Shaping Embodied Neural Networks for Adaptive Goal-directed Behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

Interpretability of the European Heart Failure Self-care Behaviour scale

Kim P Wagenaar,1 Berna DL Broekhuizen,1 Frans H Rutten,1 Anna Strömberg,2 Henk F van Stel,1 Arno W Hoes,1 Tiny Jaarsma2 1Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; 2Department of Social and Welfare Studies, Linköping University, Linköping, Sweden Objective: The European Heart Failure Self-care Behaviour scale (EHFScBs) is a valid patient-reported questionnaire to measure self-care behavior of heart failure (HF) patients. We assessed the interpretability of the EHFScBs.Methods: We used data of 1,023 HF patients. Interpretability refers to the clinical meaning of the score and its changes over time. We operationalized interpretability by evaluating distributions of EHFScBs scores across relevant HF subgroups by eyeballing, by testing the risk on hospitalizations and mortality of a plausible threshold, and by determining a clinically relevant minimal important change (MIC). The scale score ranged from 0 to 100, with a higher score meaning better self-care. A threshold of ≥70 was defined as adequate and <70 as inadequate self-care.Results: The EHFScBs scores were similarly normally distributed among the subgroups with a mean between 57.8 (SD 19.4) and 72.0 (SD 18.0). The 464 HF patients with adequate self-care had significantly less all-cause hospitalizations than the 559 patients with inadequate self-care.Conclusion: The degree of self-care showed to be independent of relevant HF subgroups. A single threshold of 70 accurately discriminated between patients with adequate and inadequate self-care.Practice implications: The threshold of 70 can be used in designing studies and informing health policy makers. Keywords: heart failure, self-care, interpretability, patient-reported outcome, threshold and minimal important chang