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Journal ArticleDOI

Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network?

TL;DR: Patients with schizophrenia show both failure to activate and failure to deactivate during performance of a working memory task, including an area in the anterior prefrontal/anterior cingulate cortex that corresponds to one of the two midline components of the ‘default mode network’ implicated in functions related to maintaining one's sense of self.
Abstract: BackgroundFunctional imaging studies using working memory tasks have documented both prefrontal cortex (PFC) hypo- and hyperactivation in schizophrenia. However, these studies have often failed to consider the potential role of task-related deactivation.MethodThirty-two patients with chronic schizophrenia and 32 age- and sex-matched normal controls underwent functional magnetic resonance imaging (fMRI) scanning while performing baseline, 1-back and 2-back versions of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups.ResultsThe controls showed activation in the expected frontal regions. There were also clusters of deactivation, particularly in the anterior cingulate/ventromedial PFC and the posterior cingulate cortex/precuneus. Compared to the controls, the schizophrenic patients showed reduced activation in the right dorsolateral prefrontal cortex (DLPFC) and other frontal areas. There was also an area in the anterior cingulate/ventromedial PFC where the patients showed apparently greater activation than the controls. This represented a failure of deactivation in the schizophrenic patients. Failure to activate was a function of the patients' impaired performance on the n-back task, whereas the failure to deactivate was less performance dependent.ConclusionsPatients with schizophrenia show both failure to activate and failure to deactivate during performance of a working memory task. The area of failure of deactivation is in the anterior prefrontal/anterior cingulate cortex and corresponds to one of the two midline components of the ‘default mode network’ implicated in functions related to maintaining one's sense of self.
Citations
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Book ChapterDOI
01 Jan 2014

1 citations

Book ChapterDOI
01 Jan 2016
TL;DR: The self is a superordinate schema and information about the self is encoded in a separate cognitive structure than information about other topics as discussed by the authors, and there is a brain network somewhat dedicated to self-reflection.
Abstract: Thinking about ourselves is a cognitive process fundamental to human mental life. This chapter focuses on the cognitive neuroscience approach taken by psychologists to understand self-reflection. Several principles have emerged. First, the self is a superordinate schema—information about the self is encoded in a separate cognitive structure than information about other topics. Second, there is a brain network somewhat dedicated to self-reflection. Third, this brain network overlaps with a network that is active when we rest. Fourth, such overlaps suggest that much of our mental machinery is in fact given over to social processes, a conclusion unthinkable prior to the onset of functional neuroimaging. Finally, disorders of the self (e.g., autism and schizophrenia) leave individuals with difficulties in recalling the stable nature of their selves. Future directions for the cognitive neuroscience of self-reflection are discussed at the end of the chapter.

1 citations

Dissertation
28 Jul 2014
TL;DR: Assessment of the architecture of resting state brain networks using functional magnetic resonance imaging in a cohort of participants exposed to prolonged stress and respective gender and age-matched controls reveals that stress impacts on activationdeactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity.
Abstract: Resting state brain networks (RSNs) are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI) studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during shift to task performance. Herein we assessed the architecture of the RSNs using functional magnetic resonance imaging (fMRI) in a cohort of participants exposed to prolonged stress (participants that had just finished their long period of preparation for the medical residence selection exam), and respective genderand age-matched controls (medical students under normal academic activities). Analysis focused on the pattern of activity in resting state conditions and after deactivation. A volumetric estimation of the RSNs was also performed. Data shows that stressed participants displayed greater activation of the default mode (DMN), dorsal attention (DAN), ventral attention (VAN), sensorimotor (SMN), and primary visual (VN) networks than controls. Importantly, stressed participants also evidenced impairments in the deactivation of resting statenetworks when compared to controls. These functional changes are paralleled by a constriction of the DMN that is in line with the pattern of brain atrophy observed after stress exposure. These results reveal that stress impacts on activationdeactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity. Citation: Soares JM, Sampaio A, Ferreira LM, Santos NC, Marques P, et al. (2013) Stress Impact on Resting State Brain Networks. PLoS ONE 8(6): e66500. doi:10.1371/journal.pone.0066500 Editor: Wang Zhan, University of Maryland, College Park, United States of America Received January 30, 2013; Accepted May 6, 2013; Published June 19, 2013 Copyright: ß 2013 Soares et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: JMS, NCS and PM are supported by fellowships of the project SwitchBox-FP7-HEALTH-2010-grant 259772-2; FM is supported by the fellowship SFRH/ BPD/33379/2008 funded by the Fundação para a Ciência e Tecnologia (FCT, Portugal). The work was supported by SwitchBox-FP7-HEALTH-2010-grant 259772-2. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: njcsousa@ecsaude.uminho.pt . These authors contributed equally to this work. Introduction For many years it has been recognized that acute stress is state of increased vigilance and alertness and to get the organism ready to take action before the impact of dangers [1]. Under brief stressful conditions, the ability to perceive changes in the surrounding environment becomes critical to mount an appropriate response. However, when the homeostatic mechanisms are disrupted, namely through prolonged stress exposure, maladaptive responses take place and trigger inappropriate functional responses with behavioral consequences, including deficits in attention control [2–5]. Recently, we showed, both in humans and rodents, that chronic stress triggers long-lasting, but reversible, changes in the frontostriatal networks that govern instrumental behavior decisions with impairments in decision-making processes [6,7]. It is well established that the brain is organized into multiple spatially distributed large-scale networks; this is evidenced by taskbased functional magnetic resonance imaging (fMRI) studies [8– 10] but also by resting state fMRI studies [11–13]. The latter, also known as resting state networks (RSNs), include the default mode (DMN), attention (dorsal and ventral), sensorimotor (SMN), visual (VN), auditory (AN), language and memory networks. The DMN is a network of brain cortical areas that present high metabolic activity when the brain is ‘‘at rest’’ and the individual is not focused on any external demand. This network displays a high degree of functional connectivity between various interacting brain areas. Typically, the DMN comprises areas of the posterior cingulate cortex (pCC) and adjacent precuneus (PCu), the medial prefrontal cortex (mPFC), medial, lateral and inferior parietal cortex, and medial and inferior temporal cortex [14,15]. The DMN is thought to serve important cognitive functions such as supporting internal mental activity detached from the external world, but also in connecting internal and external attention in monitoring the world around us [16,17]. There is also evidence that task-induced deactivations of the DMN have been functionally associated with goal-directed behavior [18]. Specifically, deactivation may correspond to a deviation in the default-mode towards a tuning down task-focused behavior that requires attention focus and other demanding cognitive processes. Moreover, task-induced DMN deactivation was related with performance in several cognitive tasks (e.g. [19]), whereas failure of deactivation has been associated with neuropsychiatric diseases (e.g. [20,21]). While the DMN shows deactivation during cognitively demanding tasks [19,22], activation in attentional PLOS ONE | www.plosone.org 1 June 2013 | Volume 8 | Issue 6 | e66500 networks (dorsal attention and ventral attention networks) typically increases [23,24]. Specifically, in addition to the typical DMN, two largely segregated canonical networks in their spatial distribution have also been consistently observed during the brain’s resting state and related with attention-demanding tasks: a bilateral dorsal attention network (DAN), which includes the dorsal frontal and parietal cortices (intraparietal sulcus), and the ventral attention network (VAN), largely right-lateralized, which includes the ventral frontal and parietal cortices (temporo-parietal junction), the insular cortex and subcortical regions [24,25]. While the DAN has been associated with goal-directed, top-down attention processes as inhibitory control, working memory and response selection, the VAN is related with salience processing and mediates stimulus-driven, bottom-up attention processes [24–26]. Moreover, it is relevant to note that dorsal and ventral systems appear to interact not only during cognitive tasks [27,28] but also during spontaneous activity [25]. In addition to the typical DMN, VAN and DAN, other networks have also been consistently observed during the brain’s resting state, including: the VN involving the occipital and bilateral temporal regions which is linked to the visual processing network and mental imagery [13,29]; the AN including the superior temporal and inferior frontal gyrus, known for being responsible in auditory processing and language comprehension; the SMN involving the precentral, postcentral gyrus, cerebellum, portion of the frontal gyrus that subserves sensorial and motor tasks [12,25,30,31] and the self-referential network including the medial prefrontal, the anterior cingulate cortex and the hypothalamus [13]. Importantly, all these RSNs were also shown to present abnormal functional patterns in many neuropsychiatric disorders [32–36] For example, in autism, RSNs are much more loosely connected [32,33]; increased functional connectivity was found in social anxiety disorder patients between the right posterior inferior temporal gyrus and the left inferior occipital gyrus, and between the right parahippocampal/hippocampal gyrus and the left middle temporal gyrus [34]; patients with borderline personality disorder showed an increase in functional connectivity in the left frontopolar cortex and the left insula, whereas decreased connectivity was found in the left cuneus [35]; patients with major depressive disorder exhibited increased functional connectivity in the anterior medial cortex regions and decreased functional connectivity in the posterior medial cortex regions compared with controls [36]. Notably, the effect of stress in the functional architecture of RSNs, both during task performance or resting state conditions, is largely unknown. Moreover, although neuropsychiatric diseases (e.g. bipolar disorders, schizophrenia) have been associated with abnormal patterns of RSNs deactivation, which may be related with difficulties in task-focusing and cognitive resources allocation, studies performed during prolonged stress, an established risk factor for neuropsychiatric disorders, are absent. Thus, the main goal of this study was to test if the functional connectivity of RSNs might be aberrant in chronic stress conditions. To achieve this goal, we assessed the architectural differences of RSNs using fMRI independent component analysis (ICA) on resting state data and task induced deactivation analysis, and region-of-interest surface assessments. Materials and Methods Participants, Psychological Tests and Cortisol Measurements The participants included in this study were 8 controls (2 males, 6 females; mean age, 24.2561.98) and 8 stress (2 males, 6 females; mean age, 23.8660.35) participants submitted to prolonged psychological stress exposure. Control participants included a cohort of medical students under their normal academic activities, whereas the stress group included participants that had just finished their long period of preparation for the medical residence selection exam. Participants responded to a laterality test and to a self-administered questionnaire regarding stress assessment (Perceived Stress Scale – PSS [37]. Participants were further assessed with the Hamilton anxiety scale [38] and the Hamilton depression scal

Cites background from "Failure to deactivate in the prefro..."

  • ...Additionally, abnormal patterns of RSNs deactivation have been associated with several neuropsychiatric diseases (Pomarol-Clotet et al., 2008; Guerrero-Pedraza et al., 2012)....

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Journal ArticleDOI
TL;DR: In this article, a task-relevant replay-default mode network coupling was found to be associated with memory maintenance of learned task sequences in schizophrenia, which was not explained by differential replay or altered default mode network dynamics between groups nor by reference to antipsychotic exposure.
Abstract: Abstract Schizophrenia is characterized by an abnormal resting state and default mode network brain activity. However, despite intense study, the mechanisms linking default mode network dynamics to neural computation remain elusive. During rest, sequential hippocampal reactivations, known as ‘replay’, are played out within default mode network activation windows, highlighting a potential role of replay-default mode network coupling in memory consolidation and model-based mental simulation. Here, we test a hypothesis of reduced replay-default mode network coupling in schizophrenia, using magnetoencephalography and a non-spatial sequence learning task designed to elicit off-task (i.e. resting state) neural replay. Participants with a diagnosis of schizophrenia (n = 28, mean age 28.2 years, range 20–40, 6 females, 13 not taking antipsychotic medication) and non-clinical control participants (n = 29, mean age 28.1 years, range 18–45, 6 females, matched at group level for age, intelligence quotient, gender, years in education and working memory) underwent a magnetoencephalography scan both during task completion and during a post-task resting state session. We used neural decoding to infer the time course of default mode network activation (time-delay embedding hidden Markov model) and spontaneous neural replay (temporally delayed linear modelling) in resting state magnetoencephalography data. Using multiple regression, we then quantified the extent to which default mode network activation was uniquely predicted by replay events that recapitulated the learned task sequences (i.e. ‘task-relevant’ replay-default mode network coupling). In control participants, replay-default mode network coupling was augmented following sequence learning, an augmentation that was specific for replay of task-relevant (i.e. learned) state transitions. This task-relevant replay-default mode network coupling effect was significantly reduced in schizophrenia (t(52) = 3.93, P = 0.018). Task-relevant replay-default mode network coupling predicted memory maintenance of learned sequences (ρ(52) = 0.31, P = 0.02). Importantly, reduced task-relevant replay-default mode network coupling in schizophrenia was not explained by differential replay or altered default mode network dynamics between groups nor by reference to antipsychotic exposure. Finally, task-relevant replay-default mode network coupling during rest correlated with stimulus-evoked default mode network modulation as measured in a separate task session. In the context of a proposed functional role of replay-default mode network coupling, our findings shed light on the functional significance of default mode network abnormalities in schizophrenia and provide for a consilience between task-based and resting state default mode network findings in this disorder.
Proceedings ArticleDOI
16 Mar 2016
TL;DR: The use of latest computational tools for analysis of data from human brain and a vision for future developments that could revolutionize the use of computational techniques in making neuropsychiatry a quantitative practice are offered.
Abstract: Magnetic resonance imaging (MRI) has developed into an indispensible diagnostic tool in medicine. MRI has also demonstrated immense potential for researchers who are making progress in every aspect of this modality expanding its applications into uncharted territories. Computational techniques have made major contributions to MRI enabling detection of minute signals from human brain. Functional MRI (fMRI) offers imaging of the mind as well as the brain in the same session. Complex computational tools are used to visualize brain networks that offer a new powerful tool to study the brain and its disorders. Functional connectivity (fc) maps using resting state fMRI (rsfMRI) is computed by detecting temporal synchronicity of neuronal activation patterns of anatomically separated brain regions. But, a great deal of technological advancement, both in hardware and software, had to be made to make computation of brain networks possible. The critical technologies that made computational modeling of functional brain networks possible were high quality gradients for implementation of distortion free fMRI, faster pulse sequences and radio frequency (RF) coils to capture the fluctuation frequency of neuronal activity, and complex post processing computation of brain networks. rsfMRI is capable of detecting brain function that mediate high cognitive processes in normal brain. We aim to ultimately detect the disruption of this mediation in psychiatric patients. We have already obtained functional connectivity in normal subjects using fMRI data during resting state. We did this as a function of spatial resolution to explore the required computational sources and susceptibility effects on the sensitivity of fMRI to anatomic specialization. We provide a conceptual summary of the role of computational techniques in fMRI data analysis. In exploring this question, ultimately MRI's capability in accessing information at the neuronal level comes to surface. We use latest computational tools for analysis of data from human brain and offer a vision for future developments that could revolutionize the use of computational techniques in making neuropsychiatry a quantitative practice.

Cites background from "Failure to deactivate in the prefro..."

  • ...When brain engages in focused attention on the external environment DMN activities are supposed to be suppressed to let the network specialized in the task to increase its activity [9, 10]....

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References
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Journal ArticleDOI
TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.

12,097 citations

Book
01 Jan 1966
TL;DR: This book discusses statistical decision theory and sensory processes in signal detection theory and psychophysics and describes how these processes affect decision-making.
Abstract: Book on statistical decision theory and sensory processes in signal detection theory and psychophysics

11,820 citations


"Failure to deactivate in the prefro..." refers methods in this paper

  • ...The behavioural measure used was the signal detection theory index of sensitivity, dk (Green & Swets, 1966)....

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Journal ArticleDOI
TL;DR: A baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF is identified, suggesting the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
Abstract: A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

10,708 citations


"Failure to deactivate in the prefro..." refers background or result in this paper

  • ...This interpretation is supported by (a) the spatial correspondence between this area and that identified in studies of the default mode network (e.g. Gusnard et al. 2001 ; Raichle et al. 2001), and (b) the fact that the controls in our study showed deactivation in the same area while performing the n-back task....

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  • ...the inferior parietal cortex and parts of the temporal lobe including the hippocampus), these are thought to constitute a ‘default mode network’ that is active at rest or when engaging in ‘stimulus-independent’ thought, but which undergoes a reduction in activity when attentiondemanding goal-directed cognition needs to be undertaken (Gusnard et al. 2001 ; Raichle et al. 2001 ; Greicius et al. 2003 ; Gusnard, 2005)....

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  • ...…is supported by (a) the spatial correspondence between this area and that identified in studies of the default mode network (e.g. Gusnard et al. 2001 ; Raichle et al. 2001), and (b) the fact that the controls in our study showed deactivation in the same area while performing the n-back task....

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  • ...…a ‘default mode network’ that is active at rest or when engaging in ‘stimulus-independent’ thought, but which undergoes a reduction in activity when attentiondemanding goal-directed cognition needs to be undertaken (Gusnard et al. 2001 ; Raichle et al. 2001 ; Greicius et al. 2003 ; Gusnard, 2005)....

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Journal ArticleDOI
TL;DR: This study constitutes, to the knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network.
Abstract: Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.

6,025 citations


"Failure to deactivate in the prefro..." refers background in this paper

  • ...the inferior parietal cortex and parts of the temporal lobe including the hippocampus), these are thought to constitute a ‘default mode network’ that is active at rest or when engaging in ‘stimulus-independent’ thought, but which undergoes a reduction in activity when attentiondemanding goal-directed cognition needs to be undertaken (Gusnard et al. 2001 ; Raichle et al. 2001 ; Greicius et al. 2003 ; Gusnard, 2005)....

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  • ...…a ‘default mode network’ that is active at rest or when engaging in ‘stimulus-independent’ thought, but which undergoes a reduction in activity when attentiondemanding goal-directed cognition needs to be undertaken (Gusnard et al. 2001 ; Raichle et al. 2001 ; Greicius et al. 2003 ; Gusnard, 2005)....

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Journal ArticleDOI
TL;DR: This work explores the possibility that there might be a baseline or resting state of brain function involving a specific set of mental operations, including the manner in which a baseline is defined and the implications of such a baseline for the understanding ofbrain function.
Abstract: Functional brain imaging in humans has revealed task-specific increases in brain activity that are associated with various mental activities. In the same studies, mysterious, task-independent decreases have also frequently been encountered, especially when the tasks of interest have been compared with a passive state, such as simple fixation or eyes closed. These decreases have raised the possibility that there might be a baseline or resting state of brain function involving a specific set of mental operations. We explore this possibility, including the manner in which we might define a baseline and the implications of such a baseline for our understanding of brain function.

3,285 citations


"Failure to deactivate in the prefro..." refers background or result in this paper

  • ...Two studies, however, had opposite results to ours : Harrison et al. (2007) found that 12 schizophrenic patients showed greater deactivation of both the anterior and posterior cingulate midline loci than in 14 controls during a task requiring response suppression. Using an auditory oddball task, Garrity et al. (2007) found that 21 patients with schizophrenia showed a complex pattern of abnormality compared to 22 normal controls, but deactivation was increased in the anterior cingulate/ superior medial frontal gyri. The remaining two studies (Bluhm et al. 2007 ; Zhou et al. 2007) focused exclusively on connectivity, and cannot be directly compared with our findings. Of note, Kennedy et al. (2006) have also documented default mode network dysfunction in adult high-functioning autisticspectrum patients, although they found that the failure of deactivation affected both the anterior and posterior midline loci of the network....

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  • ...Gusnard et al. 2001 ; Raichle et al. 2001), and (b) the fact that the controls in our study showed deactivation in the same area while performing the n-back task. Menzies et al. (2007) also interpreted the failure to deactivate they found in schizophrenia in terms of default mode network dysfunction. However, as neither we nor Menzies et al. (2007) set out specifically to examine default mode network function in schizophrenia, such an interpretation should be regarded as provisional....

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  • ...Two studies, however, had opposite results to ours : Harrison et al. (2007) found that 12 schizophrenic patients showed greater deactivation of both the anterior and posterior cingulate midline loci than in 14 controls during a task requiring response suppression. Using an auditory oddball task, Garrity et al. (2007) found that 21 patients with schizophrenia showed a complex pattern of abnormality compared to 22 normal controls, but deactivation was increased in the anterior cingulate/ superior medial frontal gyri....

    [...]

  • ...the inferior parietal cortex and parts of the temporal lobe including the hippocampus), these are thought to constitute a ‘default mode network’ that is active at rest or when engaging in ‘stimulus-independent’ thought, but which undergoes a reduction in activity when attentiondemanding goal-directed cognition needs to be undertaken (Gusnard et al. 2001 ; Raichle et al. 2001 ; Greicius et al. 2003 ; Gusnard, 2005)....

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  • ...Gusnard et al. (2001) have also reviewed various lines of evidence that suggest that different parts of the default mode network are involved in gathering information about the world, orienting oneself to salient environmental stimuli, theory of mind and self-representation....

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How long can a schizophrenic go without sleep?

This represented a failure of deactivation in the schizophrenic patients.