Edith Pomarol-Clotet

Modafinil improves cognition and attentional set shifting in patients with chronic schizophrenia

Modafinil, a novel cognitive enhancer, selectively improves neuropsychological task performance in healthy volunteers and adult patients with attention deficit hyperactivity disorder (ADHD). It has been argued that persistent cognitive deficits in patients with schizophrenia are responsible for the failure of many patients to rehabilitate socially even when psychotic symptoms are in remission. The present study examined the potential of modafinil as a cognitive enhancer in schizophrenia. Twenty chronic patients with a diagnosis of schizophrenia were entered into a double-blind, randomized, placebo-controlled crossover study using a 200 mg dose of modafinil. Modafinil had some cognitive enhancing properties in schizophrenia similar to those observed in healthy adults and adult patients with ADHD. Improvement was seen on short-term verbal memory span, with trends towards improved visual memory and spatial planning. This was accompanied by slowed response latency on the spatial planning task. No effect on stop-signal performance was seen. Importantly, significant improvement in attentional set shifting was seen, despite no effect of modafinil on this task being seen in healthy volunteers or ADHD patients. Modafinil may have potential as an important therapy for cognitive impairment in patients with schizophrenia, particularly because of its beneficial effects on attentional set shifting.

A simple view of the brain through a frequency-specific functional connectivity measure

Here we develop a measure of functional connectivity describing the degree of covariability between a brain region and the rest of the brain. This measure is based on previous formulas for the mutual information (MI) between clusters of regions in the frequency domain. Under the current scenario, the MI can be given as a simple monotonous function of the multiple coherence and it leads to an easy visual representation of connectivity patterns. Computationally efficient formulas, adequate for short time series, are presented and applied to functional magnetic resonance imaging (fMRI) data measured in subjects (N=34) performing a working memory task or being at rest. While resting state coherence in high (0.17-0.25 Hz) and middle (0.08-0.17 Hz) frequency intervals is bilaterally salient in several limbic and temporal areas including the insula, the amygdala, and the primary auditory cortex, low frequencies (<0.08 Hz) have greatest connectivity in frontal structures. Results from the comparison between resting and N-back conditions show enhanced low frequency coherence in many of the areas previously reported in standard fMRI activation studies of working memory, but task related reductions in high frequency connectivity are also found in regions of the default mode network. Finally, potentially confounding effects of head movement and regional volume on MI are identified and addressed.

Overall brain connectivity maps show cortico-subcortical abnormalities in schizophrenia.

Abnormal interactions between areas of the brain have been pointed as possible causes for schizophrenia. However, the nature of these disturbances and the anatomical location of the regions involved are still unclear. Here, we describe a method to estimate maps of net levels of connectivity in the resting brain, and we apply it to look for differential patterns of connectivity in schizophrenia. This method uses partial coherences as a basic measure of covariability, and it minimises the effect of major physiological noise. When overall (net) connectivity maps of a sample of 40 patients with schizophrenia were compared with the maps from a matched sample of 40 controls, a single area of abnormality was found. It is an area of patient hyper‐connectivity and is located frontally, in medial and orbital structures, clearly overlapping the anterior node of the default mode network (DMN). When this area is used as a region of interest in a second‐level analysis, it shows functional hyper‐connections with several cortical and subcortical structures. Interestingly, the most significant abnormality is found with the caudate, which has a bilateral pattern of abnormality, pointing to a possible DMN–striatum deviant relation in schizophrenia. However, hyper‐connectivity observed with other regions (right hippocampus and amygdala, and other cortical structures) suggests a more pervasive alteration of brain connectivity in this disease. Hum Brain Mapp, 2010.

Anisotropic Kernels for Coordinate-Based Meta-Analyses of Neuroimaging Studies

Peak-based meta-analyses of neuroimaging studies create, for each study, a brain map of effect size or peak likelihood by convolving a kernel with each reported peak. A kernel is a small matrix applied in order that voxels surrounding the peak have a value similar to, but slightly lower than that of the peak. Current kernels are isotropic, i.e., the value of a voxel close to a peak only depends on the Euclidean distance between the voxel and the peak. However, such perfect spheres of effect size or likelihood around the peak are rather implausible: a voxel that correlates with the peak across individuals is more likely to be part of the cluster of significant activation or difference than voxels uncorrelated with the peak. This paper introduces anisotropic kernels, which assign different values to the different neighboring voxels based on the spatial correlation between them. They are specifically developed for effect-size signed differential mapping (ES-SDM), though might be easily implemented in other meta-analysis packages such as activation likelihood estimation (ALE). The paper also describes the creation of the required correlation templates for gray matter/BOLD response, white matter, cerebrospinal fluid, and fractional anisotropy. Finally, the new method is validated by quantifying the accuracy of the recreation of effect size maps from peak information. This empirical validation showed that the optimal degree of anisotropy and full-width at half-maximum (FWHM) might vary largely depending on the specific data meta-analyzed. However, it also showed that the recreation substantially improved and did not depend on the FWHM when full anisotropy was used. Based on these results, we recommend the use of fully anisotropic kernels in ES-SDM and ALE, unless optimal meta-analysis-specific parameters can be estimated based on the recreation of available statistical maps. The new method and templates are freely available at http://www.sdmproject.com/.

Probabilistic reasoning in schizophrenia: A comparison of the performance of deluded and nondeluded schizophrenic patients and exploration of possible cognitive underpinnings

Introduction. A number of studies have suggested that deluded patients show a “jumping to conclusions” reasoning style on probabilistic reasoning tasks. In order to systematically explore the cognitive underpinnings of this task, we compared deluded and nondeluded patients on a number of experimental manipulations to investigate the role of memory and task pragmatics on performance. This research was collected as part of the first authors doctoral dissertation. A portion of these data were presented at the Schizophrenia Congress, March 2003, Colorado Springs, USA. The first author was supported by studentships from the Overseas Research Scholarship Scheme and the Cambridge Commonwealth Trust. No conflicts of interest exist that could affect the collection or interpretation of these data. The authors would like to thank Dr Mike Aitken for his input on statistical analysis, and Dr Todd Woodward and Dr Steffen Moritz for useful comments on earlier drafts of this paper. Methods. In Study 1, the performance of deluded and nondeluded schizophrenia patient groups was compared to nonpsychiatric controls on a battery of probabilistic reasoning tests. In Study 2, two variants of the standard “beads in jars” task were compared in order to explore the possible role of working memory load on task performance. Results. In Study 1, there were no significant differences between any of the groups on any of the probabilistic reasoning tasks. In Study 2, we found a significant difference between the two schizophrenic groups and the controls, but no difference in performance between deluded and nondeluded patient groups. The deluded group responded fastest in the memory intensive condition. Conclusions. Deluded and nondeluded schizophrenic patients perform similarly on probabilistic reasoning tasks and only show the “jumping to conclusions” response pattern under some conditions but not under others. Memory demands may influence the appearance of this pattern of responding in schizophrenia.

Validity of modulation and optimal settings for advanced voxel-based morphometry.

Voxel-based morphometry (VBM) is a widely-used structural neuroimaging technique for comparing meso- and macroscopic regional brain volumes between patients and controls in vivo, but some of its steps, particularly the modulation, lack an experimental validation. The aims of this study were two-fold: a) to assess the effects of modulation to detect mesoscopic (i.e. between microscopic and macroscopic) abnormalities on published, classic VBM; and b) to suggest a set of potentially optimal settings for detecting mesoscopic abnormalities with new, advanced, high-resolution diffeomorphic VBM normalization algorithms. Sensitivity and false positive rate after modulating or not in classic VBM using different software packages and spatial statistics, and after setting a range of different parameters in advanced VBM (ANTS-SyN), were calculated in 10 VBM comparisons of 32 altered vs. 32 unaltered gray matter images from different healthy controls. Simulated brain abnormalities comprised mesoscopic volume differences mainly due to cortical thinning. In classic VBM, modulation was associated with a substantial decrease of the sensitivity to detect mesoscopic abnormalities (p<0.001). Optimal settings for advanced VBM included the omission of modulation, the use of large smoothing kernels, and the application of voxel-based or threshold-free cluster enhancement (TFCE) spatial statistics. The modulation-related decrease in sensitivity was due to an increase in variance, and it was more severe in higher-resolution normalization algorithms. Findings from this study suggest the use of unmodulated VBM to detect mesoscopic abnormalities such as cortical thinning.

Individual Differences in Psychotic Effects of Ketamine Are Predicted by Brain Function Measured under Placebo

The symptoms of major psychotic illness are diverse and vary widely across individuals. Furthermore, the prepsychotic phase is indistinct, providing little indication of the precise pattern of symptoms that may subsequently emerge. Likewise, although in some individuals who have affected family members the occurrence of disease may be predicted, the specific symptom profile may not. An important question, therefore, is whether predictive physiological markers of symptom expression can be identified. We conducted a placebo-controlled, within-subjects study in healthy individuals to investigate whether individual variability in baseline physiology, as assessed using functional magnetic resonance imaging, predicted psychosis elicited by the psychotomimetic drug ketamine and whether physiological change under drug reproduced those reported in patients. Here we show that brain responses to cognitive task demands under placebo predict the expression of psychotic phenomena after drug administration. Frontothalamic responses to a working memory task were associated with the tendency of subjects to experience negative symptoms under ketamine. Bilateral frontal responses to an attention task were also predictive of negative symptoms. Frontotemporal activations during language processing tasks were predictive of thought disorder and auditory illusory experiences. A subpsychotic dose of ketamine administered during a second scanning session resulted in increased basal ganglia and thalamic activation during the working memory task, paralleling previous reports in patients with schizophrenia. These results demonstrate precise and predictive brain markers for individual profiles of vulnerability to drug-induced psychosis.

Subdissociative dose ketamine produces a deficit in manipulation but not maintenance of the contents of working memory.

We investigated the effects of subdissociative dose ketamine on executive processes during a working memory task. A total of 11 healthy volunteers participated in a double-blind, placebo-controlled, randomized, within-subjects study. They attended on three occasions, receiving intravenous infusions of placebo, a lower ketamine dose, and a higher ketamine dose. On each occasion, they underwent a series of tasks engaging working memory function in verbal and visuo-spatial domains. Further tasks explored aspects of long-term memory, planning, attention, and perceptual processing. With respect to working memory/executive function, a highly specific pattern of impairment was observed. Impairments were seen only at the higher dose of ketamine and restricted to a subgroup of the verbal working memory tasks: While visuo-spatial working memory showed no evidence of impairment, and while simple maintenance processes during verbal working memory were also unimpaired, higher dose ketamine produced a significant impairment in the manipulation of information within working memory. This process-specific effect of ketamine was reflected in a drug-by-task interaction. The specificity of this ketamine effect suggests that the earliest effect of NMDA receptor blockade is in higher order control of executive function rather than in more basic maintenance processes.

Frequency based mutual information measures between clusters of brain regions in functional magnetic resonance imaging.

Mutual information tools have been recently applied to quantify the connectivity between brain regions in functional magnetic resonance imaging (fMRI). Here we develop measures of mutual information between clusters of brain regions in the frequency domain. The properties and limitations of the method are exemplified through a single resting state fMRI dataset, and with a comparison involving frontostriatal connections in schizophrenic patients and healthy controls.

Bipolar depressed patients show both failure to activate and failure to de-activate during performance of a working memory task

BACKGROUND Bipolar depression has been found to be associated with changes in prefrontal cortex activity during performance of cognitive tasks. However, the role of task-related de-activations has been little investigated. METHOD Forty-one bipolar depressed patients and 41 matched normal controls underwent fMRI scanning while performing baseline, 1-back and 2-back versions of the n-back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups. RESULTS The bipolar depressed patients showed reduced activation in the dorsolateral prefrontal cortex (DLPFC) bilaterally and several other regions. After controlling for differences in task performance only differences in the DLPFC and cerebellum remained. Left DLPFC activation was inversely correlated with Hamilton and MADRS scores. The patients showed failure to de-activate in the medial prefrontal cortex, an area corresponding to the anterior medial node of the default mode network. LIMITATIONS To confirm default mode network dysfunction demonstration of resting-state connectivity abnormalities would also be required. The study was carried out on treated patients, and did not assess for presence of depressive symptoms in the healthy controls. CONCLUSIONS Both prefrontal cortical and default mode network dysfunction appear to characterise bipolar depression. The former, but not the latter, is associated with symptom severity.