An abnormal resting-state functional brain network indicates progression towards Alzheimer＇s disease

Brain structure and cognitive function change in the temporal lobe,hippocampus,and prefrontal cortex of patients with mild cognitive impairment and Alzheimer’s disease,and brain network-connection strength,network efficiency,and nodal attributes are abnormal.However,existing research has only analyzed the differences between these patients and normal controls.In this study,we constructed brain networks using resting-state functional MRI data that was extracted from four populations(normal controls,patients with early mild cognitive impairment,patients with late mild cognitive impairment,and patients with Alzheimer’s disease)using the Alzheimer’s Disease Neuroimaging Initiative data set.The aim was to analyze the characteristics of resting-state functional neural networks,and to observe mild cognitive impairment at different stages before the transformation to Alzheimer’s disease.Results showed that as cognitive deficits increased across the four groups,the shortest path in the resting-state functional network gradually increased,while clustering coefficients gradually decreased.This evidence indicates that dementia is associated with a decline of brain network efficiency.In addition,the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and Alzheimer’s disease.The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions,and we speculate that early impairments in memory,hearing,and language function can eventually lead to diffuse brain injury and other cognitive impairments.     

Abnormal Rich-Club Organization Associated with Compromised Cognitive Function in Patients with Schizophrenia and Their Unaffected Parents

Schizophrenia is considered to be a disorder of brain connectivity, which might result from a disproportionally impaired rich-club organization. The rich-club is composed of highly interconnected hub regions that play crucial roles in integrating information between different brain regions. Few studies have yet investigated whether the structural rich-club organization is impaired in patients and their first-degree relatives. In this study, we established a weighted network model of white matter connections using diffusion tensor imaging of 19 patients and 39 unaffected parents, 22 young healthy controls for the patients, and 25 old healthy controls for the parents. Feeder edges between rich-club nodes and non-rich-club nodes were significantly decreased in both schizophrenic patients and their unaffected parents compared with controls.Furthermore, the feeder edges showed significant positive correlations with the scores in Category Fluency Test—animal naming in the unaffected parents. Specific feeder edges exhibited discriminative power with accuracy of 84.4% in distinguishing unaffected parents from old healthy controls. Our findings suggest that impaired richclub organization, especially impaired feeder edges, may be related to familial vulnerability to schizophrenia,possibly reflecting a genetic predisposition for schizophrenia.     

Compromised small-world efficiency of structural brain networks in schizophrenic patients and their unaffected parents

Several lines of evidence suggest that efficient information integration between brain regions is disrupted in schizophrenia. Abnormalities in white matter tracts that interconnect brain regions may be directly relevant to this pathophysiological process. As a complex mental disorder with high heritability, mapping abnormalities in patients and their firstdegree relatives may help to disentangle the risk factors for schizophrenia. We established a weighted network model of white matter connections using diffusion tensor imaging in 25 nuclear families with schizophrenic probands(19 patients and 41 unaffected parents) and two unrelated groups of normal controls(24 controls matched with patients and 26 controls matched with relatives). The patient group showed lower global efficiency and local efficiency. The decreased regional efficiency was localized in hubs such as the bilateral frontal cortices, bilateral anterior cingulate cortices, and left precuneus. The global effi ciency was negatively correlated with cognition scores derived from a 5-factor model of schizophrenic psychopathology.We also found that unaffected parents displayed decreased regional efficiency in the right temporal cortices, left supplementary motor area, left superior temporal pole, and left thalamus. The global efficiency tended to be lower in unaffected parents. Our data suggest that(1) the global effi ciency loss in neuroanatomical networks may be associated with the cognitive disturbances in schizophrenia; and(2) genetic vulnerability to schizophrenia may influence the anatomical organization of an individual’s brain networks.     

Disrupted structural and functional brain connectomes in mild cognitive impairment and Alzheimer＇s disease

Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous studies have demonstrated that these impairments are associated with abnormal structural and functional connections among brain regions, leading to a disconnection concept of AD. With the advent of a combination of non-invasive neuroimaging （structural magnetic resonance imaging （MRI）, diffusion MRI, and functional MRI） and neurophysiological techniques （electroencephalography and magnetoencephaJography） with graph theoretical analysis, recent studies have shown that patients with AD and mild cognitive impairment （MCI）, the prodromal stage of AD, exhibit disrupted topological organization in large-scale brain networks （i.e., connectomics） and that this disruption is significantly correlated with the decline of cognitive functions. In this review, we summarize the recent progress of brain connectomics in AD and MCI, focusing on the changes in the topological organization of large-scale structural and functional brain networks using graph theoretical approaches. Based on the two different perspectives of information segregation and integration, the literature reviewed here suggests that AD and MCI are associated with disrupted segregation and integration in brain networks. Thus, these connectomics studies open up a new window for understanding the pathophysiological mechanisms of AD and demonstrate the potential to uncover imaging biomarkers for clinical diagnosis and treatment evaluation for this disease.     

Abnormal characterization of dynamic functional connectivity in Alzheimer’s disease

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.     

In this issue

This issue starts with a review of the status of research in China on the cognitive functioning of individuals with schizophrenia.[1] Two major factors have accelerated this type of research in China since the early 1990s： （a） the realization that the quality of life and social functioning of individuals afflicted by schizophrenia are closely associated with the degree of cognitive impairment they experience as part of their illness; and （b） the rapid development of functional imaging technologies that have made it possible to localize and, to some extent, characterize the brain abnormalities associated with specific cognitive disabilities. The review considers research in China about the assessment of the various types of cognitive impairments seen in schizophrenia, the factors that are correlated with the severity of cognitive dysfunction, the biological basis and structural localization of cognitive impairment, and the available pharmacological and non-pharmacological treatments. The authors conclude that more cross-disciplinary research and more long-term cohort studies are needed to understand the natural history of cognitive functioning during the course of schizophrenia and, thus, to develop effective strategies to prevent or limit cognitive dysfunction in persons with schizophrenia.     

Auditory event-related brain potentials for an early discrimination between normal and pathological brain aging

The brain as a system with gradually decreasing resources maximizes its chances by reorganizing neural networks to ensure efficient performance. Auditory event-related potentials were recorded in 28 healthy volunteers comprising 14 young and 14 elderly subjects in auditory discrimination motor task (low frequency tone - right hand movement and high frequency tone - left hand movement). The amplitudes of the sensory event-related potential components (N1, P2) were more pronounced with increasing age for either tone and this effect for P2 amplitude was more pronounced in the frontal region. The latency relationship of N1 between the groups was tone-dependent, while that of P2 was tone-independent with a prominent delay in the elderly group over all brain regions. The amplitudes of the cognitive components (N2, P3) diminished with increasing age and the hemispheric asymmetry of N2 (but not for P3) reduced with increasing age. Prolonged N2 latency with increasing age was widespread for either tone while between-group difference in P3 latency was tone-dependent. High frequency tone stimulation and movement requirements lead to P3 delay in the elderly group. The amplitude difference of the sensory components between the age groups could be due to a general greater alertness, less expressed habituation, or decline in the ability to retreat attentional resources from the stimuli in the elderly group. With aging, a neural circuit reorganization of the brain activity affects the cognitive processes. The approach used in this study is useful for an early discrimination between normal and pathological brain aging for early treatment of cognitive alterations and dementia.     

A new computational approach for modeling diffusion tractography in the brain

Computational models provide additional tools for studying the brain, however, many techniques are cur-rently disconnected from each other. hTere is a need for new computational approaches that span the range of physics operating in the brain. In this review paper, we offer some new perspectives on how the embedded element method can ifll this gap and has the potential to connect a myriad of modeling genre. hTe embedded element method is a mesh superposition technique used within ifnite element analysis. hTis method allows for the incorporation of axonal ifber tracts to be explicitly represented. Here, we explore the use of the approach beyond its original goal of predicting axonal strain in brain injury. We explore the potential application of the embedded element method in areas of electrophysiology, neurodegeneration, neuropharmacology and mech-anobiology. We conclude that this method has the potential to provide us with an integrated computational framework that can assist in developing improved diagnostic tools and regeneration technologies.     

Abnormal activation of the occipital lobes during emotion picture processing in major depressive disorder patients

A large number of studies have demonstrated that depression patients have cognitive dysfunction. With recently developed brain functional imaging, studies have focused on changes in brain function to investigate cognitive changes. However, there is still controversy regarding abnormalities in brain functions or correlation between cognitive impairment and brain function changes. Thus, it is important to design an emotion-related task for research into brain function changes. We selected positive, neutral, and negative pictures from the International Affective Picture System. Patients with major depressive disorder were asked to judge emotion pictures. In addition, functional MRI was performed to synchronously record behavior data and imaging data. Results showed that the total correct rate for recognizing pictures was lower in patients compared with normal controls. Moreover, the consistency for recognizing pictures for depressed patients was worse than normal controls, and they frequently recognized positive pictures as negative pictures. The consistency for recognizing pictures was negatively correlated with the Hamilton Depression Rating Scale. Functional MRI suggested that the activation of some areas in the frontal lobe, temporal lobe, parietal lobe, limbic lobe, and cerebellum was enhanced, but that the activation of some areas in the frontal lobe, parietal lobe and occipital lobe was weakened while the patients were watching positive and neutral pictures compared with normal controls. The activation of some areas in the frontal lobe, temporal lobe, parietal lobe, and limbic lobe was enhanced, but the activation of some areas in the occipital lobe were weakened while the patients were watching the negative pictures compared with normal controls. These findings indicate that patients with major depressive disorder have negative cognitive disorder and extensive brain dysfunction. Thus, reduced activation of the occipital lobe may be an initiating factor for cognitive disorder in depressed patients.     

Prefrontal cortex and the dysconnectivity hypothesis of schizophrenia

Schizophrenia is hypothesized to arise from disrupted brain connectivity. This "dysconnectivity hypothesis" has generated interest in discovering whether there is anatomical and functional dysconnectivity between the prefrontal cortex(PFC) and other brain regions, and how this dysconnectivity is linked to the impaired cognitive functions and aberrant behaviors of schizophrenia. Critical advances in neuroimaging technologies, including diffusion tensor imaging(DTI) and functional magnetic resonance imaging(f MRI), make it possible to explore these issues. DTI affords the possibility to explore anatomical connectivity in the human brain in vivo and f MRI can be used to make inferences about functional connections between brain regions. In this review, we present major advances in the understanding of PFC anatomical and functional dysconnectivity and their implications in schizophrenia. We then briefl y discuss future prospects that need to be explored in order to move beyond simple mapping of connectivity changes to elucidate the neuronal mechanisms underlying schizophrenia.     

The development of neural synchrony and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis

Recent data from developmental cognitive neuroscience highlight the profound changes in the organization and function of cortical networks during the transition from adolescence to adulthood. While previous studies have focused on the development of gray and white matter, recent evidence suggests that brain maturation during adolescence extends to fundamental changes in the properties of cortical circuits that in turn promote the precise temporal coding of neural activity. In the current article, we will highlight modifications in the amplitude and synchrony of neural oscillations during adolescence that may be crucial for the emergence of cognitive deficits and psychotic symptoms in schizophrenia. Specifically, we will suggest that schizophrenia is associated with impaired parameters of synchronous oscillations that undergo changes during late brain maturation, suggesting an important role of adolescent brain development for the understanding, treatment, and prevention of the disorder.     

Response inhibition and cognitive flexibility in schizophrenia with and without comorbid substance use disorder

Addiction is a frequent comorbid disorder in schizophrenia related to dopaminergic dysfunction in fronto-subcortical circuits. These brain networks are relevant for both (executive) cognition and the neuropathology of schizophrenia. The aim of the present study was to elucidate whether response inhibition and cognitive flexibility - executive abilities relevant for achieving and maintaining abstinence - are differentially impaired in schizophrenia patients with or without comorbid substance use disorder. Patients suffering from major depression or alcoholism as well as healthy controls served as comparison groups. The ability to inhibit predominant response tendencies during response conflict and to efficiently shift the focus of attention between different task requirements was assessed by verbal and non-verbal cognitive tasks. Contrary to expectation, non-addicted schizophrenia patients showed the most pronounced executive function impairments relative to the control groups, affecting both response suppression and cognitive flexibility. Dual diagnosis patients did not differ significantly from non-addicted schizophrenia patients or from the alcoholic group, but were impaired at cognitive flexibility relative to the depression subgroup and healthy controls. Whether the relative preservation of response inhibition and cognitive flexibility in the dual disorder patients is due to high premorbid functioning, beneficial self-medication effects or compensatory brain activation remains to be elucidated. The relatively intact executive abilities in young, addicted schizophrenia patients might represent a beneficial resource for treatment strategies.     

Impaired vigilance networks in temporal lobe epilepsy: Mechanisms and clinical implications

Mesial temporal lobe epilepsy (mTLE) is a neurological disorder in which patients suffer from frequent consciousness-impairing seizures, broad neurocognitive deficits, and diminished quality of life. Although seizures in mTLE originate focally in the hippocampus or amygdala, mTLE patients demonstrate cognitive deficits that extend beyond temporal lobe function—such as decline in executive function, cognitive processing speed, and attention—as well as diffuse decreases in neocortical metabolism and functional connectivity. Given prior observations that mTLE patients exhibit impairments in vigilance, and that seizures may disrupt the activity and long-range connectivity of subcortical brain structures involved in vigilance regulation, we propose that subcortical activating networks underlying vigilance play a critical role in mediating the widespread neural and cognitive effects of focal mTLE. Here, we review evidence for impaired vigilance in mTLE, examine clinical implications and potential network underpinnings, and suggest neuroimaging strategies for determining the relationship between vigilance, brain connectivity, and neurocognition in patients and healthy controls.     

Latent Clinical-Anatomical Dimensions of Schizophrenia

Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.     

Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks

Brain regions which exhibit temporally coherent fluctuations, have been increasingly studied using functional magnetic resonance imaging (fMRI). Such networks are often identified in the context of an fMRI scan collected during rest (and thus are called "resting state networks"); however, they are also present during (and modulated by) the performance of a cognitive task. In this article, we will refer to such networks as temporally coherent networks (TCNs). Although there is still some debate over the physiological source of these fluctuations, TCNs are being studied in a variety of ways. Recent studies have examined ways TCNs can be used to identify patterns associated with various brain disorders (e.g. schizophrenia, autism or Alzheimer's disease). Independent component analysis (ICA) is one method being used to identify TCNs. ICA is a data driven approach which is especially useful for decomposing activation during complex cognitive tasks where multiple operations occur simultaneously. In this article we review recent TCN studies with emphasis on those that use ICA. We also present new results showing that TCNs are robust, and can be consistently identified at rest and during performance of a cognitive task in healthy individuals and in patients with schizophrenia. In addition, multiple TCNs show temporal and spatial modulation during the cognitive task versus rest. In summary, TCNs show considerable promise as potential imaging biological markers of brain diseases, though each network needs to be studied in more detail.     

Executive function in schizophrenia

Many domains of executive function are impaired in patients with schizophrenia including forward planning, concept formation, initiation, self-monitoring, and the ability to direct attention and memory. These impairments are noticeable against a background of generalized cognitive deficits, and many affect 40% to 95% of individuals with this disorder. Specific executive deficits appear to be related to specific symptom clusters and are linked to structural and functional brain abnormalities. Executive impairment predicts multiple domains of functional outcome in schizophrenia patients. Atypical antipsychotic agents and cognitive rehabilitation may be promising new approaches for the treatment of cognitive and functional impairment in schizophrenia.     

When Top-Down Meets Bottom-Up: Auditory Training Enhances Verbal Memory in Schizophrenia

A critical research priority for our field is to develop treatments that enhance cognitive functioning in schizophrenia and thereby attenuate the functional losses associated with the illness. In this article, we describe such a treatment method that is grounded in emerging research on the widespread sensory processing impairments of schizophrenia, as described elsewhere in this special issue. We first present the rationale for this treatment approach, which consists of cognitive training exercises that make use of principles derived from the past 2 decades of basic science research in learning-induced neuroplasticity; these exercises explicitly target not only the higher order or “top-down” processes of cognition but also the content building blocks of accurate and efficient sensory representations to simultaneously achieve “bottom-up” remediation. We then summarize our experience to date and briefly review our behavioral and serum biomarker findings from a randomized controlled trial of this method in outpatients with long-term symptoms of schizophrenia. Finally, we present promising early psychophysiological evidence that supports the hypothesis that this cognitive training method induces changes in aspects of impaired bottom-up sensory processing in schizophrenia. We conclude with the observation that neuroplasticity-based cognitive training brings patients closer to physiological patterns seen in healthy participants, suggesting that it changes the brain in an adaptive manner in schizophrenia.     

Performance of schizophrenic patients on putative neuropsychological tests of frontal lobe function

Though individual tests thought to assess frontal lobe function have been administered to patients with schizophrenia for many years, approaches in which a number of tests thought to tap a single function or brain region have rarely been used. Such an approach might define a critical test or a common dysfunctional cognitive process. In the present study four putative neuropsychological tests of frontal lobe integrity, namely, the Wisconsin Card Sorting Test, the Category Test, Trail Making B, and verbal fluency, were administered to 28 patients with schizophrenia. Seventy-five percent performed abnormally on at least one test. However, relationships among the test results were difficult to characterize, either by correlation or factor analysis. A hierarchical arrangement in which "higher order" tests proscribe performance on "lower order" tests did not appear to be present. Regarding sensitivity, Trails B, the only timed test, was most frequently impaired and verbal fluency was least frequently impaired. The results suggest that the tests assess somewhat different aspects of frontal lobe function, and that no single frontal lobe test is uniquely sensitive to cognitive impairment in schizophrenia.     

Cognition and resting-state functional connectivity in schizophrenia

Individuals with schizophrenia consistently display deficits in a multitude of cognitive domains, but the neurobiological source of these cognitive impairments remains unclear. By analyzing the functional connectivity of resting-state functional magnetic resonance imaging (rs-fcMRI) data in clinical populations like schizophrenia, research groups have begun elucidating abnormalities in the intrinsic communication between specific brain regions, and assessing relationships between these abnormalities and cognitive performance in schizophrenia. Here we review studies that have reported analysis of these brain–behavior relationships. Through this systematic review we found that patients with schizophrenia display abnormalities within and between regions comprising (1) the cortico-cerebellar-striatal-thalamic loop and (2) task-positive and task-negative cortical networks. Importantly, we did not observe unique relationships between specific functional connectivity abnormalities and distinct cognitive domains, suggesting that the observed functional systems may underlie mechanisms that are shared across cognitive abilities, the disturbance of which could contribute to the “generalized” cognitive deficit found in schizophrenia. We also note several areas of methodological change that we believe will strengthen this literature.     

Schizophrenia, cognition and neuroimaging

Schizophrenia is a complex illness whose mechanisms are still largely unknown. Functional brain imaging, by making the link between psyche and brain, has recently become an indispensable tool to study in vivo the neural bases underlying cognitive dysfunction in this disease. But despite the proliferation of data coming from this approach, the exact impact of functional imaging on our understanding of the disease remains blurry. In general, studies of the brain functioning of patients with schizophrenia found activation abnormalities which vary in nature and localization depending of the cognitive paradigm used. However, it appears that neurofunctional abnormalities observed in patients cannot be reduced to a simple well-localized deficit. It would be rather an alteration of the dynamics of the interactions between different brain regions that underlie the cognitive disturbances encountered in the disease. Functional brain imaging now offers new perspectives to clarify the dynamics of the brain networks, and particularly those involved in high-level cognitive functions, such as cognitive control or social cognition which seem to play a crucial role in the disease. The characterization of these features is an important issue not only to develop new hypotheses on the pathophysiology of the disorder, but also more pragmatically to identify potential therapeutic targets.