MAOA and mechanisms of panic disorder revisited: from bench to molecular psychotherapy.

Panic disorder with agoraphobia (PD/AG) is a prevalent mental disorder featuring a substantial complex genetic component. At present, only a few established risk genes exist. Among these, the gene encoding monoamine oxidase A (MAOA) is noteworthy given that genetic variation has been demonstrated to influence gene expression and monoamine levels. Long alleles of the MAOA-uVNTR promoter polymorphism are associated with PD/AG and correspond with increased enzyme activity. Here, we have thus investigated the impact of MAOA-uVNTR on therapy response, behavioral avoidance and brain activity in fear conditioning in a large controlled and randomized multicenter study on cognitive behavioral therapy (CBT) in PD/AG. The study consisted of 369 PD/AG patients, and genetic information was available for 283 patients. Carriers of the risk allele had significantly worse outcome as measured by the Hamilton Anxiety scale (46% responders vs 67%, P=0.017). This was accompanied by elevated heart rate and increased fear during an anxiety-provoking situation, that is, the behavioral avoidance task. All but one panic attack that happened during this task occurred in risk allele carriers and, furthermore, risk allele carriers did not habituate to the situation during repetitive exposure. Finally, functional neuroimaging during a classical fear conditioning paradigm evidenced that the protective allele is associated with increased activation of the anterior cingulate cortex upon presentation of the CS+ during acquisition of fear. Further differentiation between high- and low-risk subjects after treatment was observed in the inferior parietal lobes, suggesting differential brain activation patterns upon CBT. Taken together, we established that a genetic risk factor for PD/AG is associated with worse response to CBT and identify potential underlying neural mechanisms. These findings might govern how psychotherapy can include genetic information to tailor individualized treatment approaches.

Brain correlates of hypnotic paralysis-a resting-state fMRI study.

Hypnotic paralysis has been used since the times of Charcot to study altered states of consciousness; however, the underlying neurobiological correlates are poorly understood. We investigated human brain function during hypnotic paralysis using resting-state functional magnetic resonance imaging (fMRI), focussing on two core regions of the default mode network and the representation of the paralysed hand in the primary motor cortex. Hypnotic suggestion induced an observable left-hand paralysis in 19 participants. Resting-state fMRI at 3T was performed in pseudo-randomised order awake and in the hypnotic condition. Functional connectivity analyses revealed increased connectivity of the precuneus with the right dorsolateral prefrontal cortex, angular gyrus, and a dorsal part of the precuneus. Functional connectivity of the medial frontal cortex and the primary motor cortex remained unchanged. Our results reveal that the precuneus plays a pivotal role during maintenance of an altered state of consciousness. The increased coupling of selective cortical areas with the precuneus supports the concept that hypnotic paralysis may be mediated by a modified representation of the self which impacts motor abilities.

Neural correlates of trait anxiety in fear extinction.

BACKGROUND: Fear conditioning involves the amygdala as the main neural structure for learning fear responses whereas fear extinction mainly activates the inhibitory prefrontal cortex (PFC). In this study we investigated whether individual differences in trait anxiety affect amygdala and dorsal anterior cingulate cortex (dACC) activation during fear conditioning and extinction. METHOD: Thirty-two healthy subjects were investigated by functional magnetic resonance imaging (fMRI) at 3 T while performing a cued fear-conditioning task. All participants completed the trait version of the State-Trait Anxiety Inventory (STAI-T). Activations of the amygdala and the dACC were examined with respect to the effects of trait anxiety. RESULTS: Analysis of the fMRI data demonstrated enhanced activation in fear-related brain areas, such as the insula and the ACC, during both fear conditioning and extinction. Activation of the amygdala appeared only during the late acquisition phase whereas deactivation was observed during extinction. Regression analyses revealed that highly trait-anxious subjects exhibited sustained amygdala activation and reduced dACC involvement during the extinction of conditioned responses. CONCLUSIONS: This study reveals that high levels of trait anxiety are associated with both increased amygdala activation and reduced dACC recruitment during the extinction of conditioned fear. This hyper-responsivity of the amygdala and the deficient cognitive control during the extinction of conditioned fear in anxious subjects reflect an increased resistance to extinct fear responses and may thereby enhance the vulnerability to developing anxiety disorders.

Attenuated prefrontal activation during decision-making under uncertainty in schizophrenia: a multi-center fMRI study.

Decisions are called decisions under uncertainty when either prior information is incomplete or the outcomes of the decision are unclear. Alterations in these processes related to decisions under uncertainty have been linked to delusions. In patients with schizophrenia, the underlying neural networks have only rarely been studied. We aimed to disentangle the neural correlates of decision-making and relate them to neuropsychological and psychopathological parameters in a large sample of patients with schizophrenia and healthy subjects. Fifty-seven patients and fifty-seven healthy volunteers from six centers had to either indicate via button-press from which of two bottles red or blue balls were drawn (decision-making under uncertainty condition), or indicate whether eight red balls had been presented (baseline condition) while BOLD signal was measured with fMRI. Patients based their decisions on less conclusive evidence and had decreased activations in the underlying neural network, comprising of medial and lateral frontal as well as parietal areas, as compared to healthy subjects. While current psychopathology was not correlated with brain activation, positive symptoms led to longer decision latencies in patients. These results suggest that decision-making under uncertainty in schizophrenia is affected by a complex interplay of aberrant neural activation. Furthermore, reduced neuropsychological functioning in patients was related to impaired decision-making and task performance was modulated by distinct positive symptoms.

Investigation of decision-making under uncertainty in healthy subjects: a multi-centric fMRI study.

Decision-making is an everyday routine that entails several subprocesses. Decisions under uncertainty occur when either prior information is incomplete or the outcomes of the decision are unclear. The aim of the present study was to disentangle the neural correlates of information gathering as well as reaching a decision and to explore effects of uncertainty acceptance or avoidance in a large sample of healthy subjects. Sixty-four healthy volunteers performed a decision-making under uncertainty task in a multi-center approach while BOLD signal was measured with fMRI. Subjects either had to indicate via button press from which of two bottles red or blue balls were drawn (decision-making under uncertainty condition), or they had to indicate whether 8 red balls had been presented (baseline condition). During the information gathering phase (contrasted against the counting phase) a widespread network was found encompassing (pre-)frontal, inferior temporal and inferior parietal cortices. Reaching a decision was correlated with activations in the medial frontal cortex as well as the posterior cingulate and the precuneus. Effects of uncertainty acceptance were found within a network comprising of the superior frontal cortex as well as the insula and precuneus while uncertainty avoidance was correlated with activations in the right middle frontal cortex. The results depict two distinct networks for information gathering and the indication of having made a decision. While information-gathering networks are modulated by uncertainty avoidance and - acceptance, underlying networks of the decision itself are independent of these factors.

Dynamic causal modeling with genetic algorithms.

In the last years, dynamic causal modeling has gained increased popularity in the neuroimaging community as an approach for the estimation of effective connectivity from functional magnetic resonance imaging (fMRI) data. The algorithm calls for an a priori defined model, whose parameter estimates are subsequently computed upon the given data. As the number of possible models increases exponentially with additional areas, it rapidly becomes inefficient to compute parameter estimates for all models in order to reveal the family of models with the highest posterior probability. In the present study, we developed a genetic algorithm for dynamic causal models and investigated whether this evolutionary approach can accelerate the model search. In this context, the configuration of the intrinsic, extrinsic and bilinear connection matrices represents the genetic code and Bayesian model selection serves as a fitness function. Using crossover and mutation, populations of models are created and compared with each other. The most probable ones survive the current generation and serve as a source for the next generation of models. Tests with artificially created data sets show that the genetic algorithm approximates the most plausible models faster than a random-driven brute-force search. The fitness landscape revealed by the genetic algorithm indicates that dynamic causal modeling has excellent properties for evolution-driven optimization techniques.