Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease.

INTRODUCTION: Memory-associated neural circuits produce oscillatory events including theta bursts (TBs), sleep spindles (SPs), and slow waves (SWs) in sleep electroencephalography (EEG). Changes in the "coupling" of these events may indicate early Alzheimer's disease (AD) pathogenesis. METHODS: We analyzed 205 aging adults using single-channel sleep EEG, cerebrospinal fluid (CSF) AD biomarkers, and Clinical Dementia Rating® (CDR®) scale. We mapped SW-TB and SW-SP neural circuit coupling precision to amyloid positivity, cognitive impairment, and CSF AD biomarkers. RESULTS: Cognitive impairment correlated with lower TB spectral power in SW-TB coupling. Cognitively unimpaired, amyloid positive individuals demonstrated lower precision in SW-TB and SW-SP coupling compared to amyloid negative individuals. Significant biomarker correlations were found in oscillatory event coupling with CSF Aß42 /Aß40 , phosphorylated- tau181 , and total-tau. DISCUSSION: Sleep-dependent memory processing integrity in neural circuits can be measured for both SW-TB and SW-SP coupling. This breakdown associates with amyloid positivity, increased AD pathology, and cognitive impairment. HIGHLIGHTS: At-home sleep EEG is a potential biomarker of neural circuits linked to memory. Circuit precision is associated with amyloid positivity in asymptomatic aging adults. Levels of CSF amyloid and tau also correlate with circuit precision in sleep EEG. Theta burst EEG power is decreased in very early mild cognitive impairment. This technique may enable inexpensive wearable EEGs for monitoring brain health.

Magnetoencephalography for Epilepsy Presurgical Evaluation.

PURPOSE OF THE REVIEW: Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG. RECENT FINDINGS: MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.

Spatiotemporal dynamics of selective attention and visual conflict monitoring using a Stroop task.

Selective attention and conflict monitoring are daily human phenomena, yet the spatial and temporal neurological underpinnings of these processes are not fully understood. Current literature suggests these executive functions occur via diverse and highly interconnected neural networks, including top-down, bottom-up, and conflict-control loops. To investigate the spatiotemporal activity of these processes, we collected neuromagnetic data using magnetoencephalography (MEG) in 28 healthy adults (age 19-36), while they performed a computerized Stroop task based on color naming. We focused on low-frequency oscillations in the context of top-down control and hypothesized that conflict monitoring-related activity would first be observed in the left anterior cingulate cortex, followed by the left dorsolateral prefrontal cortex, and subsequently in the parietal and temporal lobes. Significant activity between 600-1000 ms post-stimulus onset was found for incongruent vs. congruent/neutral contrasts. Interestingly, spatiotemporal analysis did not provide evidence for a top-down pattern of activation, instead revealing a simultaneous pattern of activation in the frontal and temporal lobes. Most notable is the involvement of the left posterior inferior temporal cortex (pITC) and the left temporoparietal junction (TPJ), which have not conventionally been considered active players in attentional control. These results may be largely driven by alpha and beta oscillations from our sample population. Our findings challenge early theoretical models of top-down processing in the context of cognitive control from an attention perspective and also suggest a need to investigate attentional centers in the temporal lobe. Furthermore, the study highlights the valuable temporal data provided by MEG, which has been missing from previous studies.

An integrated full-head OPM-MEG system based on 128 zero-field sensors.

Compact optically-pumped magnetometers (OPMs) are now commercially available with noise floors reaching 10 fT/Hz1/2. However, to be used effectively for magnetoencephalography (MEG), dense arrays of these sensors are required to operate as an integrated turn-key system. In this study, we present the HEDscan, a 128-sensor OPM MEG system by FieldLine Medical, and evaluate its sensor performance with regard to bandwidth, linearity, and crosstalk. We report results from cross-validation studies with conventional cryogenic MEG, the Magnes 3,600 WH Biomagnetometer by 4-D Neuroimaging. Our results show high signal amplitudes captured by the OPM-MEG system during a standard auditory paradigm, where short tones at 1000 Hz were presented to the left ear of six healthy adult volunteers. We validate these findings through an event-related beamformer analysis, which is in line with existing literature results.

Sex Differences in Effects of Mood, Eating-Related Behaviors, and BMI on Food Appeal and Desire to Eat: A Cross-Sectional Survey Study.

Although sex differences in food intake have been observed consistently, contributing factors are not well understood. Using a cross-sectional online survey (n = 306; 151 men, 155 women), this study aimed to assess how sex impacts relationships between food ratings (appeal/desire to eat for high-calorie (HC) and low-calorie (LC) food images) and eating-related attitudes/behaviors, body mass index (BMI), and mood. Across participants, increased state- and trait-based hunger, disinhibition, and cravings were associated with both increased HC appeal and desire (p < 0.001). Increased state-based hunger and cravings were associated with greater LC desire (p < 0.001). Greater satiety was associated with decreased desire for both HC and LC (p < 0.001), while greater anxiety was associated with increased desire for both HC and LC (p < 0.001). Significant associations between BMI and food ratings were not observed. Women reported greater dietary restraint, trait-based hunger, disinhibition, eating disorder-related behaviors, depression, and stress compared to men, in addition to greater appeal and familiarity with LC foods (all p < 0.05). Significant effects of sex on the associations between food ratings and eating-related attitudes/behaviors, BMI, and mood were not observed, however. Findings support the importance of considering mood and eating-related attitudes/behaviors in investigations of food cue responsivity.

Mapping Sleep's Oscillatory Events as a Biomarker of Alzheimer's Disease.

Objective: Memory-associated neural circuits produce oscillatory events within single-channel sleep electroencephalography (EEG), including theta bursts (TBs), sleep spindles (SPs) and multiple subtypes of slow waves (SWs). Changes in the temporal "coupling" of these events are proposed to serve as a biomarker for early stages of Alzheimer's disease (AD) pathogenesis. Methods: We analyzed data from 205 aging adults, including single-channel sleep EEG, cerebrospinal fluid (CSF) AD-associated biomarkers, and Clinical Dementia Rating® (CDR®) scale. Individual SW events were sorted into high and low transition frequencies (TF) subtypes. We utilized time-frequency spectrogram locations within sleep EEG to "map" the precision of SW-TB and SW-SP neural circuit coupling in relation to amyloid positivity (by CSF Aß 42 /Aß 40 threshold), cognitive impairment (by CDR), and CSF levels of AD-associated biomarkers. Results: Cognitive impairment was associated with lower TB spectral power in both high and low TF SW-TB coupling (p<0.001, p=0.001). Cognitively unimpaired, amyloid positive aging adults demonstrated lower precision of the neural circuits propagating high TF SW-TB (p<0.05) and low TF SW-SP (p<0.005) event coupling, compared to cognitively unimpaired amyloid negative individuals. Biomarker correlations were significant for high TF SW-TB coupling with CSF Aß 42 /Aß 40 (p=0.005), phosphorylated-tau 181 (p<0.005), and total-tau (p<0.05). Low TF SW-SP coupling was also correlated with CSF Aß 42 /Aß 40 (p<0.01). Interpretation: Loss of integrity in neural circuits underlying sleep-dependent memory processing can be measured for both SW-TB and SW-SP coupling in spectral time-frequency space. Breakdown of sleep's memory circuit integrity is associated with amyloid positivity, higher levels of AD-associated pathology, and cognitive impairment.

Hippocampal, basal ganglia and olfactory connectivity contribute to cognitive impairments in Parkinson's disease.

Cognitive impairment is increasingly recognized as a characteristic feature of Parkinson's disease (PD), yet relatively little is known about its underlying neurobiology. Previous investigations suggest that dementia in PD is associated with subcortical atrophy, but similar studies in PD with mild cognitive impairment have been mixed. Variability in cognitive phenotypes and diversity of PD symptoms suggest that a common neuropathological origin results in a multitude of impacts within the brain. These direct and indirect impacts of disease pathology can be investigated using network analysis. Functional connectivity, for instance, may be more sensitive than atrophy to decline in specific cognitive domains in the PD population. Fifty-eight participants with PD underwent a neuropsychological test battery and scanning with structural and resting state functional MRI in a comprehensive whole-brain association analysis. To investigate atrophy as a potential marker of impairment, structural gray matter atrophy was associated with cognitive scores in each cognitive domain using voxel-based morphometry. To investigate connectivity, large-scale networks were correlated with voxel time series and associated with cognitive scores using distance covariance. Structural atrophy was not associated with any cognitive domain, with the exception of visuospatial measures in primary sensory and motor cortices. In contrast, functional connectivity was associated with attention, executive function, language, learning and memory, visuospatial, and global cognition in the bilateral hippocampus, left putamen, olfactory cortex, and bilateral anterior temporal poles. These preliminary results suggest that cognitive domain-specific networks in PD are distinct from each other and could provide a network signature for different cognitive phenotypes.

The Rise and Fall of Slow Wave Tides: Vacillations in Coupled Slow Wave/Spindle Pairing Shift the Composition of Slow Wave Activity in Accordance With Depth of Sleep.

Slow wave activity (SWA) during sleep is associated with synaptic regulation and memory processing functions. Each cycle of non-rapid-eye-movement (NREM) sleep demonstrates a waxing and waning amount of SWA during the transitions between stages N2 and N3 sleep, and the deeper N3 sleep is associated with an increased density of SWA. Further, SWA is an amalgam of different types of slow waves, each identifiable by their temporal coupling to spindle subtypes with distinct physiological features. The objectives of this study were to better understand the neurobiological properties that distinguish different slow wave and spindle subtypes, and to examine the composition of SWA across cycles of NREM sleep. We further sought to explore changes in the composition of NREM cycles that occur among aging adults. To address these goals, we analyzed subsets of data from two well-characterized cohorts of healthy adults: (1) The DREAMS Subjects Database (n = 20), and (2) The Cleveland Family Study (n = 60). Our analyses indicate that slow wave/spindle coupled events can be characterized as frontal vs. central in their relative distribution between electroencephalography (EEG) channels. The frontal predominant slow waves are identifiable by their coupling to late-fast spindles and occur more frequently during stage N3 sleep. Conversely, the central-associated slow waves are identified by coupling to early-fast spindles and favor occurrence during stage N2 sleep. Together, both types of slow wave/spindle coupled events form the composite of SWA, and their relative contribution to the SWA rises and falls across cycles of NREM sleep in accordance with depth of sleep. Exploratory analyses indicated that older adults produce a different composition of SWA, with a shift toward the N3, frontal subtype, which becomes increasingly predominant during cycles of NREM sleep. Overall, these data demonstrate that subtypes of slow wave/spindle events have distinct cortical propagation patterns and differ in their distribution across lighter vs. deeper NREM sleep. Future efforts to understand how slow wave sleep and slow wave/spindle coupling impact memory performance and neurological disease may benefit from examining the composition of SWA to avoid potential confounds that may occur when comparing dissimilar neurophysiological events.

Does Prefrontal Glutamate Index Cognitive Changes in Parkinson's Disease?

Introduction: Cognitive impairment is a highly prevalent non-motor feature of Parkinson's disease (PD). A better understanding of the underlying pathophysiology may help in identifying therapeutic targets to prevent or treat dementia. This study sought to identify metabolic alterations in the prefrontal cortex (PFC), a key region for cognitive functioning that has been implicated in cognitive dysfunction in PD. Methods: Proton Magnetic Resonance Spectroscopy was used to investigate metabolic changes in the PFC of a cohort of cognitively normal individuals without PD (CTL), as well as PD participants with either normal cognition (PD-NC), mild cognitive impairment (PD-MCI), or dementia (PDD). Ratios to Creatine (Cre) resonance were obtained for glutamate (Glu), glutamine and glutamate combined (Glx), N-acetylaspartate (NAA), myoinositol (mI), and total choline (Cho), and correlated with cognitive scores across multiple domains (executive function, learning and memory, language, attention, visuospatial function, and global cognition) administered to the PD participants only. Results: When individuals retain cognitive capabilities, the presence of Parkinson's disease does not create metabolic disturbances in the PFC. However, when cognitive symptoms are present, PFC Glu/Cre ratios decrease with significant differences between the PD-NC and PPD groups. In addition, Glu/Cre ratios and memory scores were marginally associated, but not after Bonferroni correction. Conclusion: These preliminary findings indicate that fluctuations in prefrontal glutamate may constitute a biomarker for the progression of cognitive impairments in PD. We caution for larger MRS investigations of carefully defined PD groups.

An implicit priming intervention alters brain and behavioral responses to high-calorie foods: a randomized controlled study.

BACKGROUND: Conditioned food cues (e.g., smell, sight) can affect intake of foods associated with those cues, regardless of homeostatic need. As such, altering automatic associations with food cues could support weight loss or maintenance efforts by affecting the salience of those cues and the effort required to resist consumption. OBJECTIVES: This study investigated neuronal and behavioral effects of an implicit priming (IP) intervention, in which negatively valenced images were paired with high-calorie foods and positively valenced images with low-calorie foods. Priming images were presented immediately before food images, but below conscious perception (20 ms). We hypothesized that this evaluative conditioning approach could alter food cue responses by modifying affective associations. METHODS: The final sample included 41 adults with BMI ≥25 kg/m2 (n = 22, active IP; n = 19, control IP). In control IP, food images were primed with neutral, scrambled images. Participants completed a visual food cue task during fMRI, both before and after IP. To determine the replicability of prior behavioral findings, food image ratings were completed before and after IP as a secondary outcome. RESULTS: In a whole-brain analysis, reduced dorsolateral prefrontal cortex (dlPFC) response to high-calorie foods was observed after active compared with control IP (t = 4.93, P = 0.033). With a region of interest analysis, reduced response to high-calorie foods in active compared with control IP was also observed in the striatum (t = 2.40, P = 0.009) and insula (t = 2.38, P = 0.010). Active compared with control IP was associated with reduced high-calorie food ratings (F = 4.70, P = 0.038). CONCLUSIONS: Reduced insula and striatum response to high-calorie foods after active compared with control IP suggests effectiveness of IP in altering food cue salience. Reduced dlPFC response to high-calorie foods after active compared with control IP may reflect fewer attentional resources being directed to those images and reduced engagement of inhibitory processes.This trial was registered at clinicaltrials.gov as NCT02347527.

The aging slow wave: a shifting amalgam of distinct slow wave and spindle coupling subtypes define slow wave sleep across the human lifespan.

STUDY OBJECTIVES: Slow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. METHODS: Coupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. RESULTS: Two different subtypes of spindles were identified during the upstates of (distinct) slow waves: an "early-fast" spindle, more common in stage N2 sleep, and a "late-fast" spindle, more common in stage N3. We further found stages N2 and N3 sleep contain a mixture of discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails with increasing age. CONCLUSIONS: Distinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease.

Stable Meta-Networks, Noise, and Artifacts in the Human Connectome: Low- to High-Dimensional Independent Components Analysis as a Hierarchy of Intrinsic Connectivity Networks.

Connectivity within the human connectome occurs between multiple neuronal systems-at small to very large spatial scales. Independent component analysis (ICA) is potentially a powerful tool to facilitate multi-scale analyses. However, ICA has yet to be fully evaluated at very low (10 or fewer) and ultra-high dimensionalities (200 or greater). The current investigation used data from the Human Connectome Project (HCP) to determine the following: (1) if larger networks, or meta-networks, are present at low dimensionality, (2) if nuisance sources increase with dimensionality, and (3) if ICA is prone to overfitting. Using bootstrap ICA, results suggested that, at very low dimensionality, ICA spatial maps consisted of Visual/Attention and Default/Control meta-networks. At fewer than 10 components, well-known networks such as the Somatomotor Network were absent from results. At high dimensionality, nuisance sources were present even in denoised high-quality data but were identifiable by correlation with tissue probability maps. Artifactual overfitting occurred to a minor degree at high dimensionalities. Basic summary statistics on spatial maps (maximum cluster size, maximum component weight, and average weight outside of maximum cluster) quickly and easily separated artifacts from gray matter sources. Lastly, by using weighted averages of bootstrap stability, even ultra-high dimensional ICA resulted in highly reproducible spatial maps. These results demonstrate how ICA can be applied in multi-scale analyses, reliably and accurately reproducing the hierarchy of meta-networks, large-scale networks, and subnetworks, thereby characterizing cortical connectivity across multiple spatial scales.

Auditory entrainment of motor responses in older adults with and without Parkinson's disease: An MEG study.

Medical therapies applied to Parkinson's disease (PD) have advanced tremendously since the 1960's based on advances in our understanding of the underlying neurophysiology. Behavioral therapies, such as rhythmic auditory stimulation (RAS), have been developed more recently and demonstrated efficacy. However, the neural mechanisms of RAS are only vaguely understood. In this study, we examined the neurophysiology of RAS using magnetoencephalography (MEG) in a sample of older adults with (21 people) and without PD (23 participants). All participants underwent high-density MEG during a beat-based cued tapping task with rhythmic and non-rhythmic patterns, and the resulting data were analyzed using a Bayesian image reconstruction method. Complex wavelet based time-frequency decomposition was used to compute inter-trial phase locking factor (PLF) to auditory stimuli for left and right signal space projection vectors. Tapping with a rhythm compared to a non-rhythmic sequence resulted in differential brain activity in each group: (i) a greater activation of temporal, motor and parietal areas was found in healthy adults; (ii) a greater reliance on parietal and frontal gyri was found in PD participants. During rhythmic tapping, older adults without PD had significantly stronger neural activity in bilateral frontal, supplementary and primary motor areas compared to those with PD. Conversely, older adults with PD exhibited significantly stronger activity in the bilateral parietal regions, as well as the rolandic operculum and bilateral supramarginal gyri, relative to their healthy peers. These data suggest that RAS mobilizes diverse oscillatory networks; Healthy controls may shift to frontal areas mobilization whereas PD patients rely on parietal areas to a greater extent, which may reflect frontal network dysfunction with compensation in PD, and could serve as specific regions of interest for further RAS studies.

Nicotinic modulation of salience network connectivity and centrality in schizophrenia.

Although functional abnormalities of the salience network are associated with schizophrenia, the acute effects of nicotine on its function and network dynamics during the resting state in patients are poorly understood. In this study, the effects of a 7 mg nicotine patch (vs. placebo) on salience network connectivity were examined in 17 patients with schizophrenia and 19 healthy subjects. We hypothesized abnormal connectivity between the salience network and other major networks (e.g. executive network) in patients under placebo administration and amelioration of this difference after nicotine. We also examined effects of nicotine on betweenness centrality (a measure of the influence of a region on information transfer throughout the brain) and local efficiency (a measure of local information transfer) of the network. A hybrid independent component analysis (ICA)/seed-based connectivity approach was implemented in which the salience network was extracted by ICA and cortical network peaks (anterior cingulate cortex (ACC), left and right insula) were used as seeds for whole-brain seed-to-voxel connectivity analysis. Significant drug X diagnosis interactions were observed between the ACC seed and superior parietal lobule and ventrolateral prefrontal cortex. A significant interaction effect was also observed between the left insula seed and middle cingulate cortex. During placebo conditions, abnormal connectivity predicted negative symptom severity and lower global functioning in patients. A significant drug X diagnosis interaction was also observed for betweenness centrality of the ACC. These results suggest that nicotine may target abnormalities in functional connectivity between salience and executive network areas in schizophrenia as well as affect the ability of the salience network to act as an integrator of global signaling in the disorder.

Levodopa modulates small-world architecture of functional brain networks in Parkinson's disease.

BACKGROUND: PD is associated with disrupted connectivity to a large number of distributed brain regions. How the disease alters the functional topological organization of the brain, however, remains poorly understood. Furthermore, how levodopa modulates network topology in PD is largely unknown. The objective of this study was to use resting-state functional MRI and graph theory to determine how small-world architecture is altered in PD and affected by levodopa administration. METHODS: Twenty-one PD patients and 20 controls underwent functional MRI scanning. PD patients were scanned off medication and 1 hour after 200 mg levodopa. Imaging data were analyzed using 226 nodes comprising 10 intrinsic brain networks. Correlation matrices were generated for each subject and converted into cost-thresholded, binarized adjacency matrices. Cost-integrated whole-brain global and local efficiencies were compared across groups and tested for relationships with disease duration and severity. RESULTS: Data from 2 patients and 4 controls were excluded because of excess motion. Patients off medication showed no significant changes in global efficiency and overall local efficiency, but in a subnetwork analysis did show increased local efficiency in executive (P = 0.006) and salience (P = 0.018) networks. Levodopa significantly decreased local efficiency (P = 0.039) in patients except within the subcortical network, in which it significantly increased local efficiency (P = 0.007). CONCLUSIONS: Levodopa modulates global and local efficiency measures of small-world topology in PD, suggesting that degeneration of nigrostriatal neurons in PD may be associated with a large-scale network reorganization and that levodopa tends to normalize the disrupted network topology in PD. © 2016 International Parkinson and Movement Disorder Society.

Between-network connectivity occurs in brain regions lacking layer IV input.

To better understand the cortical circuitry underlying connectivity between large-scale neural networks, we develop a novel, data-driven approach to identify potential integration subregions. Between-network connectivity (BNC) associated with any anatomical region is the amount of connectivity between that point and all large-scale networks, as measured using simple and multiple correlations. It is straightforward to calculate and applicable to functional networks identified using independent components analysis. We calculated BNC for all fMRI voxels within the brain and compared the results to known regional cytoarchitectural patterns. Based on previous observations of the relationship between macroscopic connectivity and microscopic cytoarchitecture, we predicted that areas with high BNC will be located in paralimbic subregions with an undifferentiated laminar structure. Results suggest that the anterior insula and dorsal posterior cingulate cortices play prominent roles in information integration. Cytoarchitecturely, these areas show agranular or dysgranular cytologies with absent or disrupted cortical layer IV. Since layer IV is the primary recipient of feed-forward thalamocortical connections, and due to the exclusive nature of driving connections to this layer, we suggest that the absence of cortical layer IV might allow for information to be exchanged across networks, and is an organizational characteristic of brain-subregions serving as inter-network communication hubs.

Intrinsic hippocampal activity as a biomarker for cognition and symptoms in schizophrenia.

OBJECTIVE: Identification of biomarkers for cognitive dysfunction in schizophrenia is a priority for psychiatry research. Functional imaging studies suggest that intrinsic "resting state" hippocampal hyperactivity is a characteristic feature of schizophrenia. The relationships between this phenotype and symptoms of the illness, however, are largely unexplored. The authors examined resting hippocampal activity in schizophrenia patients and healthy comparison subjects and analyzed the relationship between intrinsic hippocampal activity and cognitive function in patients as measured by the MATRICS Consensus Cognitive Battery (MCCB). METHOD: Twenty-eight schizophrenia patients and 28 age-matched healthy comparison subjects underwent functional "resting state" 3-T MR scanning. Hippocampal activity was extracted by group independent component analysis. Correlation analyses were used to examine the relationship between hippocampal activity and MCCB composite and domain scores in patients, as well as between hippocampal activity and positive and negative symptoms. RESULTS: Greater activity of the right hippocampus at rest was observed in patients relative to comparison subjects. In patients, a significant negative correlation was observed between right hippocampal activity and composite MCCB T-score. The correlation was driven by the MCCB domains of attention/vigilance, working memory, and visual learning. Hippocampal activity was positively correlated with negative symptoms. MCCB scores were inversely correlated with negative symptoms. CONCLUSIONS: These findings suggest that greater intrinsic hippocampal activity is a characteristic feature of schizophrenia that is broadly associated with cognitive dysfunction, and they support hippocampal activity as a candidate biomarker for therapeutic development.

Altered oscillation patterns and connectivity during picture naming in autism.

Similar behavioral deficits are shared between individuals with autism spectrum disorders (ASD) and their first-degree relatives, such as impaired face memory, object recognition, and some language aspects. Functional neuroimaging studies have reported abnormalities in ASD in at least one brain area implicated in those functions, the fusiform gyrus (FG). High frequency oscillations have also been described as abnormal in ASD in a separate line of research. The present study examined whether low- and high-frequency oscillatory power, localized in part to FG and other language-related regions, differs in ASD subjects and first-degree relatives. Twelve individuals with ASD, 16 parents of children with ASD, and 35 healthy controls participated in a picture-naming task using magnetoencephalography (MEG) to assess oscillatory power and connectivity. Relative to controls, we observed reduced evoked high-gamma activity in the right superior temporal gyrus (STG) and reduced high-beta/low-gamma evoked power in the left inferior frontal gyrus (IFG) in the ASD group. Finally, reductions in phase-locked beta-band were also seen in the ASD group relative to controls, especially in the occipital lobes (OCC). First degree relatives, in contrast, exhibited higher high-gamma band power in the left STG compared with controls, as well as increased high-beta/low-gamma evoked power in the left FG. In the left hemisphere, beta- and gamma-band functional connectivity between the IFG and FG and between STG and OCC were higher in the autism group than in controls. This suggests that, contrary to what has been previously described, reduced connectivity is not observed across all scales of observation in autism. The lack of behavioral correlation for the findings warrants some caution in interpreting the relevance of such changes for language function in ASD. Our findings in parents implicates the gamma- and beta-band ranges as potential compensatory phenomena in autism relatives.

Evidence for gamma and beta sensory gating deficits as translational endophenotypes for schizophrenia.

Thorough analysis of translational endophenotypes is needed to improve therapeutic development in schizophrenia. Abnormal sensory gating, one such endophenotype, is associated with reduced expression of the α7 nicotinic receptor. However, typical gating measures such as the P50 evoked response are often low-pass filtered, and it is unclear how α7 expression affects gating at higher frequencies. Therefore, this study used time-frequency analysis to compare sensory gating at the beta and gamma frequencies between human patients and healthy controls as well as between α7 heterozygote mutant mice and wild-type. Gating of total beta (15-26Hz) and gamma (30-50Hz) power during paired clicks was assessed from mouse in vivo hippocampal CA3 recordings. Gating was also assessed in schizophrenia patients and healthy controls using electroencephalography. Relative to wild-type, α7 heterozygote mice showed impaired gating of total beta and gamma power. Similarly, relative to controls, patients showed impaired gating of total beta and gamma power. Poor beta gating was associated with negative symptoms. These results demonstrate that schizophrenia patients and α7 heterozygote mice show similar deficits in gating high frequency power. Time-frequency analysis of beta and gamma gating may thus be a translational method of assessing the genetic basis of gating deficits in schizophrenia.