Source Imaging Techniques Research Articles

Evaluation of multiple comparison correction procedures in drug assessment studies using LORETA maps.

The identification of the brain regions involved in the neuropharmacological action is a potential procedure for drug development. These regions are commonly determined by the voxels showing significant statistical differences after comparing placebo-induced effects with drug-elicited effects. LORETA is an electroencephalography (EEG) source imaging technique frequently used to identify brain structures affected by the drug. The aim of the present study was to evaluate different methods for the correction of multiple comparisons in the LORETA maps. These methods which have been commonly used in neuroimaging and also simulated studies have been applied on a real case of pharmaco-EEG study where the effects of increasing benzodiazepine doses on the central nervous system measured by LORETA were investigated. Data consisted of EEG recordings obtained from nine volunteers who received single oral doses of alprazolam 0.25, 0.5, and 1mg, and placebo in a randomized crossover double-blind design. The identification of active regions was highly dependent on the selected multiple test correction procedure. The combined criteria approach known as cluster mass was useful to reveal that increasing drug doses led to higher intensity and spread of the pharmacologically induced changes in intracerebral current density.

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery.

The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables noninvasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the presurgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. We performed a retrospective cohort study of patients with focal epilepsy who received MEG for interictal spike mapping followed by surgical resection at our institution. We studied 132 surgical patients, with mean postoperative follow-up of 3.6 years (minimum 1 year). Dipole source modeling was successful in 103 patients (78%), whereas no interictal spikes were seen in others. Among patients with successful dipole modeling, MEG findings were concordant with and specific to the following: (1) the region of resection in 66% of patients, (2) invasive electrocorticography (ECoG) findings in 67% of individuals, and (3) the magnetic resonance imaging (MRI) abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were nonspecific to or discordant with the region of resection (χ(2) = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp electroencephalography (EEG), and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (95% confidence interval [CI] 2.23-11.8). MEG is a valuable tool for noninvasive interictal spike mapping in epilepsy surgery, including patients with nonlocalized findings receiving long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated with improved seizure outcomes.

Ictal EEG Source Imaging in Frontal Lobe Epilepsy Leads to Improved Lateralization Compared With Visual Analysis

To investigate the utility of EEG source imaging to lateralize ictal patterns in frontal lobe epilepsy, which were nonlateralized by standard EEG analysis. Prospective analysis of 17 seizures in 8 patients with unilateral frontal lobe epilepsy MRI lesions and nonlateralizing ictal scalp EEG. We applied four EEG source imaging techniques (phase maps, symmetric dipoles, low-resolution brain electromagnetic tomography analysis, and classical low-resolution brain electromagnetic tomography analysis recursively applied) to the averaged seizure pattern. We tested (1) the ability of these techniques to lateralize seizure patterns, (2) the agreement of the lateralization result with MRI lesion side and subdural EEG recordings, individually for each method and for concordance of all. We found lateralizing results in 5 of 17 seizures when analyzing phase maps, 8 of 17 when analyzing dipoles, and 5 of 17 in both classical low-resolution brain electromagnetic tomography analysis recursively applied and low-resolution brain electromagnetic tomography analysis. No discordance with the MRI lesion side was seen when analyzing phase maps, whereas dipole analysis was discordant to the MRI lesion in two seizures, classical low-resolution brain electromagnetic tomography analysis recursively applied in one, and low-resolution brain electromagnetic tomography analysis in two. Agreement between all imaging methods was found in three seizures (three patients), all in line with the side of the MRI lesion. Advanced EEG review methods and source localization provide useful lateralizing information in difficult frontal lobe epilepsy seizure patterns.

Voxel-wise resting-state MEG source magnitude imaging study reveals neurocircuitry abnormality in active-duty service members and veterans with PTSD.

Post-traumatic stress disorder (PTSD) is a leading cause of sustained impairment, distress, and poor quality of life in military personnel, veterans, and civilians. Indirect functional neuroimaging studies using PET or fMRI with fear-related stimuli support a PTSD neurocircuitry model that includes amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC). However, it is not clear if this model can fully account for PTSD abnormalities detected directly by electromagnetic-based source imaging techniques in resting-state. The present study examined resting-state magnetoencephalography (MEG) signals in 25 active-duty service members and veterans with PTSD and 30 healthy volunteers. In contrast to the healthy volunteers, individuals with PTSD showed: 1) hyperactivity from amygdala, hippocampus, posterolateral orbitofrontal cortex (OFC), dorsomedial prefrontal cortex (dmPFC), and insular cortex in high-frequency (i.e., beta, gamma, and high-gamma) bands; 2) hypoactivity from vmPFC, Frontal Pole (FP), and dorsolateral prefrontal cortex (dlPFC) in high-frequency bands; 3) extensive hypoactivity from dlPFC, FP, anterior temporal lobes, precuneous cortex, and sensorimotor cortex in alpha and low-frequency bands; and 4) in individuals with PTSD, MEG activity in the left amygdala and posterolateral OFC correlated positively with PTSD symptom scores, whereas MEG activity in vmPFC and precuneous correlated negatively with symptom score. The present study showed that MEG source imaging technique revealed new abnormalities in the resting-state electromagnetic signals from the PTSD neurocircuitry. Particularly, posterolateral OFC and precuneous may play important roles in the PTSD neurocircuitry model.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses.

Inverse source imaging methods in recovering distributed brain sources

Over the past decades tremendous efforts have been made in developing functional neuroimaging techniques to better understand human brain functions in both normal and diseased states. Towards this goal, it is essential to develop a technique that can noninvasively image human brain activity with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are important tools for studying the human brain’s large-scale neuronal dynamics, thanks to their millisecond temporal resolution. However, EEG and MEG are limited in providing spatial information concerning the location of active sources in the brain. Localizing the sources of EEG/MEG dynamics can be achieved by the so-called electrophysiological source imaging techniques. Recently, there has been a growing interest in source imaging techniques in recovering distributed brain sources. Such distributed source imaging techniques have been advanced in many aspects, including the forward modeling and the inverse imaging, and have been shown promising in many neuroscience and clinical applications. This paper reviews the basic principles, recent advancements and applications of the distributed source imaging techniques.

Electrophysiological Evidence for Ventral Stream Deficits in Schizophrenia Patients

Schizophrenic patients suffer from many deficits including visual, attentional, and cognitive ones. Visual deficits are of particular interest because they are at the fore-end of information processing and can provide clear examples of interactions between sensory, perceptual, and higher cognitive functions. Visual deficits in schizophrenic patients are often attributed to impairments in the dorsal (where) rather than the ventral (what) stream of visual processing. We used a visual-masking paradigm in which patients and matched controls discriminated small vernier offsets. We analyzed the evoked electroencephalography (EEG) responses and applied distributed electrical source imaging techniques to estimate activity differences between conditions and groups throughout the brain. Compared with controls, patients showed strongly reduced discrimination accuracy, confirming previous work. The behavioral deficits corresponded to pronounced decreases in the evoked EEG response at around 200 ms after stimulus onset. At this latency, patients showed decreased activity for targets in left parietal cortex (dorsal stream), but the decrease was most pronounced in lateral occipital cortex (in the ventral stream). These deficiencies occurred at latencies that reflect object processing and fine shape discriminations. We relate the reduced ventral stream activity to deficient top-down processing of target stimuli and provide a framework for relating the commonly observed dorsal stream deficiencies with the currently observed ventral stream deficiencies.

Seizure source imaging by means of FINE spatio-temporal dipole localization and directed transfer function in partial epilepsy patients

ObjectiveTo investigate the usage of a high-density EEG recording system and source imaging technique for localizing seizure activity in patients with medically intractable partial epilepsy. MethodsHigh-density, 76-channel scalp EEG signals were recorded in 10 patients with partial epilepsy. The patients underwent routine clinical pre-surgical evaluation and all had resective surgery with seizure free outcome. After applying a FINE (first principle vectors) spatio–temporal source localization and DTF (directed transfer function) connectivity analysis approach, ictal sources were imaged. Effects of number of scalp EEG electrodes on the seizure localization were also assessed using 76, 64, 48, 32, and 21 electrodes, respectively. ResultsSurgical resections were used to assess the source imaging results. Results from the 76-channel EEG in the 10 patients showed high correlation with the surgically resected brain regions. The localization of seizure onset zone from 76-channel EEG showed improved source detection accuracy compared to other EEG configurations with fewer electrodes. ConclusionsFINE together with DTF was able to localize seizure onset zones of partial epilepsy patients. High-density EEG recording can help achieve improved seizure source imaging. SignificanceThe present results suggest the promise of high-density EEG and electrical source imaging for noninvasively localizing seizure onset zones.

Preliminary study of coded-source-based neutron imaging at the CPHS

Abstract A cold neutron radiography/tomography instrument is under construction at the Compact Pulsed Hadron Source (CPHS) at Tsinghua University, China. The neutron flux is so low that an acceptable neutron radiographic image requires a long exposure time in the single-hole imaging mode. The coded-source-based imaging technique is helpful to increase the utilization of neutron flux to reduce the exposure time without loss in spatial resolution and provides high signal-to-noise ratio (SNR) images. Here we report a preliminary study on the feasibility of coded-source-based technique applied to the cold neutron imaging with a low-brilliance neutron source at the CPHS. A proper coded aperture is designed to be used in the beamline instead of the single-hole aperture. Two image retrieval algorithms, the Wiener filter algorithm and the Richardson–Lucy algorithm, are evaluated by using analytical and Monte Carlo simulations. The simulation results reveal that the coded source imaging technique is suitable for the CPHS to partially solve the problem of low neutron flux.

Coded source neutron imaging at the PULSTAR reactor

Abstract A neutron imaging facility is located on beam-tube #5 of the 1-MW PULSTAR reactor at North Carolina State University. An investigation of high resolution imaging using the coded source imaging technique has been initiated at the facility. Coded imaging uses a mosaic of pinholes to encode an aperture, thus generating an encoded image of the object at the detector. To reconstruct the image data received by the detector, the corresponding decoding patterns are used. The optimized design of coded mask is critical for the performance of this technique and will depend on the characteristics of the imaging beam. In this work, a 34×38 uniformly redundant array (URA) coded aperture system is studied for application at the PULSTAR reactor neutron imaging facility. The URA pattern was fabricated on a 500 μm gadolinium sheet. Simulations and experiments with a pinhole object have been conducted using the Gd URA and the optimized beam line.

Locating non-volcanic tremor along the San Andreas Fault using a multiple array source imaging technique

Non-volcanic tremor (NVT) has been observed at several subduction zones and at the San Andreas Fault (SAF). Tremor locations are commonly derived by cross-correlating envelope-transformed seismic traces in combination with source-scanning techniques. Recently, they have also been located by using relative relocations with master events, that is low-frequency earthquakes that are part of the tremor; locations are derived by conventional traveltime-based methods. Here we present a method to locate the sources of NVT using an imaging approach for multiple array data. The performance of the method is checked with synthetic tests and the relocation of earthquakes. We also applied the method to tremor occurring near Cholame, California. A set of small-aperture arrays (i.e. an array consisting of arrays) installed around Cholame provided the data set for this study. We observed several tremor episodes and located tremor sources in the vicinity of SAF. During individual tremor episodes, we observed a systematic change of source location, indicating rapid migration of the tremor source along SAF.

Magnetoencephalography reveals early activation of V4 in grapheme-color synesthesia

Grapheme-color synesthesia is a neurological phenomenon in which letters and numbers (graphemes) consistently evoke particular colors (e.g. A may be experienced as red). The cross-activation theory proposes that synesthesia arises as a result of cross-activation between posterior temporal grapheme areas (PTGA) and color processing area V4, while the disinhibited feedback theory proposes that synesthesia arises from disinhibition of pre-existing feedback connections. Here we used magnetoencephalography (MEG) to test whether V4 and PTGA activate nearly simultaneously, as predicted by the cross-activation theory, or whether V4 activation occurs only after the initial stages of grapheme processing, as predicted by the disinhibited feedback theory. Using our high-resolution MEG source imaging technique (VESTAL), PTGA and V4 regions of interest (ROIs) were separately defined, and activity in response to the presentation of achromatic graphemes was measured. Activation levels in PTGA did not significantly differ between synesthetes and controls (suggesting similar grapheme processing mechanisms), whereas activation in V4 was significantly greater in synesthetes. In synesthetes, PTGA activation exceeded baseline levels beginning 105–109ms, and V4 activation did so 5ms later, suggesting nearly simultaneous activation of these areas. Results are discussed in the context of an updated version of the cross-activation model, the cascaded cross-tuning model of grapheme-color synesthesia.

Optimized microphone deployment for near-field acoustic holography: To be, or not to be random, that is the question

Arrays with sparse and random sensor deployment are known to be capable of delivering high quality far-field images without grating lobes. This raises the question of whether or not this idea can be applied to near-field imaging as well. To answer this question that has not yet been widely investigated in previous research, numerical simulations are undertaken in this paper to optimize the microphone deployment for both far-field and near-field arrays with the latter being the main focus. In the simulation, a recently introduced near-field equivalent source imaging (NESI) technique is employed for the near-field imaging. Global optimization techniques including the simulated annealing (SA) algorithm and the intra-block Monte Carlo (IBMC) algorithm are exploited to find the optimal microphone position efficiently. The combined use of the SA and the IBMC algorithms enables efficient search for satisfactory deployment with excellent beam pattern and relatively uniform distribution of microphones. In the near-field optimization, a special kind of beam pattern and cost function definition is used for the multiple-input-multiple-output (MIMO) imaging problem. As indicated by the simulation results, random deployment of microphones is necessary to avoid grating lobes in far-field imaging. In the near-field simulation, all results suggest that the optimal near-field array is the uniform rectangular array (URA) and the random deployment presents no particular benefit in near-field imaging.

Distinct neuronal oscillatory responses between patients with bipolar and unipolar disorders: A magnetoencephalographic study

BackgroundBipolar disorder (BD) and major depressive disorder (MDD) have distinct pathophysiologies but similar depressive appearances. The present study aimed at the differentiation of the brain responses between BD and MDD patients. We hypothesized that different affective disorder patients may have distinct patterns of oscillatory cortical activities in response to negative emotional stimuli. MethodsTwenty BD patients, twenty MDD patients, and twenty age- and gender-matched healthy normal subjects were recruited. We adopted an implicit emotional task with facial image stimuli. The acquired event-related magnetoencephalographic signals were processed by the time-frequency analysis and beamformer-based source imaging techniques followed by statistical inference. ResultsWe found that there were gamma oscillation decreases in the frontal regions of both BD and MDD patients, gamma oscillation increases in the bilateral temporal regions of MDD, and alpha-beta rhythm increases in BD patients. Relative to the cortical activation in the control group, the BD patients displayed more widely increased oscillatory activities over the fronto-parieto-occipital regions than MDD patients. ConclusionsOur results demonstrate the distinct neuropathological patterns of emotional responses in BD and MDD patients. The findings suggest that the dysfunction of emotion regulation in BD may result from the increased sensitivity to emotionally salient information, implicating the potential cause of the emotion lability. The present study also suggests that the implicit emotional task is an effective approach to differentiate bipolar from unipolar disorders and their distinct neuropathological patterns to emotional stimuli may provide objective and quantitative measures for potential diagnostic significance.

Combined SEEG and source localisation study of temporal lobe schizencephaly and polymicrogyria

Type 1 schizencephaly (SZ) is a cerebral malformation characterised by a cleft lined and surrounded by a polymicrogyric cortex, extending from the pial region to the peri-ventricular heterotopia. Our purpose was to combine and compare dipole source imaging technique and Stereo-EEG (SEEG) technique in determining the irritative and epileptogenic zones in a case of type 1 schizencephaly. High-resolution (64-channel) video-EEG with electrical source imaging and SEEG recordings were performed during a pre-surgical evaluation for medically intractable epilepsy. Anatomo-electro-clinical correlations based on SEEG and source localisation identified two irritative and epileptogenic zones partially overlapping the polymicrogyric cortex surrounding the SZ: an anterior medio-lateral network primarily involving dysplasic limbic structures and a lateral network involving the anterior and middle part of the cleft and polymicrogyric cortex. The most posterior part (at the temporo-parieto-occipital junction) displayed a normal background activity. Both epileptogenic and electrophysiologically normal cortices coexisted within the same widespread malformation: only the anterior part belonged to the anterior medio-lateral epileptogenic network defined by the SEEG. In cases of widespread cortical malformation such as SZ, source localization techniques can help to define the irritative zone and relevant targets for SEEG.

Distribution-based minimum-norm estimation with multiple trials

The goal of this study is to develop a source imaging method for electroencephalography and magnetoencephalography by analyzing a distance measure based on a Euclidean norm of difference between pre- and post-stimulus brain activities. Conventional source imaging techniques generally detect evoked responses by averaging multiple trials at each source point. These methods are limited in their ability to fully analyze complex brain signals with a mixture of evoked and induced activities because they compare means or variances. In this article, we propose a novel approach for eliciting significant evoked and induced activity. To this aim, response and baseline ranges from each trial are separately mapped in an anatomically constrained source space by minimum-norm estimation. The extent within a distribution and the distance between distributions of brain activities at each source point are estimated from the set of trials. Then, this distance analysis determines the degree of difference between the response and baseline activities. The statistical significance of the distance comparison was computed using a nonparametric permutation test. In the evaluation of simulated data sets, the proposed method provided robust images of the simulated location ( p<0.05), whereas the average method did not detect the perturbed source. A total of 200 randomly selected locations were tested with a signal-to-noise ratio (SNR) of 2 dB, and the error between simulated points and the maximum-value-points analyzed using this method was 9±15 mm.

PHENIX measurements of 3D emission source functions in Au+Au collisions at GeV

A state-of-the-art 3D source imaging technique is used to extract the 3D two-pion source function in central and mid-central Au+Au collisions at GeV. The source function indicates a previously unresolved non-Gaussian tail in the directions of the pion pair transverse momentum (out) and along the beam (long). Model comparisons give robust estimates for several characteristics of the emission source, including its transverse size, mean proper breakup time τ and emission duration Δτ. These estimates point to significant relative emission times which could result from a crossover phase transition.

Patient-specific volume conductor modeling for non-invasive imaging of cardiac electrophysiology.

We propose a general workflow to numerically estimate the spread of electrical excitation in the patients’ hearts. To this end, a semi-automatic segmentation pipeline for extracting the volume conductor model of structurally normal hearts is presented. The cardiac electrical source imaging technique aims to provide information about the spread of electrical excitation in order to assist the cardiologist in developing strategies for the treatment of cardiac arrhythmias. The volume conductor models of eight patients were extracted from cine-gated short-axis magnetic resonance imaging (MRI) data. The non-invasive estimation of electrical excitation was compared with the CARTO™ maps. The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.

FMRI–EEG integrated cortical source imaging by use of time-variant spatial constraints

In response to the need of establishing a high-resolution spatiotemporal neuroimaging technique, tremendous efforts have been focused on developing multimodal strategies that combine the complementary advantages of high-spatial-resolution functional magnetic resonance imaging (fMRI) and high-temporal-resolution electroencephalography (EEG) or magnetoencephalography (MEG). A critical challenge to the fMRI–EEG/MEG integration lies in the spatial mismatches between fMRI activations and instantaneous electrical source activities. Such mismatches are fundamentally due to the fact that fMRI and EEG/MEG signals are generated and collected in highly different time scales. In this paper, we propose a new theoretical framework to solve the problem of fMRI–EEG integrated cortical source imaging. The new framework has two principal technical advancements. First, by assuming a linear neurovascular coupling, a method is derived to quantify the fMRI signal in each voxel as proportional to the time integral of the power of local electrical current during the period of event-related potentials (ERP). Second, the EEG inverse problem is solved for every time instant using an adaptive Wiener filter, in which the prior time-variant source covariance matrix is estimated by combining the quantified fMRI responses and the segmented EEG signals before response averaging. A series of computer simulations were conducted to evaluate the proposed methods in terms of imaging the instantaneous cortical current density (CCD) distribution and estimating the source time courses with a millisecond temporal resolution. As shown in the simulation results, the instantaneous CCD reconstruction by using the proposed fMRI–EEG integration method was robust against both fMRI false positives and false negatives while retaining a spatial resolution nearly as high as that of fMRI. The proposed method could also reliably estimate the source waveforms when multiple sources were temporally correlated or uncorrelated, or were sustained or transient, or had some features in frequency or phase, or had even more complicated temporal dynamics. Moreover, applying the proposed method to real fMRI and EEG data acquired in a visual experiment yielded a time series of reconstructed CCD images, in agreement with the traditional view of hierarchical visual processing. In conclusion, the proposed method provides a reliable technique for the fMRI–EEG integration and represents a significant advancement over the conventional fMRI-weighted EEG (or MEG) source imaging techniques and is also applicable to the fMRI–MEG integrated source imaging.

Selected results on strong and coulomb-induced correlations from the STAR experiment

Using recent high-statistics STAR data from Au+Au and Cu+Cu collisions at full RHIC energy I discuss strong and Coulomb-induced final state interaction effects on identical ($\pi-\pi$) and non-identical ($\pi-\Xi$) particle correlations. Analysis of $\pi-\Xi$ correlations reveals the strong and Coulomb-induced FSI effects allowing for the first time to estimate space extension of $\pi$ and $\Xi$ sources and average shift between them. Source imaging technique providing clean separation of these effects from effects due to the source function itself is applied to one-dimensional relative momentum correlation function of identical pions. For low momentum pions and/or non-central collisions large departure from a single-Gaussian shape is observed.