Dissociable brain correlates for depression, anxiety, dissociation, and somatization in depersonalization-derealization disorder.

OBJECTIVE: The cerebral mechanisms of traits associated with depersonalization-derealization disorder (DPRD) remain poorly understood. METHOD: Happy and sad emotion expressions were presented to DPRD and non-referred control (NC) subjects in an implicit event-related functional magnetic resonance imaging (fMRI) design, and correlated with self report scales reflecting typical co-morbidities of DPRD: depression, dissociation, anxiety, somatization. RESULTS: Significant differences between the slopes of the two groups were observed for somatization in the right temporal operculum (happy) and ventral striatum, bilaterally (sad). Discriminative regions for symptoms of depression were the right pulvinar (happy) and left amygdala (sad). For dissociation, discriminative regions were the left mesial inferior temporal gyrus (happy) and left supramarginal gyrus (sad). For state anxiety, discriminative regions were the left inferior frontal gyrus (happy) and parahippocampal gyrus (sad). For trait anxiety, discriminative regions were the right caudate head (happy) and left superior temporal gyrus (sad). Discussion The ascertained brain regions are in line with previous findings for the respective traits. The findings suggest separate brain systems for each trait. CONCLUSION: Our results do not justify any bias for a certain nosological category in DPRD.

Shared and drug-specific effects of atomoxetine and methylphenidate on inhibitory brain dysfunction in medication-naive ADHD boys.

The stimulant methylphenidate (MPX) and the nonstimulant atomoxetine (ATX) are the most commonly prescribed medications for attention deficit hyperactivity disorder (ADHD). However, no functional magnetic resonance imaging (fMRI) study has as yet investigated the effects of ATX on inhibitory or any other brain function in ADHD patients or compared its effects with those of MPX. A randomized, double-blind, placebo-controlled, crossover pharmacological design was used to compare the neurofunctional effects of single doses of MPX, ATX, and placebo during a stop task, combined with fMRI within 19 medication-naive ADHD boys, and their potential normalization effects relative to 29 age-matched healthy boys. Compared with controls, ADHD boys under placebo showed bilateral ventrolateral prefrontal, middle temporal, and cerebellar underactivation. Within patients, MPX relative to ATX and placebo significantly upregulated right ventrolateral prefrontal activation, which correlated with enhanced inhibitory capacity. Relative to controls, both drugs significantly normalized the left ventrolateral prefrontal underactivation observed under placebo, while MPX had a drug-specific effect of normalizing right ventrolateral prefrontal and cerebellar underactivation observed under both placebo and ATX. The findings show shared and drug-specific effects of MPX and ATX on performance and brain activation during inhibitory control in ADHD patients with superior upregulation and normalization effects of MPX.

Pattern classification of response inhibition in ADHD: toward the development of neurobiological markers for ADHD.

The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) is based on subjective measures despite evidence for multisystemic structural and functional deficits. ADHD patients have consistent neurofunctional deficits in motor response inhibition. The aim of this study was to apply pattern classification to task-based functional magnetic resonance imaging (fMRI) of inhibition, to accurately predict the diagnostic status of ADHD. Thirty adolescent ADHD and thirty age-matched healthy boys underwent fMRI while performing a Stop task. fMRI data were analyzed with Gaussian process classifiers (GPC), a machine learning approach, to predict individual ADHD diagnosis based on task-based activation patterns. Traditional univariate case-control analyses were also performed to replicate previous findings in a relatively large dataset. The pattern of brain activation correctly classified up to 90% of patients and 63% of controls, achieving an overall classification accuracy of 77%. The regions of the discriminative network most predictive of controls included later developing lateral prefrontal, striatal, and temporo-parietal areas that mediate inhibition, while regions most predictive of ADHD were in earlier developing ventromedial fronto-limbic regions, which furthermore correlated with symptom severity. Univariate analysis showed reduced activation in ADHD in bilateral ventrolateral prefrontal, striatal, and temporo-parietal regions that overlapped with areas predictive of controls, suggesting the latter are dysfunctional areas in ADHD. We show that significant individual classification of ADHD patients of 77% can be achieved using whole brain pattern analysis of task-based fMRI inhibition data, suggesting that multivariate pattern recognition analyses of inhibition networks can provide objective diagnostic neuroimaging biomarkers of ADHD.

Group analysis of self-organizing maps based on functional MRI using restricted Frechet means.

Studies of functional MRI data are increasingly concerned with the estimation of differences in spatio-temporal networks across groups of subjects or experimental conditions. Unsupervised clustering and independent component analysis (ICA) have been used to identify such spatio-temporal networks. While these approaches have been useful for estimating these networks at the subject-level, comparisons over groups or experimental conditions require further methodological development. In this paper, we tackle this problem by showing how self-organizing maps (SOMs) can be compared within a Frechean inferential framework. Here, we summarize the mean SOM in each group as a Frechet mean with respect to a metric on the space of SOMs. The advantage of this approach is twofold. Firstly, it allows the visualization of the mean SOM in each experimental condition. Secondly, this Frechean approach permits one to draw inference on group differences, using permutation of the group labels. We consider the use of different distance functions, and introduce one extension of the classical sum of minimum distance (SMD) between two SOMs, which take into account the spatial pattern of the fMRI data. The validity of these methods is illustrated on synthetic data. Through these simulations, we show that the two distance functions of interest behave as expected, in the sense that the ones capturing temporal and spatial aspects of the SOMs are more likely to reach significance under simulated scenarios characterized by temporal, spatial [and spatio-temporal] differences, respectively. In addition, a re-analysis of a classical experiment on visually-triggered emotions demonstrates the usefulness of this methodology. In this study, the multivariate functional patterns typical of the subjects exposed to pleasant and unpleasant stimuli are found to be more similar than the ones of the subjects exposed to emotionally neutral stimuli. In this re-analysis, the group-level SOM output units with the smallest sample Jaccard indices were compared with standard GLM group-specific z-score maps, and provided considerable levels of agreement. Taken together, these results indicate that our proposed methods can cast new light on existing data by adopting a global analytical perspective on functional MRI paradigms.

Sex differences in brain response to anticipated and experienced visceral pain in healthy subjects.

Women demonstrate higher pain sensitivity and prevalence of chronic visceral pain conditions such as functional gastrointestinal disorders than men. The role of sex differences in the brain processing of visceral pain is still unclear. In 16 male and 16 female healthy subjects we compared personality, anxiety levels, skin conductance response (SCR), and brain processing using functional MRI during anticipation and pain induced by esophageal distension at pain toleration level. There was no significant difference in personality scores, anxiety levels, SCR, and subjective ratings of pain between sexes. In group analysis, both men and women demonstrated a similar pattern of brain activation and deactivation during anticipation and pain consistent with previous reports. However, during anticipation women showed significantly greater activation in the cuneus, precuneus, and supplementary motor area (SMA) and stronger deactivation in the right amygdala and left parahippocampal gyrus, whereas men demonstrated greater activation in the cerebellum. During pain, women demonstrated greater activation in the midcingulate cortex, anterior insula, premotor cortex, and cerebellum and stronger deactivation in the caudate, whereas men showed increased activity in the SMA. The pattern of brain activity suggests that, during anticipation, women may demonstrate stronger limbic inhibition, which is considered to be a cognitive modulation strategy for impending painful stimulation. During pain, women significantly activate brain areas associated with the affective and motivation components of pain. These responses may underlie the sex differences that exist in pain conditions, whereby women may attribute more emotional importance to painful stimuli compared with men.

A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy.

Pattern recognition approaches to the analysis of neuroimaging data have brought new applications such as the classification of patients and healthy controls within reach. In our view, the reliance on expensive neuroimaging techniques which are not well tolerated by many patient groups and the inability of most current biomarker algorithms to accommodate information about prior class frequencies (such as a disorder's prevalence in the general population) are key factors limiting practical application. To overcome both limitations, we propose a probabilistic pattern recognition approach based on cheap and easy-to-use multi-channel near-infrared spectroscopy (fNIRS) measurements. We show the validity of our method by applying it to data from healthy controls (n = 14) enabling differentiation between the conditions of a visual checkerboard task. Second, we show that high-accuracy single subject classification of patients with schizophrenia (n = 40) and healthy controls (n = 40) is possible based on temporal patterns of fNIRS data measured during a working memory task. For classification, we integrate spatial and temporal information at each channel to estimate overall classification accuracy. This yields an overall accuracy of 76% which is comparable to the highest ever achieved in biomarker-based classification of patients with schizophrenia. In summary, the proposed algorithm in combination with fNIRS measurements enables the analysis of sub-second, multivariate temporal patterns of BOLD responses and high-accuracy predictions based on low-cost, easy-to-use fNIRS patterns. In addition, our approach can easily compensate for variable class priors, which is highly advantageous in making predictions in a wide range of clinical neuroimaging applications.

Functional neuroanatomy of body checking in people with anorexia nervosa.

OBJECTIVE: The neural correlates of body checking perceptions in eating disorders have not yet been identified. This functional Magnetic Resonance Imaging study examined the neuroanatomy involved in altered perception and identification with body checking in female with anorexia nervosa (AN). METHOD: Brain activation while viewing images depicting normal weight individuals involved in either body checking behavior or a neutral (noneating disorder) body action, was compared between 20 females with AN and 15 matched healthy controls (HC). RESULTS: Females with AN reported higher anxiety compared to HC during the body checking task. The level of anxiety positively correlated with body shape concern scores. People with AN had less activation in the medial prefrontal cortex (PFC) and right fusiform gyrus compared to HC in response to body checking compared to neutral action images. Body shape concern scores correlated negatively with medial PFC activation in AN group. DISCUSSION: This preliminary study with modest power suggests that AN patients have reduced activation in cortical areas associated with self-reference, body action perception, and social cognition in females with AN.

Self-evaluation in schizophrenia: an fMRI study with implications for the understanding of insight.

BACKGROUND: Lack of insight is a core feature of schizophrenia and is associated with structural brain abnormalities. The functional neuroanatomy of insight has only recently been investigated. When people evaluate their personality traits compared to those of another, activation is seen in central midline structures (CMS) of the brain. This study set out to compare cerebral activation in schizophrenia patients versus controls during a self-evaluation task which included positive and negative traits as well as mental and physical illness terms. METHODS: Eleven schizophrenia patients and 8 healthy controls, matched for age were studied. Insight was assessed using the Schedule for the Assessment of Insight-expanded version (SAI-E). FMRI data were obtained with a 1.5 Tesla GE system and interactions between participant group, self versus other, significant at the cluster level, were recorded. RESULTS: Significant hypoactivation in the medial superior frontal gyrus (dorsomedial prefrontal cortex) was observed in patients vs. controls during self-evaluation of all traits combined. A second cluster of hypoactivation in the posterior cingulate was also detected. When the response to individual traits was explored, underactivation in other frontal regions plus right inferior parietal lobule emerged and this tended to correlate, albeit weakly with lower insight scores. Further, there were areas of hyperactivation relative to controls in anterior cingulate, frontal and parietal regions (especially precuneus) which showed moderate inverse correlations with insight scores. CONCLUSIONS: We have demonstrated that the CMS, identified as a key system underpinning self-evaluation, is dysfunctional in patients with schizophrenia, particularly dorso-medial PFC. This may have implications for lack of insight in schizophrenia. Hypofunction within the dorsomedial prefrontal region seems to be particularly important although other posterior and lateral cortical regions play a part and may modulate self-evaluative responses depending on the type of trait under consideration.

Facial expression recognition is linked to clinical and neurofunctional differences in autism.

BACKGROUND: Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses. METHODS: Between 255 and 488 participants aged 6-30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task. RESULTS: We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup. LIMITATIONS: Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication. CONCLUSIONS: We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals.

Describing the brain in autism in five dimensions--magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.

Disorder-specific dysfunctions in patients with attention-deficit/hyperactivity disorder compared to patients with obsessive-compulsive disorder during interference inhibition and attention allocation.

BACKGROUND: Abnormalities in inhibitory control and underlying fronto-striatal networks is common to both attention deficit hyperactivity disorder (ADHD) and obsessive-compulsive-disorder (OCD). The aim of this study was to investigate disorder-specific abnormalities in neural networks mediating interference inhibition and selective attention. METHOD: Event-related functional magnetic resonance imaging (fMRI) was used to compare brain activation of boys with ADHD (18), with OCD (10), and healthy boys during (20) during a Simon task that measures interference inhibition and controls for and therefore comeasures attention allocation. RESULTS: During interference inhibition, both patient groups shared mesial frontal dysfunction compared to controls. Disorder-specific dysfunctions were observed in OCD patients in dorsolateral prefrontal cortex during the oddball condition and in ADHD patients in inferior parietal lobe during interference inhibition and in caudate and posterior cingulate during the simpler oddball condition. The decreased activation in caudate and cingulate in ADHD was furthermore negatively correlated with ADHD symptoms and positively with OCD behavioral traits. CONCLUSIONS: The study shows that ADHD and OCD patients have shared but also disorder-specific brain dysfunctions during interference inhibition and attention allocation. Both disorders shared dysfunction in mesial frontal cortex. Disorder-specific dysfunctions, however, were observed in dorsolateral prefrontal cortex in OCD patients and in caudate, cingulate, and parietal brain regions in ADHD patients. The disorder-specific dissociation of striato-cingulate activation that was increased in OCD compared to ADHD patients, was furthermore inversely related to the symptomatology of the two disorders, and may potentially reflect differential dopamine modulation of striatal brain regions.

Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis.

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single "representative" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI.

Investigating the predictive value of whole-brain structural MR scans in autism: a pattern classification approach.

Autistic spectrum disorder (ASD) is accompanied by subtle and spatially distributed differences in brain anatomy that are difficult to detect using conventional mass-univariate methods (e.g., VBM). These require correction for multiple comparisons and hence need relatively large samples to attain sufficient statistical power. Reports of neuroanatomical differences from relatively small studies are thus highly variable. Also, VBM does not provide predictive value, limiting its diagnostic value. Here, we examined neuroanatomical networks implicated in ASD using a whole-brain classification approach employing a support vector machine (SVM) and investigated the predictive value of structural MRI scans in adults with ASD. Subsequently, results were compared between SVM and VBM. We included 44 male adults; 22 diagnosed with ASD using "gold-standard" research interviews and 22 healthy matched controls. SVM identified spatially distributed networks discriminating between ASD and controls. These included the limbic, frontal-striatal, fronto-temporal, fronto-parietal and cerebellar systems. SVM applied to gray matter scans correctly classified ASD individuals at a specificity of 86.0% and a sensitivity of 88.0%. Cases (68.0%) were correctly classified using white matter anatomy. The distance from the separating hyperplane (i.e., the test margin) was significantly related to current symptom severity. In contrast, VBM revealed few significant between-group differences at conventional levels of statistical stringency. We therefore suggest that SVM can detect subtle and spatially distributed differences in brain networks between adults with ASD and controls. Also, these differences provide significant predictive power for group membership, which is related to symptom severity.

Neural response to specific components of fearful faces in healthy and schizophrenic adults.

Perception of fearful faces is associated with functional activation of cortico-limbic structures, which has been found altered in individuals with psychiatric disorders such as schizophrenia, autism and major depression. The objective of this study was to isolate the brain response to the features of standardized fearful faces by incorporating principal component analysis (PCA) into the analysis of neuroimaging data of healthy volunteers and individuals with schizophrenia. At the first stage, the visual characteristics of morphed fearful facial expressions (FEEST, Young et al., 2002) were classified with PCA, which produced seven orthogonal factors, with some of them related to emotionally salient facial features (eyes, mouth, brows) and others reflecting non-salient facial features. Subsequently, these PCA-based factors were included into the functional magnetic resonance imaging (fMRI) analysis of 63 healthy volunteers and 32 individuals with schizophrenia performing a task that involved implicit processing of FEEST stimuli. In healthy volunteers, significant neural response was found to visual characteristics of eyes, mouth or brows. In individuals with schizophrenia, PCA-based analysis enabled us to identify several significant clusters of activation that were not detected by the standard approach. These clusters were implicated in processing of visual and emotional information and were attributable to the perception of eyes and brows. PCA-based analysis could be useful in isolating brain response to salient facial features in psychiatric populations.

Dynamics of brain responses to phobic-related stimulation in specific phobia subtypes.

Very few studies have investigated to what extent different subtypes of specific phobia share the same underlying functional neuroanatomy. This study aims to investigate the potential differences in the anatomy and dynamics of the blood oxygen level-dependent (BOLD) responses associated with spider and blood-injection-injury phobias. We used an event-related paradigm in 14 untreated spider phobics, 15 untreated blood-injection-injury phobics and 17 controls. Phobic images successfully induced distress only in phobic participants. Both phobic groups showed a similar pattern of heart rate increase following the presentation of phobic stimuli, this being different from controls. The presentation of phobic images induced activity within the same brain network in all participants, although the intensity of brain responses was significantly higher in phobics. Only blood-injection-injury phobics showed greater activity in the ventral prefrontal cortex compared with controls. This phobia group also presented a lower activity peak in the left amygdala compared with spider phobics. Importantly, looking at the dynamics of BOLD responses, both phobia groups showed a quicker time-to-peak in the right amygdala than controls, but only spider phobics also differed from controls in this parameter within the left amygdala. Considering these and previous findings, both phobia subtypes show very similar responses regarding their immediate reaction to phobia-related images, but critical differences in their sustained responses to these stimuli. These results highlight the importance of considering complex mental processes potentially associated with coping and emotion regulation processes, rather than exclusively focusing on primary neural responses to threat, when investigating fear and phobias.

Disorder-specific dysfunction in right inferior prefrontal cortex during two inhibition tasks in boys with attention-deficit hyperactivity disorder compared to boys with obsessive-compulsive disorder.

BACKGROUND: Inhibitory dysfunction is a key behavioral and cognitive phenotype of attention-deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD). Both disorders show neuropsychological deficits and fronto-striatal dysfunction during tasks of motor response inhibition and cognitive flexibility. This study investigates differences and commonalities in functional neural networks mediating inhibitory control between adolescents with ADHD and those with OCD to identify disorder-specific neurofunctional markers that distinguish these two inhibitory disorders. METHODS: Event-related fMRI was used to compare brain activation between 20 healthy boys, 18 (Stop task) or 12 boys (Switch task) with ADHD, and 10 boys with OCD during a tracking Stop task that measures inhibition and stopping failure and during a visual-spatial switching task measuring cognitive flexibility. RESULTS: Both patient groups shared brain dysfunction compared to healthy controls in right orbitofrontal (successful inhibition) and left dorsolateral prefrontal cortices (failed inhibition). Right inferior prefrontal dysfunction, however, was disorder-specific to ADHD during both tasks. Left inferior prefrontal dysfunction during the Switch task was significant in children with ADHD relative to controls, but only reached a trend in patients with OCD. Patients with ADHD furthermore showed disorder-specific dysfunction in left basal ganglia and cingulate gyrus during the Switch task. CONCLUSIONS: Patients with ADHD compared to those with OCD have both common and distinct dysfunctions during inhibitory control. The most consistently reported functional abnormality in children with ADHD in right inferior prefrontal cortex during inhibitory control appears to be disorder-specific when compared to patients with OCD and may be a specific neurofunctional biomarker of ADHD.

Enhanced activation of the left inferior frontal gyrus in deaf and dyslexic adults during rhyming.

Hearing developmental dyslexics and profoundly deaf individuals both have difficulties processing the internal structure of words (phonological processing) and learning to read. In hearing non-impaired readers, the development of phonological representations depends on audition. In hearing dyslexics, many argue, auditory processes may be impaired. In congenitally profoundly deaf individuals, auditory speech processing is essentially absent. Two separate literatures have previously reported enhanced activation in the left inferior frontal gyrus in both deaf and dyslexic adults when contrasted with hearing non-dyslexics during reading or phonological tasks. Here, we used a rhyme judgement task to compare adults from these two special populations to a hearing non-dyslexic control group. All groups were matched on non-verbal intelligence quotient, reading age and rhyme performance. Picture stimuli were used since this requires participants to generate their own phonological representations, rather than have them partially provided via text. By testing well-matched groups of participants on the same task, we aimed to establish whether previous literatures reporting differences between individuals with and without phonological processing difficulties have identified the same regions of differential activation in these two distinct populations. The data indicate greater activation in the deaf and dyslexic groups than in the hearing non-dyslexic group across a large portion of the left inferior frontal gyrus. This includes the pars triangularis, extending superiorly into the middle frontal gyrus and posteriorly to include the pars opercularis, and the junction with the ventral precentral gyrus. Within the left inferior frontal gyrus, there was variability between the two groups with phonological processing difficulties. The superior posterior tip of the left pars opercularis, extending into the precentral gyrus, was activated to a greater extent by deaf than dyslexic participants, whereas the superior posterior portion of the pars triangularis extending into the ventral pars opercularis, was activated to a greater extent by dyslexic than deaf participants. Whether these regions play differing roles in compensating for poor phonological processing is not clear. However, we argue that our main finding of greater inferior frontal gyrus activation in both groups with phonological processing difficulties in contrast to controls suggests greater reliance on the articulatory component of speech during phonological processing when auditory processes are absent (deaf group) or impaired (dyslexic group). Thus, the brain appears to develop a similar solution to a processing problem that has different antecedents in these two populations.

A parametric approach to voxel-based meta-analysis.

A key aim of meta-analysis in functional neuroimaging is to quantify the consistency of regional cerebral responses across studies. We derive here a parametric approach to voxel-based meta-analysis, based on spatial statistics. In this method, the value of each voxel in the meta-analysis summary map reflects the proportion of studies reporting an activation within a specified local neighborhood. We threshold this map by testing whether voxel scores could have been expected had the activation peaks been generated at random locations. Our aim is to detect 'signal' regions, with scores that are unlikely to arise under such null hypothesis. The method is applicable to both fixed-effects (in which each study is considered as deriving from the same generating process) and random-effects (in which the process varies across studies) meta-analysis. Simulations show strict false positive control, and this approach leads to increased power and substantial gains in computational time relative to existing simulation-based alternatives. We illustrate the technique by performing a random-effects meta-analysis of word production. Parametric voxel-based meta-analysis provides a powerful and practical tool for neuroimaging meta-analysis.

Increased inferior frontal activation during word generation: a marker of genetic risk for schizophrenia but not bipolar disorder?

During verbal-fluency tasks, impairments in performance and functional abnormalities in the inferior frontal cortex have been observed in both schizophrenia patients and their unaffected relatives. We sought to examine whether such functional abnormalities are a specific marker of genetic vulnerability to schizophrenia. We studied a sample of 132 subjects, comprising 39 patients with schizophrenia, 10 unaffected monozygotic (MZ) cotwins of schizophrenia probands, 28 patients with bipolar disorder, 7 unaffected MZ cotwins of bipolar disorder probands and 48 healthy controls. Blood oxygen level-dependent response was measured using functional magnetic resonance imaging during the performance of an overt verbal-fluency task with two levels of task difficulty, in a cytoarchitectonic region of interest encompassing Brodmann areas 44 and 45 bilaterally. Patients with schizophrenia and the unaffected MZ cotwins of schizophrenia probands showed increased activation in the inferior frontal cortex relative to healthy controls and bipolar patients. Increased engagement of the inferior frontal cortex during verbal-fluency may thus be a marker of genetic vulnerability to schizophrenia.

Psychosis and autism: magnetic resonance imaging study of brain anatomy.

BACKGROUND: Autism-spectrum disorder is increasingly recognised, with recent studies estimating that 1% of children in South London are affected. However, the biology of comorbid mental health problems in people with autism-spectrum disorder is poorly understood. AIMS: To investigate the brain anatomy of people with autism-spectrum disorder with and without psychosis. METHOD: We used in vivo magnetic resonance imaging and compared 30 adults with autism-spectrum disorder (14 with a history psychosis) and 16 healthy controls. RESULTS: Compared with controls both autism-spectrum disorder groups had significantly less grey matter bilaterally in the temporal lobes and the cerebellum. In contrast, they had increased grey matter in striatal regions. However, those with psychosis also had a significant reduction in grey matter content of frontal and occipital regions. Contrary to our expectation, within autism-spectrum disorder, comparisons revealed that psychosis was associated with a reduction in grey matter of the right insular cortex and bilaterally in the cerebellum extending into the fusiform gyrus and the lingual gyrus. CONCLUSIONS: The presence of neurodevelopmental abnormalities normally associated with autism-spectrum disorder might represent an alternative 'entry-point' into a final common pathway of psychosis.