Using micro-cognition biomarkers of neurosystem dysfunction to redefine ADHD subtypes: A scalable digital path to diagnosis based on brain function

Symptom-based diagnosis does not align with underlying neruropathology, confounding new treatment development and treatment selection for individual patients. Using high precision micro-cognition biomarkers of neurosystem dysfunction acquired during digital neurotherapy (DNT), we characterized subgroups of ADHD children with different neuropathology. K-means clustering applied to 69 children 6-9 years old with ADHD using performance variables from a Go/NoGo test normalized against 58 typically developing (TD) children identified four subgroups that were validated and further characterized by micro-cognition biomarkers extracted from thousands of responses during the DNT. The clusters differed on emblematic features of ADHD. Cluster 4 showed poor response inhibition and inconsistent attention. Cluster 3 showed only poor response inhibition and the other two showed neither. Cluster 2 showed faster and more consistent responses, higher detection of simple targets and better working memory than TD children but marked performance decrements when required to track multiple targets or ignore distractors. Cluster 1 showed much greater ability recognizing members of abstract categories rather than natural categories that children learn through physical interaction with the environment while Cluster 4 was the opposite. Fine-grained, low-cost, noninvasive, and scalable digital micro-cognition biomarkers can identify patients with the same symptom-based diagnosis but differing neuropathology.

Burning down the house: reinventing drug discovery in psychiatry for the development of targeted therapies

Despite advances in neuroscience, limited progress has been made in developing new and better medications for psychiatric disorders. Available treatments in psychiatry rely on a few classes of drugs that have a broad spectrum of activity across disorders with limited understanding of mechanism of action. While the added value of more targeted therapies is apparent, a dearth of pathophysiologic mechanisms exists to support targeted treatments, and where mechanisms have been identified and drugs developed, results have been disappointing. Based on serendipity and early successes that led to the current drug armamentarium, a haunting legacy endures that new drugs should align with outdated and overinclusive diagnostic categories, consistent with the idea that "one size fits all". This legacy has fostered clinical trial designs focused on heterogenous populations of patients with a single diagnosis and non-specific outcome variables. Disturbingly, this approach likely contributed to missed opportunities for drugs targeting the hypothalamic-pituitary-adrenal axis and now inflammation. Indeed, cause-and-effect data support the role of inflammatory processes in neurotransmitter alterations that disrupt specific neurocircuits and related behaviors. This pathway to pathology occurs across disorders and warrants clinical trial designs that enrich for patients with increased inflammation and use primary outcome variables associated with specific effects of inflammation on brain and behavior. Nevertheless, such trial designs have not been routinely employed, and results of anti-inflammatory treatments have been underwhelming. Thus, to accelerate development of targeted therapeutics including in the area of inflammation, regulatory agencies and the pharmaceutical industry must embrace treatments and trials focused on pathophysiologic pathways that impact specific symptom domains in subsets of patients, agnostic to diagnosis. Moreover, closer collaboration among basic and clinical investigators is needed to apply neuroscience knowledge to reveal disease mechanisms that drive psychiatric symptoms. Together, these efforts will support targeted treatments, ultimately leading to new and better therapeutics in psychiatry.

An integrated program of computer-presented and physical cognitive training exercises for children with attention-deficit/hyperactivity disorder

BACKGROUND

This study integrated an experimental medicine approach and a randomized cross-over clinical trial design following CONSORT recommendations to evaluate a cognitive training (CT) intervention for attention deficit hyperactivity disorder (ADHD). The experimental medicine approach was adopted because of documented pathophysiological heterogeneity within the diagnosis of ADHD. The cross-over design was adopted to provide the intervention for all participants and make maximum use of data.

METHODS

Children (n = 93, mean age 7.3 +/- 1.1 years) with or sub-threshold for ADHD were randomly assigned to CT exercises over 15 weeks, before or after 15 weeks of treatment-as-usual (TAU). Fifteen dropped out of the CT/TAU group and 12 out of the TAU/CT group, leaving 66 for cross-over analysis. Seven in the CT/TAU group completed CT before dropping out making 73 available for experimental medicine analyses. Attention, response inhibition, and working memory were assessed before and after CT and TAU.

RESULTS

Children were more likely to improve with CT than TAU (27/66 v. 13/66, McNemar p = 0.02). Consistent with the experimental medicine hypotheses, responders improved on all tests of executive function (p = 0.009-0.01) while non-responders improved on none (p = 0.27-0.81). The degree of clinical improvement was predicted by baseline and change scores in focused attention and working memory (p = 0.008). The response rate was higher in inattentive and combined subtypes than hyperactive-impulsive subtype (p = 0.003).

CONCLUSIONS

Targeting cognitive dysfunction decreases clinical symptoms in proportion to improvement in cognition. Inattentive and combined subtypes were more likely to respond, consistent with targeted pathology and clinically relevant heterogeneity within ADHD.

Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards

The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.

Generalizable brain network markers of major depressive disorder across multiple imaging sites

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up

The scope of human consciousness includes states departing from what most of us experience as ordinary wakefulness. These altered states of consciousness constitute a prime opportunity to study how global changes in brain activity relate to different varieties of subjective experience. We consider the problem of explaining how global signatures of altered consciousness arise from the interplay between large-scale connectivity and local dynamical rules that can be traced to known properties of neural tissue. For this purpose, we advocate a research program aimed at bridging the gap between bottom-up generative models of whole-brain activity and the top-down signatures proposed by theories of consciousness. Throughout this paper, we define altered states of consciousness, discuss relevant signatures of consciousness observed in brain activity, and introduce whole-brain models to explore the biophysics of altered consciousness from the bottom-up. We discuss the potential of our proposal in view of the current state of the art, give specific examples of how this research agenda might play out, and emphasize how a systematic investigation of altered states of consciousness via bottom-up modeling may help us better understand the biophysical, informational, and dynamical underpinnings of consciousness.

Traces of culture: The feedback loop between behavior, brain, and disorder

Culture is part of an extensive series of feedback loops, which involve multiple organismic levels including social contexts, cognitive mediations, neural processes, and behavior. Recent studies in neuroscience show that culturally contingent social processes shape some neural pathways. Studying the influence of cultural context on neural processes may yield new insights into psychiatric disorders. New methodologies in the neurosciences offer innovative ways to assess the impact of culture on mental health and illness. However, implementing these methodologies raises important theoretical and ethical concerns, which must be resolved to address patient individuality and the complexity of cultural diversity. This article discusses cultural context as a major influence on (and consequence of) human neural plasticity and advocates a culture-brain-behavior (CBB) interaction model for conceptualizing the relationship between culture, brain, and psychiatric disorders. Recommendations are made for integrating neuroscientific techniques into transcultural psychiatric research by taking a systems approach to evaluating disorders.

Diagnostic Issues of Depressive Disorders from Kraepelinian Dualism to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Because the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) was mainly influenced by the neo-Kraepelinian approach, its categorical approach to defining mental disorders has been criticized from the viewpoint of etiological neutrality. In the context of bridging the gap between "presumed etiologies-based symptomatology" and "identifiable pathophysiological etiologies," the content in 5th edition, the DSM-5, has been revised to incorporate a combination of categorical and dimensional approaches. The most remarkable change of note regarding the diagnostic classification of depressive disorders in the DSM-5 is the splitting of mood disorders into bipolar disorders and depressive disorders, which is in accordance with the deconstruction of the Kraepelinian dualism for psychoses. The transdiagnostic specifiers "with mixed features," "with psychotic features," and "with anxious distress" are introduced to describe the relationships of depressive disorders with bipolar disorders, schizophrenia, and generalized anxiety disorder, respectively, in a dimensional manner. The lowering of the diagnostic threshold for major depressive disorder (MDD) may be caused by the addition of "hopelessness" to the subjective descriptors of depressive mood and the elimination of "bereavement exclusion" from the definition of MDD. Since the heterogeneity of MDD is equivalent to the Wittgensteinian "games" analogy, the different types of MDD are related not by a single essential feature but rather by "family resemblance." Network analyses of MDD symptoms may therefore need further review to elucidate the connections among interrelated symptoms and other clinical elements.

Polygenic Risk and Neural Substrates of Attention-Deficit/Hyperactivity Disorder Symptoms in Youths With a History of Mild Traumatic Brain Injury

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a major sequela of traumatic brain injury (TBI) in youths. The objective of this study was to examine whether ADHD symptoms are differentially associated with genetic risk and brain structure in youths with and without a history of TBI.

METHODS

Medical history, ADHD symptoms, genetic data, and neuroimaging data were obtained from a community sample of youths. ADHD symptom severity was compared between those with and without TBI (TBI n = 418, no TBI n = 3193). The relationship of TBI history, genetic vulnerability, brain structure, and ADHD symptoms was examined by assessing 1) ADHD polygenic score (discovery sample ADHD n = 19,099, control sample n = 34,194), 2) basal ganglia volumes, and 3) fractional anisotropy in the corpus callosum and corona radiata.

RESULTS

Youths with TBI reported greater ADHD symptom severity compared with those without TBI. Polygenic score was positively associated with ADHD symptoms in youths without TBI but not in youths with TBI. The negative association between the caudate volume and ADHD symptoms was not moderated by a history of TBI. However, the relationship between ADHD symptoms and structure of the genu of the corpus callosum was negative in youths with TBI and positive in youths without TBI.

CONCLUSIONS

The identification of distinct ADHD etiology in youths with TBI provides neurobiological insight into the clinical heterogeneity in the disorder. Results indicate that genetic predisposition to ADHD does not increase the risk for ADHD symptoms associated with TBI. ADHD symptoms associated with TBI may be a result of a mechanical insult rather than neurodevelopmental factors.

Neurocognitive and Perceptual Processing in Genetic Mouse Models of Schizophrenia: Emerging Lessons

During the past two decades, the number of animal models of psychiatric disorders has grown exponentially. Of these, genetic animal models that are modeled after rare but highly penetrant mutations hold great promise for deciphering critical molecular, synaptic, and neurocircuitry deficits of major psychiatric disorders, such as schizophrenia. Animal models should aim to focus on core aspects rather than capture the entire human disease. In this context, animal models with strong etiological validity, where behavioral and neurophysiological phenotypes and the features of the disease being modeled are in unambiguous homology, are being used to dissect both elementary and complex cognitive and perceptual processing deficits present in psychiatric disorders at the level of neurocircuitry, shedding new light on critical disease mechanisms. Recent progress in neuroscience along with large-scale initiatives that propose a consistent approach in characterizing these deficits across different laboratories will further enhance the efficacy of these studies that will ultimately lead to identifying new biological targets for drug development.

Classification of Psychiatric Disorders

Because of the poor link between psychiatric diagnosis and neurobiological findings, it is difficult to classify mental disorders. The changes made to psychiatric diagnostic systems over the years can be understood in terms of "practical conservatism." The Diagnostic and Statistical Manual of Mental Disorders (DSM)-I and DSM-II were theoretically supported by the psychoanalytic and psychodynamic approach. Subsequently, psychiatric diagnoses of this kind were opposed by the anti-psychiatry movement, as well as by the findings of the Rosenhan experiment. Thus, the DSM-III revolution contained more empiricism, aligning psychiatry with biomedicine. Psychiatric diagnoses are classified and defined in terms of Kraepelinian dualism, using a categorical approach. The empirical trend was continued in the DSM-IV. To overcome the limitations of current psychiatric diagnostic systems and integrate fundamental genetic, neurobiological, behavioral, environmental, and experimental components into psychiatry, the Research Domain Criteria (RDoC) were established. To overcome the limitations of the categorical approach, psychiatrists have considered adopting a dimensional approach. However, their efforts were frustrated in the DSM-5 revision process. Thus, the DSM-5 is characterized by the rearrangement of psychiatric diagnoses, the partial adoption of a dimensional approach, the introduction of new diagnoses, and harmonization with the International Classification of Diseases.

EEG Source Imaging Indices of Cognitive Control Show Associations with Dopamine System Genes

Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness.

Problematic alcohol use and reduced hippocampal volume: a meta-analytic review

BACKGROUND

A number of studies reports reduced hippocampal volume in individuals who engage in problematic alcohol use. However, the magnitude of the difference in hippocampal volume between individuals with v. without problematic alcohol use has varied widely, and there have been null findings. Moreover, the studies comprise diverse alcohol use constructs and samples, including clinically significant alcohol use disorders and subclinical but problematic alcohol use (e.g. binge drinking), adults and adolescents, and males and females.

METHODS

We conducted the first quantitative synthesis of the published empirical research on associations between problematic alcohol use and hippocampal volume. In total, 23 studies were identified and selected for inclusion in the meta-analysis; effects sizes were aggregated using a random-effects model.

RESULTS

Problematic alcohol use was associated with significantly smaller hippocampal volume (d = -0.53). Moderator analyses indicated that effects were stronger for clinically significant v. subclinical alcohol use and among adults relative to adolescents; effects did not differ among males and females.

CONCLUSIONS

Problematic alcohol use is associated with reduced hippocampal volume. The moderate overall effect size suggests the need for larger samples than are typically included in studies of alcohol use and hippocampal volume. Because the existing literature is almost entirely cross-sectional, future research using causally informative study designs is needed to determine whether this association reflects premorbid risk for the development of problematic alcohol use and/or whether alcohol has a neurotoxic effect on the hippocampus.

[A new classification for better care. The promises of the translational psychiatric neuroscience]

This article explores the way neuroscientists call for the "deconstruction" of the classifications of mental disorders as we know them, in order to provide solutions to the slowdown of therapeutical innovation in psychiatry. It is based on the case study of the Research Domain Criteria (RDoC) project of the US National Institute of Mental Health (NIMH). My purpose is to show that neuroscience interested in mental disorders offers narratives of innovation, transformation, and desirable futures that are at the heart of the ambitious current research projects and influence them. I approach the versions of the futures proposed by the promoters of translational psychiatric neuroscience in terms of productivity at the scientific, epistemological and socio-political levels.

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various support vector machine (SVM) classifiers were developed. The data were from a 2-year, prospective, longitudinal study of 81 patients (age 9-17 years) with early-onset FEP and a stable diagnosis during follow-up and 42 age- and sex-matched healthy controls (HC). The input was different combinations of baseline clinical, neuropsychological, magnetic resonance imaging brain volumetric and biochemical data, and the output was the diagnosis at follow-up (SSD vs. non-SSD, SSD vs. HC, and non-SSD vs. HC). Enhanced recursive feature elimination was performed for the SSD vs. non-SSD classifier to select and rank the input variables with the highest predictive value for a diagnostic outcome of SSD. After validation with a test set and considering all baseline variables together, the SSD vs. non-SSD, SSD vs. HC and non-SSD vs. HC classifiers achieved an accuracy of 0.81, 0.99 and 0.99, respectively. Regarding the SSD vs. non-SSD classifier, a combination of baseline clinical variables (severity of negative, disorganized symptoms and hallucinations or poor insight) and neuropsychological variables (impaired attention, motor coordination, and global cognition) showed the highest predictive value for a diagnostic outcome of SSD. Neuroimaging and biochemical variables at baseline did not add to the predictive value. Thus, comprehensive clinical/cognitive assessment remains the most reliable approach for differential diagnosis during early-onset FEP. SVMs may constitute promising multivariate tools in the search for predictors of diagnostic outcome in FEP.

Research review: Functional brain connectivity and child psychopathology--overview and methodological considerations for investigators new to the field

BACKGROUND

Functional connectivity MRI is an emerging technique that can be used to investigate typical and atypical brain function in developing and aging populations. Despite some of the current confounds in the field of functional connectivity MRI, the translational potential of the technique available to investigators may eventually be used to improve diagnosis, early disease detection, and therapy monitoring.

METHOD AND SCOPE

Based on a comprehensive survey of the literature, this review offers an introduction of resting-state functional connectivity for new investigators to the field of resting-state functional connectivity. We discuss a brief history of the technique, various methods of analysis, the relationship of functional networks to behavior, as well as the translational potential of functional connectivity MRI to investigate neuropsychiatric disorders. We also address some considerations and limitations with data analysis and interpretation.

CONCLUSIONS

The information provided in this review should serve as a foundation for investigators new to the field of resting-state functional connectivity. The discussion provides a means to better understand functional connectivity and its application to typical and atypical brain function.

The association of post-stroke anhedonia with salivary cortisol levels and stroke lesion in hippocampal/parahippocampal region

BACKGROUND

Anhedonia constitutes a coherent construct, with neural correlates and negative clinical impact, independent of depression. However, little is known about the neural correlates of anhedonia in stroke patients. In this study, we investigated the association of post-stroke anhedonia with salivary cortisol levels and stroke location and volume.

PATIENTS AND METHODS

A psychiatrist administered the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition to identify anhedonia in 36 inpatients, without previous depression, consecutively admitted in a neurology clinic in the first month after a first-ever ischemic stroke. Salivary cortisol levels were assessed in the morning, evening, and after a dexamethasone suppression test. We used magnetic resonance imaging and a semi-automated brain morphometry method to assess stroke location, and the MRIcro program according to the Brodmann Map to calculate the lesion volume.

RESULTS

Patients with anhedonia had significantly larger diurnal variation (P-value =0.017) and higher morning levels of salivary cortisol (1,671.9±604.0 ng/dL versus 1,103.9±821.9 ng/dL; P-value =0.022), and greater stroke lesions in the parahippocampal gyrus (Brodmann area 36) compared to those without anhedonia (10.14 voxels; standard deviation ±17.72 versus 0.86 voxels; standard deviation ±4.64; P-value =0.027). The volume of lesion in the parahippocampal gyrus (Brodmann area 36) was associated with diurnal variation of salivary cortisol levels (rho=0.845; P-value =0.034) only in anhedonic patients.

CONCLUSION

Our findings suggest that anhedonia in stroke patients is associated with the volume of stroke lesion in the parahippocampal gyrus and with dysfunction of the hypothalamic-pituitary-adrenal axis.

What are we missing? The costs versus benefits of skip rule designs

Many research diagnostic interviews employ skip rules, such that some questions are only asked based on answers to prior questions. In the context of large-scale epidemiological studies, skip rules are important to study feasibility by reducing the time, money, and participant burden required for assessment. However, less is understood about information lost when questions are skipped. This study examines the relative prevalence, clinical significance, and additional time required to assess eating disorder symptom patterns skipped in the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) to understand the costs and benefits of following skip rules. Data come from the second stage of a two-stage cohort sample (N = 400) in which the SCID-I eating disorders module was administered without following skip rules. Results were weighted to correct for the sampling framework. Over a third of subjects endorsed symptoms that would have been missed had skip rules been followed. Uncaptured symptom patterns were associated with increased psychosocial impairment, and the additional time required to assess all symptoms averaged 1.8 minutes per participant. Clinically significant symptom patterns are missed by the SCID-I and similar diagnostic tools, suggesting that epidemiologic studies using such instruments under-estimate the prevalence and public health impact of mental disorders.

Debating DSM-5: diagnosis and the sociology of critique

The development of the fifth edition of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders-the DSM-5-has reenergised and driven further forward critical discourse about the place and role of diagnosis in mental health. The DSM-5 has attracted considerable criticism, not least about its role in processes of medicalisation. This paper suggests the need for a sociology of psychiatric critique. Sociological analysis can help map fields of contention, and cast fresh light on the assumptions and nuances of debate around the DSM-5; it underscores the importance of diagnosis to the governance of social and clinical life, as well as the wider discourses critical commentaries connect with and are activated by. More normatively, a sociology of critique can indicate which interests and values are structuring the dialogues being articulated, and just how diverse clinical opinion regarding the DSM can actually be. This has implications for the considerations of health services and policy decision-makers who might look to such debates for guidance.

Missing data estimation in fMRI dynamic causal modeling

Dynamic Causal Modeling (DCM) can be used to quantify cognitive function in individuals as effective connectivity. However, ambiguity among subjects in the number and location of discernible active regions prevents all candidate models from being compared in all subjects, precluding the use of DCM as an individual cognitive phenotyping tool. This paper proposes a solution to this problem by treating missing regions in the first-level analysis as missing data, and performing estimation of the time course associated with any missing region using one of four candidate methods: zero-filling, average-filling, noise-filling using a fixed stochastic process, or one estimated using expectation-maximization. The effect of this estimation scheme was analyzed by treating it as a preprocessing step to DCM and observing the resulting effects on model evidence. Simulation studies show that estimation using expectation-maximization yields the highest classification accuracy using a simple loss function and highest model evidence, relative to other methods. This result held for various dataset sizes and varying numbers of model choice. In real data, application to Go/No-Go and Simon tasks allowed computation of signals from the missing nodes and the consequent computation of model evidence in all subjects compared to 62 and 48 percent respectively if no preprocessing was performed. These results demonstrate the face validity of the preprocessing scheme and open the possibility of using single-subject DCM as an individual cognitive phenotyping tool.

A comprehensive assessment of memory, delay aversion, timing, inhibition, decision making and variability in attention deficit hyperactivity disorder: advancing beyond the three-pathway models

BACKGROUND

Although attention deficit hyperactivity disorder (ADHD) has been associated with a broad range of deficits across various neuropsychological domains, most studies have assessed only a narrow range of neuropsychological functions. Direct cross-domain comparisons are rare, with almost all studies restricted to less than four domains. Therefore, the relationships between these various domains remain undefined. In addition, almost all studies included previously medicated participants, limiting the conclusions that can be drawn. We present the first study to compare a large cohort of medication-naive boys with ADHD with healthy controls on a broad battery of neuropsychological tasks, assessing six key domains of neuropsychological functioning.

METHOD

The neuropsychological functioning of 83 medication-naive boys with well-characterized ADHD (mean age 8.9 years) was compared with that of 66 typically developing (TYP) boys (mean age 9.0 years) on a broad battery of validated neuropsychological tasks.

RESULTS

Data reduction using complementary factor analysis (CFA) confirmed six distinct neuropsychological domains: working memory, inhibition, delay aversion, decision making, timing and response variability. Boys with ADHD performed less well across all six domains although, for each domain, only a minority of boys with ADHD had a deficit [effect size (% with deficit) ADHD versus TYP: working memory 0.95 (30.1), inhibition 0.61 (22.9), delay aversion 0.82 (36.1), decision making 0.55 (20.5), timing 0.71 (31.3), response variability 0.37 (18.1)].

CONCLUSIONS

The clinical syndrome of ADHD is neuropsychologically heterogeneous. These data highlight the complexity of the relationships between the different neuropsychological profiles associated with ADHD and the clinical symptoms and functional impairment.

In search of biomarkers in psychiatry: EEG-based measures of brain function

Current clinical parameters used for diagnosis and phenotypic definitions of psychopathology are both highly variable and subjective. Intensive research efforts for specific and sensitive biological markers, or biomarkers, for psychopathology as objective alternatives to the current paradigm are ongoing. While biomarker research in psychiatry has focused largely on functional neuroimaging methods for identifying the neural functions that associate with psychopathology, scalp electroencephalography (EEG) has been viewed, historically, as offering little specific brain source information, as scalp appearance is only loosely correlated to its brain source dynamics. However, ongoing advances in signal processing of EEG data can now deliver functional EEG brain-imaging with distinctly improved spatial, as well as fine temporal, resolution. One computational approach proving particularly useful for EEG cortical brain imaging is independent component analysis (ICA). ICA decomposition can be used to identify distinct cortical source activities that are sensitive and specific to the pathophysiology of psychiatric disorders. Given its practical research advantages, relatively low cost, and ease of use, EEG-imaging is now both feasible and attractive, in particular for studies involving the large samples required by genetically informative designs to characterize causal pathways to psychopathology. The completely non-invasive nature of EEG data acquisition, coupled with ongoing advances in dry, wireless, and wearable EEG technology, makes EEG-imaging increasingly attractive and appropriate for psychiatric research, including the study of developmentally young samples. Applied to large genetically and developmentally informative samples, EEG imaging can advance the search for robust diagnostic biomarkers and phenotypes in psychiatry.

Association study of gene polymorphisms and depression with abnormal humor in traditional Uighur medicine

Background

According to the humor theory of Traditional Uighur Medicine (TUM), a same disease is classified into different abnormal humor types and corresponding methods are applied to treat the diseases according to the type of abnormal humor characteristics. To date the biological foundation of classification of diseases by humor theory has been little studied and the mechanism of action is still unclear. In the present study, we aimed to investigate the association between some related gene polymorphisms and depression with abnormal humor in TUM.

Methods

201 cases of depression patients in a Uighur population were divided into two groups as: 107 cases of depression patients with abnormal black bile (ABB), 94 cases of depression patients with none abnormal black bile (nABB), and 50 healthy people were served as control group. Venous blood was used to isolate DNA samples, and the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique was used for genotyping of single nucleotide polymorphisms (SNPs). Polymorphisms in the serotonin 2A (5-HT_2A) receptor gene, brain derived neurotrophic factor (BDNF), serotonin 1A (5-HT_1A) receptor gene were investigated in each groups, respectively.

Results

The 5-HT_2A A-1438G, 5-HT_2A T102C, BDNF Val66Met, and 5-HT_1A C-1019G gene polymorphisms showed significant association with ABB. However, no difference between nABB and controls was found for those genotype distribution and allele frequency. Moreover, the T102C and A1438G SNPs in the 5-HT_2A receptor gene polymorphisms were in linkage disequilibrium. In addition, the OR associated with the combination of Val66Met-Val/Val genotype plus the presence of -1019C allele was 8.393 for ABB compared with controls (OR 8.393; 95% CI 1.807 ~ 38.991; P= 0.003). Moreover, the OR associated with the presence of -Met plus -1019C alleles was 12.194 for ABB compared with controls (OR 12.194; 95% CI 1.433 ~ 103.776; P= 0.005). The OR associated with the presence of -1438C/C plus Val/Val genotypes was 7.738 for ABB compared with controls (OR 7.738; 95% CI 1.566 ~ 38.241; P= 0.005).

Conclusion

It was concluded that there were significant relationship between the gene polymorphisms and classification of depression with abnormal humor in TUM. The 5-HT_2A A-1438G, 5-HT_2A T102C, BDNF Val66Met, and 5-HT_1A C-1019G gene polymorphisms might predict the incidence of depression with ABB.

The relationship between effortful control, current psychopathology and interpersonal difficulties in adulthood

This study examined whether the relationship between low effortful control (EC), general psychopathology and interpersonal maladjustment previously reported among children extends to adulthood. Two hundred and forty undergraduate students were assessed using the EC scale of the Adult Temperament Questionnaire, the General Severity Index of the Brief Symptom Inventory (BSI-GSI) and the interpersonal distress index of the Inventory of Interpersonal Problems-Short Circumplex (IIP-distress). Both the BSI-GSI and the IIP-distress scores were related to low levels of EC. Furthermore, interpersonal distress mediated the association between low EC and greater psychopathology severity. These results suggest that deficits in regulatory temperament among adults may be associated with experiencing greater psychopathology distress, and that this relationship may be explained by an impairment in interpersonal adjustment. Such preliminary findings may constitute a useful starting point for investigating this hypothesis among clinical populations.

A multistep general theory of transition to addiction

BACKGROUND

Several theories propose alternative explanations for drug addiction.

OBJECTIVES

We propose a general theory of transition to addiction that synthesizes knowledge generated in the field of addiction into a unitary explanatory frame.

MAJOR PRINCIPLES OF THE THEORY

Transition to addiction results from a sequential three-step interaction between: (1) individual vulnerability; (2) degree/amount of drug exposure. The first step, sporadic recreational drug use is a learning process mediated by overactivation of neurobiological substrates of natural rewards that allows most individuals to perceive drugs as highly rewarding stimuli. The second, intensified, sustained, escalated drug use occurs in some vulnerable individuals who have a hyperactive dopaminergic system and impaired prefrontal cortex function. Sustained and prolonged drug use induces incentive sensitization and an allostatic state that makes drugs strongly wanted and needed. Habit formation can also contribute to stabilizing sustained drug use. The last step, loss of control of drug intake and full addiction, is due to a second vulnerable phenotype. This loss-of-control-prone phenotype is triggered by long-term drug exposure and characterized by long-lasting loss of synaptic plasticity in reward areas in the brain that induce a form of behavioral crystallization resulting in loss of control of drug intake. Because of behavioral crystallization, drugs are now not only wanted and needed but also pathologically mourned when absent.

CONCLUSIONS

This general theory demonstrates that drug addiction is a true psychiatric disease caused by a three-step interaction between vulnerable individuals and amount/duration of drug exposure.

Common and distinct neural features of social and non-social reward processing in autism and social anxiety disorder

Autism spectrum disorders (ASDs) and social anxiety disorder (SAD) are both characterized by social dysfunction, but no study to date has compared neural responses to social rewards in ASDs and SAD. Neural responses during social and non-social reward anticipation and outcomes were examined in individuals with ASD (n = 16), SAD (n = 15) and a control group (n = 19) via functional magnetic resonance imaging. Analyses modeling all three groups revealed increased nucleus accumbens (NAc) activation in SAD relative to ASD during monetary reward anticipation, whereas both the SAD and ASD group demonstrated decreased bilateral NAc activation relative to the control group during social reward anticipation. During reward outcomes, the SAD group did not differ significantly from the other two groups in ventromedial prefrontal cortex activation to either reward type. Analyses comparing only the ASD and SAD groups revealed greater bilateral amygdala activation to social rewards in SAD relative to ASD during both anticipation and outcome phases, and the magnitude of left amygdala hyperactivation in the SAD group during social reward anticipation was significantly correlated with the severity of trait anxiety symptoms. Results suggest reward network dysfunction to both monetary and social rewards in SAD and ASD during reward anticipation and outcomes, but that NAc hypoactivation during monetary reward anticipation differentiates ASD from SAD.

Data-driven subtypes of major depressive disorder: a systematic review

BACKGROUND

According to current classification systems, patients with major depressive disorder (MDD) may have very different combinations of symptoms. This symptomatic diversity hinders the progress of research into the causal mechanisms and treatment allocation. Theoretically founded subtypes of depression such as atypical, psychotic, and melancholic depression have limited clinical applicability. Data-driven analyses of symptom dimensions or subtypes of depression are scarce. In this systematic review, we examine the evidence for the existence of data-driven symptomatic subtypes of depression.

METHODS

We undertook a systematic literature search of MEDLINE, PsycINFO and Embase in May 2012. We included studies analyzing the depression criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) of adults with MDD in latent variable analyses.

RESULTS

In total, 1176 articles were retrieved, of which 20 satisfied the inclusion criteria. These reports described a total of 34 latent variable analyses: 6 confirmatory factor analyses, 6 exploratory factor analyses, 12 principal component analyses, and 10 latent class analyses. The latent class techniques distinguished 2 to 5 classes, which mainly reflected subgroups with different overall severity: 62 of 71 significant differences on symptom level were congruent with a latent class solution reflecting severity. The latent class techniques did not consistently identify specific symptom clusters. Latent factor techniques mostly found a factor explaining the variance in the symptoms depressed mood and interest loss (11 of 13 analyses), often complemented by psychomotor retardation or fatigue (8 of 11 analyses). However, differences in found factors and classes were substantial.

CONCLUSIONS

The studies performed to date do not provide conclusive evidence for the existence of depressive symptom dimensions or symptomatic subtypes. The wide diversity of identified factors and classes might result either from the absence of patterns to be found, or from the theoretical and modeling choices preceding analysis.

Exploring the interface of neurobehaviorally linked personality dimensions and personality organization in borderline personality disorder: the Multidimensional Personality Questionnaire and Inventory of Personality Organization

Advances in our understanding of complex psychopathology will likely benefit from approaches to mind, brain, and behavior that seek to (a) specify those general neurobehavioral processes underpinning pathology and (b) bridge to other process-based models of psychopathology at different levels of analysis. Well-defined neurobehavioral processes (e.g., positive emotionality, negative emotionality, nonaffective constraint, fear, affiliation) and their phenotypic indicators are firmly rooted in neural substrates (Depue & Lenzenweger, 2005). Furthermore, long-studied psychodynamic psychological processes, such as identity diffusion, primitive psychological defensive functioning, and reality-testing dimensions, are important to understanding personality pathology (Kernberg & Caligor, 2005). Both theoretical perspectives view the cardinal processes involved in the determination of personality disorders (PDs) as relevant across existing PD diagnostic entities. The authors examined relationships between psychometric indicators of these two sets of processes, the neurobehavioral and the psychodynamic, in a well-characterized sample of individuals with borderline personality disorder (BPD; N = 92). In bridging these two levels of analysis, the authors found that the alienation, aggression, and absorption constructs represent important linkages to the psychodynamic processes, especially primitive psychological defenses and reality-testing impairments. These results are discussed in terms of their potential for joining these two domains of analysis--a neurobehaviorally informed view of personality and the psychodynamic--in efforts to (a) foster a process-oriented approach, (b) resolve heterogeneity, and (c) facilitate identification of endophenotypes in BPD. The heuristic value of this approach for understanding other forms of psychopathology is also discussed.

The Puzzle of Neuroimaging and Psychiatric Diagnosis: Technology and Nosology in an Evolving Discipline

Brain imaging provides ever more sensitive measures of structure and function relevant to human psychology and has revealed correlates for virtually every psychiatric disorder. Yet it plays no accepted role in psychiatric diagnosis beyond ruling out medical factors such as tumors or traumatic brain injuries. Why is brain imaging not used in the diagnosis of primary psychiatric disorders, such as depression, bipolar disease, schizophrenia, and ADHD? The present article addresses this question. It reviews the state of the art in psychiatric imaging, including diagnostic and other applications, and explains the nonutility of diagnostic imaging in terms of aspects of both the current state of imaging and the current nature of psychiatric nosology. The likely future path by which imaging-based diagnoses will be incorporated into psychiatry is also discussed. By reviewing one well-known attempt to use SPECT-scanning in psychiatric diagnosis, the article examines a real-world practice that illustrates several related points: the appeal of the idea of image-assisted diagnosis for physicians, patients and families, despite a lack of proven effectiveness, and the mismatch between the categories and dimensions of current nosology and those suggested by imaging.

Neuropattern: a new translational tool to detect and treat stress pathology I. Strategical consideration

Translational research is most prominently represented by the search for biomarkers and preclinical research. Aside from generating such new measures and methodologies, translational research additionally refers to translation of integrated knowledge. This strategy involves synthesis, exchange, and dissemination of available knowledge, with the goal of improving health services and health care systems. For stress-related disorders, such as depression and anxiety disorders, this strategy meets numerous challenges, as the great majority of these patients are treated by family physicians. Here, we introduce Neuropattern, a new diagnostic tool, which allows translation of psychobiological knowledge to this stress "bedside." Neuropatterns are conceptualized endophenotypes of the activity and reactivity status of neurobiological interfaces, which participate in the crosstalk between the brain and peripheral organs under stressful conditions. Neuropattern can easily be implemented in routine clinical work, and helps the physician to individualize those therapeutic interventions that are already available.

Neuropattern: a new translational tool to detect and treat stress pathology. II. The Teltow study

The present study was designed to test the clinical utility of Neuropattern (NP), a newly developed translational diagnostic tool. NP consists of biological and psychological measures that facilitate the identification of functional changes (called "neuropatterns") in patients with stress-related health problems. In this prospective, randomized control trial, we expected NP to improve therapeutic efficacy, as compared with the usual treatment. NP was applied to 101 in-patients suffering from various mental disorders (mainly depression, anxiety disorders, and adjustment disorders), and scoring high on the Symptom Checklist-90-R (SCL-90-R) somatization scale. The patients (73% females, mean ± standard deviation age 46 ± 9.03 years) were randomly assigned to two groups: in the experimental group (n = 51), physicians received results from NP diagnostics, while in the control group (n = 50), this information was not available until discharge from the hospital. Improvements of symptoms in consequence of treatment were monitored by two self-rating scales, the SCL-90-R and Short Form-12 health survey, and a physician's clinical global rating (Beeinträchtigungs-Schwere Score). There was a significantly greater improvement in the experimental group in the self-rating assessments on symptom severity (p = 0.03) and quality of life (p = 0.05), but not in the observer rating of emotional, physical, and social-communicative functioning (p = 0.13). Treatment efficacy in patients can be improved by providing the attendant physician and the patient with diagnostic information and treatment recommendations by NP. The role of concrete mediators of treatment efficacy awaits further research.

Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings

This review summarizes evidence of dysregulated reward circuitry function in a range of neurodevelopmental and psychiatric disorders and genetic syndromes. First, the contribution of identifying a core mechanistic process across disparate disorders to disease classification is discussed, followed by a review of the neurobiology of reward circuitry. We next consider preclinical animal models and clinical evidence of reward-pathway dysfunction in a range of disorders, including psychiatric disorders (i.e., substance-use disorders, affective disorders, eating disorders, and obsessive compulsive disorders), neurodevelopmental disorders (i.e., schizophrenia, attention-deficit/hyperactivity disorder, autism spectrum disorders, Tourette's syndrome, conduct disorder/oppositional defiant disorder), and genetic syndromes (i.e., Fragile X syndrome, Prader-Willi syndrome, Williams syndrome, Angelman syndrome, and Rett syndrome). We also provide brief overviews of effective psychopharmacologic agents that have an effect on the dopamine system in these disorders. This review concludes with methodological considerations for future research designed to more clearly probe reward-circuitry dysfunction, with the ultimate goal of improved intervention strategies.

Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD

Research and clinical investigations in psychiatry largely rely on the de facto assumption that the diagnostic categories identified in the Diagnostic and Statistical Manual (DSM) represent homogeneous syndromes. However, the mechanistic heterogeneity that potentially underlies the existing classification scheme might limit discovery of etiology for most developmental psychiatric disorders. Another, perhaps less palpable, reality may also be interfering with progress-heterogeneity in typically developing populations. In this report we attempt to clarify neuropsychological heterogeneity in a large dataset of typically developing youth and youth with attention deficit/hyperactivity disorder (ADHD), using graph theory and community detection. We sought to determine whether data-driven neuropsychological subtypes could be discerned in children with and without the disorder. Because individual classification is the sine qua non for eventual clinical translation, we also apply support vector machine-based multivariate pattern analysis to identify how well ADHD status in individual children can be identified as defined by the community detection delineated subtypes. The analysis yielded several unique, but similar subtypes across both populations. Just as importantly, comparing typically developing children with ADHD children within each of these distinct subgroups increased diagnostic accuracy. Two important principles were identified that have the potential to advance our understanding of typical development and developmental neuropsychiatric disorders. The first tenet suggests that typically developing children can be classified into distinct neuropsychological subgroups with high precision. The second tenet proposes that some of the heterogeneity in individuals with ADHD might be "nested" in this normal variation.

Decreased regional cortical thickness and thinning rate are associated with inattention symptoms in healthy children

OBJECTIVE

Children with attention-deficit/hyperactivity disorder (ADHD) have delayed cortical maturation, evidenced by regionally specific slower cortical thinning. However, the relationship between cortical maturation and attention capacities in typically developing children is unknown. This study examines cortical thickness correlates of inattention symptoms in a large sample of healthy children.

METHOD

Data from 357 healthy subjects (6.0-18.4 years of age) were obtained from the NIH MRI Study of Normal Brain Development. In cross-sectional analysis (first visit, n = 257), Child Behavior Checklist Attention Problems (AP) scores were linearly regressed against cortical thickness, controlling for age, gender, total brain volume, and site. For longitudinal data (up to three visits, n = 357/672 scans), similar analyses were performed using mixed-effects linear regressions. Interactions of AP with age and gender were tested.

RESULTS

A cross-sectional "AP by age" interaction was found in bilateral orbito-frontal cortex, right inferior frontal cortex, bilateral ventromedial prefrontal cortex, bilateral dorsolateral prefrontal cortex, and several additional attention network regions. The interaction was due to negative associations between AP and thickness in younger subjects (6-10 years of age) that gradually disappeared over time secondary to slower cortical thinning. Similar trends were present in longitudinal analyses.

CONCLUSIONS

Higher AP scores were associated with thinner cortex at baseline and slower cortical thinning with aging in multiple areas involved in attention processes. Similar patterns have been identified in ADHD, suggesting a dimensional component to the link between attention and cortical maturation. The identified association between cortical maturation and attention in healthy development will help to inform studies of neuroimaging biomarkers of ADHD.

The genetic blueprint of major depressive disorder: contributions of imaging genetics studies

OBJECTIVES

To review neuroimaging intermediate phenotypes of MDD and their relation to genetic risk variants.

METHODS

A systematic literature search of peer-reviewed English language articels using PubMed ( www.pubmed.org ) was performed.

RESULTS

Comprehensive evidence on the influence of serotonergic genes (SLC6A4, HTR1A, MAOA, TPH2) and BDNF on the following neural intermediate phenotypes is displayed: amygdala reactivity, coupling of amygdala-anterior cingulate cortex (ACC) activity, ACC volume, hippocampal volume and serotonin receptor 1A (5-HT1A) binding potential (BP).

CONCLUSIONS

Intermediate phenotypes may bridge the gap between genotype and phenotype by reducing the impreciseness of psychiatric phenotypes and yield more insights into the underlying biology.

Cognitive regulation of emotion in bipolar I disorder and unaffected biological relatives

OBJECTIVE

We examined the use of particular cognitive strategies for regulating negative emotion in relation to mood and temperament in BD-I, unaffected relatives of bipolar patients (UR), and healthy controls (HC).

METHOD

Participants were 105 patients with BD-I, 124 UR, and 63 HC; all participants completed the Cognitive Emotion Regulation Questionnaire (CERQ), the Depression Anxiety Stress Scales (DASS), and the Hypomanic Personality Scale (HPS).

RESULTS

The BD-I group reported more frequent use of rumination, catastrophizing and self-blame, and less frequent use of putting into perspective, in response to negative life events, relative to the UR and HC groups. In BD-I, more frequent use of rumination was associated with increased DASS and HPS scores. By contrast, within the UR group, more frequent use of catastrophizing and self-blame were associated with increased DASS and HPS scores. In all participants, less frequent use of adaptive cognitive reframing strategies (e.g. putting into perspective) were associated with increased DASS scores.

CONCLUSION

Both BD-I and UR groups reported more frequent use of maladaptive regulatory strategies previously associated with depression. Emotion regulation strategies of catastrophizing, self-blame, and cognitive reframing techniques may be associated with vulnerability for mood disorders, with the latter active within the general population regardless of biological vulnerability to disorder.

Posterior cortical atrophy: an exemplar for renovating diagnostic formulation in neuropsychiatry

Neurodegenerative dementias represent among the most clinically and pathologically complex syndromes in neuropsychiatry. Phenomenologically protean, and often initially presenting with subtle subsyndromal characteristics, neurodegenerative behavioral syndromes can manifest with an assortment of cognitive, mood, personality, and comportmental changes, often alloyed with elementary neurologic (e.g., motor) signs. A range of pathogenic mechanisms (e.g., amyloid plaques, Pick bodies, etc) typically underlie corresponding clinical syndromes. However, overlap in both clinical expression and histopathologic comorbidities frequently exist among cortical and subcortical neurodegenerative disorders. Moreover, secondary central nervous system pathologies (e.g., cerebrovascular disease) commonly coexist with neurodegenerative processes, further complicating clinical phenomenology-based nosologic categorization. Evolving insight into the etiologic mechanisms of neurodegenerative dementias, and correspondingly improving potential for intervention, require more precise differentiation among dementia subtypes and comprehensive identification of contemporaneous neurodegenerative processes. Increasing appreciation of this diagnostic complexity is prompting the need for renovation of existing diagnostic schemas. We address these issues by reviewing the atypical dementia type known as posterior cortical atrophy. We then use posterior cortical atrophy as an exemplar for renovating neuropsychiatric diagnostic classification to better account for the layered complexity of clinical and pathologic domains needing to be characterized to accurately and completely diagnose neuropsychiatric disturbances.

An integrated genome research network for studying the genetics of alcohol addiction

Alcohol drinking is highly prevalent in many cultures and contributes to the global burden of disease. In fact, it was shown that alcohol constitutes 3.2% of all worldwide deaths in the year 2006 and is linked to more than 60 diseases, including cancers, cardiovascular diseases, liver cirrhosis, neuropsychiatric disorders, injuries and foetal alcohol syndrome. Alcoholism, which has been proven to have a high genetic load, is one potentially fatal consequence of chronic heavy alcohol consumption, and may be regarded as one of the most prevalent neuropsychiatric diseases afflicting our society today. The aim of the integrated genome research network 'Genetics of Alcohol Addiction'--which is a German inter-/trans-disciplinary life science consortium consisting of molecular biologists, behavioural pharmacologists, system biologists with mathematicians, human geneticists and clinicians--is to better understand the genetics of alcohol addiction by identifying and validating candidate genes and molecular networks involved in the aetiology of this pathology. For comparison, addictive behaviour to other drugs of abuse (e.g. cocaine) is studied as well. Here, we present an overview of our research consortium, the current state of the art on genetic research in the alcohol field, and list finally several of our recently published research highlights. As a result of our scientific efforts, better insights into the molecular and physiological processes underlying addictive behaviour will be obtained, new targets and target networks in the addicted brain will be defined, and subsequently, novel and individualized treatment strategies for our patients will be delivered.

Reconsidering anhedonia in depression: lessons from translational neuroscience

Anhedonia is a core symptom of major depressive disorder (MDD), the neurobiological mechanisms of which remain poorly understood. Despite decades of speculation regarding the role of dopamine (DA) in anhedonic symptoms, empirical evidence has remained elusive, with frequent reports of contradictory findings. In the present review, we argue that this has resulted from an underspecified definition of anhedonia, which has failed to dissociate between consummatory and motivational aspects of reward behavior. Given substantial preclinical evidence that DA is involved primarily in motivational aspects of reward, we suggest that a refined definition of anhedonia that distinguishes between deficits in pleasure and motivation is essential for the purposes of identifying its neurobiological substrates. Moreover, bridging the gap between preclinical and clinical models of anhedonia may require moving away from the conceptualization of anhedonia as a steady-state, mood-like phenomena. Consequently, we introduce the term "decisional anhedonia" to address the influence of anhedonia on reward decision-making. These proposed modifications to the theoretical definition of anhedonia have implications for research, assessment and treatment of MDD.