Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.

In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).

Brain structure and verbal function across adulthood while controlling for cerebrovascular risks.

The development and decline of brain structure and function throughout adulthood is a complex issue, with cognitive aging trajectories influenced by a host of factors including cerebrovascular risk. Neuroimaging studies of age-related cognitive decline typically reveal a linear decrease in gray matter (GM) volume/density in frontal regions across adulthood. However, white matter (WM) tracts mature later than GM, particularly in regions necessary for executive functions and memory. Therefore, it was predicted that a middle-aged group (MC: 35-45 years) would perform best on a verbal working memory task and reveal greater regional WM integrity, compared with both young (YC: 18-25 years) and elder groups (EC: 60+ years). Diffusion tensor imaging (DTI) and magnetoencephalography (MEG) were obtained from 80 healthy participants. Objective measures of cerebrovascular risk and cognition were also obtained. As predicted, MC revealed best verbal working memory accuracy overall indicating some maturation of brain function between YC and MC. However, contrary to the prediction fractional anisotropy values (FA), a measure of WM integrity, were not greater in MC (i.e., there were no significant differences in FA between YC and MC but both groups showed greater FA than EC). An overall multivariate model for MEG ROIs showed greater peak amplitudes for MC and YC, compared with EC. Subclinical cerebrovascular risk factors (systolic blood pressure and blood glucose) were negatively associated with FA in frontal callosal, limbic, and thalamic radiation regions which correlated with executive dysfunction and slower processing speed, suggesting their contribution to age-related cognitive decline. Hum Brain Mapp 38:3472-3490, 2017. © 2017 Wiley Periodicals, Inc.

Characterization of a normal control group: are they healthy?

We examined the health of a control group (18-81years) in our aging study, which is similar to control groups used in other neuroimaging studies. The current study was motivated by our previous results showing that one third of the elder control group had moderate to severe white matter hyperintensities and/or cortical volume loss which correlated with poor performance on memory tasks. Therefore, we predicted that cardiovascular risk factors (e.g., hypertension, high cholesterol) within the control group would account for significant variance on working memory task performance. Fifty-five participants completed 4 verbal and spatial working memory tasks, neuropsychological exams, diffusion tensor imaging (DTI), and blood tests to assess vascular risk. In addition to using a repeated measures ANOVA design, a cluster analysis was applied to the vascular risk measures as a data reduction step to characterize relationships between conjoint risk factors. The cluster groupings were used to predict working memory performance. The results show that higher levels of systolic blood pressure were associated with: 1) poor spatial working memory accuracy; and 2) lower fractional anisotropy (FA) values in multiple brain regions. In contrast, higher levels of total cholesterol corresponded with increased accuracy in verbal working memory. An association between lower FA values and higher cholesterol levels were identified in different brain regions from those associated with systolic blood pressure. The conjoint risk analysis revealed that Risk Cluster Group 3 (the group with the greatest number of risk factors) displayed: 1) the poorest performance on the spatial working memory tasks; 2) the longest reaction times across both spatial and verbal memory tasks; and 3) the lowest FA values across widespread brain regions. Our results confirm that a considerable range of vascular risk factors are present in a typical control group, even in younger individuals, which have robust effects on brain anatomy and function. These results present a new challenge to neuroimaging studies both for defining a cohort from which to characterize 'normative' brain circuitry and for establishing a control group to compare with other clinical populations.

Using joint ICA to link function and structure using MEG and DTI in schizophrenia.

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p<0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (neurophysiology) and structure (white matter integrity) and demonstrates that this multivariate, multimodal integration technique is sensitive to group differences in function and structure.

MEG-SIM: a web portal for testing MEG analysis methods using realistic simulated and empirical data.

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes ( http://cobre.mrn.org/megsim/ ). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.

Development and decline of memory functions in normal, pathological and healthy successful aging.

Many neuroimaging studies of age-related memory decline interpret resultant differences in brain activation patterns in the elderly as reflecting a type of compensatory response or regression to a simpler state of brain organization. Here we review a series of our own studies which lead us to an alternative interpretation, and highlights a couple of potential confounds in the aging literature that may act to increase the variability of results within age groups and across laboratories. From our perspective, level of cognitive functioning achieved by a group of elderly is largely determined by the health of individuals within this group. Individuals with a history of hypertension, for example, are likely to have multiple white matter insults which compromise cognitive functioning, independent of aging processes. The health of the elderly group has not been well-documented in most previous studies and elderly participants are rarely excluded, or placed into a separate group, due to health-related problems. In addition, recent results show that white matter tracts within the frontal and temporal lobes, regions critical for higher cognitive functions, continue to mature well into the 4th decade of life. This suggests that a young age group may not be the best control group for understanding aging effects on the brain since development is ongoing within this age range. Therefore, we have added a middle-age group to our studies in order to better understand normal development across the lifespan as well as effects of pathology on cognitive functioning in the aging brain.

Different strategies for auditory word recognition in healthy versus normal aging.

To explore the effects of commonly encountered pathology on auditory recognition strategies in elderly participants, magnetoencephalographic (MEG) brain activation patterns and performance were examined in 30 elderly [18 controls and 12 elderly with mild cognitive impairment (MCI) or probable Alzheimer's disease (AD)]. It was predicted that participants with known pathology would reveal different networks of brain activation, compared to healthy elderly, which should correlate with poorer performance. Participants heard a list of words representing common objects, twice. After 20 minutes a list of new and old words was presented and participants judged whether each word was heard earlier. MEG responses were analyzed using a semiautomated source modeling procedure. A cluster analysis using all subjects' MEG sources revealed three dominant patterns of activity which correlated with IQ and task performance. The highest performing group revealed activity in premotor, anterior temporal, and superior parietal lobes with little contribution from prefrontal cortex. Performance and brain activation patterns were also compared for individuals with or without abnormalities such as white matter hyperintensities and/or volume reduction evidenced on their MRIs. Memory performance and activation patterns for individuals with white matter hyperintensities resembled the group of MCI/AD patients. These results emphasize the following: (1) general pathology correlates with cognitive decline and (2) full characterization of the health of elderly participants is important in studies of normal aging since random samples from the elderly population are apt to include individuals with subclinical pathology that can affect cognitive performance.

Modelling the magnetic signature of neuronal tissue.

Neuronal communication in the brain involves electrochemical currents, which produce magnetic fields. Stimulus-evoked brain responses lead to changes in these fields and can be studied using magneto- and electro-encephalography (MEG/EEG). In this paper we model the spatiotemporal distribution of the magnetic field of a physiologically idealized but anatomically realistic neuron to assess the possibility of using magnetic resonance imaging (MRI) for directly mapping the neuronal currents in the human brain. Our results show that the magnetic field several centimeters from the centre of the neuron is well approximated by a dipole source, but the field close to the neuron is not, a finding particularly important for understanding the possible contrast mechanism underlying the use of MRI to detect and locate these currents. We discuss the importance of the spatiotemporal characteristics of the magnetic field in cortical tissue for evaluating and optimizing an experiment based on this mechanism and establish an upper bound for the expected MRI signal change due to stimulus-induced cortical response. Our simulations show that the expected change of the signal magnitude is 1.6% and its phase shift is 1 degrees . An unexpected finding of this work is that the cortical orientation with respect to the external magnetic field has little effect on the predicted MRI contrast. This encouraging result shows that magnetic resonance contrast directly based on the neuronal currents present in the cortex is theoretically a feasible imaging technique. MRI contrast generation based on neuronal currents depends on the dendritic architecture and we obtained high-resolution optical images of cortical tissue to discuss the spatial structure of the magnetic field in grey matter.

Task relevance enhances early transient and late slow-wave activity of distributed cortical sources.

The primary purpose of these studies was to link together concepts related to attention/working memory and feedforward/feedback activity using MEG response profiles obtained in humans. Similar to recent studies of attention in monkeys, we show early "spike-like" activity (<200 ms poststimulus), most likely reflecting an early transient excitatory response mixed with feedback influences, followed by "slow-wave" activity (>200 ms poststimulus) in MEG cortical response profiles evoked by a visual working memory task. We experimentally dissociated the early transient activity from the later sustained activity (predominantly feedback) by conducting an auditory size classification task. Words, representing common objects, evoked activity in occipital cortex (presumably due to imagery) even though visual stimuli were not present in this task. The initial "spike" was absent from the response profile obtained from occipital cortex, leaving only "slow-wave" activity, thereby allowing us to characterize or profile feedback activity in this situation. Attention or task relevance enhanced the initial "spike" and "slow-wave" activity in visually responsive areas. Prefrontal activity, along the superior frontal sulcus, evoked by the working memory task, was active later in time than initial activity in visual cortex and later than the earliest effect of attention modulation in visual cortex.

Multidipole analysis of simulated epileptic spikes with real background activity.

This simulated magnetoencephalographic study was designed to determine the variability in source parameters with real subject background activity when applying multidipole spatial-temporal dipole analyses, for which the correct model was compared with undermodeled and overmodeled cases. The simulated sources were created from patches of the cortical surface of each subject's MRI. One- and two-source frontal lobe spikes were generated in two cortical regions seen commonly in frontal lobe epilepsy patients tested at our site (orbital frontal and premotor cortex). In general, the modeling results were adequate for the correct model order and the correct model order plus one. In addition, if the localization error was less than 10 mm from the simulated source, the peak latency of the spike and orientation were very reliable, but the peak amplitude was not. The additional source in the overmodeled condition, on the other hand, was not localized reliably across the different epochs within subjects. The results suggest that consistency of the spike localization and inconsistency of other sources will allow one to determine reliably the appropriate model order in real data, and therefore determine single and multifocal spike generators.

Single vs. paired visual stimulation: superposition of early neuromagnetic responses and retinotopy in extrastriate cortex in humans.

Neuromagnetic techniques were used in conjunction with magnetic resonance imaging (MRI) techniques to: (1) localize and characterize cortical sources evoked by visual stimuli presented at different locations in the lower right visual field; (2) examine the superposition of cortical responses by comparing the summation of responses to the presentation of single stimuli with responses to paired stimuli; and (3) examine the spatial resolution of magnetoencephalographic (MEG) techniques by comparing the identified source locations evoked by the presentation of single vs. paired stimuli. Using multi-dipole, non-linear minimization analyses, three sources were localized for each stimulus condition during the initial 80-170 ms poststimulus interval for all subjects. In addition to an occipital source, two extrastriate sources were identified: occipital-parietal and occipital-temporal. Each source evidenced a systematic shift in location associated with changes in stimulus placement parallel to the vertical meridian. To our knowledge, this is the first demonstration of retinotopic organization of extrastriate areas, using non-invasive neuromagnetic techniques. The paired presentation of stimuli reflected superposition of the responses evoked by single stimuli but only for early activity up to 150 ms poststimulus. Undersummation was evident after 150 ms. All sources identified for single stimuli were also identified in the paired-stimulus responses; but at the expense of larger errors for some of the estimated parameters.

Multi-start downhill simplex method for spatio-temporal source localization in magnetoencephalography.

A multi-start downhill simplex method is examined as a global minimization technique for fitting multidipole, spatio-temporal magnetoencephalography (MEG) data. This procedure has been performed on both simulated and empirical human visual data, known to exhibit complex field patterns due to multiple sources. Unlike some other non-linear fitting techniques the multi-start downhill simplex method does not require users to provide initial guesses for the dipole parameters, hence the fitting procedure is less time-consuming, more objective, and user-friendly. In addition, this method offers more than one adequate solution thus providing a range of uncertainty for the estimated parameters. The Multi-start downhill simplex method is used to fit the non-linear dipole spatial parameters, while the linear temporal parameters are fit using a separate linear fitting procedure. Singular value decomposition (SVD) is also used in order to improve the procedure for determining the adequate number of modeled dipoles.

Spatio-temporal modeling of neuromagnetic data: I. Multi-source location versus time-course estimation accuracy.

Numerical simulations were conducted to examine multi-source spatio-temporal resolution for neuromagnetic field distributions "measured" by a large sensor array (i.e., 135). spatio-temporal field distributions were generated by a series of two-dipole and three-dipole configurations in which source locations, orientations, and temporal dynamics of individual sources were systematically varied to represent classes of cases of interest for neuromagnetic studies. The specific goals of our numerical simulations were to examine multi-source resolution and parameter estimation accuracy as a function of 1) specific multi-source configurations; 2) different time courses, i.e., degree of temporal correlation; 3) measurement noise; 4) spatio-temporal modeling strategy (i.e., sequential fitting of instantaneous field distributions, two-step spatio-temporal modeling); 5) source modeling assumptions associated with model order; and 6) effects of initial modeling assumptions (i.e., starting points for the nonlinear minimization procedure derived by MUltiple SIgnal Classification (MUSIC), sequential instantaneous fitting, and arbitrary selections). The ability to determine the number of active sources by different approaches is compared, and the consequences on the accuracy of estimated solutions for simulated data are discussed. In all cases, model adequacy was assessed using reduced chi-square as a measure of goodness-of-fit. The present simulations demonstrate that location estimation was more robust and accurate compared to the estimation of temporal dynamics of individual sources. Implications for spatio-temporal modeling of neuromagnetic empirical data are suggested.

Spatio-temporal modeling of neuromagnetic data: II. Multi-source resolvability of a MUSIC-based location estimator.

A MUItiple SIgnal Classification-based (MUSIC) approach for neuromagnetic multi-source localization (Mosher et al. [1992] (IEEE Trans Med Eng BME-39:541-557) was evaluated through numerical simulations and by applying it to visually evoked neuromagnetic responses. A series of two-dipole and three-dipole spatio-temporal data were generated to examine effects of 1) source configurations, 2) temporal correlations, 3) noise, and 4) subspace dimensionality assumptions on the number of MUSIC metric maxima, their amplitudes, and how the resulting metric maxima locations relate to the actual source locations. In its present form, i.e., using simple one-dipole scanning over an assumed source subspace, MUSIC resulted either in 1) peaks sufficiently close to 1, but fewer than the actual number of sources which affected location estimation accuracy, or 2) the peaks were too low to qualify as source locations. Our simulations indicate difficulties in defining threshold values as to which peak values are close enough to 1 while avoiding significant type II errors (i.e., accepting peaks which should not be interpreted as source locations). Modifications to the MUSIC approach are necessary in order for the method to be considered of practical value for reliably localizing multiple neuromagnetic sources in empirical cases in which a high degree of temporal correlation between sources is likely (e.g., visual data).

Nonlinear analysis of biological systems using short M-sequences and sparse-stimulation techniques.

The m-sequence pseudorandom signal has been shown to be a more effective probing signal than traditional Gaussian white noise for studying nonlinear biological systems using cross-correlation techniques. The effectiveness is evidenced by the high signal-to-noise (S/N) ratio and speed of data acquisition. However, the "anomalies" that occur in the estimations of the cross-correlations represent an obstacle that prevents m-sequences from being more widely used for studying nonlinear systems. The sparse-stimulation method for measuring system kernels can help alleviate estimation errors caused by anomalies. In this paper, a "padded sparse-stimulation" method is evaluated, a modification of the "inserted sparse-stimulation" technique introduced by Sutter, along with a short m-sequence as a probing signal. Computer simulations show that both the "padded" and "inserted" methods can effectively eliminate the anomalies in the calculation of the second-order kernel, even when short m-sequences were used (length of 1023 for a binary m-sequence, and 728 for a ternary m-sequence). Preliminary experimental data from neuromagnetic studies of the human visual system are also presented, demonstrating that the system kernels can be measured with high signal-to-noise (S/N) ratios using short m-sequences.

Retinotopic organization of human visual cortex: departures from the classical model.

Retinotopic mapping strategies similar to those used for invasive electrophysiological studies to identify multiple visual areas in monkeys have been adapted for noninvasive studies in humans, using magnetic recordings of brain activity in conjunction with anatomical magnetic resonance imaging. The retinotopic organization of the primary visual area (V1) in the left hemisphere of human subjects was examined by presenting a small patterned stimuli near the vertical and horizontal meridians in the lower right visual field. In contrast with the classical model of V1 retinotopy, our results suggest that the representation of the horizontal meridian does not necessarily correspond in a one-to-one manner with the base of the calcarine fissure and that some lower field stimuli can activate regions in the lower bank of the fissure. The results also indicate significant individual variability in the details of how V1 maps around the calcarine fissure.

Mapping function in the human brain with magnetoencephalography, anatomical magnetic resonance imaging, and functional magnetic resonance imaging.

Integrated analyses of human anatomical and functional measurements offer a powerful paradigm for human brain mapping. Magnetoencephalography (MEG) and EEG provide excellent temporal resolution of neural population dynamics as well as capabilities for source localization. Anatomical magnetic resonance imaging (MRI) provides excellent spatial resolution of head and brain anatomy, whereas functional MRI (fMRI) techniques provide an alternative measure of neural activation based on associated hemodynamic changes. These methodologies constrain and complement each other and can thereby improve our interpretation of functional neural organization. We have developed a number of computational tools and techniques for the visualization, comparison, and integrated analysis of multiple neuroimaging techniques. Construction of geometric anatomical models from volumetric MRI data allows improved models of the head volume conductor and can provide powerful constraints for neural electromagnetic source modeling. These approaches, coupled to enhanced algorithmic strategies for the inverse problem, can significantly enhance the accuracy of source-localization procedures. We have begun to apply these techniques for studies of the functional organization of the human visual system. Such studies have demonstrated multiple, functionally distinct visual areas that can be resolved on the basis of their locations, temporal dynamics, and differential sensitivity to stimulus parameters. Our studies have also produced evidence of internal retinotopic organization in both striate and extrastriate visual areas but have disclosed organizational departures from classical models. Comparative studies of MEG and fMRI suggest a reasonable but imperfect correlation between electrophysiological and hemodynamic responses. We have demonstrated a method for the integrated analysis of fMRI and MEG, and we outline strategies for improvement of these methods. By combining multiple measurement techniques, we can exploit the complementary strengths and transcend the limitations of the individual neuro-imaging methods.

Temporal dynamics of visual-evoked neuromagnetic sources: effects of stimulus parameters and selective attention.

Results are reviewed from several neuromagnetic studies which characterize the temporal dynamics of neural sources contributing to the visual evoked response and effects of attention on these sources. Different types of pattern-onset stimuli (< or = 2 degrees) were presented sequentially to a number of field locations in the right visual field. Multiple dipole models were applied to a sequence of instantaneous field distributions constructed at 10 ms intervals. Best-fitting source parameters were superimposed on Magnetic Resonance images (MRI) of each subject to identify the anatomical structure(s) giving rise to the surface patterns. At least three sources, presumably corresponding to different visual areas, were routinely identified from 80-150 ms following the onset of visual stimulation. This observation was consistent across subjects and studies. The temporal sequence and strength of activation of these sources, however, were dependent upon the specific stimulus parameters used to evoke the response (e.g., eccentricity) and on the relevance of the stimulus to the subject. In addition, our results provide evidence for the recurrence of activity in striate and extrastriate regions, following the initial cycle of responses.

A conceptual overview and critique of functional neuroimaging techniques in humans: I. MRI/FMRI and PET.

A critical evaluation of current, noninvasive brain-mapping techniques indicates that no one technique in isolation can adequately address the varied questions of interest to basic researchers and clinicians. Consequently, an integrated analysis of anatomical and functional measurements has become the ultimate goal to better characterize the nature of neuronal and hemodynamic responses to sensory and cognitive stimulation. Such an analysis will optimize both spatial and temporal resolution, thereby enabling patterns of activation to be followed throughout the central nervous system, a prerequisite for examining stages of information processing. This review, written in two parts, provides a conceptual overview of three techniques (MRI/fMRI, PET, and MEG/EEG) and examines current efforts at integrating these measures. Each technique is initially evaluated in isolation by considering a set of primary issues (e.g., spatial resolution, temporal resolution, the nature of the signal, individual variability, repeatability, etc.). The first part compares and contrasts MRI/fMRI techniques with PET. Part II, which examines MEG/EEG techniques and current attempts at integrating techniques, will appear in a subsequent volume. This two-part review focuses on issues, not results per se, and it is assumed that the reader is not proficient in any of the techniques described.

Simulation studies of multiple dipole neuromagnetic source localization: model order and limits of source resolution.

Numerical simulation studies were performed using a multiple dipole source model and a spherical approximation of the head to examine how the resolution of simultaneously active neuromagnetic sources depends upon: 1) source modeling assumptions (i.e., number of assumed dipoles); 2) actual source parameters (e.g., location, orientation, and moment); and 3) measurement errors. Forward calculations were conducted for a series of source configurations in which the number of dipoles, specific dipole parameters, and noise levels were systematically varied. Simulated noisy field distributions were fit by multiple dipole models of increasing model order (1, 2, ..., 6 and alternative statistical approaches (i.e., percent of variance, reduced chi-square, and F-ratio) were compared for their effectiveness in determining adequate model order. Limits of spatial resolution were established for a variety of multi-source configurations and noise conditions. Implications for the analysis of empirical data are discussed.