Roland R. Lee

Magnetoencephalographic patterns of epileptiform activity in children with regressive autism spectrum disorders

Background. One-third of children diagnosed with autism spectrum disorders (ASDs) are reported to have had normal early development followed by an autistic regression between the ages of 2 and 3 years. This clinical profile partly parallels that seen in Landau-Kleffner syndrome (LKS), an acquired language disorder (aphasia) believed to be caused by epileptiform activity. Given the additional observation that one-third of autistic children experience one or more seizures by adolescence, epileptiform activity may play a causal role in some cases of autism. Objective. To compare and contrast patterns of epileptiform activity in children with autistic regressions versus classic LKS to determine if there is neurobiological overlap between these conditions. It was hypothesized that many children with regressive ASDs would show epileptiform activity in a multifocal pattern that includes the same brain regions implicated in LKS. Design. Magnetoencephalography (MEG), a noninvasive method for identifying zones of abnormal brain electrophysiology, was used to evaluate patterns of epileptiform activity during stage III sleep in 6 children with classic LKS and 50 children with regressive ASDs with onset between 20 and 36 months of age (16 with autism and 34 with pervasive developmental disorder–not otherwise specified). Whereas 5 of the 6 children with LKS had been previously diagnosed with complex-partial seizures, a clinical seizure disorder had been diagnosed for only 15 of the 50 ASD children. However, all the children in this study had been reported to occasionally demonstrate unusual behaviors (eg, rapid blinking, holding of the hands to the ears, unprovoked crying episodes, and/or brief staring spells) which, if exhibited by a normal child, might be interpreted as indicative of a subclinical epileptiform condition. MEG data were compared with simultaneously recorded electroencephalography (EEG) data, and with data from previous 1-hour and/or 24-hour clinical EEG, when available. Multiple-dipole, spatiotemporal modeling was used to identify sites of origin and propagation for epileptiform transients. Results. The MEG of all children with LKS showed primary or secondary epileptiform involvement of the left intra/perisylvian region, with all but 1 child showing additional involvement of the right sylvian region. In all cases of LKS, independent epileptiform activity beyond the sylvian region was absent, although propagation of activity to frontal or parietal regions was seen occasionally. MEG identified epileptiform activity in 41 of the 50 (82%) children with ASDs. In contrast, simultaneous EEG revealed epileptiform activity in only 68%. When epileptiform activity was present in the ASDs, the same intra/perisylvian regions seen to be epileptiform in LKS were active in 85% of the cases. Whereas primary activity outside of the sylvian regions was not seen for any of the children with LKS, 75% of the ASD children with epileptiform activity demonstrated additional nonsylvian zones of independent epileptiform activity. Despite the multifocal nature of the epileptiform activity in the ASDs, neurosurgical intervention aimed at control has lead to a reduction of autistic features and improvement in language skills in 12 of 18 cases. Conclusions. This study demonstrates that there is a subset of children with ASDs who demonstrate clinically relevant epileptiform activity during slow-wave sleep, and that this activity may be present even in the absence of a clinical seizure disorder. MEG showed significantly greater sensitivity to this epileptiform activity than simultaneous EEG, 1-hour clinical EEG, and 24-hour clinical EEG. The multifocal epileptiform pattern identified by MEG in the ASDs typically includes the same perisylvian brain regions identified as abnormal in LKS. When epileptiform activity is present in the ASDs, therapeutic strategies (antiepileptic drugs, steroids, and even neurosurgery) aimed at its control can lead to a significant improvement in language and autistic features. autism, pervasive developmental disorder–not otherwise specified, epilepsy, magnetoencephalography, Landau-Kleffner syndrome.

Integrated imaging approach with MEG and DTI to detect mild traumatic brain injury in military and civilian patients.

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild (and some moderate) TBI can be difficult to diagnose due to lack of obvious external injuries and because the injuries are often not visible on conventional acute MRI or CT. Injured brain tissues in TBI patients generate pathological low-frequency neuronal magnetic signal (delta waves 1-4 Hz) that can be measured and localized by magnetoencephalography (MEG). We hypothesize that abnormal MEG delta waves originate from gray matter neurons that experience de-afferentation due to axonal injury to the underlying white matter fiber tracts, which is manifested on diffusion tensor imaging (DTI) as reduced fractional anisotropy. The present study used a neuroimaging approach integrating findings of magnetoencephalography (MEG) and diffusion tensor imaging (DTI), evaluating their utility in diagnosing mild TBI in 10 subjects in whom conventional CT and MRI showed no visible lesions in 9. The results show: (1) the integrated approach with MEG and DTI is more sensitive than conventional CT and MRI in detecting subtle neuronal injury in mild TBI; (2) MEG slow waves in mild TBI patients originate from cortical gray matter areas that experience de-afferentation due to axonal injuries in the white matter fibers with reduced fractional anisotropy; (3) findings from the integrated imaging approach are consistent with post-concussive symptoms; (4) in some cases, abnormal MEG delta waves were observed in subjects without obvious DTI abnormality, indicating that MEG may be more sensitive than DTI in diagnosing mild TBI.

Commonalities and Differences Among Vectorized Beamformers in Electromagnetic Source Imaging

A number of beamformers have been introduced to localize neuronal activity using magnetoencephalography (MEG) and electroencephalography (EEG). However, currently available information about the major aspects of existing beamformers is incomplete. In the present study, detailed analyses are performed to study the commonalities and differences among vectorized versions of existing beamformers in both theory and practice. In addition, a novel beamformer based on higher-order covariance analysis is introduced. Theoretical formulas are provided on all major aspects of each beamformer; to examine their performance, computer simulations with different levels of correlation and signal-to-noise ratio are studied. Then, an empirical data set of human MEG median-nerve responses with a large number of neuronal generators is analyzed using the different beamformers. The results show substantial differences among existing MEG/EEG beamformers in their ways of describing the spatial map of neuronal activity. Differences in performance are observed among existing beamformers in terms of their spatial resolution, false-positive background activity, and robustness to highly correlated signals. Superior performance is obtained using our novel beamformer with higher-order covariance analysis in simulated data. Excellent agreement is also found between the results of our beamformer and the known neurophysiology of the median-nerve MEG response.

The neural networks underlying endogenous auditory covert orienting and reorienting

Auditory information communicated through vocalizations, music, or sounds in the environment is commonly used to orient and direct attention to different locations in extrapersonal space. The neural networks subserving attention to auditory space remain poorly understood in comparison to our knowledge about attention in the visual system. The present study investigated whether a parietal-prefrontal right-hemisphere network controls endogenous orienting and reorienting of attention to the location of sounds just as it does for visual-spatial information. Seventeen healthy adults underwent event-related functional magnetic resonance imaging (FMRI) while performing an endogenous auditory orienting task, in which peripheral cues correctly (valid) or incorrectly (invalid) specified the location of a forthcoming sound. The results showed that a right precuneus and bilateral temporal-frontal network mediated the reorienting of auditory attention at both short and long stimulus onset asynchronies (SOAs). In contrast, the more automatic stage of auditory reorienting at the shorter SOA was associated with activation in a bilateral inferior parietal-frontal oculomotor network. These findings suggest that the reorienting of auditory attention is generally supported by a similar inferior parietal-frontal network as visual attention, but in both hemispheres. However, peripheral auditory cues also appear to elicit an automatic orienting response to the spatial location of a sound followed by a period of reduced processing of information that occurs in the same location later in time.

Sources on the anterior and posterior banks of the central sulcus identified from magnetic somatosensory evoked responses using Multi-Start Spatio-Temporal localization

A Multi‐Start Spatio‐Temporal (MSST) multidipole localization algorithm was used to study sources on the anterior and posterior banks of the central sulcus localized from early somatosensory magnetoencephalography (MEG) responses. Electrical stimulation was applied to the right and left median nerves of 8 normal subjects. Two sources, one on the anterior and one on the posterior bank of the central sulcus, were localized from 16 data sets (8 subjects, 2 hemispheres). Compared with the more traditional practice of single‐dipole fits to peak latencies, MSST provided more reliable source locations. The temporal dynamics of the anterior and posterior central sulcus sources, obtained using MSST, showed considerable temporal overlap. In some cases, the two sources appeared synchronous. On the other hand, in the traditional single‐dipole peak‐latency fit approach, there is no time course other than a focal dipole moment activated only at the selected peak latency. The same group of subjects also performed a motor task involving index‐finger lifting; the anterior central sulcus source obtained from electrical median nerve stimulation localized to the same or similar region in the primary motor area identified from the finger‐lift task. The physiological significance of the anterior central sulcus source is discussed. The findings suggest that one can test the integrity of cortical tissue in the region of primary motor cortex using electrical somatosensory stimulation. Hum. Brain Mapping 11:59–76, 2000.

Predicting EEG responses using MEG sources in superior temporal gyrus reveals source asynchrony in patients with schizophrenia

OBJECTIVE An integrated analysis using Electroencephalography (EEG) and magnetoencephalography (MEG) is introduced to study abnormalities in early cortical responses to auditory stimuli in schizophrenia. METHODS Auditory responses were recorded simultaneously using EEG and MEG from 20 patients with schizophrenia and 19 control subjects. Bilateral superior temporal gyrus (STG) sources and their time courses were obtained using MEG for the 30-100 ms post-stimulus interval. The MEG STG source time courses were used to predict the EEG signal at electrode Cz. RESULTS In control subjects, the STG sources predicted the EEG Cz recording very well (97% variance explained). In schizophrenia patients, the STG sources accounted for substantially (86%) and significantly (P<0.0002) less variance. After MEG-derived STG activity was removed from the EEG Cz signal, the residual signal was dominated by 40 Hz activity, an indication that the remaining variance in EEG is probably contributed by other brain generators, rather than by random noise. CONCLUSIONS Integrated MEG and EEG analysis can differentiate patients and controls, and suggests a basis for a well established abnormality in the cortical auditory response in schizophrenia, implicating a disorder of functional connectivity in the relationship between STG sources and other brain generators.

A Novel Integrated MEG and EEG Analysis Method for Dipolar Sources

The ability of magnetoencephalography (MEG) to accurately localize neuronal currents and obtain tangential components of the source is largely due to MEGs insensitivity to the conductivity profile of the head tissues. However, MEG cannot reliably detect the radial component of the neuronal current. In contrast, the localization accuracy of electroencephalography (EEG) is not as good as MEG, but EEG can detect both the tangential and radial components of the source. In the present study, we investigated the conductivity dependence in a new approach that combines MEG and EEG to accurately obtain, not only the location and tangential components, but also the radial component of the source. In this approach, the source location and tangential components are obtained from MEG alone, and optimal conductivity values of the EEG model are estimated by best-fitting EEG signal, while precisely matching the tangential components of the source in EEG and MEG. Then, the radial components are obtained from EEG using the previously estimated optimal conductivity values. Computer simulations testing this integrated approach demonstrated two main findings. First, there are well-organized optimal combinations of the conductivity values that provide an accurate fit to the combined MEG and EEG data. Second, the radial component, in addition to the location and tangential components, can be obtained with high accuracy without needing to know the precise conductivity profile of the head. We then demonstrated that this new approach performed reliably in an analysis of the 20-ms component from human somatosensory responses elicited by electric median-nerve stimulation.

An automatic MEG low-frequency source imaging approach for detecting injuries in mild and moderate TBI patients with blast and non-blast causes

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. Injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1-4 Hz) that can be measured and localized by magnetoencephalography (MEG). We developed a new automated MEG low-frequency source imaging method and applied this method in 45 mild TBI (23 from combat-related blasts, and 22 from non-blast causes) and 10 moderate TBI patients (non-blast causes). Seventeen of the patients with mild TBI from blasts had tertiary injuries resulting from the blast. The results show our method detected abnormalities at the rates of 87% for the mild TBI group (blast-induced plus non-blast causes) and 100% for the moderate group. Among the mild TBI patients, the rates of abnormalities were 96% and 77% for the blast and non-blast TBI groups, respectively. The spatial characteristics of abnormal slow-wave generation measured by Z scores in the mild blast TBI group significantly correlated with those in non-blast mild TBI group. Among 96 cortical regions, the likelihood of abnormal slow-wave generation was less in the mild TBI patients with blast than in the mild non-blast TBI patients, suggesting possible protective effects due to the military helmet and armor. Finally, the number of cortical regions that generated abnormal slow-waves correlated significantly with the total post-concussive symptom scores in TBI patients. This study provides a foundation for using MEG low-frequency source imaging to support the clinical diagnosis of TBI.

Temporal dynamics of ipsilateral and contralateral motor activity during voluntary finger movement

The role of motor activity ipsilateral to movement remains a matter of debate, due in part to discrepancies among studies in the localization of this activity, when observed, and uncertainty about its time course. The present study used magnetoencephalography (MEG) to investigate the spatial localization and temporal dynamics of contralateral and ipsilateral motor activity during the preparation of unilateral finger movements. Eight right‐handed normal subjects carried out self‐paced finger‐lifting movements with either their dominant or nondominant hand during MEG recordings. The Multi‐Start Spatial Temporal multi‐dipole method was used to analyze MEG responses recorded during the movement preparation and early execution stage (−800 msec to +30 msec) of movement. Three sources were localized consistently, including a source in the contralateral primary motor area (M1) and in the supplementary motor area (SMA). A third source ipsilateral to movement was located significantly anterior, inferior, and lateral to M1, in the premotor area (PMA) (Brodmann area [BA] 6). Peak latency of the SMA and the ipsilateral PMA sources significantly preceded the peak latency of the contralateral M1 source by 60 msec and 52 msec, respectively. Peak dipole strengths of both the SMA and ipsilateral PMA sources were significantly weaker than was the contralateral M1 source, but did not differ from each other. Altogether, the results indicated that the ipsilateral motor activity was associated with premotor function, rather than activity in M1. The time courses of activation in SMA and ipsilateral PMA were consistent with their purported roles in planning movements. Hum. Brain Mapp. 23:26–39, 2004.

Neurobehavioral mechanisms of temporal processing deficits in Parkinson's disease.

Background Parkinsons disease (PD) disrupts temporal processing, but the neuronal sources of deficits and their response to dopamine (DA) therapy are not understood. Though the striatum and DA transmission are thought to be essential for timekeeping, potential working memory (WM) and executive problems could also disrupt timing. Methodology/Findings The present study addressed these issues by testing controls and PD volunteers ‘on’ and ‘off’ DA therapy as they underwent fMRI while performing a time-perception task. To distinguish systems associated with abnormalities in temporal and non-temporal processes, we separated brain activity during encoding and decision-making phases of a trial. Whereas both phases involved timekeeping, the encoding and decision phases emphasized WM and executive processes, respectively. The methods enabled exploration of both the amplitude and temporal dynamics of neural activity. First, we found that time-perception deficits were associated with striatal, cortical, and cerebellar dysfunction. Unlike studies of timed movement, our results could not be attributed to traditional roles of the striatum and cerebellum in movement. Second, for the first time we identified temporal and non-temporal sources of impaired time perception. Striatal dysfunction was found during both phases consistent with its role in timekeeping. Activation was also abnormal in a WM network (middle-frontal and parietal cortex, lateral cerebellum) during encoding and a network that modulates executive and memory functions (parahippocampus, posterior cingulate) during decision making. Third, hypoactivation typified neuronal dysfunction in PD, but was sometimes characterized by abnormal temporal dynamics (e.g., lagged, prolonged) that were not due to longer response times. Finally, DA therapy did not alleviate timing deficits. Conclusions/Significance Our findings indicate that impaired timing in PD arises from nigrostriatal and mesocortical dysfunction in systems that mediate temporal and non-temporal control-processes. However, time perception impairments were not improved by DA treatment, likely due to inadequate restoration of neuronal activity and perhaps corticostriatal effective-connectivity.