Changes in functional network centrality underlie cognitive dysfunction and physical disability in multiple sclerosis.

BACKGROUND: Cognitive dysfunction in multiple sclerosis (MS) has a large impact on the quality of life and is poorly understood. OBJECTIVE: The aim of this study was to investigate functional network integrity in MS, and relate this to cognitive dysfunction and physical disability. METHODS: Resting state fMRI scans were included of 128 MS patients and 50 controls. Eigenvector centrality mapping (ECM) was applied, a graph analysis technique that ranks the importance of brain regions based on their connectivity patterns. Significant ECM changes were related to physical disability and cognitive dysfunction. RESULTS: In MS patients, ECM values were increased in bilateral thalamus and posterior cingulate (PCC) areas, and decreased in sensorimotor and ventral stream areas. Sensorimotor ECM decreases were related to higher EDSS (rho = -0.24, p = 0.007), while ventral stream decreases were related to poorer average cognition (rho = 0.23, p = 0.009). The thalamus displayed increased connectivity to sensorimotor and ventral stream areas. CONCLUSION: In MS, areas in the ventral stream and sensorimotor cortex appear to become less central in the entire functional network of the brain, which is associated with clinico-cognitive dysfunction. The thalamus, however, displays increased connectivity with these areas. These findings may aid in further elucidating the function of functional reorganization processes in MS.

A framework to integrate EEG-correlated fMRI and intracerebral recordings.

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings. For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients. The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery.

Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease.

In this study we examined changes in the large-scale structure of resting-state brain networks in patients with Alzheimer's disease compared with non-demented controls, using concepts from graph theory. Magneto-encephalograms (MEG) were recorded in 18 Alzheimer's disease patients and 18 non-demented control subjects in a no-task, eyes-closed condition. For the main frequency bands, synchronization between all pairs of MEG channels was assessed using a phase lag index (PLI, a synchronization measure insensitive to volume conduction). PLI-weighted connectivity networks were calculated, and characterized by a mean clustering coefficient and path length. Alzheimer's disease patients showed a decrease of mean PLI in the lower alpha and beta band. In the lower alpha band, the clustering coefficient and path length were both decreased in Alzheimer's disease patients. Network changes in the lower alpha band were better explained by a 'Targeted Attack' model than by a 'Random Failure' model. Thus, Alzheimer's disease patients display a loss of resting-state functional connectivity in lower alpha and beta bands even when a measure insensitive to volume conduction effects is used. Moreover, the large-scale structure of lower alpha band functional networks in Alzheimer's disease is more random. The modelling results suggest that highly connected neural network 'hubs' may be especially at risk in Alzheimer's disease.

Interactions between different EEG frequency bands and their effect on alpha-fMRI correlations.

In EEG/fMRI correlation studies it is common to consider the fMRI BOLD as filtered version of the EEG alpha power. Here the question is addressed whether other EEG frequency components may affect the correlation between alpha and BOLD. This was done comparing the statistical parametric maps (SPMs) of three different filter models wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. EEG and fMRI were co-registered in a 30 min resting state condition in 15 healthy young subjects. Power variations in the delta, theta, alpha, beta and gamma bands were extracted from the EEG and used as regressors in a general linear model. Statistical parametric maps (SPMs) were computed using three different filter models, wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. Results show that the SPMs of different EEG frequency bands, when significant, are very similar to that of the alpha rhythm. This is true in particular for the beta band, despite the fact that the alpha harmonics were discarded. It is shown that inclusion of EEG frequency bands as confounder in the fMRI-alpha correlation model has a large effect on the resulting SPM, in particular when for each frequency band the HRF is extracted from the data. We conclude that power fluctuations of different EEG frequency bands are mutually highly correlated, and that a multi frequency model is required to extract the SPM of the frequency of interest from EEG/fMRI data. When no constraints are put on the shapes of the HRFs of the nuisance frequencies, the correlation model looses so much statistical power that no correlations can be detected.

How does upper extremity Fugl-Meyer motor score relate to resting-state EEG in chronic stroke? A power spectral density analysis.

OBJECTIVE: We investigated the potential added value of high-density resting-state EEG by addressing differences with healthy individuals and associations with Fugl-Meyer motor assessment of the upper extremity (FM-UE) scores in chronic stroke. METHODS: Twenty-one chronic stroke survivors with initial upper limb paresis and eleven matched controls were included. Group differences regarding resting-state EEG parameters (Delta Alpha ratio (DAR) and pairwise-derived Brain Symmetry Index (BSI)) and associations with FM-UE were investigated, as well as lateralization of BSI and the value of different frequency bands. RESULTS: Chronic stroke survivors showed higher BSI compared to controls (p < 0.001), most pronounced in delta and theta frequency bands (p < 0.0001; p < 0.001). In the delta and theta band, BSI was significantly negatively associated with FM-UE (both p = 0.008) corrected for confounding factors. DAR showed no differences between groups nor association with FM-UE. Directional BSI showed increased power in the affected versus the unaffected hemisphere. CONCLUSIONS: Asymmetry in spectral power between hemispheres was present in chronic stroke, most pronounced in low frequencies and related to upper extremity motor function deficit. SIGNIFICANCE: BSI is related to motor impairment and higher in chronic stroke patients compared to healthy controls, suggesting that BSI may be a marker of selective motor control.

Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia.

OBJECTIVE: To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD). BACKGROUND: Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans. MATERIALS AND METHODS: Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20  AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods. RESULTS: Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other. DISCUSSION AND CONCLUSION: Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.

Inter-observer variation of hippocampus delineation in hippocampal avoidance prophylactic cranial irradiation.

BACKGROUND: Hippocampal avoidance prophylactic cranial irradiation (HA-PCI) techniques have been developed to reduce radiation damage to the hippocampus. An inter-observer hippocampus delineation analysis was performed and the influence of the delineation variability on dose to the hippocampus was studied. MATERIALS AND METHODS: For five patients, seven observers delineated both hippocampi on brain MRI. The intra-class correlation (ICC) with absolute agreement and the generalized conformity index (CIgen) were computed. Median surfaces over all observers' delineations were created for each patient and regional outlining differences were analysed. HA-PCI dose plans were made from the median surfaces and we investigated whether dose constraints in the hippocampus could be met for all delineations. RESULTS: The ICC for the left and right hippocampus was 0.56 and 0.69, respectively, while the CIgen ranged from 0.55 to 0.70. The posterior and anterior-medial hippocampal regions had most variation with SDs ranging from approximately 1 to 2.5 mm. The mean dose (Dmean) constraint was met for all delineations, but for the dose received by 1% of the hippocampal volume (D1%) violations were observed. CONCLUSION: The relatively low ICC and CIgen indicate that delineation variability among observers for both left and right hippocampus was large. The posterior and anterior-medial border have the largest delineation inaccuracy. The hippocampus Dmean constraint was not violated.

Inter-rater agreement in glioma segmentations on longitudinal MRI.

BACKGROUND: Tumor segmentation of glioma on MRI is a technique to monitor, quantify and report disease progression. Manual MRI segmentation is the gold standard but very labor intensive. At present the quality of this gold standard is not known for different stages of the disease, and prior work has mainly focused on treatment-naive glioblastoma. In this paper we studied the inter-rater agreement of manual MRI segmentation of glioblastoma and WHO grade II-III glioma for novices and experts at three stages of disease. We also studied the impact of inter-observer variation on extent of resection and growth rate. METHODS: In 20 patients with WHO grade IV glioblastoma and 20 patients with WHO grade II-III glioma (defined as non-glioblastoma) both the enhancing and non-enhancing tumor elements were segmented on MRI, using specialized software, by four novices and four experts before surgery, after surgery and at time of tumor progression. We used the generalized conformity index (GCI) and the intra-class correlation coefficient (ICC) of tumor volume as main outcome measures for inter-rater agreement. RESULTS: For glioblastoma, segmentations by experts and novices were comparable. The inter-rater agreement of enhancing tumor elements was excellent before surgery (GCI 0.79, ICC 0.99) poor after surgery (GCI 0.32, ICC 0.92), and good at progression (GCI 0.65, ICC 0.91). For non-glioblastoma, the inter-rater agreement was generally higher between experts than between novices. The inter-rater agreement was excellent between experts before surgery (GCI 0.77, ICC 0.92), was reasonable after surgery (GCI 0.48, ICC 0.84), and good at progression (GCI 0.60, ICC 0.80). The inter-rater agreement was good between novices before surgery (GCI 0.66, ICC 0.73), was poor after surgery (GCI 0.33, ICC 0.55), and poor at progression (GCI 0.36, ICC 0.73). Further analysis showed that the lower inter-rater agreement of segmentation on postoperative MRI could only partly be explained by the smaller volumes and fragmentation of residual tumor. The median interquartile range of extent of resection between raters was 8.3% and of growth rate was 0.22 mm/year. CONCLUSION: Manual tumor segmentations on MRI have reasonable agreement for use in spatial and volumetric analysis. Agreement in spatial overlap is of concern with segmentation after surgery for glioblastoma and with segmentation of non-glioblastoma by non-experts.

A study of the brain's resting state based on alpha band power, heart rate and fMRI.

Considering that there are several theoretical reasons why fMRI data is correlated to variations in heart rate, these correlations are explored using experimental resting state data. In particular, the possibility is discussed that the "default network", being a brain area that deactivates during non-specific general tasks, is a hemodynamic effect caused by heart rate variations. Of fifteen healthy controls ECG, EEG and fMRI were co-registered. Slice time dependent heart rate regressors were derived from the ECG data and correlated to fMRI using a linear correlation analysis where the impulse response is estimated from the data. It was found that in most subjects substantial correlations between heart rate variations and fMRI exist, both within the brain and at the ventricles. The brain areas with high correlation to heart rate are different from the "default network" and the response functions deviate from the canonical hemodynamic response function. Furthermore, a general negative correlation was found between heart beat intervals (reverse of heart rate) and alpha power. We interpret this finding by assuming that subject's state varies between drowsiness and wakefulness. Finally, given this large correlation, we re-examined the contribution of heart rate variations to earlier reported fMRI/alpha band correlations, by adding heart rate regressors as confounders. It was found that inclusion of these confounders most often had a negligible effect. From its strong correlation to alpha power, we conclude that the heart rate variations contain important physiological information about subject's resting state. However, it does not provide a full explanation of the behaviour of the "default network". Its application as confounder in fMRI experiments is a relatively small computational effort, but may have a substantial impact in paradigms where heart rate is controlled by the stimulus.

Artifact removal in co-registered EEG/fMRI by selective average subtraction.

OBJECTIVE: Co-registration of EEG (electroencephalogram) and fMRI (functional magnetic resonance imaging) remains a challenge due to the large artifacts induced on the EEG by the MR (magnetic resonance) sequence magnetic fields. Thus, we present an algorithm, based on the average-subtraction method, which is able to correct EEG data for gradient and pulse artifacts. METHODS: MR sequence timing parameters are estimated from the EEG data and both slice and volume artifact templates are subtracted from the data. A clustering algorithm is proposed to account for the variability of the pulse artifact. RESULTS: The algorithm is able to keep the spontaneous EEG as well as visual evoked potentials (VEPs), while removing gradient and pulse artifacts with only a subtraction of selectively averaged data. In the frequency domain, the artifact frequencies are strongly attenuated. Estimated MR sequence time parameters showed that the correction is extremely sensitive to the slice time value. Pulse artifact clustering showed that most of the variability is due to the time jitter of the pulse artifact markers. CONCLUSIONS: Selective subtraction of averages in combination with proper time alignment is enough to remove most of the MR-induced artifacts. SIGNIFICANCE: Clean EEG can be obtained from raw signals that are corrupted by MR-induced artifacts during simultaneous EEG-fMRI scanning without using dedicated hardware to synchronize EEG and fMRI clocks.

Multimodal Source Imaging: Basic Methods, Signal Processing Techniques, and Applications.

Multimodal source imaging is an emerging field in biomedical engineering. Its central goal is to combine different imaging modalities in a single model or data representation, such that the combination provides an enhanced insight into the underlying physiological organ, compared to each modality separately. It requires advanced signal acquisition and processing techniques and has applications in cognitive neuroscience, clinical neuroscience and electrocardiology. Therefore, it belongs to the heart of biomedical engineering.

Event-related desynchronization during anticipatory attention for an upcoming stimulus: a comparative EEG/MEG study.

OBJECTIVES: Our neurophysiological model of anticipatory behaviour (e.g. Acta Psychol 101 (1999) 213; Bastiaansen et al., 1999a) predicts an activation of (primary) sensory cortex during anticipatory attention for an upcoming stimulus. In this paper we attempt to demonstrate this by means of event-related desynchronization (ERD). METHODS: Five subjects performed a time estimation task, and were informed about the quality of their time estimation by either visual or auditory stimuli providing Knowledge of Results (KR). EEG and MEG were recorded in separate sessions, and ERD was computed in the 8-10 and 10-12 Hz frequency bands for both datasets. RESULTS: Both in the EEG and the MEG we found an occipitally maximal ERD preceding the visual KR for all subjects. Preceding the auditory KR, no ERD was present in the EEG, whereas in the MEG we found an ERD over the temporal cortex in two of the 5 subjects. These subjects were also found to have higher levels of absolute power over temporal recording sites in the MEG than the other subjects, which we consider to be an indication of the presence of a 'tau' rhythm (e.g. Neurosci Lett 222 (1997) 111). CONCLUSIONS: It is concluded that the results are in line with the predictions of our neurophysiological model.

A whole head MEG study of the amplitude-modulation-following response: phase coherence, group delay and dipole source analysis.

OBJECTIVE: The amplitude-modulation-following response (AMFR) is the frequency component detectable in the electroencephalogram (EEG) or magnetoencephalography (MEG) corresponding to the modulation frequency of an amplitude modulated tone used as a continuous acoustic stimulus. Various properties of the AMFR depend on modulation frequency, suggesting that different generators along the auditory pathway are involved. The present study addresses these issues on the basis of a whole head MEG experiment. METHODS: AM tones with modulators in the 40 Hz and 80 Hz range were presented unilaterally to 10 normal hearing subjects. Biomagnetic responses were recorded with a 151 channel MEG system. The data analysis concentrated on the phase coherence of the responses, group delays and the estimated location of underlying equivalent dipole sources. RESULTS: MEG AMFR is more reliably detected in the 40 Hz than in the 80 Hz range. Both response amplitude and phase coherence indicate clear bilateral activation over the parietal/temporal region. Dipole source analysis confirms that sources are located in or near the auditory cortex. Group delays at 80 Hz are shorter than at 40 Hz. CONCLUSIONS: In both modulation frequency ranges MEG responses are dominated by activity in the auditory cortex, in apparent contrast with EEG data in the literature, pointing to dominant contributions of thalamic sources to the 80 Hz AMFR.

Magnetic source imaging contributes to the presurgical identification of sensorimotor cortex in patients with frontal lobe epilepsy.

OBJECTIVE: One of the primary goals of preoperative evaluation of patients considered to be candidates for epilepsy surgery is the delineation of eloquent cortex adjacent to the area of resection. The aim of this study is the functional localization of the sensorimotor cortex in relation to an epileptogenic frontal lobe lesion, thus enabling a more complete resection in these patients while minimizing the risk of postoperative neurological deficits. METHODS: Participating in this study were patients with epilepsy, diagnosed as being related to a left or right frontal lobe lesion. Magnetoencephalographic responses evoked by electrical stimulation of the left and right hand median nerve were localized using single time-point equivalent dipole (ED) modeling, taking into account the realistic shape of the head. Instead of relying on the primary component (N/P 20) of the somatosensory evoked magnetic fields (SEFs) in this study ED fits were obtained for each time-point of the somatosensory evoked responses. On a cortical rendering, the reconstructed dipoles were depicted relative to the anatomy obtained from 3D-magnetic resonance imaging. RESULTS: The results of single time-point ED analysis including all the components of the responses indicated that the sources underlying the SEFs are located at the borders of the central sulcus (CS). The opposite direction of the sources underlying, respectively, the primary and subsequent late component of the SEFs indicated distinct sources located at the opposite banks of the CS. These sources, therefore, might correspond to the sensory hand projection area and the primary motor area of the sensorimotor cortex. It appeared that the location of the EDs obtained for the SEFs of 4 of the 7 patients studied were asymmetric for the left and right hemisphere, probably because of a displacement of the sensorimotor areas relative to the CS. The systematic assessment of the dipole fits compared to brain anatomy confirmed that volume conduction changes due to the lesion were not responsible for these observed deviations, thus leaving as explanation space-occupying and neurophysiological changes due to the lesion.

The localization of spontaneous brain activity: first results in patients with cerebral tumors.

OBJECTIVE: From EEG studies, it is known that structural brain lesions are accompanied by abnormal rhythmic electric activity. With the better spatial resolution of MEG, MEG dipole analysis can extend the knowledge based on EEG power spectra. This study presents the first results of a completely automatic analysis method applied to spontaneous MEG. METHODS: Spontaneous MEG data of 5 patients with cerebral brain tumors and 4 controls were collected using a whole-head MEG system. Signals were bandpass-filtered with cut-off frequencies according to standard EEG bands. A moving dipole model was fitted to samples with at least twice the average sample power. Dipoles explaining 90% or more of the magnetic variance were projected onto a matched MR scan. RESULTS: In controls, dipole distributions are symmetrical with respect to the mid-sagittal plane whereas distributions in patients often are asymmetrical to it. Dipoles describing gamma activity were located contralateral, and dipoles describing delta and theta activity were located ipsilateral to lesions. CONCLUSIONS: The automatic method gives plausible 3-dimensional information about generator foci of abnormal slow waves and other rhythms with respect to lesion foci and thereby adds physiological knowledge to that derived from EEG power spectra.

Spike cluster analysis in neocortical localization related epilepsy yields clinically significant equivalent source localization results in magnetoencephalogram (MEG).

OBJECTIVE: In magnetoencephalogram (MEG) recordings of patients with epilepsy several types of sharp transients with different spatiotemporal distributions are commonly present. Our objective was to develop a computer based method to identify and classify groups of epileptiform spikes, as well as other transients, in order to improve the characterization of irritative areas in the brain of epileptic patients. METHODS: MEG data centered on selected spikes were stored in signal matrices of C channels by T time samples. The matrices were normalized and euclidean distances between spike representations in vector space R(CxT) were input to a Ward's hierarchical clustering algorithm. RESULTS: The method was applied to MEG data from 4 patients with localization-related epilepsy. For each patient, distinct spike subpopulations were found with clearly different topographical field maps. Inverse computations to selected spike subaverages yielded source solutions in agreement with seizure classification and location of structural lesions, if present, on magnetic resonance images. CONCLUSIONS: With the proposed method a reliable categorization of epileptiform spikes is obtained, that can be applied in an automatic way. Computation of subaverages of similar spikes enhances the signal-to-noise ratio of spike field maps and allows for more accurate reconstruction of sources generating the epileptiform discharges.

Automatic registration of pelvic computed tomography data and magnetic resonance scans including a full circle method for quantitative accuracy evaluation.

The purpose of this study is to develop a method for registration of CT and MR scans of the pelvis with minimal user interaction and to obtain a means for objective quantification of the registration accuracy of clinical data without markers. CT scans were registered with proton density MR scans using chamfer matching on automatically segmented bone. A fixed threshold was used to segment CT, while morphological filters were used to segment MR. The method was tested with transverse and coronal MR scans of 18 patients and sagittal MR scans of 8 patients. The registration accuracy was estimated by comparing (triangulating) registrations of a single CT scan with MR in different orientations in a "full circle." For example, CT is first matched on transverse MR, next transverse MR is matched independently on coronal MR, and finally coronal MR is matched independently on CT. The product of the three transformations is the identity if all matching steps are perfect. Deviations from identity occur both due to random errors and due to some types of systematic errors. MR was registered on MR (to close the "circle") by minimization of rms voxel value differences. CT-MR registration takes about 1 min, including user interaction. The random error for CT-MR registration with transverse or coronal MR was 0.5 mm in translation and 0.4 degree in rotation (standard deviation) for each axis. A systematic registration error of about 1 mm was demonstrated along the MR frequency encoding direction, which is attributed to the chemical shift. In conclusion, the presented algorithm efficiently and accurately registers pelvic CT and MR scans on bone. The "full circle" method provides an estimate of the registration accuracy on clinical data.

Magnetic source imaging in fixation-off sensitivity: relationship with alpha rhythm.

A patient in whom a variety of abnormal EEG findings can be elicited by elimination of central vision and fixation demonstrates fixation-off sensitivity. The underlying mechanisms of fixation-off sensitivity and its relationship with alpha rhythm remain unclear. To obtain a better understanding of this issue, we used a whole-head magnetoencephalograph to study an epileptic child with fixation-off sensitivity resulting in a 3-Hz, large-amplitude oscillation (300 microV) over the occipital regions on the EEG. Magnetic source localization revealed alpha activity around the calcarine fissure and surrounding parieto-occipital areas. Magnetic sources of abnormalities relating to fixation-off sensitivity, however, usually were located deeper in the brain, suggesting more extensively distributed sources, with involvement of the cingulate gyrus and the basomesial occipitotemporal region. Distributions of the sources of both types of activities show independent clusters but also an appreciable domain of overlap. Our findings indicate that abnormalities related to fixation-off sensitivity can emerge in thalamocortical networks, with larger and more anterior cortical distribution than those that generate alpha rhythm. Transition in the type of oscillation appears not only to depend on a change in cellular dynamics but also to be reflected in a different spatial distribution of the underlying neuronal networks.

The development of hemispheric asymmetry in human motion VEPs.

In six healthy adults we examined the sources underlying P1 and N2 of the motion VEP. For this purpose was acquired, in addition to the VEP, MRI images and patterns of regional cerebral blood flow with SPECT for three of the subjects. With the same motion stimulus we also examined the spatial distribution of N2 in children. In both adults and children left and right half-field responses were compared. It was found that N2 is generated by extrastriate activity and that motion stimuli are not equivalently processed in the two cerebral hemispheres. In adults, N2 dominates in one hemisphere irrespective of the visual half-field used for stimulation whereas children show an ipsilateral maximum for N2 upon half-field presentation.

Hemispheric asymmetry in the maturation of the extrastriate checkerboard onset evoked potential.

Recently we have shown that the single positive deflection in the checkerboard onset evoked potential (EP) of young children of striate origin develops into a negative-positive complex. However, also an early positive peak becomes apparent in the checkerboard onset EP. To determine the origin and development of the activity underlying this early positive deflection we studied the checkerboard onset EPs in children of 9-16 years of age. It was found that for the children in this age group two different dipole sources are responsible for the activity underlying the pattern onset EP. One of the dipoles corresponds to the activity generated in the striate cortex, whereas a second dipole of extrastriate origin is responsible for the appearance of the early positive deflection. This extrastriate activity shows hemispheric asymmetry, i.e. the strength of the right hemispheric extrastriate source exceeds the strength of the left hemispheric source. These results are in accordance with histological studies of Conel (1939-1963) [The postnatal development of the human cerebral cortex (Vols 1-8). Cambridge, Mass.: Harvard Univ. Press] which show that the maturation of the extrastriate areas of the left hemisphere is delayed with respect to the right hemisphere.