Cortical Connectivity Patterns Research Articles

Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age

The basal nucleus of Meynert (BNM) provides the primary cholinergic inputs to the cerebral cortex. Loss of neurons in the BNM is linked to cognitive deficits in Alzheimer's disease and other degenerative conditions. Numerous animal studies described cholinergic and non-cholinergic neuronal responses in the BNM; however, work in humans has been hampered by the difficulty of defining the BNM anatomically. Here, on the basis of a previous study that delineated the BNM of post-mortem human brains in a standard stereotaxic space, we sought to examine functional connectivity of the BNM, as compared to the nucleus accumbens (or ventral striatum, VS), in a large resting state functional magnetic resonance imaging data set. The BNM and VS shared but also showed a distinct pattern of cortical and subcortical connectivity. Compared to the VS, the BNM showed stronger positive connectivity with the putamen, pallidum, thalamus, amygdala and midbrain, as well as the anterior cingulate cortex, supplementary motor area and pre-supplementary motor area, a network of brain regions that respond to salient stimuli and orchestrate motor behavior. In contrast, compared to the BNM, the VS showed stronger positive connectivity with the ventral caudate and medial orbitofrontal cortex, areas implicated in reward processing and motivated behavior. Furthermore, the BNM and VS each showed extensive negative connectivity with visual and lateral prefrontal cortices. Together, the distinct cerebral functional connectivities support the role of the BNM in arousal, saliency responses and cognitive motor control and the VS in reward related behavior. Considering the importance of BNM in age-related cognitive decline, we explored the effects of age on BNM and VS connectivities. BNM connectivity to the visual and somatomotor cortices decreases while connectivity to subcortical structures including the midbrain, thalamus, and pallidum increases with age. These findings of age-related changes of cerebral functional connectivity of the BNM may facilitate research of the neural bases of cognitive decline in health and illness.

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia

Although a number of recent studies have examined functional connectivity at rest, few have assessed differences between connectivity both during rest and across active task paradigms. Therefore, the question of whether cortical connectivity patterns remain stable or change with task engagement continues to be unaddressed. We collected multi-scan fMRI data on healthy controls (N=53) and schizophrenia patients (N=42) during rest and across paradigms arranged hierarchically by sensory load. We measured functional network connectivity among 45 non-artifactual distinct brain networks. Then, we applied a novel analysis to assess cross paradigm connectivity patterns applied to healthy controls and patients with schizophrenia. To detect these patterns, we fit a group by task full factorial ANOVA model to the group average functional network connectivity values. Our approach identified both stable (static effects) and state-based differences (dynamic effects) in brain connectivity providing a better understanding of how individuals' reactions to simple sensory stimuli are conditioned by the context within which they are presented. Our findings suggest that not all group differences observed during rest are detectable in other cognitive states. In addition, the stable differences of heightened connectivity between multiple brain areas with thalamus across tasks underscore the importance of the thalamus as a gateway to sensory input and provide new insight into schizophrenia.

Ketamine as the prototype glutamatergic antidepressant: pharmacodynamic actions, and a systematic review and meta-analysis of efficacy

The burden of depressive disorders and the frequent inadequacy of their current pharmacological treatments are well established. The anaesthetic and hallucinogenic drug ketamine has provoked much interest over the past decade or so as an extremely rapidly acting antidepressant that does not modify 'classical' monoaminergic receptors. Current evidence has shown several ways through which it might exert therapeutic antidepressant actions: blockade of glutamatergic NMDA receptors and relative upregulation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) subtypes may alter cortical connectivity patterns; through intracellular changes in protein expression, including the proteins mammalian target of rapamycin (mTOR) and brain-derived neurotrophic factor (BDNF); and alteration of intracellular signalling cascades. The clinical evidence demonstrates rapid improvements in mood and suicidal thinking in most participants, although study numbers have generally been small and many trials are unblinded and methodologically weak. There is a small body of work to suggest ketamine might also augment electroconvulsive therapy and potentially have a role as a surgical anaesthetic in depressed patients. A major problem is that the effects of ketamine appear temporary, disappearing after days to weeks (although longer benefits have been sustained in some), and attempts to circumvent this through pharmacological augmentation have been disappointing thus far. These exciting data are providing new insights into neurobiological models of depression, and potentially opening up a new class of antidepressants, but there are significant practical and ethical issues about any future mainstream clinical role it might have.

Task-related fronto-striatal functional connectivity during working memory performance in schizophrenia

Working memory (WM) deficits and associated brain dysfunction are among the most well replicated candidate endophenotypic processes in schizophrenia. However, previous studies demonstrate inconsistent over- and under-activation of dorsolateral and ventrolateral prefrontal cortices (DLPFC; VLPFC), inferior parietal lobule (IPL) during WM performance, as well as subcortical structures including the striatum, and dysfunctional connectivity among fronto-striatal regions in schizophrenia. However, no previous study has investigated task-related functional connectivity (FC) of DLPFC and striatal regions using a seed-based method; here we employed this method to assess patterns of cortical and subcortical functional connectivity among WM structures during a standard 2-back WM task performed by 28 schizophrenia (SZ) and 28 healthy controls (HC). Initial group comparisons of blood oxygenation level dependent (BOLD) responses during the WM task revealed significantly greater bilateral activity in the striatum in SZ relative to HC, but there was no significant group difference in WM cortical activity (right DLPFC, VLPFC or IPL). Analyses of FC within the cortico-subcortical WM network in the HC group revealed positive performance-related FC between the right DLPFC and the right caudate, and between the right VLPFC and the right IPL; this pattern was absent in SZ. In contrast, SZ patients showed negative performance-related functional connectivity between the left putamen and the right VLPFC. Direct group comparisons in functional connectivity showed significantly greater performance-related FC between the VLPFC and bilateral putamen, as well as unilaterally between the VLPFC and the right IPL, in HC. Results suggest a critical dysfunction of cortico-striatal connectivity underpinning information retrieval for SZ patients during WM performance.

Neurons in the Basal Forebrain Project to the Cortex in a Complex Topographic Organization that Reflects Corticocortical Connectivity Patterns: An Experimental Study Based on Retrograde Tracing and 3D Reconstruction

The most prominent feature of the Basal Forebrain (BF) is the collection of large cortically projecting neurons (basal nucleus of Meynert) that serve as the primary source of cholinergic input to the entire cortical mantle. Despite its broad involvement in cortical activation, attention, and memory, the functional details of the BF are not well understood due to the anatomical complexity of the region. This study tested the hypothesis that basalocortical connections reflect cortical connectivity patterns. Distinct retrograde tracers were deposited into various frontal and posterior cortical areas, and retrogradely labeled cholinergic and noncholinergic neurons were mapped in the BF. Concurrently, we mapped retrogradely labeled cells in posterior cortical areas that project to various frontal areas, and all cell populations were combined in the same coordinate system. Our studies suggest that the cholinergic and noncholinergic projections to the neocortex are not diffuse, but instead, are organized into segregated or overlapping pools of projection neurons. The extent of overlap between BF populations projecting to the cortex depends on the degree of connectivity between the cortical targets of these projection populations. We suggest that the organization of projections from the BF may enable parallel modulation of multiple groupings of interconnected yet nonadjacent cortical areas.

Age-related changes in brain structural covariance networks

Previous neuroimaging studies have suggested that cerebral changes over normal aging are not simply characterized by regional alterations, but rather by the reorganization of cortical connectivity patterns. The investigation of structural covariance networks (SCNs) using voxel-based morphometry is an advanced approach to examining the pattern of covariance in gray matter (GM) volumes among different regions of the human cortex. To date, how the organization of critical SCNs change during normal aging remains largely unknown. In this study, we used an SCN mapping approach to investigate eight large-scale networks in 240 healthy participants aged 18–89 years. These participants were subdivided into young (18–23 years), middle aged (30–58 years), and older (61–89 years) subjects. Eight seed regions were chosen from widely reported functional intrinsic connectivity networks. The voxels showing significant positive associations with these seed regions were used to describe the topological organization of an SCN. All of these networks exhibited non-linear patterns in their spatial extent that were associated with normal aging. These networks, except the primary motor network, had a distributed topology in young participants, a sharply localized topology in middle aged participants, and were relatively stable in older participants. The structural covariance derived using the primary motor cortex was limited to the ipsilateral motor regions in the young and older participants, but included contralateral homologous regions in the middle aged participants. In addition, there were significant between-group differences in the structural networks associated with language-related speech and semantics processing, executive control, and the default-mode network (DMN). Taken together, the results of this study demonstrate age-related changes in the topological organization of SCNs, and provide insights into normal aging of the human brain.

Altered cortical and subcortical local coherence in obstructive sleep apnea: a functional magnetic resonance imaging study

Obstructive sleep apnea (OSA) syndrome is the most common sleep-related breathing disorder, characterized by excessive snoring and repetitive apneas and arousals, which leads to fragmented sleep and, most importantly, to intermittent nocturnal hypoxaemia during apneas. Considering previous studies about morphovolumetric alterations in sleep apnea, in this study we aimed to investigate for the first time the functional connectivity profile of OSA patients and age-gender-matched healthy controls, using resting-state functional magnetic resonance imaging (fMRI). Twenty severe OSA patients (mean age 43.2±8years; mean apnea-hypopnea index, 36.3h(-1) ) and 20 non-apneic age-gender-body mass index (BMI)-matched controls underwent fMRI and polysomnographic (PSG) registration, as well as mood and sleepiness evaluation. Cerebro-cerebellar regional homogeneity (ReHo) values were calculated from fMRI acquisition, in order to identify pathology-related alterations in the local coherence of low-frequency signal (<0.1Hz). Multivariate pattern classification was also performed using ReHo values as features. We found a significant pattern of cortical and subcortical abnormal local connectivity in OSA patients, suggesting an overall rearrangement of hemispheric connectivity balance, with a decrease of local coherence observed in right temporal, parietal and frontal lobe regions. Moreover, an increase in bilateral thalamic and somatosensory/motor cortices coherence have been found, a finding due possibly to an aberrant adaptation to incomplete sleep-wake transitions during nocturnal apneic episodes, induced by repetitive choke sensation and physical efforts attempting to restore breathing. Different hemispheric roles into sleep processes and a possible thalamus key role in OSA neurophysiopathology are intriguing issues that future studies should attempt to clarify.

Comment on “Preserved Feedforward But Impaired Top-Down Processes in the Vegetative State”

Boly et al. (Reports, 13 May 2011, p. 858) investigated cortical connectivity patterns in patients suffering from a disorder of consciousness, using electroencephalography in an auditory oddball paradigm. We point to several inconsistencies in their data, including a failure to replicate the classical mismatch negativity. Data quality, source reconstruction, and statistics would need to be improved to support their conclusions.

An EEG-based real-time cortical functional connectivity imaging system

In the present study, we introduce an EEG-based, real-time, cortical functional connectivity imaging system capable of monitoring and tracing dynamic changes in cortical functional connectivity between different regions of interest (ROIs) on the brain cortical surface. The proposed system is based on an EEG-based dynamic neuroimaging system, which is capable of monitoring spatiotemporal changes of cortical rhythmic activity at a specific frequency band by conducting real-time cortical source imaging. To verify the implemented system, we performed three test experiments in which we monitored temporal changes in cortical functional connectivity patterns in various frequency bands during structural face processing, finger movements, and working memory task. We also traced the changes in the number of connections between all possible pairs of ROIs whose correlations exceeded a predetermined threshold. The quantitative analysis results were consistent with those of previous off-line studies, thereby demonstrating the possibility of imaging cortical functional connectivity in real-time. We expect our system to be applicable to various potential applications, including real-time diagnosis of psychiatric diseases and EEG neurofeedback.

Resting functional connectivity in patients with brain tumors in eloquent areas

Resection of brain tumors adjacent to eloquent areas represents a challenge in neurosurgery. If maximal resection is desired without inducing postoperative neurological deficits, a detailed knowledge of the functional topography in and around the tumor is crucial. The aim of the present work is to evaluate the value of preoperative magnetoencephalography (MEG) imaging of functional connectivity to predict the results of intraoperative electrical stimulation (IES) mapping, the clinical gold standard for neurosurgical localization of functional areas. Resting-state whole-cortex MEG recordings were obtained from 57 consecutive subjects with focal brain tumors near or within motor, sensory, or language areas. Neural activity was estimated using adaptive spatial filtering algorithms, and the mean imaginary coherence between the rest of the brain and voxels in and around brain tumors were compared to the mean imaginary coherence between the rest of the brain and contralesional voxels as an index of functional connectivity. IES mapping was performed in all subjects. The cortical connectivity pattern near the tumor was compared to the IES results. Maps with decreased resting-state functional connectivity in the entire tumor area had a negative predictive value of 100% for absence of eloquent cortex during IES. Maps showing increased resting-state functional connectivity within the tumor area had a positive predictive value of 64% for finding language, motor, or sensory cortical sites during IES mapping. Preoperative resting state MEG connectivity analysis is a useful noninvasive tool to evaluate the functionality of the tissue surrounding tumors within eloquent areas, and could potentially contribute to surgical planning and patient counseling.

Enhanced connectivity between visual cortex and other regions of the brain in autism: a REM sleep EEG coherence study

Functional interregional neural coupling was measured as EEG coherence during REM sleep, a state of endogenous cortical activation, in 9 adult autistic individuals (21.1±4.0 years) and 13 typically developed controls (21.5±4.3 years) monitored for two consecutive nights in a sleep laboratory. Spectral analysis was performed on 60 s of artefact-free EEG samples distributed equally throughout the first four REM sleep periods of the second night. EEG coherence was calculated for six frequency bands (delta, theta, alpha, sigma, beta, and total spectrum) using a 22-electrode montage. The magnitude of coherence function was computed for intra- and interhemispheric pairs of recording sites. Results were compared by Multivariate Analysis of Variance (MANOVA). Each time the autistic group showed a greater EEG coherence than the controls; it involved intrahemispheric communication among the left visual cortex (O1) and other regions either close to or distant from the occipital cortex. In contrast, lower coherence values involved frontal electrodes in the right hemisphere. No significant differences between groups were found for interhemispheric EEG coherence. These results show that the analysis of EEG coherence during REM sleep can disclose patterns of cortical connectivity that can be reduced or increased in adults with autism compared to typically developed individuals, depending of the cortical areas studied. Superior coherence involving visual perceptual areas in autism is consistent with an enhanced role of perception in autistic brain organization.

Using GLMs to recover sparse connectivity in complex networks

Information processing at the network level is highly dependent on the underlying network structure. Existing functional connectivity measures are useful but it is unclear how well they coincide with the real underlying anatomical connectivity of the network. In particular, it is difficult to avoid false positives - finding links between neurons that are correlated but not directly connected. Indeed, standardized measures do not currently appear to be defined in the literature for evaluating the performance of connectivity recovery algorithms. We introduce an efficient technique for discovering the sparse network structure of complex neuronal networks from spike train data, and a simple metric by which the performance of this algorithm (and others) may be judged. We then test our technique by generating simulated spike trains from networks with a known structure, and comparing the recovered connectivity against the original (anatomical) one. Network connectivity is recovered in two stages. We begin by fitting (using maximum likelihood) a generalized linear model (GLM) to the spike train data. The model includes interneuronal coupling terms to model the network's pairwise connectivity. We then use the Bayesian Information Criterion (BIC) to remove extraneous edges: any couplings which, when set to zero, improve the BIC score, are removed. This technique requires only a single trial of data (multiple trials can be combined through simple concatenation), and can be used in both evoked and spontaneous contexts. To test the technique's performance, we simulate spontaneous spike trains from a medium sized network (150 neurons) of Izhikevich neurons. This network has a ``clustered'' structure, as depicted in Figure ​Figure1.1. Qualitatively, we can see that the clustered structure of the networks is recovered. We can also quantitatively characterize reconstruction quality by considering our algorithm to be a binary classifier (edges exist or don't). Figure ​Figure22 shows the receiver operating curve (ROC) of our classifier as data length is increased for the medium-sized simulation, from 100 to 2000 spikes per neuron. Our technique provides adequate reconstructions with even moderate amounts of data, and more data leads to drastic improvements in performance (roughly, ten-fold more true positives than false positives). It requires few computational resources, and identifies sparse network structures quite successfully. Figure 1 Connectivity Matrices Figure 2 Recovery Performance Future work will test the method under noise regimes including dropped spikes and “dark” neurons. The technique will be applied to large-scale spike train recordings from electrophysiological or optogenetic experiments, to test hypotheses concerning cortical connectivity patterns.

Coclustering for Cross-Subject Fiber Tract Analysis Through Diffusion Tensor Imaging

One of the fundamental goals of computational neuroscience is the study of anatomical features that reflect the functional organization of the brain. The study of physical associations between neuronal structures and the examination of brain activity in vivo have given rise to the concept of anatomical and functional connectivity, which has been invaluable for our understanding of brain mechanisms and their plasticity during development. However, at present, there is no robust and accurate computational framework for the quantitative assessment of cortical connectivity patterns. In this paper, we present a quantitative analysis and modeling tool that is able to characterize anatomical connectivity patterns based on a newly developed coclustering algorithm, termed the business model-based coclustering algorithm (BCA). We apply BCA to diffusion tensor imaging (DTI) data in order to provide an automated and reproducible assessment of the connectivity patterns between different cortical areas in human brains. BCA not only partitions the cortical mantel into well-defined clusters, but also maximizes the connectivity strength between these clusters. Moreover, BCA is computationally robust and allows both outlier detection as well as parameter-independent determination of the number of clusters. Our coclustering results have showed good performance of BCA in identifying major white matter fiber bundles in human brains and facilitate the detection of abnormal connectivity patterns in patients suffering from various neurological diseases.

Estimation of Effective and Functional Cortical Connectivity From Neuroelectric and Hemodynamic Recordings

In this paper, different linear and nonlinear methodologies for the estimation of cortical connectivity from neuroelectric and hemodynamic measurements are reviewed and applied on common data set in order to highlight similarities and differences in the results. Different effective and functional connectivity methods were applied to motor and cognitive data sets, including structural equation modeling (SEM), directed transfer function (DTF), partial directed coherence (PDC), and direct directed transfer function (dDTF). Comparisons were made between the results in order to understand if, for a same dataset, effective and functional connectivity estimators can return the same cortical connectivity patterns. An application of a nonlinear method [phase synchronization index (PSI)] to similar executed and imagined movements was also reviewed. Connectivity patterns estimated with the use of the neuroelectric information and of the information from the multimodal integration of neuroelectric and hemodynamic data were also compared. Results suggests that the estimation of the cortical connectivity patterns performed with the linear methods (SEM, DTF, PDC, dDTF) or with the nonlinear method (PSI) on movement related potentials returned similar cortical networks. Differences in cortical connectivity were noted between the patterns estimated with the use of multimodal integration and those estimated by using only the neuroelectric data.

Radial cytoarchitecture and patterns of cortical connectivity in autism.

To explain the pattern of preserved and superior abilities found in autism spectrum disorders, a hypothesis has emerged, which assumes that there is a developmental bias towards the formation of short-range connections. This would result in excessive activity and overconnectivity within susceptible local networks. These networks might become partially isolated and acquire novel functional properties. In turn, this would affect the formation of long-range circuits and systems governing top-down control and integration. Despite many tantalizing clues, mechanisms relating pathogenesis and altered cell function to the 'disconnection' of integrative and focal activity remain obscure. However, recent post-mortem studies of brains of individuals with autism have shown characteristic differences in the morphometry of radial cell minicolumns, which add credence to the connectivity hypothesis.

Neural Basis for Brain Responses to TV Commercials: A High-Resolution EEG Study

We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on all the cortical networks and their behavior during the memorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision-making and recognition tasks.

Complex network analysis of human ECoG data

Localization of the epileptogenic zone (EZ) is an important issue in epileptology, even though there is not a unique definition of the epileptic focus. By using complex network analysis of electrocorticographic (ECoG) data we identify three singular areas in the temporal lobe of epileptic patients, the node with highest local synchronization power, the most connected node, and the node with highest interactions load. Connectivity in the data is extracted from the Minimum Spanning Tree (MST) of global correlations. We address the question whether removal of these nodes during the surgery is crucial in the suppression or reduction in the quantity of post-operative seizures. From five ECoG records, local areas with high synchronization power appear to be significantly involved in the development of epileptic seizures. The other two areas seem not to be fundamental in the seizures onset and development. Moreover, the approach proposed shed new light in cortical connectivity patterns in the human temporal lobe. All the analyzed records are during the inter-ictal state.

Posterior parietal cortex: An interface between attention and learning?

The posterior parietal cortex (PPC) of rats has most recently been defined based on patterns of thalamic and cortical connectivity. The anatomical characteristics of this area suggest that it may be homologous to the PPC of primates and contribute to similar functions. This review summarizes evidence for and against a role for the rat PPC in attention and working memory and evaluates how the function of the rat PPC compares to that of primates on these dimensions. Theories of how the rat PPC contributes to behavior are presented, including the notion that PPC may serve as an interface between attention and learning. Finally, several avenues for future research are considered.

Atypical connectivity in autistic spectrum disorders

Autism is a developmental disorder that is currently defined in terms of a triad of impairments in social interaction, communication, and behavioural flexibility. Psychological models have focussed on deficits in high level social and cognitive processes, such as ‘weak central coherence’ and deficits in ‘theory of mind’. Converging evidence from different fields of neuroscience research indicates that the underlying neural dysfunction is associated with atypical patterns of cortical connectivity (Rippon et al., 2007). This arises very early in development and results in sensory, perceptual and cognitive deficits at a much earlier and more fundamental level than previously suggested, but with cascading effects on higher level psychological and social processes. Earlier research in this sphere has focussed mainly on patterns of underconnectivity in distributed cortical networks underpinning process such as language and executive function. (Just et al., 2007). Such research mainly utilises imaging techniques with high spatial resolution. This paper focuses on evidence associated with local over-connectivity, evident in more low level and transitory processes and hence more easily measurable with techniques with high temporal resolution, such as MEG and EEG. Results are described which provide evidence of such local over-connectivity, characterised by atypical results in the gamma frequency range (Brown et al., 2005) together with discussions about the future directions of such research and its implications for remediation.

Neural Stimulation Successfully Treats Depression in Patients With Prior Ablative Cingulotomy

In this article, we describe the case of a patient who, under the direction of a multidisciplinary case committee, underwent both an ablative cingulotomy and subsequent bilateral deep brain stimulation placement in the Cg25 area. Review of this case provides a means of comparing the two techniques and of illustrating what we feel are some important advantages to using stimulation in the treatment of major depression. This report also provides potential insight into common and unique mechanisms mediating the two procedures.