Tracking the subprocesses of decision-based action in the human frontal lobes

Situationally adaptive behavior relies on the identification of relevant target stimuli, the evaluation of these with respect to the current context and the selection of an appropriate action. We used functional magnetic resonance imaging (fMRI) to disentangle the neural networks underlying these processes within a single task. Our results show that activation of mid-ventrolateral prefrontal cortex (PFC) reflects the perceived presence of a target stimulus regardless of context, whereas context-appropriate evaluation is subserved by mid-dorsolateral PFC. Enhancing demands on response selection by means of response conflict activated a network of regions, all of which are directly connected to motor areas. On the midline, rostral anterior paracingulate cortex was found to link target detection and response selection by monitoring for the presence of behaviorally significant conditions. In summary, we provide new evidence for process-specific functional dissociations in the frontal lobes. In target-centered processing, target detection in the VLPFC is separable from contextual evaluation in the DLPFC. Response-centered processing in motor-associated regions occurs partly in parallel to these processes, which may enhance behavioral efficiency, but it may also lead to reaction time increases when an irrelevant response tendency is elicited.

A Normative Theory of Forgetting: Lessons from the Fruit Fly

Recent experiments revealed that the fruit fly Drosophila melanogaster has a dedicated mechanism for forgetting: blocking the G-protein Rac leads to slower and activating Rac to faster forgetting. This active form of forgetting lacks a satisfactory functional explanation. We investigated optimal decision making for an agent adapting to a stochastic environment where a stimulus may switch between being indicative of reward or punishment. Like Drosophila, an optimal agent shows forgetting with a rate that is linked to the time scale of changes in the environment. Moreover, to reduce the odds of missing future reward, an optimal agent may trade the risk of immediate pain for information gain and thus forget faster after aversive conditioning. A simple neuronal network reproduces these features. Our theory shows that forgetting in Drosophila appears as an optimal adaptive behavior in a changing environment. This is in line with the view that forgetting is adaptive rather than a consequence of limitations of the memory system.

Messung dispositioneller Selbstkontroll-Kapazität: Eine deutsche Adaptation der Kurzform der Self-Control Scale (SCS-K-D)

Self-control is defined as the overriding or modification of one’s own response tendencies. Dispositional self control capacity is positively linked to various kinds of adaptive behavior. In order to economically measure self-control capacity in German-speaking samples, the brief version of the Self-Control Scale by Tangney, Baumeister and Boone (2004) was adapted into German. The translated entire Self-Control Scale consisting of 36 items was administered to university students (N = 316, study 1) and secondary school students (N = 335, study 2). The brief version consisting of 13 items, which were included in the entire scale, proved to be one-dimensional, reliable, and valid in terms of expected correlations with criteria. The comparison between the brief and the entire scale showed that the costs of the more economical brief measure with regard to reliability and validity are low.

Functional lateralization of the anterior insula during feedback processing

Effective adaptive behavior rests on an appropriate understanding of how much responsibility we have over outcomes in the environment. This attribution of agency to ourselves or to an external event influences our behavioral and affective response to the outcomes. Despite its special importance to understanding human motivation and affect, the neural mechanisms involved in self-attributed rewards and punishments remain unclear. Previous evidence implicates the anterior insula (AI) in evaluating the consequences of our own actions. However, it is unclear if the AI has a general role in feedback evaluation (positive and negative) or plays a specific role during error processing. Using functional magnetic resonance imaging and a motion prediction task, we investigate neural responses to self- and externally attributed monetary gains and losses. We found that attribution effects vary according to the valence of feedback: significant valence × attribution interactions in the right AI, the anterior cingulate cortex (ACC), the midbrain, and the right ventral putamen. Self-attributed losses were associated with increased activity in the midbrain, the ACC and the right AI, and negative BOLD response in the ventral putamen. However, higher BOLD activity to self-attributed feedback (losses and gains) was observed in the left AI, the thalamus, and the cerebellar vermis. These results suggest a functional lateralization of the AI. The right AI, together with the midbrain and the ACC, is mainly involved in processing the salience of the outcome, whereas the left is part of a cerebello-thalamic-cortical pathway involved in cognitive control processes important for subsequent behavioral adaptations.

Appraisal-driven somatovisceral response patterning: effects of intrinsic pleasantness and goal conduciveness.

Several componential emotion theories suggest that appraisal outcomes trigger characteristic somatovisceral changes that facilitate information processing and prepare the organism for adaptive behavior. The current study tested predictions derived from Scherer's Component Process Model. Participants viewed unpleasant and pleasant pictures (intrinsic pleasantness appraisal) and were asked to concurrently perform either an arm extension or an arm flexion, leading to an increase or a decrease in picture size. Increasing pleasant stimuli and decreasing unpleasant stimuli were considered goal conducive; decreasing pleasant stimuli and increasing unpleasant stimuli were considered goal obstructive (goal conduciveness appraisal). Both appraisals were marked by several somatovisceral changes (facial electromyogram, heart rate (HR)). As predicted, the changes induced by the two appraisals showed similar patterns. Furthermore, HR results, compared with data of earlier studies, suggest that the adaptive consequences of both appraisals may be mediated by stimulus proximity.

Intracranial EEG correlates of implicit relational inference within the hippocampus

Drawing inferences from past experiences enables adaptive behavior in future situations. Inference has been shown to depend on hippocampal processes. Usually, inference is considered a deliberate and effortful mental act which happens during retrieval, and requires the focus of our awareness. Recent fMRI studies hint at the possibility that some forms of hippocampus-dependent inference can also occur during encoding and possibly also outside of awareness. Here, we sought to further explore the feasibility of hippocampal implicit inference, and specifically address the temporal evolution of implicit inference using intracranial EEG. Presurgical epilepsy patients with hippocampal depth electrodes viewed a sequence of word pairs, and judged the semantic fit between two words in each pair. Some of the word pairs entailed a common word (e.g.,‘winter - red’, ‘red - cat’) such that an indirect relation was established in following word pairs (e.g, ‘winter - cat’). The behavioral results suggested that drawing inference implicitly from past experience is feasible because indirect relations seemed to foster ‘fit’ judgments while the absence of indirect relations fostered 'do not fit' judgments, even though the participants were unaware of the indirect relations. A event-related potential (ERP) difference emerging 400 ms post-stimulus was evident in the hippocampus during encoding, suggesting that indirect relations were already established automatically during encoding of the overlapping word pairs. Further ERP differences emerged later post-stimulus (1500 ms), were modulated by the participants' responses and were evident during encoding and test. Furthermore, response-locked ERP effects were evident at test. These ERP effects could hence be a correlate of the interaction of implicit memory with decision-making. Together, the data map out a time-course in which the hippocampus automatically integrates memories from discrete but related episodes to implicitly influence future decision making.

Maternal modulation of natal dispersal in a passerine bird: An adaptive strategy to cope with parasitism?

The decision of how far to disperse from the natal territory has profound and long-lasting consequences for young animals, yet the optimal dispersal behavior often depends on environmental factors that are difficult or impossible to assess by inexperienced juveniles. Natural selection thus favors mechanisms that allow the adaptive and flexible adjustment of the offspring's dispersal behavior by their parents via either paternal or maternal effects. Here we show that different dispersal strategies maximize the reproductive success of young great tits (Parus major) originating from a parasite-infested or a parasite-free nest and demonstrate that differential transfer of maternal yolk androgens in response to parasitism can result in a modification of the offspring's dispersal behavior that appears adaptive. It demonstrates that prenatal maternal effects are an important yet so far neglected determinant of natal dispersal and highlights the potential importance of maternal effects in mediating coevolutionary processes in host-parasite systems.

Swimming and diving behavior in apes (Pan troglodytes and Pongo pygmaeus): first documented report

Extant hominoids, including humans, are well known for their inability to swim instinctively. We report swimming and diving in two captive apes using visual observation and video recording. One common chimpanzee and one orangutan swam repeatedly at the water surface over a distance of 2-6 m; both individuals submerged repeatedly. We show that apes are able to overcome their negative buoyancy by deliberate swimming, using movements which deviate from the doggy-paddle pattern observed in other primates. We suggest that apes' poor swimming ability is due to behavioral, anatomical, and neuromotor changes related to an adaptation to arboreal life in their early phylogeny. This strong adaptive focus on arboreal life led to decreased opportunities to interact with water bodies and consequently to a reduction of selective pressure to maintain innate swimming behavior. As the doggy paddle is associated with quadrupedal walking, a deviation from terrestrial locomotion might have interfered with the fixed rhythmic action patterns responsible for innate swimming.

CAOR: Context-aware Adaptive Opportunistic Routing in Mobile Ad-hoc Networks

Opportunistic routing (OR) employs a list of candidates to improve wireless transmission reliability. However, conventional list-based OR restricts the freedom of opportunism, since only the listed nodes are allowed to compete for packet forwarding. Additionally, the list is generated statically based on a single network metric prior to data transmission, which is not appropriate for mobile ad-hoc networks (MANETs). In this paper, we propose a novel OR protocol - Context-aware Adaptive Opportunistic Routing (CAOR) for MANETs. CAOR abandons the idea of candidate list and it allows all qualified nodes to participate in packet transmission. CAOR forwards packets by simultaneously exploiting multiple cross-layer context information, such as link quality, geographic progress, energy, and mobility.With the help of the Analytic Hierarchy Process theory, CAOR adjusts the weights of context information based on their instantaneous values to adapt the protocol behavior at run-time. Moreover, CAOR uses an active suppression mechanism to reduce packet duplication. Simulation results show that CAOR can provide efficient routing in highly mobile environments. The adaptivity feature of CAOR is also validated.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

The association of feeding behavior with the resistance and tolerance to parasites in recently diverged sticklebacks

Divergent natural selection regimes can contribute to adaptive population divergence, but can be sensitive to human-mediated environmental change. Nutrient loading of aquatic ecosystems, for example, might modify selection pressures by altering the abundance and distribution of resources and the prevalence and infectivity of parasites. Here, we used a mesocosm experiment to test for interactive effects of nutrient loading and parasitism on host condition and feeding ecology. Specifically, we investigated whether the common fish parasite Gyrodactylus sp. differentially affected recently diverged lake and stream ecotypes of three-spined stickleback (Gasterosteus aculeatus). We found that the stream ecotype had a higher resistance to Gyrodactylus sp. infections than the lake ecotype, and that both ecotypes experienced a cost of parasitism, indicated by negative relationships between parasite load and both stomach fullness and body condition. Overall, our results suggest that in the early stages of adaptive population divergence of hosts, parasites can affect host resistance, body condition, and diet.