Brain network dynamics codify heterogeneity in seizure propagation

Dynamic functional brain connectivity facilitates adaptive cognition and behavior. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A central but unresolved question concerns the mechanisms by which extraordinarily diverse dynamics of seizures emerge. Here, we apply a graph-theoretical approach to assess dynamic reconfigurations in the functional brain connectivity before, during, and after seizures that display heterogeneous propagation patterns despite sharing similar origins. We demonstrate unique reconfigurations in globally-defined network properties preceding seizure onset that predict propagation patterns of impending seizures, and in locally-defined network properties that differentiate post-onset dynamics. These results characterize quantitative network features underlying the heterogeneity of seizure dynamics and the accompanying clinical manifestations. Decoding these network properties could improve personalized preventative treatment strategies for epilepsy as well as other neurological disorders.

Value shapes the structure of schematic representations in the medial prefrontal cortex

Adaptive cognition is fostered by knowledge about the structure and value of our environment. Here, we hypothesize that these two kinds of information are inherently intertwined as value-weighted schemas in the medial prefrontal cortex (mPFC). Schemas (e.g., of a social network) emerge by extracting commonalities across experiences and can be understood as graphs comprising nodes (e.g., people) and edges (e.g., their relationships). We sampled information about unique real-life environments (i.e., about personally familiar people and places) and probed the neural representations of their schemas with fMRI. Using representational similarity analysis, we show that the mPFC encodes both, the nodes and edges of the schemas. Critically, the strength of the edges is not only determined by experience and centrality of a given node but also by its value. We thus account for the involvement of the mPFC in seemingly disparate functions and suggest that valuation emerges naturally from encoded memory representations.

Cognitive representations and the predictive brain depend heavily on the environment

In their scholarly target article, Gilead et al. explain how abstract mental representations and the predictive brain enable prospection and time-traveling. However, their exclusive focus on intrapsychic capacities misses an important point, namely, the degree to which mind and brain are tuned by the environment. This neglected aspect of adaptive cognition is discussed and illustrated from a cognitive-ecological perspective.

The Truth Is Around Here Somewhere

Recent years have seen a sharp acceleration in the publication of empirical studies on conspiracy beliefs. Collectively this work demonstrates markers of an energized but exploratory field still seeking theoretical focus and depth. The research has arrived at an inflection point that will lead to increased expectations for theory-driven work that tests specific predictions and arrives at answers with the potential to improve public discourse about conspiracy theories. Three specific lines of research can advance our understanding of the place of conspiracy beliefs in adaptive cognition: clearly defining the phenomenon under investigation, exploring the situational factors that contribute to conspiracy beliefs, and testing the positive as well as negative outcomes that result from conspiracy beliefs.

Learning from observation, feedback, and intervention in linear and non-linear task environments

This multiple-cue judgment study investigates whether we can manipulate the judgment strategy and increase accuracy in linear and non-linear cue–criterion environments just by changing the training mode. Three experiments show that accuracy in simple linear additive task environments are improved with feedback training and intervention training, while accuracy in complex multiplicative tasks are improved with observational training. The observed interaction effect suggests that the training mode invites different strategies that are adjusted as a function of experience to the demands from the underlying cue–criterion structure. Thus, feedback and the intervention training modes invite cue abstraction, an effortful but successful strategy in combination with simple linear task structures, and observational training invites exemplar memory processes, a simple but successful strategy in combination with complex non-linear task structures. The study discusses adaptive cognition and the implication of the different training modes across a life span and for clinical populations.