morphometry of gray matter volume in men with first-episode schizophrenia.

OBJECTIVES: There is a lot of variability between the results of studies reporting the pattern of gray matter volume changes in schizophrenia. Methodological issues may play an important role in this heterogeneity. The aim of the present study was to replicate the better performance of multivariate "source-based morphometry" (SBM) over the mass-univariate approach. EXPERIMENTAL DESIGN: Voxel-based morphometry of Jacobian-modulated gray matter volume images, using voxel and cluster level inference, and SBM were performed in a group of first-episode schizophrenia patients (N = 49) and healthy controls (N = 127). RESULTS: Using SBM we were able to find a significant reduction of gray matter volume in fronto-temporo-cerebellar areas whereas no significant results were obtained using voxel-based morphometry. CONCLUSION: Multivariate analysis of gray matter volume seems to be a suitable method for characterization of the pattern of changes at the beginning of the illness in schizophrenia subjects.