Robert J. Thoma

A Baseline for the Multivariate Comparison of Resting-State Networks

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

Resting state and task-induced deactivation: A methodological comparison in patients with schizophrenia and healthy controls

Changes in the default mode network (DMN) have been linked to multiple neurological disorders including schizophrenia. The anticorrelated relationship the DMN shares with task‐related networks permits the quantification of this network both during task (task‐induced deactivations: TID) and during periods of passive mental activity (extended rest). However, the effects of different methodologies (TID vs. extended rest) for quantifying the DMN in the same clinical population are currently not well understood. Moreover, several different analytic techniques, including independent component analyses (ICA) and seed‐based correlation analyses, exist for examining functional connectivity during extended resting states. The current study compared both methodologies and analytic techniques in a group of patients with schizophrenia (SP) and matched healthy controls. Results indicated that TID analyses, ICA, and seed‐based correlation all consistently identified the midline (anterior and posterior cingulate gyrus) and lateral parietal cortex as core regions of the DMN, as well as more variable involvement of temporal lobe structures. In addition, SP exhibited increased deactivation during task, as well as decreased functional connectivity with frontal regions and increased connectivity with posterior and subcortical areas during periods of extended rest. The increased posterior and reduced anterior connectivity may partially explain some of the cognitive dysfunction and clinical symptoms that are frequently associated with schizophrenia. Hum Brain Mapp, 2010.

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.

Adolescent Substance Abuse: The Effects of Alcohol and Marijuana on Neuropsychological Performance

BACKGROUND Adolescence is a period in which cognition and brain undergo dramatic parallel development. Whereas chronic use of alcohol and marijuana is known to cause cognitive impairments in adults, far less is known about the effect of these substances of abuse on adolescent cognition, including possible interactions with developmental processes. METHODS Neuropsychological performance, alcohol use, and marijuana use were assessed in 48 adolescents (ages 12 to 18), recruited in 3 groups: a healthy control group (HC, n = 15), a group diagnosed with substance abuse or dependence (SUD, n = 19), and a group with a family history positive for alcohol use disorder (AUD) but no personal substance use disorder (FHP, n = 14). Age, drinks per drinking day (DPDD), percentage days drinking, and percentage days using marijuana were considered as covariates in a MANCOVA in which 6 neuropsychological composites (Verbal Reasoning, Visuospatial Ability, Executive Function, Memory, Attention, and Processing Speed) served as dependent variables. RESULTS More DPDD predicted poorer performance on Attention and Executive Function composites, and more frequent use of marijuana was associated with poorer Memory performance. In separate analyses, adolescents in the SUD group had lower scores on Attention, Memory, and Processing Speed composites, and FHP adolescents had poorer Visuospatial Ability. CONCLUSIONS In combination, these analyses suggest that heavy alcohol use in adolescence leads to reduction in attention and executive functioning and that marijuana use exerts an independent deleterious effect on memory. At the same time, premorbid deficits associated with family history of AUD appeared to be specific to visuospatial ability.

M50 sensory gating predicts negative symptoms in schizophrenia.

Impaired auditory sensory gating is considered characteristic of schizophrenia and a marker of the information processing deficit inherent to that disorder. Predominance of negative symptoms also reflects the degree of deficit in schizophrenia and is associated with poorer pre-morbid functioning, lower IQ, and poorer outcomes. However, a consistent relationship between auditory sensory gating and negative symptoms in schizophrenia has yet to be demonstrated. The absence of such a finding is surprising, since both impaired auditory gating and negative symptoms have been linked with impaired fronto-temporal cortical function. The present study measured auditory gating using the P50 event related potential (ERP) in a paired-click paradigm and capitalized on the relative localization advantage of magnetoencephalography (MEG) to assess auditory sensory gating in terms of the event related field (ERF) M50 source dipoles on bilateral superior temporal gyrus (STG). The primary hypothesis was that there would be a positive correlation between lateralized M50 auditory sensory gating measures and negative symptoms in patients with schizophrenia. A standard paired-click paradigm was used during simultaneous EEG and MEG data collection to determine S2/S1 sensory gating ratios in a group of 20 patients for both neuroimaging techniques. Participants were administered the Schedule for the Assessment of Negative Symptoms (SANS), the Positive and Negative Symptom Scale (PANSS), and the Calgary Depression Scale for Schizophrenia. Consistent with previous reports, there was no relationship between ERP P50 sensory gating and negative symptoms. However, right (not left) hemisphere ERF M50 sensory gating ratio was significantly and positively correlated with negative symptoms. This finding is compatible with information processing theories of negative symptoms and with more recent findings of fronto-temporal abnormality in patients with predominantly negative symptoms.

Studying Hallucinations Within the NIMH RDoC Framework

We explore how hallucinations might be studied within the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) framework, which asks investigators to step back from diagnoses based on symptoms and focus on basic dimensions of functioning. We start with a description of the objectives of the RDoC project and its domains and constructs. Because the RDoC initiative asks investigators to study phenomena across the wellness spectrum and different diagnoses, we address whether hallucinations experienced in nonclinical populations are the same as those experienced by people with psychotic diagnoses, and whether hallucinations studied in one clinical group can inform our understanding of the same phenomenon in another. We then discuss the phenomenology of hallucinations and how different RDoC domains might be relevant to their study. We end with a discussion of various challenges and potential next steps to advance the application of the RDoC approach to this area of research.

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.

The evolutionary genetic underpinnings of schizophrenia: the developmental instability model.

The importance of genes in the etiology of schizophrenia is well known, but the manner in which the relevant genomic factors influence neural development and the nature of selection forces operating on these factors are poorly understood. In several prominent papers, Crow has provided a unique and comprehensive theory that attempts to deal with these issues. A central aspect of his theory is that a single gene leads to reduced cerebral lateralization, increased ventricular size, and risk for developing schizophrenia. He relies greatly on Annetts right shift theory of individual variation in handedness. An alternative approach, based on the construct of developmental instability, provides a different way to conceptualize genetic influences, selection forces, and atypical lateralization in schizophrenia. We suggest that the developmental instability model has stronger empirical support and is better grounded in contemporary evolutionary genetics.

Developmental instability and cerebral lateralization.

On the basis of prior studies of handedness, it was predicted that variations from modal asymmetry scores on cognitive tasks, in either direction from the mean, would be associated with an elevated incidence of classic markers of developmental instability (minor physical anomalies and fluctuating anatomic asymmetries). University students (N = 146) were administered 4 tasks that typically reveal functional asymmetries: the fused rhymed words dichotic listening task, the line bisection task, the chimeric faces task, and the cartoon faces task. A composite measure of developmental instability was computed from minor physical anomalies and fluctuating asymmetries. Participants with greater evidence of developmental instability had more atypical lateralization scores, deviating more from the sample mean, in either direction. Directional asymmetries were unrelated to developmental instability. These results suggest that developmental instability influences variation in the lateralization of cognitive skills as well as handedness.

A parietal-frontal network studied by somatosensory oddball MEG responses, and its cross-modal consistency.

Previous studies using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) of the brain have found that a distributed parietal-frontal neuronal network is activated in normals during both auditory and visual oddball tasks. The common cortical regions in this network are inferior parietal lobule (IPL)/supramarginal gyrus (SMG), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). It is not clear whether the same network is activated by oddball tasks during somatosensory stimulation. The present study addressed this question by testing healthy adults as they performed a novel median-nerve oddball paradigm while undergoing magnetoencephalography (MEG). An automated multiple dipole analysis technique, the Multi-Start Spatio-Temporal (MSST) algorithm, localized multiple neuronal generators, and identified their time-courses. IPL/SMG, ACC, and DLPFC were reliably localized in the MEG median-nerve oddball responses, with IPL/SMG activation significantly preceding ACC and DLPFC activation. Thus, the same parietal-frontal neuronal network that shows activation during auditory and visual oddball tests is activated in a median-nerve oddball paradigm. Regions uniquely related to somatosensory oddball responses (e.g., primary and secondary somatosensory, dorsal premotor, primary motor, and supplementary motor areas) were also localized. Since the parietal-frontal network supports attentional allocation during performance of the task, this study may provide a novel method, as well as normative baseline data, for examining attention-related deficits in the somatosensory system of patients with neurological or psychiatric disorders.