Altered Connectivity Patterns Research Articles

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

BackgroundWhile there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism. MethodsWe assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6years with autism (n=87), developmental delay without autism (n=21), or typical development (n=29). FindingsWe found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep. InterpretationFunctional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

BackgroundSchizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing.MethodsThis study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors’ discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON–CHR differences within the superior temporal gyri.ResultsVariable reduction by PCA identified 40 coherence-based factors explaining 77.8 % of the total variance and 40 spectral factors explaining 95.9 % of the variance. DFA demonstrated significant CON–CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7 %; CHR, 86.4 % correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON–CHR group differences.ConclusionsCHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Connectivity.

Connectivity is a technique that uses functional MRI (fMRI) to explore global brain function in healthy and diseased states. Connectivity is now being studied as a part of global brain function in major national and international studies. It is, therefore, timely to review its relevance to anaesthesia. Dynamic connectivity in the brain, which transcends anatomical boundaries, links functionally related regions. Clinical manifestations in neuropsychiatric diseases such has Alzheimer's disease and schizophrenia can be explained on the basis of altered connectivity patterns in the brain. Anaesthetic agents primarily disrupt long-range networks and affect the higher order networks linked to cognition causing cognitive unbinding in the brain. Lower-order, basic sensorimotor networks are less sensitive. Normal ageing causes alterations in connectivity that affects the default mode network (DMN) and certain other networks, which in turn impair fluidic measures of brain function such as reaction time, dual task performance and executive function in elderly. Higher mental function related networks such as the DMN, the executive control network and salience are more sensitive to anaesthesia. In geriatric patients, the DMN is impaired, which affects cognition. Hence, the combined effect of age and anaesthesia in elderly on mental function can cause significant postoperative cognitive impairment.

A parsimonious statistical method to detect groupwise differentially expressed functional connectivity networks.

Group-level functional connectivity analyses often aim to detect the altered connectivity patterns between subgroups with different clinical or psychological experimental conditions, for example, comparing cases and healthy controls. We present a new statistical method to detect differentially expressed connectivity networks with significantly improved power and lower false-positive rates. The goal of our method was to capture most differentially expressed connections within networks of constrained numbers of brain regions (by the rule of parsimony). By virtue of parsimony, the false-positive individual connectivity edges within a network are effectively reduced, whereas the informative (differentially expressed) edges are allowed to borrow strength from each other to increase the overall power of the network. We develop a test statistic for each network in light of combinatorics graph theory, and provide p-values for the networks (in the weak sense) by using permutation test with multiple-testing adjustment. We validate and compare this new approach with existing methods, including false discovery rate and network-based statistic, via simulation studies and a resting-state functional magnetic resonance imaging case-control study. The results indicate that our method can identify differentially expressed connectivity networks, whereas existing methods are limited.

Carbamate nerve agent prophylatics exhibit distinct toxicological effects in the zebrafish embryo model

Pyridostigmine bromide (PB) is an FDA-approved drug for the treatment of myasthenia gravis and a prophylactic pre-treatment for organophosphate nerve agent poisoning. Current methods for evaluating nerve agent treatments include enzymatic studies and mammalian models. Rapid whole animal screening tools for assessing the effects of nerve agent pre-treatment and post-exposure drugs represent an underdeveloped area of research. We used zebrafish as a model for acute and chronic developmental exposure to PB and two related carbamate acetylcholinesterase (AChE) inhibitors, neostigmine bromide (NB) and physostigmine (PS). Lethal doses and gross morphological phenotypes resulting from exposure to sub-lethal doses of these compounds were determined. Quantitative analyses of motility impairment and AChE enzyme inhibition were used to determine optimal dosing conditions for evaluation of the effects of carbamate exposures on neuronal development; ~50% impairment of response to startle stimuli and >50% inhibition of AChE activity were observed at 80mMPB, 20mM NB and 0.1mM PS. PB induced stunted somite length, but no other phenotypic effects were observed. In contrast, NB and PS induced more severe phenotypic morphological defects than PB as well as neurite outgrowth mislocalization. Additionally, NB induced mislocalization of nicotinic acetylcholine receptors, resulting in impaired synapse formation. Taken together, these data suggest that altered patterns of neuronal connectivity contribute to the developmental neurotoxicity of carbamates and demonstrate the utility of the zebrafish model for distinguishing subtle structure-based differential effects of AChE inhibitors, which include nerve agents, pesticides and drugs.

History of Depression and Frontostriatal Connectivity During Reward Processing in Late Adolescent Boys

Given that depression in men is associated with risk for seriously adverse consequences, evaluating how putative neural mechanisms of depression—such as reward-related frontostriatal connectivity—may be altered in late adolescent boys with a history of depression is an important research aim. Adolescents and adults with depression have been demonstrated to show blunted striatal response and heightened medial prefrontal cortex (mPFC) activation to winning reward. Function in reward circuits appears to be best understood as coordination of regions within frontostriatal circuitry, and alterations to this circuitry could occur in those with a history of depression. The current study evaluated functional connectivity between the nucleus accumbens and mPFC in a sample of 166 ethnically diverse boys with and without a history of depression. Participants completed an fMRI monetary reward paradigm at age 20. Lifetime history of depression and other psychiatric illnesses was measured prospectively and longitudinally, using structured clinical interviews at 7 time points from ages 8 to 20. Boys with a history of depression showed heightened positive connectivity between the nucleus accumbens and the mPFC relative to boys with no psychiatric history when winning rewards relative to losing rewards. This altered frontostriatal connectivity pattern was also associated with greater number of depressive episodes in the boys’ lifetime. History of depression in late adolescent boys may be associated with altered coordination between the nucleus accumbens and mPFC when winning reward. This coordination could reflect oversignaling of the mPFC to dampen typical ventral striatum response or enhance weak ventral striatum response.

Identifying patients with Alzheimer’s disease using resting-state fMRI and graph theory

ObjectiveStudy of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. MethodIn this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer’s disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject’s graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. ResultsUsing the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. ConclusionResults of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. SignificanceClassification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer’s disease.

A splitting brain: Imbalanced neural networks in schizophrenia

Dysconnectivity between key brain systems has been hypothesized to underlie the pathophysiology of schizophrenia. The present study examined the pattern of functional dysconnectivity across whole-brain neural networks in 121 first-episode, treatment-naïve patients with schizophrenia by using resting-state functional magnetic resonance imaging (rsfMRI). Group independent component analysis (ICA) was first applied to rsfMRI data to extract 90 functional components of the brain. The functional connectivity between these ICA components was then evaluated and compared between the patient and control groups. To examine the functional roles of significantly altered between-component connections in patients, each ICA component was ascribed to one of 10 previously well-defined brain networks/areas. Relative to findings in healthy controls (n=103), 29 altered functional connections including 19 connections with increased connectivity and 10 connections with decreased connectivity in schizophrenia patients were found. Increased connectivity was mainly within the default mode network (DMN) and between the DMN and cognitive networks, whereas decreased connectivity was predominantly associated with sensory networks. Given the key roles of the DMN in internal mental processes and sensory networks in inputs from the external environment, these patterns of altered brain network connectivity could suggest imbalanced neural processing of internal and external information in schizophrenia.

Differential relations between juvenile psychopathic traits and resting state network connectivity.

Traditionally, neurobiological research on psychopathy has focused on categorical differences in adults. However, there is evidence that psychopathy is best described by a set of relatively independent personality dimensions, that is, callous-unemotional, grandiose-manipulative, and impulsive-irresponsible traits, which can be reliably detected in juveniles, allowing investigation of the neural mechanisms leading to psychopathy. Furthermore, complex psychiatric disorders like psychopathy are increasingly being conceptualized as disorders of brain networks. The intrinsic organization of the brain in such networks is reflected by coherent fluctuations in resting state networks (RSNs), but these have not been studied in sufficient detail in relation to juvenile psychopathic traits yet. The current study investigated the distinct associations of juvenile psychopathic traits dimensions with RSN connectivity. Resting-state functional MRI and independent component analysis were used to assess RSN connectivity in a large sample of adolescents (n = 130, mean age 17.8 years) from a childhood arrestee cohort. Associations between scores on each of the three psychopathic traits dimensions and connectivity within and between relevant RSNs were investigated. Callous-unemotional traits were related to aberrant connectivity patterns of the default mode network, which has been implicated in self-referential and moral processes. Impulsive-irresponsible traits were associated with altered connectivity patterns in the frontoparietal cognitive control networks. Grandiose-manipulative traits were not associated with altered connectivity patterns. These findings confirm the association between psychopathic traits and brain network connectivity, and considerably add to emerging evidence supporting neurobiological heterogeneity in the processes leading to psychopathy.

Ontogeny of biochemical, morphological and functional parameters of synaptogenesis in primary cultures of rat hippocampal and cortical neurons.

BackgroundSynaptogenesis is a critical neurodevelopmental process whereby pre- and postsynaptic neurons form apposed sites of contact specialized for chemical neurotransmission. Many neurodevelopmental disorders are thought to reflect altered patterns of synaptic connectivity, including imbalances between excitatory and inhibitory synapses. Developing rapid throughput approaches for assessing synaptogenesis will facilitate toxicologic and drug screening studies of neurodevelopmental disorders. The current study describes the use of high-content imaging to quantify the ontogeny of excitatory and inhibitory synapses using in vitro models of neurodevelopment. These data are compared to biochemical and functional measures of synaptogenesis.ResultsThe ontogenetic patterns of synapse formation were compared between primary rodent hippocampal and cortical neurons over 28 days in vitro (DIV). As determined by ELISA, the increase in synaptophysin expression levels as cultures matured was similar between hippocampal and cortical cultures. High-content imaging of immunoreactivity of excitatory and inhibitory synaptic biomarkers demonstrated an overall greater number of synapses in hippocampal relative to cortical neurons with marked differences in the pattern of inhibitory synapse development between these two neuronal cell types. Functional assays revealed that both the mean firing rates and mean bursting rates were significantly increased in cortical cultures relative to hippocampal cultures. This difference may reflect decreased inhibitory synaptic tone in cortical versus hippocampal cultures.ConclusionsThese data demonstrate differences and similarities in the ontogeny of synaptogenesis between hippocampal and cortical neurons, depending on the biological level examined. Assessment of synaptophysin protein levels by ELISA showed a general increase in synapse formation in both cell types with increasing time in culture, while high-content imaging was able to delineate cell type-dependent differences in formation of excitatory versus inhibitory synapses. The functional significance of differences in the balance of excitatory to inhibitory synapses was confirmed by the assessment of network activity using microelectrode arrays. These results suggest that high-content imaging and microelectrode arrays provide complementary approaches for quantitative assessment of synaptogenesis, which should provide a robust readout of toxicologic and pharmacologic effects on this critical neurodevelopmental event.

Basal ganglia‐cortical structural connectivity in Huntington's disease

Huntington's disease is an incurable neurodegenerative disease caused by inheritance of an expanded cytosine-adenine-guanine (CAG) trinucleotide repeat within the Huntingtin gene. Extensive volume loss and altered diffusion metrics in the basal ganglia, cortex and white matter are seen when patients with Huntington's disease (HD) undergo structural imaging, suggesting that changes in basal ganglia-cortical structural connectivity occur. The aims of this study were to characterise altered patterns of basal ganglia-cortical structural connectivity with high anatomical precision in premanifest and early manifest HD, and to identify associations between structural connectivity and genetic or clinical markers of HD. 3-Tesla diffusion tensor magnetic resonance images were acquired from 14 early manifest HD subjects, 17 premanifest HD subjects and 18 controls. Voxel-based analyses of probabilistic tractography were used to quantify basal ganglia-cortical structural connections. Canonical variate analysis was used to demonstrate disease-associated patterns of altered connectivity and to test for associations between connectivity and genetic and clinical markers of HD; this is the first study in which such analyses have been used. Widespread changes were seen in basal ganglia-cortical structural connectivity in early manifest HD subjects; this has relevance for development of therapies targeting the striatum. Premanifest HD subjects had a pattern of connectivity more similar to that of controls, suggesting progressive change in connections over time. Associations between structural connectivity patterns and motor and cognitive markers of disease severity were present in early manifest subjects. Our data suggest the clinical phenotype in manifest HD may be at least partly a result of altered connectivity.

Low-frequency connectivity is associated with mild traumatic brain injury.

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

Spatial characterization of catchment dispersion mechanisms in an urban context

Previous studies have examined in-depth the dispersion mechanisms in natural catchments. In contrast, these dispersion mechanisms have been studied little in urban catchments, where artificial transport elements and morphological arrangements are expected to modify travel times and mobilize excess rainfall from spatially distributed impervious sites. This has the ability to modify the variance of the catchment’s travel times and hence the total dispersion. This work quantifies the dispersion mechanisms in an urban catchment using the theory of transport by travel times as represented by the Urban Morpho-climatic Instantaneous Unit Hydrograph (U-McIUH) model. The U-McIUH computes travel times based on kinematic wave theory and accounts explicitly for the path heterogeneities and altered connectivity patterns characteristic of an urban drainage network. The analysis is illustrated using the Aubinière urban catchment in France as a case study. We found that kinematic dispersion is dominant for small rainfall intensities, whereas geomorphologic dispersion becomes more dominant for larger intensities. The total dispersion scales with the drainage area in a power law fashion. The kinematic dispersion is dominant across spatial scales up to a threshold of approximately 2–3km2, after which the geomorphologic dispersion becomes more dominant. Overall, overland flow is responsible for most of the dispersion in the catchment, while conduits tend to counteract the increase of the geomorphologic dispersion with a negative kinematic dispersion. Further study with other catchments is needed to asses if the latter is a general feature of urban drainage networks.

P809: Altered connectivity patterns during partial seizures with different types of impaired consciousness as ictal correlate

P809: Altered connectivity patterns during partial seizures with different types of impaired consciousness as ictal correlate

Differential abnormalities of functional connectivity of the amygdala and hippocampus in unipolar and bipolar affective disorders

ObjectiveThe amygdala and hippocampus – two structures intimately associated with mood and cognition – have been reported to exhibit altered neural activity or volume in affective disorders. We hypothesized the amygdala and hippocampus would show altered and differential patterns of connectivity in patients with bipolar (BPs) and unipolar (UPs) disorder compared to healthy volunteers. MethodThirty BPs, 34 UPs, and 66 healthy volunteers were imaged using F-18-fluorodeoxyglucose and positron emission tomography while performing an auditory continuous performance task (CPT). Normalized mean activity of the amygdala and hippocampus was correlated with the rest of the brain. ResultsIn BPs, the amygdalae displayed exaggerated positive metabolic correlations with prefrontal and ventral striatal areas, while the hippocampus showed a paucity of normal inter-relations compared to controls. In contrast, in UPs the amygdala was significantly negatively correlated with prefrontal and anterior cingulate cortex, while the hippocampus was significantly more positively correlated to these same prefrontal areas. ConclusionsDuring a simple cognitive task, the functional connectivity of the amygdala and hippocampus, regions usually associated with emotion and memory regulation, was substantially different in affective illness compared to healthy controls whether or not there were baseline abnormalities in these areas. These striking differences in functional connectivity of amygdala and hippocampus should be further explored in ill and well states and using more specific emotion and cognitive evocative tasks.

Altered structure and function in the hippocampus and medial prefrontal cortex in patients with burning mouth syndrome

Burning mouth syndrome (BMS) is a debilitating, idiopathic chronic pain condition. For many BMS patients, burning oral pain begins in late morning and becomes more intense throughout the day, peaking by late afternoon or evening. We investigated brain gray matter volume (GMV) with voxel-based morphometry (VBM), white matter fractional anisotropy (FA) with diffusion tensor imaging (DTI), and functional connectivity in resting state functional MRI (rsfMRI) in a tightly screened, homogeneous sample of 9 female, postmenopausal/perimenopausal BMS patients and 9 matched healthy control subjects. Patients underwent 2 scanning sessions in the same day: in the morning, when ongoing pain/burning was low, and in the afternoon, when pain/burning was significantly higher. Patients had increased GMV and lower FA in the hippocampus (Hc), and decreased GMV in the medial prefrontal cortex (mPFC). rsfMRI revealed altered connectivity patterns in different states of pain/burning, with increased connectivity between mPFC (a node in the default mode network) and anterior cingulate cortex, occipital cortex, ventromedial PFC, and bilateral Hc/amygdala in the afternoon compared with the morning session. Furthermore, mPFC-Hc connectivity was higher in BMS patients than control subjects for the afternoon but not the morning session. mPFC-Hc connectivity was related to Beck depression inventory scores both between groups and between burning states within patients, suggesting that depression and anxiety partially explain pain-related brain dysfunction in BMS. Overall, we provide multiple lines of evidence supporting aberrant structure and function in the mPFC and Hc, and implicate a circuit involving the mPFC and Hc in regulating mood and depressive symptoms in BMS.

Widespread brain dysconnectivity associated with psychotic-like experiences in the general population

It is becoming increasingly clear that psychosis occurs along a continuum. At the high end are formal psychotic disorders such as schizophrenia, and at the low-end are individuals who experience occasional psychotic symptoms, but are otherwise healthy (non-clinical psychosis, NCP). Schizophrenia has been shown to be marked by altered patterns of connectivity between brain regions, but it is not known if such dysconnectivity exists in NCP. In the current study we used functional magnetic resonance imaging (fMRI) to compare resting-state functional connectivity in NCP individuals (n = 25) and healthy controls (n = 27) for four brain networks of interest (fronto-parietal, cingulo-opercular, default mode, and cerebellar networks). NCP individuals showed reduced connectivity compared to controls between regions of the default mode network and frontal regions, and between regions in all of the networks and the thalamus. NCP individuals showed greater connectivity compared to controls within regions of frontal control networks. Further, positive symptom scores in NCP individuals were positively correlated with connectivity between the cingulo-opercular network and the visual cortex, and were negatively correlated with connectivity between the cerebellar network and the posterior parietal cortex and dorsal premotor cortex. Connectivity was not correlated with positive symptom scores in controls. Taken together, these findings demonstrate that a spectrum of abnormal connectivity underlies the psychosis continuum, and that individuals with sub-clinical psychotic experiences represent a key population for understanding pathogenic processes.

Effects of ZNF804A on auditory P300 response in schizophrenia.

The common variant rs1344706 within the zinc-finger protein gene ZNF804A has been strongly implicated in schizophrenia (SZ) susceptibility by a series of recent genetic association studies. Although associated with a pattern of altered neural connectivity, evidence that increased risk is mediated by an effect on cognitive deficits associated with the disorder has been equivocal. This study investigated whether the same ZNF804A risk allele was associated with variation in the P300 auditory-evoked response, a cognitively relevant putative endophenotype for SZ. We compared P300 responses in carriers and noncarriers of the ZNF804A risk allele genotype groups in Irish patients and controls (n=97). P300 response was observed to vary according to genotype in this sample, such that risk allele carriers showed relatively higher P300 response compared with noncarriers. This finding accords with behavioural data reported by our group and others. It is also consistent with the idea that ZNF804A may have an impact on cortical efficiency, reflected in the higher levels of activations required to achieve comparable behavioural accuracy on the task used.

Cocaine reduces cytochrome oxidase activity in the prefrontal cortex and modifies its functional connectivity with brainstem nuclei

Cocaine-induced psychomotor stimulation may be mediated by metabolic hypofrontality and modification of brain functional connectivity. Functional connectivity refers to the pattern of relationships among brain regions, and one way to evaluate this pattern is using interactivity correlations of the metabolic marker cytochrome oxidase among different regions. This is the first study of how repeated cocaine modifies: (1) mean cytochrome oxidase activity in neural areas using quantitative enzyme histochemistry, and (2) functional connectivity among brain regions using inter-correlations of cytochrome oxidase activity. Rats were injected with 15mg/kg i.p. cocaine or saline for 5 days, which lead to cocaine-enhanced total locomotion. Mean cytochrome oxidase activity was significantly decreased in cocaine-treated animals in the superficial dorsal and lateral frontal cortical association areas Fr2 and Fr3 when compared to saline-treated animals. Functional connectivity showed that the cytochrome oxidase activity of the noradrenergic locus coeruleus and the infralimbic cortex were positively inter-correlated in cocaine but not in control rats. Positive cytochrome oxidase activity inter-correlations were also observed between the dopaminergic substantia nigra compacta and Fr2 and Fr3 areas and the lateral orbital cortex in cocaine-treated animals. In contrast, cytochrome oxidase activity in the interpeduncular nucleus was negatively correlated with that of Fr2, anterior insular cortex, and lateral orbital cortex in saline but not in cocaine groups. After repeated cocaine specific prefrontal areas became hypometabolic and their functional connectivity changed in networks involving noradrenergic and dopaminergic brainstem nuclei. We suggest that this pattern of hypofrontality and altered functional connectivity may contribute to cocaine-induced psychomotor stimulation.

Intra- and inter-frequency brain network structure in health and schizophrenia.

Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie altered cognitive functions such as working memory. However, the nature of this dysconnectivity remains far from understood. In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task. We investigate uni-, bi- and multivariate properties of sensor time series by computing wavelet entropy of and correlation between time series, and by constructing binary networks of functional connectivity both within and between classical frequency bands (, , , and ). Networks are based on the mutual information between wavelet time series, and estimated for each trial window separately, enabling us to consider both network topology and network dynamics. We observed significant decreases in time series entropy and significant increases in functional connectivity in the schizophrenia group in comparison to the healthy controls and identified an inverse relationship between these measures across both subjects and sensors that varied over frequency bands and was more pronounced in controls than in patients. The topological organization of connectivity was altered in schizophrenia specifically in high frequency and band networks as well as in the - cross-frequency networks. Network topology varied over trials to a greater extent in patients than in controls, suggesting disease-associated alterations in dynamic network properties of brain function. Our results identify signatures of aberrant neurophysiological behavior in schizophrenia across uni-, bi- and multivariate scales and lay the groundwork for further clinical studies that might lead to the discovery of new intermediate phenotypes.