Gallyas-Braak银染法在神经系统变性疾病中的应用

目的 评估Gallyas-Braak银染色方法在几种神经系统变性疾病病理诊断中的作用和价值。方法 采用修订Gallyas-Braak染色法,对经临床和常规病理方法诊断的22例神经系统变性病的脑和脊髓标本进行了回顾性研究。结果 Gallyas-Braak银染色可良好显示Alzheimer病（AD）,其他变性病痴呆,正常老年人的海马及额、颞叶皮层神经原纤维缠结,且较Bodian染色清楚。在4例有痴呆症状和明显锥体外体征患者的中脑,基底节观察到大量神经元球形团样缠结,同时在运动皮层,基底节,中脑观察到星形细胞丛状缠结,其中2例符合进行性核上性麻痹的病理诊断标准,另2例观察到运动皮层和基底节区星形细胞斑,加之皮层神经元气球样变,符合皮质基底节变性的病理特征。3例多系统萎缩的脑和脊髓白质显示广泛分布少突胶质细胞包涵体。1例AD病的颞叶和海马皮质2－3层神经毡内显示嗜银颗粒,而Bodian染色未观察到这些病理改变。结论 Gallyas-Braak染色除显示神经原纤维缠结外,还能较好显示胶质细胞变性和神经毡异常结构,因此对进行性核上性麻痹,皮质基底节变性,多系统萎缩,嗜银颗粒病的病理诊断有重要价值。     

Cognitive relevance of the community structure of the human brain functional coactivation network

There is growing interest in the complex topology of human brain functional networks, often measured using resting-state functional MRI (fMRI). Here, we used a meta-analysis of the large primary literature that used fMRI or PET to measure task-related activation (>1,600 studies; 1985–2010). We estimated the similarity (Jaccard index) of the activation patterns across experimental tasks between each pair of 638 brain regions. This continuous coactivation matrix was used to build a weighted graph to characterize network topology. The coactivation network was modular, with occipital, central, and default-mode modules predominantly coactivated by specific cognitive domains (perception, action, and emotion, respectively). It also included a rich club of hub nodes, located in parietal and prefrontal cortex and often connected over long distances, which were coactivated by a diverse range of experimental tasks. Investigating the topological role of edges between a deactivated and an activated node, we found that such competitive interactions were most frequent between nodes in different modules or between an activated rich-club node and a deactivated peripheral node. Many aspects of the coactivation network were convergent with a connectivity network derived from resting state fMRI data (n = 27, healthy volunteers); although the connectivity network was more parsimoniously connected and differed in the anatomical locations of some hubs. We conclude that the community structure of human brain networks is relevant to cognitive function. Deactivations may play a role in flexible reconfiguration of the network according to cognitive demand, varying the integration between modules, and between the periphery and a central rich club.     

Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus

To better understand intrinsic brain connections in major depression, we used a neuroimaging technique that measures resting state functional connectivity using functional MRI (fMRI). Three different brain networks—the cognitive control network, default mode network, and affective network—were investigated. Compared with controls, in depressed subjects each of these three networks had increased connectivity to the same bilateral dorsal medial prefrontal cortex region, an area that we term the dorsal nexus. The dorsal nexus demonstrated dramatically increased depression-associated fMRI connectivity with large portions of each of the three networks. The discovery that these regions are linked together through the dorsal nexus provides a potential mechanism to explain how symptoms of major depression thought to arise in distinct networks—decreased ability to focus on cognitive tasks, rumination, excessive self-focus, increased vigilance, and emotional, visceral, and autonomic dysregulation—could occur concurrently and behave synergistically. It suggests that the newly identified dorsal nexus plays a critical role in depressive symptomatology, in effect “hot wiring” networks together; it further suggests that reducing increased connectivity of the dorsal nexus presents a potential therapeutic target.     

老年人海绵状脑病一例报告及文献复习

目的：探讨老年期发病的海绵状脑病的临床特点并分析误诊原因。方法：报告1例79例老年海绵状脑病的临床病理诊断过程。并复习国内报道的经病理学证实的8例60岁以上老年海绵状脑病患者的持征及脑电图、MRI资料。结果：老年人海绵状脑病急性发病者病程短,但都有进行性痴呆、肌阵挛及各种不自主运动发作。6例脑电图有典型的周期性三相波,1例MRI发现双侧基底节区T2高信号。3例初诊为脑血管病,1例为单疱性脑炎。病理上有典型的空泡和海绵状改变。结论：急性发病的老年人海绵状脑病容易误诊为脑血管病,但根据患者典型的临床表现,结论动态脑电图特征,必要时脑活检,可尽早诊断,减少医源性传播。     

Selective changes of resting-state networks in individuals at risk for Alzheimer's disease

Alzheimer''s disease (AD) is a neurodegenerative disorder that prominently affects cerebral connectivity. Assessing the functional connectivity at rest, recent functional MRI (fMRI) studies reported on the existence of resting-state networks (RSNs). RSNs are characterized by spatially coherent, spontaneous fluctuations in the blood oxygen level-dependent signal and are made up of regional patterns commonly involved in functions such as sensory, attention, or default mode processing. In AD, the default mode network (DMN) is affected by reduced functional connectivity and atrophy. In this work, we analyzed functional and structural MRI data from healthy elderly (n = 16) and patients with amnestic mild cognitive impairment (aMCI) (n = 24), a syndrome of high risk for developing AD. Two questions were addressed: (i) Are any RSNs altered in aMCI? (ii) Do changes in functional connectivity relate to possible structural changes? Independent component analysis of resting-state fMRI data identified eight spatially consistent RSNs. Only selected areas of the DMN and the executive attention network demonstrated reduced network-related activity in the patient group. Voxel-based morphometry revealed atrophy in both medial temporal lobes (MTL) of the patients. The functional connectivity between both hippocampi in the MTLs and the posterior cingulate of the DMN was present in healthy controls but absent in patients. We conclude that in individuals at risk for AD, a specific subset of RSNs is altered, likely representing effects of ongoing early neurodegeneration. We interpret our finding as a proof of principle, demonstrating that functional brain disorders can be characterized by functional-disconnectivity profiles of RSNs.     

Disruptions in Functional Network Connectivity During Alcohol Intoxicated Driving

Background: Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published functional magnetic resonance imaging (fMRI) study ( Meda et al., 2009 ), our group identified 5, independent critical driving‐associated brain circuits whose inter‐regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol‐intoxicated states. Methods: In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following 2 alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%. Results: At the active dose, we found specific disruptions of functional network connectivity between the frontal‐temporal‐basal ganglia and the cerebellar circuits. The temporal connectivity between these 2 circuits was found to be less correlated (p < 0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering). Conclusions: Connections between frontal‐temporal‐basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior.     

Impaired brain networks functional connectivity after acute mild hypoxia

This study aimed to analyze the changes in brain networks functional connectivity of pilots exposed to simulated hypoxia using resting-state functional magnetic resonance imaging (fMRI). A total of 35 healthy male pilots exposed to 14.5% oxygen concentration (corresponding to an altitude of 3000 m) underwent resting-state fMRI scans. The independent component analysis (ICA) approach was used to analyze changes in the resting-state brain networks functional connectivity of pilots after hypoxic exposure, and 9 common components in brain functional networks were identified. In the functional connections that showed significant group differences, linear regression was used to examine the association between functional connectivity and clinical characteristics. The brain networks functional connectivity after hypoxia exposure decreased significantly, including the left frontoparietal network and visual network 1-area, left frontoparietal network and visual network 2-area, right frontoparietal network and visual network 2-area, dorsal attention network and ventral attention network, dorsal attention network and auditory network, and ventral attention network and visual network 1-area. We found no correlation between the altered functional connectivity and arterial oxygen saturation level. Our findings provide insights into the mechanisms underlying hypoxia-induced cognitive impairment in pilots.     

Energetic cost of brain functional connectivity

The brain''s functional connectivity is complex, has high energetic cost, and requires efficient use of glucose, the brain''s main energy source. It has been proposed that regions with a high degree of functional connectivity are energy efficient and can minimize consumption of glucose. However, the relationship between functional connectivity and energy consumption in the brain is poorly understood. To address this neglect, here we propose a simple model for the energy demands of brain functional connectivity, which we tested with positron emission tomography and MRI in 54 healthy volunteers at rest. Higher glucose metabolism was associated with proportionally larger MRI signal amplitudes, and a higher degree of connectivity was associated with nonlinear increases in metabolism, supporting our hypothesis for the energy efficiency of the connectivity hubs. Basal metabolism (in the absence of connectivity) accounted for 30% of brain glucose utilization, which suggests that the spontaneous brain activity accounts for 70% of the energy consumed by the brain. The energy efficiency of the connectivity hubs was higher for ventral precuneus, cerebellum, and subcortical hubs than for cortical hubs. The higher energy demands of brain communication that hinges upon higher connectivity could render brain hubs more vulnerable to deficits in energy delivery or utilization and help explain their sensitivity to neurodegenerative conditions, such as Alzheimer’s disease.     

Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease

Although previous studies have emphasized the vulnerability of the default mode network (DMN) in Alzheimer’s disease (AD), little is known about the involvement of other functional networks and their relationship to clinical phenotype. To test whether clinicoanatomic heterogeneity in AD is driven by the involvement of specific networks, network connectivity was assessed in healthy subjects by seeding regions commonly and specifically atrophied in three clinical AD variants: early-onset AD (age at onset, <65 y; memory and executive deficits), logopenic variant primary progressive aphasia (language deficits), and posterior cortical atrophy (visuospatial deficits). Four-millimeter seed regions of interest were used to obtain intrinsic connectivity maps in 131 healthy controls (age, 65.5 ± 3.5 y). Atrophy patterns in independent cohorts of AD variant patients and their correspondence to connectivity networks in controls were also assessed. The connectivity maps of commonly atrophied regions of interest support posterior DMN and precuneus network involvement across AD variants, whereas seeding regions specifically atrophied in each AD variant revealed distinct, syndrome-specific connectivity patterns. Goodness-of-fit analysis of each connectivity map with network templates showed the highest correspondence between the early-onset AD seed connectivity map and anterior salience and right executive-control networks, the logopenic aphasia seed connectivity map and the language network, and the posterior cortical atrophy seed connectivity map and the higher visual network. Connectivity maps derived from controls matched regions commonly and specifically atrophied in the patients. Our findings indicate that the posterior DMN and precuneus network are commonly affected in AD variants, whereas syndrome-specific neurodegenerative patterns are driven by the involvement of specific networks outside the DMN.Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by extracellular accumulation of amyloid plaques, intracellular neurofibrillary tangles, and neuronal loss (1). Although most patients present with memory deficits, a significant minority of patients with AD present with nonamnestic syndromes (2, 3). Patients with nonfamilial early-onset AD (EOAD, defined as onset <65 y in most studies) often show heterogeneous cognitive deficits, including impairment in attention and executive functions (4, 5). Focal syndromes such as posterior cortical atrophy (PCA, characterized by predominant visuospatial and visuoperceptual deficits; ref. 6) and the logopenic variant of primary progressive aphasia [lvPPA, a progressive disorder of language (7, 8)] are also most commonly caused by AD pathology. It has been suggested that up to 15% of patients with AD seen in dementia centers have nonamnestic presentations (2), and the importance of these syndromes is reflected in their inclusion in new diagnostic guidelines for AD (9, 10). The factors driving the clinicoanatomical heterogeneity in AD are not well understood. One possible mechanism that could explain the specific involvement of different brain regions in AD variants is the spread of disease via distinct functional networks.Recent advances in functional neuroimaging have provided important insights into the dysfunction of large-scale neural networks in neurodegenerative diseases. Studies using task-free (resting-state) functional magnetic resonance imaging (fMRI) data have shown that correlated spontaneous activity occurs between functionally related brain regions (11, 12). Disease-specific atrophy patterns have been shown to closely match intrinsic connectivity maps in cognitively normal individuals, suggesting that neurodegenerative disorders target specific functional networks in the human brain (13, 14). This observation is consistent with in vitro and in vivo studies in animal models showing that disease-associated protein aggregates spread via interconnected neural networks (15–17). Functional connectivity studies have further provided evidence for a core network, commonly referred to as the default mode network (DMN), that is particularly vulnerable and affected in AD (18, 19). Changes in DMN connectivity are detected even in the preclinical stages of AD (20, 21) and distinguish AD from other neurodegenerative diseases (22). Although the behavioral correlates of the DMN remain to be characterized in more detail, it has been hypothesized that the DMN plays a role in attending to both internally and externally generated environmental stimuli (23, 24). The DMN has been further divided into two to three functional subnetworks: a ventral component (including retrosplenial cortex and medial temporal lobe) and a dorsal component that can be further divided into anterior (prefrontal-predominant) and posterior (parietal-predominant) modules (25).Little is currently known about the dysfunction of the DMN and other networks in atypical clinical variants of AD. A recent positron emission tomography (PET) study showed that patterns of glucose hypometabolism in EOAD, lvPPA, and PCA matched the network templates of executive-control, language, and visual networks, respectively (26), suggesting that the clinical phenotype in AD may be driven by the relative involvement of functional networks outside the DMN. Structural MRI studies, in contrast, have shown that patterns of neurodegeneration converge in the DMN in different variants of AD (27, 28), suggesting that the DMN may represent a core network that is commonly affected across AD variants. These data are consistent with a model in which AD pathology spreads from the DMN to closely interconnected posterior networks, including those involved in visuospatial, language, and executive function, or conversely, that neurodegeneration in AD begins in more peripheral networks in clinical variants of AD and converges in the DMN across variants.In this study, we aimed to assess intrinsic connectivity networks in the healthy brain by seeding regions of interest (ROIs) demonstrated in a previous study to be either commonly or specifically atrophied in three AD variants: EOAD, lvPPA, and PCA. These variants, although less common than typical late-onset amnestic AD, were selected to maximize the heterogeneity of clinical phenotype and degenerative pattern. We hypothesized that seeding regions commonly atrophied in AD variants (i.e., peak atrophy voxels across all syndromes compared with controls) will produce similar network maps in healthy controls and may point toward functional networks commonly affected in all three AD variants. In contrast, seeding regions specifically atrophied in AD variants (i.e., peak atrophy voxels in each syndrome compared with the other two) will produce distinct network connectivity maps in the healthy brain and may point to networks that are specifically affected in the different variants. To assess the overlap of the resulting connectivity maps with published network templates, a goodness-of-fit analysis was conducted, testing each connectivity map against a set of 15 functional network templates (refs. 25 and 29 and http://findlab.stanford.edu/functional_ROIs.html). To ascertain the relevance of the connectivity patterns detected in controls to disease, we compared the connectivity patterns from common and syndrome-specific ROIs to regions commonly and specifically atrophied in an independent sample of patients with the three AD variants, as assessed using voxel-based morphometry (VBM). A flowchart summarizing the experimental procedures conducted in this study is presented in Fig. S1.     

From the Cover: Learning sculpts the spontaneous activity of the resting human brain

The brain is not a passive sensory-motor analyzer driven by environmental stimuli, but actively maintains ongoing representations that may be involved in the coding of expected sensory stimuli, prospective motor responses, and prior experience. Spontaneous cortical activity has been proposed to play an important part in maintaining these ongoing, internal representations, although its functional role is not well understood. One spontaneous signal being intensely investigated in the human brain is the interregional temporal correlation of the blood-oxygen level-dependent (BOLD) signal recorded at rest by functional MRI (functional connectivity-by-MRI, fcMRI, or BOLD connectivity). This signal is intrinsic and coherent within a number of distributed networks whose topography closely resembles that of functional networks recruited during tasks. While it is apparent that fcMRI networks reflect anatomical connectivity, it is less clear whether they have any dynamic functional importance. Here, we demonstrate that visual perceptual learning, an example of adult neural plasticity, modifies the resting covariance structure of spontaneous activity between networks engaged by the task. Specifically, after intense training on a shape-identification task constrained to one visual quadrant, resting BOLD functional connectivity and directed mutual interaction between trained visual cortex and frontal-parietal areas involved in the control of spatial attention were significantly modified. Critically, these changes correlated with the degree of perceptual learning. We conclude that functional connectivity serves a dynamic role in brain function, supporting the consolidation of previous experience.     

Simple models of human brain functional networks

Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.     

Nonrandom connectivity of the epileptic dentate gyrus predicts a major role for neuronal hubs in seizures

Many complex neuronal circuits have been shown to display nonrandom features in their connectivity. However, the functional impact of nonrandom network topologies in neurological diseases is not well understood. The dentate gyrus is an excellent circuit in which to study such functional implications because proepileptic insults cause its structure to undergo a number of specific changes in both humans and animals, including the formation of previously nonexistent granule cell-to-granule cell recurrent excitatory connections. Here, we use a large-scale, biophysically realistic model of the epileptic rat dentate gyrus to reconnect the aberrant recurrent granule cell network in four biologically plausible ways to determine how nonrandom connectivity promotes hyperexcitability after injury. We find that network activity of the dentate gyrus is quite robust in the face of many major alterations in granule cell-to-granule cell connectivity. However, the incorporation of a small number of highly interconnected granule cell hubs greatly increases network activity, resulting in a hyperexcitable, potentially seizure-prone circuit. Our findings demonstrate the functional relevance of nonrandom microcircuits in epileptic brain networks, and they provide a mechanism that could explain the role of granule cells with hilar basal dendrites in contributing to hyperexcitability in the pathological dentate gyrus.     

Transcranial magnetic stimulation modulates the brain's intrinsic activity in a frequency-dependent manner

Intrinsic activity in the brain is organized into networks. Although constrained by their anatomical connections, functional correlations between nodes of these networks reorganize dynamically. Dynamic organization implies that couplings between network nodes can be reconfigured to support processing demands. To explore such reconfigurations, we combined repetitive transcranial magnetic stimulation (rTMS) and functional connectivity MRI (fcMRI) to modulate cortical activity in one node of the default network, and assessed the effect of this upon functional correlations throughout the network. Two different frequencies of rTMS to the same default network node (the left posterior inferior parietal lobule, lpIPL) induced two topographically distinct changes in functional connectivity. High-frequency rTMS to lpIPL decreased functional correlations between cortical default network nodes, but not between these nodes and the hippocampal formation. In contrast, low frequency rTMS to lpIPL did not alter connectivity between cortical default network nodes, but increased functional correlations between lpIPL and the hippocampal formation. These results suggest that the default network is composed of (at least) two subsystems. More broadly, the finding that two rTMS stimulation regimens to the same default network node have distinct effects reveals that this node is embedded within a network that possesses multiple, functionally distinct relationships among its distributed partners.     

Network-level structural covariance in the developing brain

Intrinsic or resting state functional connectivity MRI and structural covariance MRI have begun to reveal the adult human brain's multiple network architectures. How and when these networks emerge during development remains unclear, but understanding ontogeny could shed light on network function and dysfunction. In this study, we applied structural covariance MRI techniques to 300 children in four age categories (early childhood, 5-8 y; late childhood, 8.5-11 y; early adolescence, 12-14 y; late adolescence, 16-18 y) to characterize gray matter structural relationships between cortical nodes that make up large-scale functional networks. Network nodes identified from eight widely replicated functional intrinsic connectivity networks served as seed regions to map whole-brain structural covariance patterns in each age group. In general, structural covariance in the youngest age group was limited to seed and contralateral homologous regions. Networks derived using primary sensory and motor cortex seeds were already well-developed in early childhood but expanded in early adolescence before pruning to a more restricted topology resembling adult intrinsic connectivity network patterns. In contrast, language, social-emotional, and other cognitive networks were relatively undeveloped in younger age groups and showed increasingly distributed topology in older children. The so-called default-mode network provided a notable exception, following a developmental trajectory more similar to the primary sensorimotor systems. Relationships between functional maturation and structural covariance networks topology warrant future exploration.     

Deficit in switching between functional brain networks underlies the impact of multitasking on working memory in older adults

Multitasking negatively influences the retention of information over brief periods of time. This impact of interference on working memory is exacerbated with normal aging. We used functional MRI to investigate the neural basis by which an interruption is more disruptive to working memory performance in older individuals. Younger and older adults engaged in delayed recognition tasks both with and without interruption by a secondary task. Behavioral analysis revealed that working memory performance was more impaired by interruptions in older compared with younger adults. Functional connectivity analyses showed that when interrupted, older adults disengaged from a memory maintenance network and reallocated attentional resources toward the interrupting stimulus in a manner consistent with younger adults. However, unlike younger individuals, older adults failed to both disengage from the interruption and reestablish functional connections associated with the disrupted memory network. These results suggest that multitasking leads to more significant working memory disruption in older adults because of an interruption recovery failure, manifest as a deficient ability to dynamically switch between functional brain networks.     

Altered Functional Connectivity in Essential Tremor: A Resting-State fMRI Study

Essential tremor (ET) has been associated with a spectrum of clinical features, with both motor and nonmotor elements, including cognitive deficits. We employed resting-state functional magnetic resonance imaging (fMRI) to assess whether brain networks that might be involved in the pathogenesis of nonmotor manifestations associated with ET are altered, and the relationship between abnormal connectivity and ET severity and neuropsychological function.Resting-state fMRI data in 23 ET patients (12 women and 11 men) and 22 healthy controls (HC) (12 women and 10 men) were analyzed using independent component analysis, in combination with a “dual-regression” technique, to identify the group differences of resting-state networks (RSNs) (default mode network [DMN] and executive, frontoparietal, sensorimotor, cerebellar, auditory/language, and visual networks). All participants underwent a neuropsychological and neuroimaging session, where resting-state data were collected.Relative to HC, ET patients showed increased connectivity in RSNs involved in cognitive processes (DMN and frontoparietal networks) and decreased connectivity in the cerebellum and visual networks. Changes in network integrity were associated not only with ET severity (DMN) and ET duration (DMN and left frontoparietal network), but also with cognitive ability. Moreover, in at least 3 networks (DMN and frontoparietal networks), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language) and depressive symptoms. Further, in the visual network, decreased connectivity was associated with worse performance on visuospatial ability.ET was associated with abnormal brain connectivity in major RSNs that might be involved in both motor and nonmotor symptoms. Our findings underscore the importance of examining RSNs in this population as a biomarker of disease.     

Premotor functional connectivity predicts impulsivity in juvenile offenders

Teenagers are often impulsive. In some cases this is a phase of normal development; in other cases impulsivity contributes to criminal behavior. Using functional magnetic resonance imaging, we examined resting-state functional connectivity among brain systems and behavioral measures of impulsivity in 107 juveniles incarcerated in a high-security facility. In less-impulsive juveniles and normal controls, motor planning regions were correlated with brain networks associated with spatial attention and executive control. In more-impulsive juveniles, these same regions correlated with the default-mode network, a constellation of brain areas associated with spontaneous, unconstrained, self-referential cognition. The strength of these brain-behavior relationships was sufficient to predict impulsivity scores at the individual level. Our data suggest that increased functional connectivity of motor-planning regions with networks subserving unconstrained, self-referential cognition, rather than those subserving executive control, heightens the predisposition to impulsive behavior in juvenile offenders. To further explore the relationship between impulsivity and neural development, we studied functional connectivity in the same motor-planning regions in 95 typically developing individuals across a wide age span. The change in functional connectivity with age mirrored that of impulsivity: younger subjects tended to exhibit functional connectivity similar to the more-impulsive incarcerated juveniles, whereas older subjects exhibited a less-impulsive pattern. This observation suggests that impulsivity in the offender population is a consequence of a delay in typical development, rather than a distinct abnormality.     

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.     

Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.