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Background: First rank symptoms (FRS) of schizophrenia have been used for decades for diagnostic purposes. In the new version of the DSM-5, the American Psychiatric Association (APA) has abolished any further reference to FRS of schizophrenia and treats them like any other "criterion A' symptom (e.g. any kind of hallucination or delusion) with regard to their diagnostic implication. The ICD-10 is currently under revision and may follow suit. In this review, we discuss central points of criticism that are directed against the continuous use of first rank symptoms (FRS) to diagnose schizophrenia.
Context. Globular clusters (GCs) are established emitters of high-energy (HE, 100 MeV < E < 100 GeV) gamma-ray radiation which could originate from the cumulative emission of the numerous millisecond pulsars (msPSRs) in the clusters’ cores or from inverse Compton (IC) scattering of relativistic leptons accelerated in the GC environment. These stellar clusters could also constitute a new class of sources in the very-high-energy (VHE, E > 100 GeV) gamma-ray regime, judging from the recent detection of a signal from the direction of Terzan 5 with the H.E.S.S. telescope array. Aims. To search for VHE gamma-ray sources associated with other GCs, and to put constraints on leptonic emission models, we systematically analyzed the observations towards 15 GCs taken with the H. E. S. S. array of imaging atmospheric Cherenkov telescopes. Methods. We searched for point-like and extended VHE gamma-ray emission from each GC in our sample and also performed a stacking analysis combining the data from all GCs to investigate the hypothesis of a population of faint emitters. Assuming IC emission as the origin of the VHE gamma-ray signal from the direction of Terzan 5, we calculated the expected gamma-ray flux from each of the 15 GCs, based on their number of millisecond pulsars, their optical brightness and the energy density of background photon fields. Results. We did not detect significant VHE gamma-ray emission from any of the 15 GCs in either of the two analyses. Given the uncertainties related to the parameter determinations, the obtained flux upper limits allow to rule out the simple IC/msPSR scaling model for NGC6388 and NGC7078. The upper limits derived from the stacking analyses are factors between 2 and 50 below the flux predicted by the simple leptonic scaling model, depending on the assumed source extent and the dominant target photon fields. Therefore, Terzan 5 still remains exceptional among all GCs, as the VHE gamma-ray emission either arises from extra-ordinarily efficient leptonic processes, or from a recent catastrophic event, or is even unrelated to the GC itself.
Gamma-ray line signatures can be expected in the very-high-energy (E-gamma > 100 GeV) domain due to self-annihilation or decay of dark matter (DM) particles in space. Such a signal would be readily distinguishable from astrophysical gamma-ray sources that in most cases produce continuous spectra that span over several orders of magnitude in energy. Using data collected with the H. E. S. S. gamma-ray instrument, upper limits on linelike emission are obtained in the energy range between similar to 500 GeV and similar to 25 TeV for the central part of the Milky Way halo and for extragalactic observations, complementing recent limits obtained with the Fermi-LAT instrument at lower energies. No statistically significant signal could be found. For monochromatic gamma-ray line emission, flux limits of (2 x 10(-7)-2 x 10(-5)) m(-2)s(-1)sr(-1) and (1 x 10(-8)- 2 x 10(-6)) m(-2)s(-1)sr(-1) are obtained for the central part of the Milky Way halo and extragalactic observations, respectively. For a DM particle mass of 1 TeV, limits on the velocity- averaged DM annihilation cross section <sigma upsilon >(chi chi ->gamma gamma) reach similar to 10(-27)cm(3)s(-1), based on the Einasto parametrization of the Galactic DM halo density profile. DOI: 10.1103/PhysRevLett.110.041301
Background Aversive stimuli in the environment influence human actions. This includes valence-dependent influences on action selection, e.g., increased avoidance but decreased approach behavior. However, it is yet unclear how aversive stimuli interact with complex learning and decision-making in the reward and avoidance domain. Moreover, the underlying computational mechanisms of these decision-making biases are unknown. Methods To elucidate these mechanisms, 54 healthy young male subjects performed a two-step sequential decision-making task, which allows to computationally model different aspects of learning, e.g., model-free, habitual, and model-based, goal-directed learning. We used a within-subject design, crossing task valence (reward vs. punishment learning) with emotional context (aversive vs. neutral background stimuli). We analyzed choice data, applied a computational model, and performed simulations. Results Whereas model-based learning was not affected, aversive stimuli interacted with model-free learning in a way that depended on task valence. Thus, aversive stimuli increased model-free avoidance learning but decreased model-free reward learning. The computational model confirmed this effect: the parameter lambda that indicates the influence of reward prediction errors on decision values was increased in the punishment condition but decreased in the reward condition when aversive stimuli were present. Further, by using the inferred computational parameters to simulate choice data, our effects were captured. Exploratory analyses revealed that the observed biases were associated with subclinical depressive symptoms. Conclusion Our data show that aversive environmental stimuli affect complex learning and decision-making, which depends on task valence. Further, we provide a model of the underlying computations of this affective modulation. Finally, our finding of increased decision-making biases in subjects reporting subclinical depressive symptoms matches recent reports of amplified Pavlovian influences on action selection in depression and suggests a potential vulnerability factor for mood disorders. We discuss our findings in the light of the involvement of the neuromodulators serotonin and dopamine.
Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation.
Photoaddressable alignment layers for fluorescent polymers in polarized electroluminescence devices
(2002)
Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping ongoing thought and behavior. The influence of pavlovian stimuli on ongoing behavior is paradigmatically measured by pavlovian-to-instrumental transfer (PIT) tasks. These involve multiple stages and are complex. Whether increased PIT is involved in human alcohol dependence is uncertain. We therefore aimed to establish and validate a modified PIT paradigm that would be robust, consistent and tolerated by healthy controls as well as by patients suffering from alcohol dependence, and to explore whether alcohol dependence is associated with enhanced PIT. Methods: Thirty-two recently detoxified alcohol-dependent patients and 32 age- and gender-matched healthy controls performed a PIT task with instrumental go/no-go approach behaviors. The task involved both pavlovian stimuli associated with monetary rewards and losses, and images of drinks. Results: Both patients and healthy controls showed a robust and temporally stable PIT effect. Strengths of PIT effects to drug-related and monetary conditioned stimuli were highly correlated. Patients more frequently showed a PIT effect, and the effect was stronger in response to aversively conditioned CSs (conditioned suppression), but there was no group difference in response to appetitive CSs. Conclusion: The implementation of PIT has favorably robust properties in chronic alcohol-dependent patients and in healthy controls. It shows internal consistency between monetary and drug-related cues. The findings support an association of alcohol dependence with an increased propensity towards PIT.
Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus–action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian–instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.
In detoxified alcohol-dependent patients, alcohol-related stimuli can promote relapse. However, to date, the mechanisms by which contextual stimuli promote relapse have not been elucidated in detail. One hypothesis is that such contextual stimuli directly stimulate the motivation to drink via associated brain regions like the ventral striatum and thus promote alcohol seeking, intake and relapse. Pavlovian-to-Instrumental-Transfer (PIT) may be one of those behavioral phenomena contributing to relapse, capturing how Pavlovian conditioned (contextual) cues determine instrumental behavior (e.g. alcohol seeking and intake). We used a PIT paradigm during functional magnetic resonance imaging to examine the effects of classically conditioned Pavlovian stimuli on instrumental choices in n=31 detoxified patients diagnosed with alcohol dependence and n=24 healthy controls matched for age and gender. Patients were followed up over a period of 3 months. We observed that (1) there was a significant behavioral PIT effect for all participants, which was significantly more pronounced in alcohol-dependent patients; (2) PIT was significantly associated with blood oxygen level-dependent (BOLD) signals in the nucleus accumbens (NAcc) in subsequent relapsers only; and (3) PIT-related NAcc activation was associated with, and predictive of, critical outcomes (amount of alcohol intake and relapse during a 3 months follow-up period) in alcohol-dependent patients. These observations show for the first time that PIT-related BOLD signals, as a measure of the influence of Pavlovian cues on instrumental behavior, predict alcohol intake and relapse in alcohol dependence.