Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging

Posterior midline and ventral parietal activity is associated with retrieval success and encoding failure

The ventral part of lateral posterior parietal cortex (VPC) and the posterior midline region (PMR), including the posterior cingulate cortex and precuneus, tend to show deactivation during demanding cognitive tasks, and have been associated with the default mode of the brain. Interestingly, PMR and VPC activity has been associated with successful episodic retrieval but also with unsuccessful episodic encoding. However, the differential contributions of PMR and VPC to retrieval vs. encoding has never been demonstrated within-subjects and within the same experiment. Here, we directly tested the prediction that PMR and VPC activity should be associated with retrieval success but with encoding failure. Consistent with this prediction, we found across five different fMRI experiments that, during retrieval, activity in these regions is greater for hits than misses, whereas during encoding, it is greater for subsequent misses than hits. We also found that these regions overlap with the ones that show deactivations during conscious rest. Our findings further aid in clarifying the role of the default mode regions in learning and memory.

Exploring predictors of outcome in the psychosis prodrome: implications for early identification and intervention

Functional disability is a key component of many psychiatric illnesses, particularly schizophrenia. Impairments in social and role functioning are linked to cognitive deficits, a core feature of psychosis. Retrospective analyses demonstrate that substantial functional decline precedes the onset of psychosis. Recent investigations reveal that individuals at clinical-high-risk (CHR) for psychosis show impairments in social relationships, work/school functioning and daily living skills. CHR youth also demonstrate a pattern of impairment across a range of cognitive domains, including social cognition, which is qualitatively similar to that of individuals with schizophrenia. While many studies have sought to elucidate predictors of clinical deterioration, specifically the development of schizophrenia, in such CHR samples, few have investigated factors relevant to psychosocial outcome. This review integrates recent findings regarding cognitive and social-cognitive predictors of outcome in CHR individuals, and proposes potential directions for future research that will contribute to targeted interventions and improved outcome for at-risk youth.

Acupuncture mobilizes the brain's default mode and its anti-correlated network in healthy subjects

Previous work has shown that acupuncture stimulation evokes deactivation of a limbic-paralimbic-neocortical network (LPNN) as well as activation of somatosensory brain regions. This study explores the activity and functional connectivity of these regions during acupuncture vs. tactile stimulation and vs. acupuncture associated with inadvertent sharp pain. Acupuncture during 201 scans and tactile stimulation during 74 scans for comparison at acupoints LI4, ST36 and LV3 was monitored with fMRI and psychophysical response in 48 healthy subjects. Clusters of deactivated regions in the medial prefrontal, medial parietal and medial temporal lobes as well as activated regions in the sensorimotor and a few paralimbic structures can be identified during acupuncture by general linear model analysis and seed-based cross correlation analysis. Importantly, these clusters showed virtual identity with the default mode network and the anti-correlated task-positive network in response to stimulation. In addition, the amygdala and hypothalamus, structures not routinely reported in the default mode literature, were frequently involved in acupuncture. When acupuncture induced sharp pain, the deactivation was attenuated or became activated instead. Tactile stimulation induced greater activation of the somatosensory regions but less extensive deactivation of the LPNN. These results indicate that the deactivation of the LPNN during acupuncture cannot be completely explained by the demand of attention that is commonly proposed in the default mode literature. Our results suggest that acupuncture mobilizes the anti-correlated functional networks of the brain to mediate its actions, and that the effect is dependent on the psychophysical response.

Functional magnetic resonance in psychiatry

Neuroimaging is a powerful tool for the study of the neurobiological changes in psychiatric disorders. Functional magnetic resonance imaging (MRI) is a noninvasive method that assesses cortical activation by measuring changes in the local concentration of deoxyhemoglobin, which is paramagnetic and therefore can be detected using MRI. This method has been referred to as blood oxygen level-dependent imaging. This article discusses the application of functional MRI techniques, with emphasis on blood oxygen level-dependent imaging, to the study of psychiatric diseases. The first part of the article provides an overview of the contribution of functional MRI research to the current understanding of mood disorders, schizophrenia, and substance abuse. The last part reviews recent advances and highlights future directions for the use of the functional MRI technique for psychiatric research.

Novel approaches to imaging epilepsy by MRI

As the concept of a network of injury has emerged in the treatment of epilepsy, the importance of evaluating that network noninvasively has also grown. Recently, studies utilizing magnetic resonance spectroscopic imaging, manganese-enhanced MRI and functional (f)MRI measures of resting state connectivity have demonstrated their ability to detect injury and dysfunction in cerebral networks involved in the propagation of seizures. The ability to noninvasively detect neuronal injury and dysfunction throughout cerebral networks should improve surgical planning, provide guidance for placement of devices that target network propagation and provide insights into the mechanisms of recurrence following resective surgery.

Neural substrates of letter fluency processing in young adults who were born very preterm: alterations in frontal and striatal regions

Several studies have described poorer performance in executive-type tasks in individuals who were born very preterm compared to controls. As there is evidence that high-order executive functions may be underpinned by neuronal activity in frontal-striatal circuits, we investigated with functional MRI a group of young adults who were born very preterm (n=28, gestational age <33 weeks) and controls (n=26) in order to detect possible alterations in brain activation during completion of a letter fluency task with differential cognitive loading ("easy" and "hard" letter trials). Structural MRI data were also collected to clarify whether any functional changes were associated with structural brain volume changes. Group membership, level of task difficulty and gestational age had significant effects on brain activation. In the absence of significant between-group differences in task performance, during "easy" letter trials, very preterm-born individuals showed attenuated activation in anterior cingulate gyrus, right caudate nucleus and left inferior frontal gyrus compared to controls. During "hard" letter trials, very preterm-born individuals showed both decreased and increased BOLD signal compared to controls, in left middle frontal and anterior cingulate gyrus, respectively. BOLD signal in caudate nucleus and anterior cingulate gyrus, in regions with peaks close to areas where between-group differences were observed, was linearly associated with gestational age. Analysis of structural MRI data showed altered grey matter distribution in the preterm-born group compared to controls. However, fMRI results were only partly explained by structural changes, and may reflect processes of functional plasticity for the successful completion of executive-type operations.

Functional connectivity of default mode network components: correlation, anticorrelation, and causality

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here, we examined functional differentiation within the DMN, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the DMN are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated.

Resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder and unipolar depression

This study for the first time investigated resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder (BD) and compared them with findings in healthy controls and unipolar major depressive disorder (MDD) patient groups. Resting state correlations of low frequency BOLD fluctuations (LFBF) in echoplanar functional magnetic resonance (fMRI) data were acquired from a priori defined regions of interests (ROIs) in the pregenual anterior cingulate cortex (pgACC), dorsomedial thalamus (DMTHAL), pallidostriatum (PST) and amygdala (AMYG), to investigate corticolimbic functional connectivity in unmedicated BD patients in comparison to healthy subjects and MDD patients. Data were acquired from 11 unmedicated BD patients [six manic (BDM) and five depressed (BDD)], and compared with data available from 15 unmedicated MDD and 15 healthy subjects. BD patients had significantly decreased pgACC connectivity to the left and right DMTHAL, similar to findings seen in MDD. Additionally, BD patients had decreased pgACC connectivity with the left and right AMYG as well as the left PST. An exploratory analysis revealed that both BDD and BDM patients had decreased connectivity between the pgACC and DMTHAL. The results of the study indicate a common finding of decreased corticolimbic functional connectivity in different types of mood disorders.

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.

Regional variation in interhemispheric coordination of intrinsic hemodynamic fluctuations

Electrophysiological studies have long demonstrated a high degree of correlated activity between the left and right hemispheres, however little is known about regional variation in this interhemispheric coordination. Whereas cognitive models and neuroanatomical evidence suggest differences in coordination across primary sensory-motor cortices versus higher-order association areas, these have not been characterized. Here, we used resting-state functional magnetic resonance imaging data acquired from 62 healthy volunteers to examine interregional correlation in spontaneous low-frequency hemodynamic fluctuations. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions comprising the entire cerebrum. We then examined regional variation in correlated activity between homotopic regions, contrasting primary sensory-motor cortices, unimodal association areas, and heteromodal association areas. Consistent with previous studies, robustly correlated spontaneous activity was noted between all homotopic regions, which was significantly higher than that between nonhomotopic (heterotopic and intrahemispheric) regions. We further demonstrated substantial regional variation in homotopic interhemispheric correlations that was highly consistent across subjects. Specifically, there was a gradient of interhemispheric correlation, with highest correlations across primary sensory-motor cortices (0.758, SD=0.152), significantly lower correlations across unimodal association areas (0.597, SD=0.230) and still lower correlations across heteromodal association areas (0.517, SD=0.226). These results demonstrate functional differences in interhemispheric coordination related to the brain's hierarchical subdivisions. Synchrony across primary cortices may reflect networks engaged in bilateral sensory integration and motor coordination, whereas lower coordination across heteromodal association areas is consistent with functional lateralization of these regions. This novel method of examining interhemispheric coordination may yield insights regarding diverse disease processes as well as healthy development.

Microstructural organization of the cingulum tract and the level of default mode functional connectivity

The default mode network is a functionally connected network of brain regions that show highly synchronized intrinsic neuronal activation during rest. However, less is known about the structural connections of this network, which could play an important role in the observed functional connectivity patterns. In this study, we examined the microstructural organization of the cingulum tract in relation to the level of resting-state default mode functional synchronization. Resting-state functional magnetic resonance imaging and diffusion tensor imaging data of 45 healthy subjects were acquired on a 3 tesla scanner. Both structural and functional connectivity of the default mode network were examined. In all subjects, the cingulum tract was identified from the total collection of reconstructed tracts to interconnect the precuneus/posterior cingulate cortex and medial frontal cortex, key regions of the default mode network. A significant positive correlation was found between the average fractional anisotropy value of the cingulum tract and the level of functional connectivity between the precuneus/posterior cingulate cortex and medial frontal cortex. Our results suggest a direct relationship between the structural and functional connectivity measures of the default mode network and contribute to the understanding of default mode network connectivity.

Functional connectivity MR imaging reveals cortical functional connectivity in the developing brain

BACKGROUND AND PURPOSE

Unlike conventional functional MR imaging where external sensory/cognitive paradigms are needed to specifically activate different regions of the brain, resting functional connectivity MR imaging acquires images in the absence of cognitive demands (a resting condition) and detects brain regions, which are highly temporally correlated. Therefore, resting functional MR imaging is highly suited for the study of brain functional development in pediatric subjects. This study aimed to determine the temporal and spatial patterns of rfc in healthy pediatric subjects between 2 weeks and 2 years of age.

MATERIALS AND METHODS

Rfc studies were performed on 85 children: 38 neonates (2-4 weeks of age), 26 one-year-olds, and 21 two-year-olds. All subjects were imaged while asleep; no sedation was used. Six regions of interest were chosen, including the primary motor, sensory, and visual cortices in each hemisphere. Mean signal intensity of each region of interest was used to perform correlation analysis pixel by pixel throughout the entire brain, identifying regions with high temporal correlation.

RESULTS

Functional connectivity was observed in all subjects in the sensorimotor and visual areas. The percent brain volume exhibiting rfc and the strength of rfc continued to increase from 2 weeks to 2 years. The growth trajectories of the percent brain volume of rfc appeared to differ between the sensorimotor and visual areas, whereas the z-score was similar. The percent brain volume of rfc in the sensorimotor area was significantly larger than that in the visual area for subjects 2 weeks of age (P = .008) and 1-year-olds (P = .017) but not for the 2-year-olds.

CONCLUSIONS

These findings suggest that rfc in the sensorimotor precedes that in the visual area from 2 weeks to 1 year but becomes comparable at 2 years. In contrast, the comparable z-score values between the sensorimotor and visual areas for all age groups suggest a disassociation between percent brain volume and the strength of cortical rfc.

Functional magnetic resonance imaging (fMRI) of attention processes in presumed obligate carriers of schizophrenia: preliminary findings

BACKGROUND

Presumed obligate carriers (POCs) are the first-degree relatives of people with schizophrenia who, although do not exhibit the disorder, are in direct lineage of it. Thus, this subpopulation of first-degree relatives could provide very important information with regard to the investigation of endophenotypes for schizophrenia that could clarify the often contradictory findings in schizophrenia high-risk populations. To date, despite the extant literature on schizophrenia endophenotypes, we are only aware of one other study that examined the neural mechanisms that underlie cognitive abnormalities in this group. The aim of this study was to investigate whether a more homogeneous group of relatives, such as POCs, have neural abnormalities that may be related to schizophrenia.

METHODS

We used functional magnetic resonance imaging (fMRI) to collect blood oxygenated level dependent (BOLD) response data in six POCs and eight unrelated healthy controls while performing under conditions of sustained, selective and divided attention.

RESULTS

The POCs indicated alterations in a widely distributed network of regions involved in attention processes, such as the prefrontal and temporal (including the parahippocampal gyrus) cortices, in addition to the anterior cingulate gyrus. More specifically, a general reduction in BOLD response was found in these areas compared to the healthy participants during attention processes.

CONCLUSION

These preliminary findings of decreased activity in POCs indicate that this more homogeneous population of unaffected relatives share similar neural abnormalities with people with schizophrenia, suggesting that reduced BOLD activity in the attention network may be an intermediate marker for schizophrenia.

Origin of synchronized low-frequency blood oxygen level-dependent fluctuations in the primary visual cortex

BACKGROUND AND PURPOSE

Low-frequency (<0.08 Hz) fluctuations in spontaneous blood oxygen level-dependent (BOLD) signal intensity show synchronization across anatomically interconnected and functionally specific brain regions, suggesting a neural origin of fluctuations. To determine the mechanism by which high-frequency neural activity results in low-frequency BOLD fluctuations, I obtained measurements of the effects of neurovascular coupling on the frequency content of BOLD fluctuations.

MATERIALS AND METHODS

3T recordings of BOLD signal intensity in the primary visual cortex were obtained in response to visual stimuli presented at varying temporal frequencies to determine which stimulus frequencies were successfully transmitted to BOLD signal intensity. Additional BOLD time series recordings were performed in a resting state and during natural visual stimulation, and frequencies comprising BOLD fluctuations were measured. Magnetoencephalographic (MEG) time series recordings were obtained in a resting state to measure which components of MEG signal intensity best correlated in frequency distribution to observed BOLD fluctuations.

RESULTS

Visually driven oscillations in BOLD signal intensity were observed up to 0.2 Hz, representing a mismatch between low-pass filter properties of neurovascular coupling and observed frequencies of spontaneous BOLD fluctuations, which are <0.05 Hz in the primary visual cortex. Visual stimulation frequencies of >0.2 Hz resulted in frequency-dependent increases in mean BOLD response. Amplitude modulation of high-frequency neural activity was measured in MEG time series data, which demonstrated 1/frequency distribution with the greatest power comprising frequencies <0.05 Hz, consistent with the distribution of observed BOLD fluctuations.

CONCLUSION

Synchronized low-frequency BOLD fluctuations likely arise from a combination of vascular low-pass filtering and low-frequency amplitude modulation of neural activity.

Resting-state functional connectivity in neuropsychiatric disorders

PURPOSE OF REVIEW

This review considers recent advances in the application of resting-state functional magnetic resonance imaging to the study of neuropsychiatric disorders.

RECENT FINDINGS

Resting-state functional magnetic resonance imaging is a relatively novel technique that has several potential advantages over task-activation functional magnetic resonance imaging in terms of its clinical applicability. A number of research groups have begun to investigate the use of resting-state functional magnetic resonance imaging in a variety of neuropsychiatric disorders including Alzheimer's disease, depression, and schizophrenia. Although preliminary results have been fairly consistent in some disorders (for example, Alzheimer's disease) they have been less reproducible in others (schizophrenia). Resting-state connectivity has been shown to correlate with behavioral performance and emotional measures. It's potential as a biomarker of disease and an early objective marker of treatment response is genuine but still to be realized.

SUMMARY

Resting-state functional magnetic resonance imaging has made some strides in the clinical realm but significant advances are required before it can be used in a meaningful way at the single-patient level.

Working memory in schizophrenia: an EEG study using power spectrum and coherence analysis to estimate cortical activation and network behavior

This study examined regional cortical activations and cortico-cortical connectivity in a group of 20 high-functioning patients with schizophrenia and 20 healthy controls matched for age and sex during a 0- and a 2-back working memory (WM) task. An earlier study comparing schizophrenia patients with education level-matched healthy controls revealed less "optimally" organized network during the 2-back task, whereas a second study with healthy volunteers had suggested that the degree of cortical organization may be inversely proportional to educational level (less optimal functional connectivity in better educated individuals interpreted as the result of higher efficiency). In the present study, both groups succeeded in the 2-back WM task although healthy individuals had generally attained a higher level of education. First absolute power spectrum of the different frequency bands corresponding to the electrodes of each lobe was calculated. Then the mean values of coherence were calculated as an index of the average synchronization to construct graphs in order to characterize local and large scale topological patterns of cortico-cortical connectivity. The power spectra analyses showed signs of hypofrontality in schizophrenics with an asymmetry. Additionally, differences between the groups with greater changes during WM in healthy individuals were visible in all lobes more on the left side. The graph parameter results indicated decreased small-world architecture i.e. less optimal cortico-cortical functional organization in patients as compared to controls. These findings are consistent with the notion of aberrant neural organization in schizophrenics which is nevertheless sufficient in supporting adequate task performance.

Resting in peace or noise: scanner background noise suppresses default-mode network

Studies have identified specific brain regions that increase activation during rest relative to attention-demanding tasks; these regions subserve the "default mode of brain function". Most of these studies have been conducted in the presence of scanner background noise (SBN). This noise has been shown to lead to altered attentional demands, and thus may modulate the default-mode network. Twelve subjects were examined during a rest condition that was contrasted with an auditory task. Words were presented either with SBN employing a conventional acquisition or without SBN using a sparse sampling approach. The number of experimental and resting trials was equated between the designs. Selecting the images in the condition with SBN that corresponded in time with the images in the condition without SBN made a direct comparison of the default-mode network (rest contrasted with active task) possible. There was typical activation of the default-mode network during rest versus task for both designs. However, SBN suppressed major components of the default-mode network, including medial prefrontal cortex, posterior cingulate, and precuneus. Our results suggest that the default mode of brain function differs when assessed in the presence compared to the absence of scanner noise, with the presence of scanner noise perhaps adding attentional demands that diminish activation changes between rest and task in a nonlinear way within the default network. Further studies are needed to clarify whether the use of a sparse sampling technique might enhance clinical utilities that have been proposed for analysis of the default-mode network.

Group independent component analysis reveals consistent resting-state networks across multiple sessions

Group independent component analysis (gICA) was performed on resting-state data from 14 healthy subjects scanned on 5 fMRI scan sessions across 16 days. The data were reduced and aggregated in 3 steps using Principal Components Analysis (PCA, within scan, within session and across session) and subjected to gICA procedures. The amount of reduction was estimated by an improved method that utilizes a first-order autoregressive fitting technique to the PCA spectrum. Analyses were performed using all sessions in order to maximize sensitivity and alleviate the problem of component identification across session. Across-session consistency was examined by three methods, all using back-reconstruction of the single-session or single-subject/session maps from the grand (5-session) maps. The gICA analysis produced 55 spatially independent maps. Obvious artifactual maps were eliminated and the remainder were grouped based upon physiological recognizability. Biologically relevant component maps were found, including sensory, motor and a 'default-mode' map. All analysis methods showed that components were remarkably consistent across session. Critically, the components with the most obvious physiological relevance were the most consistent. The consistency of these maps suggests that, at least over a period of several weeks, these networks would be useful to follow longitudinal treatment-related manipulations.

Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain

Functional magnetic resonance imaging techniques using the blood oxygenation level-dependent (BOLD) contrast are widely used to map human brain function by relating local hemodynamic responses to neuronal stimuli compared to control conditions. There is increasing interest in spontaneous cerebral BOLD fluctuations that are prominent in the low-frequency range (<0.1 Hz) and show intriguing spatio-temporal correlations in functional networks. The nature of these signal fluctuations remains unclear, but there is accumulating evidence for a neural basis opening exciting new avenues to study human brain function and its connectivity at rest. Moreover, an increasing number of patient studies report disease-dependent variation in the amplitude and spatial coherence of low-frequency BOLD fluctuations (LFBF) that may afford greater diagnostic sensitivity and easier clinical applicability than standard fMRI. The main disadvantage of this emerging tool relates to physiological (respiratory, cardiac and vasomotion) and motion confounds that are challenging to disentangle requiring thorough preprocessing. Technical aspects of functional connectivity fMRI analysis and the neuroscientific potential of spontaneous LFBF in the default mode and other resting-state networks have been recently reviewed. This review will give an update on the current knowledge of the nature of LFBF, their relation to physiological confounds and potential for clinical diagnostic and pharmacological studies.

Development of anterior cingulate functional connectivity from late childhood to early adulthood

Human cerebral development is remarkably protracted. Although microstructural processes of neuronal maturation remain accessible only to morphometric post-mortem studies, neuroimaging tools permit the examination of macrostructural aspects of brain development. The analysis of resting-state functional connectivity (FC) offers novel possibilities for the investigation of cerebral development. Using seed-based FC methods, we examined the development of 5 functionally distinct cingulate-based intrinsic connectivity networks (ICNs) in children (n = 14, 10.6 +/- 1.5 years), adolescents (n = 12, 15.4 +/- 1.2) and young adults (n=14, 22.4 +/- 1.2). Children demonstrated a more diffuse pattern of correlation with voxels proximal to the seed region of interest (ROI) ("local FC"), whereas adults exhibited more focal patterns of FC, as well as a greater number of significantly correlated voxels at long distances from the seed ROI. Adolescents exhibited intermediate patterns of FC. Consistent with evidence for different maturational time courses, ICNs associated with social and emotional functions exhibited the greatest developmental effects. Our findings demonstrate the utility of FC for the study of developing functional organization. Moreover, given that ICNs are thought to have an anatomical basis in neuronal connectivity, measures of FC may provide a quantitative index of brain maturation in healthy subjects and those with neurodevelopmental disorders.

Altered functional connectivity of primary visual cortex in early blindness

In early blindness, the primary visual area (PVA) loses the ability to process visual information, and shifts to working on the processing of somatosensory input, auditory input, and some higher-level cognitive functions. It has not yet been investigated whether such functional changes can lead to alterations of the functional connectivity between the PVA and other brain areas in resting state. The purpose of this study is to investigate the differences in the functional connectivity of the PVA between early blind and sighted subjects using resting functional MRI data. The altered functional connectivity was identified by comparing the correlation coefficients of the PVA with other brain areas between 16 early blind subjects (blindness onset within 1 year of age) and 32 gender- and age-matched healthy sighted volunteers. Compared with the sighted, the early blind subjects showed decreased functional connectivity between the left PVA and the bilateral supplementary motor area (SMA), pre- and postcentral gyri, superior parietal lobule, and the left superior and middle temporal gyri. Early blind subjects also showed decreased functional connectivity between the right PVA and the bilateral SMA, pre- and postcentral gyri. Our findings suggest that early deprivation of a single sensory modality induces alterations of functional connectivity between the deprived functional area and other associated brain areas.

Network analysis of intrinsic functional brain connectivity in Alzheimer's disease

Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.

Alzheimer's disease (AD) is a brain disorder characterized by progressive impairment of episodic memory and other cognitive domains resulting in dementia and, ultimately, death. Functional neuroimaging studies have identified brain regions that show abnormal brain function in AD. Although there is converging evidence about the identity of these regions, it is not clear how this abnormality affects the functional organization of the whole brain. In order to characterize the functional organization of the brain, our approach uses small-world measures, which have also been used to study systems such as social networks and the internet. We use graph analytical methods to compute these measures of functional connectivity brain networks, which are derived from fMRI data obtained from healthy elderly controls and AD patients. The AD patients had significantly lower regional connectivity, and showed disrupted global functional organization, when compared to healthy controls. Moreover, our results indicate that cognitive decline in Alzheimer's disease patients is associated with disrupted functional connectivity in the entire brain. Our findings further suggest that small-world measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.

Normalized cut group clustering of resting-state FMRI data

Background

Functional brain imaging studies have indicated that distinct anatomical brain regions can show coherent spontaneous neuronal activity during rest. Regions that show such correlated behavior are said to form resting-state networks (RSNs). RSNs have been investigated using seed-dependent functional connectivity maps and by using a number of model-free methods. However, examining RSNs across a group of subjects is still a complex task and often involves human input in selecting meaningful networks.

Methodology/Principal Findings

We report on a voxel based model-free normalized cut graph clustering approach with whole brain coverage for group analysis of resting-state data, in which the number of RSNs is computed as an optimal clustering fit of the data. Inter-voxel correlations of time-series are grouped at the individual level and the consistency of the resulting networks across subjects is clustered at the group level, defining the group RSNs. We scanned a group of 26 subjects at rest with a fast BOLD sensitive fMRI scanning protocol on a 3 Tesla MR scanner.

Conclusions/Significance

An optimal group clustering fit revealed 7 RSNs. The 7 RSNs included motor/visual, auditory and attention networks and the frequently reported default mode network. The found RSNs showed large overlap with recently reported resting-state results and support the idea of the formation of spatially distinct RSNs during rest in the human brain.

The "sense of agency" and its underlying cognitive and neural mechanisms

The sense of agency is a central aspect of human self-consciousness and refers to the experience of oneself as the agent of one's own actions. Several different cognitive theories on the sense of agency have been proposed implying divergent empirical approaches and results, especially with respect to neural correlates. A multifactorial and multilevel model of the sense of agency may provide the most constructive framework for integrating divergent theories and findings, meeting the complex nature of this intriguing phenomenon.

What happens after the first episode? A review of progressive brain changes in chronically ill patients with schizophrenia

Numerous imaging studies have revealed structural brain changes in schizophrenia. Decreases in brain tissue are accompanied by increases in ventricle volumes and cerebrospinal fluid. Whether or not these brain changes are progressive beyond the first episode is subject to debate. To assess if progressive brain changes occur in chronically ill patients, 11 longitudinal magnetic resonance imaging and computed tomography studies were reviewed. Patients were ill for on average 10 years at their initial scan. Follow-up intervals varied between 1 and 10 years. Overall, the findings suggest continuous progressive brain tissue decreases and lateral ventricle volume increases in chronically ill patients, up to at least 20 years after their first symptoms. The extent of progressive brain tissue decrease in patients (-0.5% per year) is twice that of healthy controls (-0.2% per year). These findings are consistent with the extent of postmortem brain tissue loss in schizophrenia. Progressive volume loss seems most pronounced in the frontal and temporal (gray matter) areas. Progressive lateral ventricle volume increases are also found. More pronounced progressive brain changes in patients is associated with poor outcome, more negative symptoms, and a decline in neuropsychological performance in one or some of the studies, but not consistently so. Higher daily cumulative dose of antipsychotic medication intake is either not associated with brain volume changes or with less prominent brain volume changes. The progressive brain changes present in chronic schizophrenia may represent a continuous pathophysiological process taking place in the brains of these patients that warrants further study.

Altered resting-state functional connectivity and anatomical connectivity of hippocampus in schizophrenia

Hippocampus has been implicated in participating in the pathophysiology of schizophrenia. However, the functional and anatomical connectivities between hippocampus and other regions are rarely concurrently investigated in schizophrenia. In the present study, both functional magnetic resonance imaging (fMRI) during rest and diffusion tensor imaging (DTI) were performed on 17 patients with paranoid schizophrenia and 14 healthy subjects. Resting-state functional connectivities of the bilateral hippocampi were separately analyzed by selecting the anterior hippocampus as region of interest. The fornix body was reconstructed by diffusion tensor tractography, and the integrity of this tract was evaluated using fractional anisotropy (FA). In patients with schizophrenia, the bilateral hippocampi showed reduced functional connectivities to some regions which have been reported to be involved in episodic memory, such as posterior cingulate cortex, extrastriate cortex, medial prefrontal cortex, and parahippocampus gyrus. We speculated that these reduced connectivity may reflect the disconnectivity within a neural network related to the anterior hippocampus in schizophrenia. Meanwhile the mean FA of the fornix body was significantly reduced in patients, indicating the damage in the hippocampal anatomical connectivity in schizophrenia. The concurrence of the functional disconnectivity and damaged anatomical connectivity between the hippocampus and other regions in schizophrenia suggest that the functional-anatomical relationship need to be further investigated.

Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics

Chronic pain patients suffer from more than just pain; depression and anxiety, sleep disturbances, and decision-making abnormalities (Apkarian et al., 2004a) also significantly diminish their quality of life. Recent studies have demonstrated that chronic pain harms cortical areas unrelated to pain (Apkarian et al., 2004b; Acerra and Moseley, 2005), but whether these structural impairments and behavioral deficits are connected by a single mechanism is as of yet unknown. Here we propose that long-term pain alters the functional connectivity of cortical regions known to be active at rest, i.e., the components of the "default mode network" (DMN). This DMN (Raichle et al., 2001; Greicius et al., 2003; Vincent et al., 2007) is marked by balanced positive and negative correlations between activity in component brain regions. In several disorders, however this balance is disrupted (Fox and Raichle, 2007). Using well validated functional magnetic resonance imaging (fMRI) paradigms to study the DMN (Fox et al., 2005), we investigated whether the impairments of chronic pain patients could be rooted in disturbed DMN dynamics. Studying with fMRI a group of chronic back pain (CBP) patients and healthy controls while executing a simple visual attention task, we discovered that CBP patients, despite performing the task equally well as controls, displayed reduced deactivation in several key DMN regions. These findings demonstrate that chronic pain has a widespread impact on overall brain function, and suggest that disruptions of the DMN may underlie the cognitive and behavioral impairments accompanying chronic pain.

Disruption of large-scale brain systems in advanced aging

Cognitive decline is commonly observed in advanced aging even in the absence of disease. Here we explore the possibility that normal aging is accompanied by disruptive alterations in the coordination of large-scale brain systems that support high-level cognition. In 93 adults aged 18 to 93, we demonstrate that aging is characterized by marked reductions in normally present functional correlations within two higher-order brain systems. Anterior to posterior components within the default network were most severely disrupted with age. Furthermore, correlation reductions were severe in older adults free from Alzheimer's disease (AD) pathology as determined by amyloid imaging, suggesting that functional disruptions were not the result of AD. Instead, reduced correlations were associated with disruptions in white matter integrity and poor cognitive performance across a range of domains. These results suggest that cognitive decline in normal aging arises from functional disruption in the coordination of large-scale brain systems that support cognition.

Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder

BACKGROUND

Pathophysiologic models of attention-deficit/hyperactivity disorder (ADHD) have focused on frontal-striatal circuitry with alternative hypotheses relatively unexplored. On the basis of evidence that negative interactions between frontal foci involved in cognitive control and the non-goal-directed "default-mode" network prevent attentional lapses, we hypothesized abnormalities in functional connectivity of these circuits in ADHD.

METHODS

Resting-state blood oxygen level-dependent functional magnetic resonance imaging (fMRI) scans were obtained at 3.0-Tesla in 20 adults with ADHD and 20 age- and sex-matched healthy volunteers.

RESULTS

Examination of healthy control subjects verified presence of an antiphasic or negative relationship between activity in dorsal anterior cingulate cortex (centered at x = 8, y = 7, z = 38) and in default-mode network components. Group analyses revealed ADHD-related compromises in this relationship, with decreases in the functional connectivity between the anterior cingulate and precuneus/posterior cingulate cortex regions (p < .0004, corrected). Secondary analyses revealed an extensive pattern of ADHD-related decreases in connectivity between precuneus and other default-mode network components, including ventromedial prefrontal cortex (p < 3 x 10(-11), corrected) and portions of posterior cingulate (p < .02, corrected).

CONCLUSIONS

Together with prior unbiased anatomic evidence of posterior volumetric abnormalities, our findings suggest that the long-range connections linking dorsal anterior cingulate to posterior cingulate and precuneus should be considered as a candidate locus of dysfunction in ADHD.

Regional homogeneity and anatomical parcellation for fMRI image classification: application to schizophrenia and normal controls

This paper presents a discriminative model of multivariate pattern classification, based on functional magnetic resonance imaging (fMRI) and anatomical template. As a measure of brain function, Regional homogeneity (ReHo) is calculated voxel by voxel, and then a widely used anatomical template is applied on ReHo map to parcelate it into 116 brain regions. The mean and standard deviation of ReHo values in each region are extracted as features. Pseudo-Fisher Linear Discriminant Analysis (PFLDA) is performed for training samples to generate discriminative model. Classification experiments have been carried out in 48 schizophrenia patients and 35 normal controls. Under a full leave-one-out (LOO) cross-validation, correct prediction rate of 80% is achieved. Anatomical parcellation process is proved useful to improve classification rate by a control experiment. The discriminative model shows its ability to reveal abnormal brain functional activities and identify people with schizophrenia.

Functional disintegration in paranoid schizophrenia using resting-state fMRI

Functional disintegration has been observed in schizophrenia during task performance. We sought to investigate functional disintegration during rest because an intrinsic functional brain organization, including both "task-negative" (i.e., "default mode") and "task-positive" networks, has been suggested to play an important role in integrating ongoing information processing. Additionally, the brain regions that are involved in the intrinsic organization are believed to be abnormal in schizophrenia. Patients with paranoid schizophrenia (N=18) and healthy volunteers (N=18) underwent a resting-state fMRI scan. Functional connectivity analysis was used to identify the connectivity between each pair of brain regions within this intrinsic organization, and differences were examined in patients versus healthy volunteers. Compared to healthy volunteers, patients showed significant differences in connectivity within networks and between networks, most notably in the connectivities associated with the bilateral dorsal medial prefrontal cortex, the lateral parietal region, the inferior temporal gyrus of the "task-negative" network and with the right dorsolateral prefrontal cortex and the right dorsal premotor cortex of the "task-positive" network. These results suggested that the interregional functional connectivities in the intrinsic organization are altered in patients with paranoid schizophrenia. These abnormalities could be the source of abnormalities in the coordination of and competition between information processing activities in the resting brain of paranoid patients.

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.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging

The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.

Competition between functional brain networks mediates behavioral variability

Increased intraindividual variability (IIV) is a hallmark of disorders of attention. Recent work has linked these disorders to abnormalities in a "default mode" network, comprising brain regions routinely deactivated during goal-directed cognitive tasks. Findings from a study of the neural basis of attentional lapses suggest that a competitive relationship between the "task-negative" default mode network and regions of a "task-positive" attentional network is a potential locus of dysfunction in individuals with increased IIV. Resting state studies have shown that this competitive relationship is intrinsically represented in the brain, in the form of a negative correlation or antiphase relationship between spontaneous activity occurring in the two networks. We quantified the negative correlation between these two networks in 26 subjects, during active (Eriksen flanker task) and resting state scans. We hypothesized that the strength of the negative correlation is an index of the degree of regulation of activity in the default mode and task-positive networks and would be positively related to consistent behavioral performance. We found that the strength of the correlation between the two networks varies across individuals. These individual differences appear to be behaviorally relevant, as interindividual variation in the strength of the correlation was significantly related to individual differences in response time variability: the stronger the negative correlation (i.e., the closer to 180 degrees antiphase), the less variable the behavioral performance. This relationship was moderately consistent across resting and task conditions, suggesting that the measure indexes moderately stable individual differences in the integrity of functional brain networks. We discuss the implications of these findings for our understanding of the behavioral significance of spontaneous brain activity, in both healthy and clinical populations.

On the centrality and significance of stimulus-encoding deficit in schizophrenia

Increased latency of stimulus encoding is presented as a central deficit in schizophrenia cognition. Encoding, here, entails the internal representation of presenting stimuli in a format facilitating their implementation in other cognitive processes, such as those taking place in working memory. Historical roots of suspected encoding debility in schizophrenia briefly are reviewed, and its singular empirical robustness is described. More recently, this deficit has been subjected to stochastic mathematical modeling, resulting in its decomposition into discrete cognitive functions. A nonmathematical exposition of this account is provided, and substantial behavioral study support is illustrated. Implications for clinical assessment of individuals and of treatment regimens, with respect to encoding-related cognitive efficiency, are noted. Finally, because stochastic dynamic trajectories of process duration are modeled, times of measurement interest, complementing neuroanatomical regions of interest, become available for enhanced temporal navigation of event-related fMRI. Results from recent implementations of such process-defined events are described.

Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: anomalies in the default network

Spontaneous low-frequency fluctuations in the blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (MRI) signal have been shown to reflect neural synchrony between brain regions. A "default network" of spontaneous low-frequency fluctuations has been described in healthy volunteers during stimulus-independent thought. Negatively correlated with this network are regions activated during attention-demanding tasks. Both these networks involve brain regions and functions that have been linked with schizophrenia in previous research. The present study examined spontaneous slow fluctuations in the BOLD signal at rest, as measured by correlation with low-frequency oscillations in the posterior cingulate, in 17 schizophrenic patients, and 17 comparable healthy volunteers. Healthy volunteers demonstrated correlation between spontaneous low-frequency fluctuations of the BOLD signal in the posterior cingulate and fluctuations in the lateral parietal, medial prefrontal, and cerebellar regions, similar to previous reports. Schizophrenic patients had significantly less correlation between spontaneous slow activity in the posterior cingulate and that in the lateral parietal, medial prefrontal, and cerebellar regions. Connectivity of the posterior cingulate was found to vary with both positive and negative symptoms in schizophrenic patients. Because these data suggest significant abnormalities in resting-state neural networks in schizophrenia, further investigations of spontaneous slow fluctuations of the BOLD signal seem warranted in this population.

Are anticorrelated networks in the brain relevant to schizophrenia?

Most models of schizophrenia are based on basal ganglia-thalamocortical (BGTC) neuronal circuits or brain structures that project to them. Two new neuronal networks have been described which include many of the brain regions associated with BGTC neuronal circuits. These networks have been characterized with a new brain-imaging technique based on low-frequency fluctuations of the blood oxygen level-dependent (BOLD) signal. The new network associated with attention-demanding tasks is referred to as the task-related network and the network associated with stimulus-independent thought during the resting state is referred to as the default network. The 2 networks have been proposed to be negatively correlated or anticorrelated. This article critically reviews the rationale for these anticorrelated networks, the technique with which they are characterized, and preliminary findings in schizophrenia and other neuropsychiatric disorders. Regions associated with the default network overlap with regions important in motivation and are activated by memory retrieval, auditory hallucinations, and ketamine. Task-related networks are necessary for performance of neurocognitive tasks on which schizophrenic patients often perform poorly. It is concluded that anticorrelated networks can be viewed as complementary ways of understanding self-monitoring and task performance which extend present models of schizophrenia based on BGTC circuits. However, there are some limitations with regard the present understanding of brain structures involved in self-monitoring and the lack of asymmetry in the network which may mediate stimulus-independent thought. Further investigations of the default network assessed by low-frequency fluctuations in the BOLD signal seem warranted.

Cortical gamma generators suggest abnormal auditory circuitry in early-onset psychosis

Neurobiological theories of schizophrenia and related psychoses have increasingly emphasized impaired neuronal coordination (i.e., dysfunctional connectivity) as central to the pathophysiology. Although neuroimaging evidence has mostly corroborated these accounts, the basic mechanism(s) of reduced functional connectivity remains elusive. In this study, we examine the developmental trajectory and underlying mechanism(s) of dysfunctional connectivity by using gamma oscillatory power as an index of local and long-range circuit integrity. An early-onset psychosis group and a matched cohort of typically developing adolescents listened to monaurally presented click-trains, as whole-head magnetoencephalography data were acquired. Consistent with previous work, gamma-band power was significantly higher in right auditory cortices across groups and conditions. However, patients exhibited significantly reduced overall gamma power relative to controls, and showed a reduced ear-of-stimulation effect indicating that ipsi- versus contralateral presentation had less impact on hemispheric power. Gamma-frequency oscillations are thought to be dependent on gamma-aminobutyric acidergic interneuronal networks, thus these patients' impairment in generating and/or maintaining such activity may indicate that local circuit integrity is at least partially compromised early in the disease process. In addition, patients also showed abnormality in long-range networks (i.e., ear-of-stimulation effects) potentially suggesting that multiple stages along auditory pathways contribute to connectivity aberrations found in patients with psychosis.

Assessing functional connectivity in the human brain by fMRI

Functional magnetic resonance imaging (fMRI) is widely used to detect and delineate regions of the brain that change their level of activation in response to specific stimuli and tasks. Simple activation maps depict only the average level of engagement of different regions within distributed systems. FMRI potentially can reveal additional information about the degree to which components of large-scale neural systems are functionally coupled together to achieve specific tasks. In order to better understand how brain regions contribute to functionally connected circuits, it is necessary to record activation maps either as a function of different conditions, at different times or in different subjects. Data obtained under different conditions may then be analyzed by a variety of techniques to infer correlations and couplings between nodes in networks. Several multivariate statistical methods have been adapted and applied to analyze variations within such data. An approach of particular interest that is suited to studies of connectivity within single subjects makes use of acquisitions of runs of MRI images obtained while the brain is in a so-called steady state, either at rest (i.e., without any specific stimulus or task) or in a condition of continuous activation. Interregional correlations between fluctuations of MRI signal potentially reveal functional connectivity. Recent studies have established that interregional correlations between different components of circuits in each of the visual, language, motor and working memory systems can be detected in the resting state. Correlations at baseline are changed during the performance of a continuous task. In this review, various methods available for assessing connectivity are described and evaluated.

Functional dysconnectivity of the dorsolateral prefrontal cortex in first-episode schizophrenia using resting-state fMRI

The known regional abnormality of the dorsolateral prefrontal cortex (DLPFC) and its role in various neural circuits in schizophrenia has given prominence to its importance in studies on the dysconnection associated with schizophrenia. Abnormal functional connectivities of the DLPFC have been found during various goal-directed tasks; however, the occurrence of the abnormality during rest in patients with schizophrenia has rarely been reported. In the present study, we selected bilateral Brodmann's area 46 as region of interest and analyzed the differences in the DLPFC functional connectivity pattern between 17 patients with first-episode schizophrenia (FES) and 17 matched controls using resting-state fMRI. We found that the bilateral DLPFC showed reduced functional connectivities to the parietal lobe, posterior cingulate cortex, thalamus and striatum in FES patients. We also found enhanced functional connectivity between the left DLPFC and the left mid-posterior temporal lobe and the paralimbic regions in FES patients. Our results suggest that functional dysconnectivity associated with the DLPFC exists in schizophrenia during rest. This may be partially related to disturbance in the intrinsic brain activity.

Alterations of fronto-temporal connectivity during word encoding in schizophrenia

Cognitive deficits, including impaired verbal memory, are prominent in schizophrenia and lead to increased disability. Functional neuroimaging of patients with schizophrenia performing memory tasks has revealed abnormal activation patterns in prefrontal cortex and temporo-limbic regions. Aberrant fronto-temporal interactions thus represent a potential pathophysiological mechanism underlying verbal memory deficits, yet this hypothesis of disturbed connectivity is not tested directly with standard activation studies. We performed within-subject correlations of frontal and temporal timeseries to measure functional connectivity during verbal encoding. Our results confirm earlier findings of aberrant fronto-temporal connectivity in schizophrenia, and extend them by identifying distinct alterations within dorsal and ventral prefrontal cortex. Relative to healthy controls, patients with schizophrenia had reduced connectivity between the dorsolateral prefrontal cortex (DLPFC) and temporal lobe areas including parahippocampus and superior temporal gyrus. In contrast, patients showed increased connectivity between a region of ventrolateral prefrontal cortex (VLPFC) and these same temporal lobe regions. Higher temporal-DLPFC connectivity during encoding was associated with better subsequent recognition accuracy in controls, but not patients. Temporal-VLPFC connectivity was uncorrelated with recognition accuracy in either group. The results suggest that reduced temporal-DLPFC connectivity in schizophrenia could underlie encoding deficits, and increased temporal-VLPFC connectivity may represent an ineffective compensatory effort.

Structural and functional magnetic resonance imaging in psychiatric disorders

OBJECTIVE

To report on recent advances in both structural and functional brain imaging studies in psychiatry and to highlight their importance for the field.

METHOD

We reviewed recently published articles dealing with such advances and abstracted them into a selective review of the field.

RESULTS

Some of the more important trends include integration of genetic information into research studies, use of novel quantitative image measurement techniques, studies of new subject populations, the use of pharmacologic probes in functional magnetic resonance imaging (fMRI) studies, the incorporation of elements of virtual reality into fMRI task stimuli, and the methodological innovation of hyperscanning.

CONCLUSIONS

A whole series of new approaches and techniques are resulting in rapid advances in neuroimaging in psychiatry. Several of these show the potential for clinical translation.

In vivo mapping of functional connectivity in neurotransmitter systems using pharmacological MRI

Pharmacological MRI (phMRI) methods map the hemodynamic response to drug challenge as a surrogate for changes in neuronal activity. However, the central effects of drugs can be complex and include activity at the primary site of action, downstream effects in other brain regions and direct effects on vasculature and neurovascular coupling. Univariate analysis, normally applied to phMRI data, does not discriminate between these effects, and can result in anatomically non-specific activation patterns. We analysed inter-subject correlations in the amplitude of the slow phMRI response to map functionally connected brain regions recruited in response to pharmacological challenge. Application of D-amphetamine and fluoxetine revealed well-defined functional structure underlying the widespread signal changes detected via standard methods. Correlated responses were found to delineate key neurotransmitter pathways selectively targeted by these drugs, corroborating a tight correspondence between the phMRI response and changes in neurotransmitter systems specific to the pharmacological action. In vivo mapping of correlated responses in this way greatly extends the range of information available from phMRI studies and provides a new window into the function of neurotransmitter systems in the active state. This approach may provide new important insights regarding the central systems underlying pharmacological action.

Conceptual issues in psychiatric neuroimaging

PURPOSE OF REVIEW

Psychiatric neuroimaging has made a dramatic impact on the understanding of the brain in mental illness in a relatively brief period of time and continues to be evolving in terms of methodology, analysis and utilization of the combination of techniques. Given the level of sophistication of the techniques and the importance of imaging in current academic psychiatry, it is timely to review its conceptual influence on psychopathology.

RECENT FINDINGS

The study will review scientific advances in psychiatric neuromaging, around the themes of functional connectivity, diffusion tensor imaging, magnetoencephalography, modality integration, meta-analyses and mega-analyses of data and discuss recent influential findings in contemporary research. We then focus on more conceptual issues relating to biological psychiatry and its relationship with cognitive neuroscience. We discuss the dominant paradigm of scientific psychopathology, namely cognitive neuropsychiatry and how it relates more broadly to imaging and cognitive science and elaborate on the philosophical positions of the paradigm and how it views abnormal mental states.

SUMMARY

We conclude that despite the advances in biological psychiatry and the power of the cognitive neuropsychiatry paradigm, its findings are logically contingent upon psychopathology and the normatively defined terms employed therein.