Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Delta-9-tetrahydrocannabinol (THC) protects partly against demyelination by modulating the inflammatory response: an in vitro study in aggregating brain cell cultures

Delta 9-tetrahydrocannabinol (THC) has been proposed as therapeutic agent in the treatment of multiple sclerosis. In the present study, we examined whether a modulation of brain inflammatory by THC may protect against demyelination. Myelinating aggregating brain cell cultures were subjected to demyelination by a repeated treatment (3x) with the two inflammatory agents interferon-y (IFN-y) and lipopolysaccharide (LPS). The effects of THC on an acute inflammatory reponse were also examined by treating the aggregates with a single application of the two inflammatory agents. THC effects on the demyelinating process and on several mediators of the inflammatory reponse were analyzed. THC treatment partially prevented the decreased immunoreactivity for MBP, and the decrease in MBP content measured by immunoblotting. It prevented IFN-y + LPS -induced microglial reactivity; and decreased the IFN-y + LPS-induced i8ncreased phosphorylation of p44/42 MAP kinase. The other inflammatory markers, I-NOS and TNF-a mRNA expression, and p38 MAP kinase phosphorylation of p44/42 MAP kinase. The other inflammatory markers, I-NOS and TNF-a mRNA expression, and p38 MAP kinase phosphorylation were downregulated by THC treatment following a single application of the inflammatory agents, but not after repeated applications. THC protected partially against the IFN-y + LPS-induced demyelination. The protective effect of THC on IFN-y + LPS-induced demyelination may be due to a decrease of the inflammatory reponse. However, the anti-inflammatory effect of THC on some inflammatory markers is lost when the inflammatory response is more proeminent and of longer duration, suggesting either that the anti-inflammatory effect of a molecule may depend on the properties of the inflammatory response, or that the anti-inflammatory potential of THC decreases in case of repeated exposure.

Brain dysfunctions, psychopathologies, and body image distortions

The major features in eating disorders are a preoccupation with food and its consumption and body dissatisfaction. Diagnostic manuals provide clusters of criteria according to which affected individuals can be categorized into one or other group of eating disorder. Yet, when considering the high proportion of comorbidities and ignoring the content of the symptoms (food, body), the major features seem to yield obsessional-compulsive, addictive, and impulsive qualities. In the present article, we review studies from the neuroscientific literature (mainly lesion studies) on eating disorder, obsessive-compulsive disorder, impulse control disorder, and addiction to investigate the possibility of a wider phenotype that can be related to a common brain network. The literature localizes this network to the right frontal lobe and its connectivities. This network, when dysfunctional, might result in a behavior that favors the preoccupation with particular thoughts, behaviors, anxieties, and uncontrollable urges that are accompanied by little scope for ongoing behavioral adjustments (e.g., impulse control). We reason that this network may turn out to be equally involved in understudied mental conditions of dysfunctional body processing such as muscle dysmorphia, body dysmorphic disorder (including esthetic surgery), and xelomelia. We finally consider previous notions of a wider phenotype approach to current diagnostic practice (using DSM), such as the possibility of a model with a reduced number of diagnostic categories and primary and secondary factors, and to etiological models of mental health conditions.

The timing of exploratory decision-making revealed by single-trial topographic EEGanalyses.

Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis.

SIRT1 Activates MAO-A in the Brain to Mediate Anxiety and Exploratory Drive.

SIRT1 is a NAD(+)-dependent deacetylase that governs a number of genetic programs to cope with changes in the nutritional status of cells and organisms. Behavioral responses to food abundance are important for the survival of higher animals. Here we used mice with increased or decreased brain SIRT1 to show that this sirtuin regulates anxiety and exploratory drive by activating transcription of the gene encoding the monoamine oxidase A (MAO-A) to reduce serotonin levels in the brain. Indeed, treating animals with MAO-A inhibitors or selective serotonin reuptake inhibitors (SSRIs) normalized anxiety differences between wild-type and mutant animals. SIRT1 deacetylates the brain-specific helix-loop-helix transcription factor NHLH2 on lysine 49 to increase its activation of the MAO-A promoter. Both common and rare variations in the SIRT1 gene were shown to be associated with risk of anxiety in human population samples. Together these data indicate that SIRT1 mediates levels of anxiety, and this regulation may be adaptive in a changing environment of food availability.

Deontological and altruistic guilt: evidence for distinct neurobiological substrates.

The feeling of guilt is a complex mental state underlying several human behaviors in both private and social life. From a psychological and evolutionary viewpoint, guilt is an emotional and cognitive function, characterized by prosocial sentiments, entailing specific moral believes, which can be predominantly driven by inner values (deontological guilt) or by more interpersonal situations (altruistic guilt). The aim of this study was to investigate whether there is a distinct neurobiological substrate for these two expressions of guilt in healthy individuals. We first run two behavioral studies, recruiting a sample of 72 healthy volunteers, to validate a set of stimuli selectively evoking deontological and altruistic guilt, or basic control emotions (i.e., anger and sadness). Similar stimuli were reproduced in a event-related functional magnetic resonance imaging (fMRI) paradigm, to investigate the neural correlates of the same emotions, in a new sample of 22 healthy volunteers. We show that guilty emotions, compared to anger and sadness, activate specific brain areas (i.e., cingulate gyrus and medial frontal cortex) and that different neuronal networks are involved in each specific kind of guilt, with the insula selectively responding to deontological guilt stimuli. This study provides evidence for the existence of distinct neural circuits involved in different guilty feelings. This complex emotion might account for normal individual attitudes and deviant social behaviors. Moreover, an abnormal processing of specific guilt feelings might account for some psychopathological manifestation, such as obsessive-compulsive disorder and depression.

Brain functional abnormality in schizo-affective disorder: an fMRI study.

Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.

Brain functional abnormality in schizo-affective disorder: an fMRI study.

Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.

Brain functional abnormality in schizo-affective disorder: an fMRI study.

Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.

Functional connectivity of reward processing in the brain

Controversial results have been reported concerning the neural mechanisms involved in the processing of rewards and punishments. On the one hand, there is evidence suggesting that monetary gains and losses activate a similar fronto-subcortical network. On the other hand, results of recent studies imply that reward and punishment may engage distinct neural mechanisms. Using functional magnetic resonance imaging (fMRI) we investigated both regional and interregional functional connectivity patterns while participants performed a gambling task featuring unexpectedly high monetary gains and losses. Classical univariate statistical analysis showed that monetary gains and losses activated a similar fronto-striatallimbic network, in which main activation peaks were observed bilaterally in the ventral striatum. Functional connectivity analysis showed similar responses for gain and loss conditions in the insular cortex, the amygdala, and the hippocampus that correlated with the activity observed in the seed region ventral striatum, with the connectivity to the amygdala appearing more pronounced after losses. Larger functional connectivity was found to the medial orbitofrontal cortex for negative outcomes. The fact that different functional patterns were obtained with both analyses suggests that the brain activations observed in the classical univariate approach identifi es the involvement of different functional networks in the current task. These results stress the importance of studying functional connectivity in addition to standard fMRI analysis in reward-related studies.

Nouvelles techniques de stimulation cérébrale: perspectives thérapeutiques en psychiatrie [Novel brain stimulation techniques: therapeutic perspectives in psychiatry]

Recent advances have allowed the development of new physical techniques in neurology and psychiatry, such as Transcranial Magnetic Stimulation (TMS), Vagus Nerve Stimulation (VNS), and Deep Brain Stimulation (DBS). These techniques are already recognized as therapeutic approaches in several late stage refractory neurological disorders (Parkinson's disease, tremor, epilepsy), and currently investigated in psychiatric conditions, refractory to medical treatment (obsessive-compulsive disorder, resistant major depression). In Paralell, these new techniques offer a new window to understand the neurobiology of human behavior.