Effects of word presentation during treadmill walking on episodic memory and gait.

Entrainment emerges when oscillatory movements synchronize with environmental stimuli processing. The purpose of this experiment was to assess how cognitive-motor entrainment during a dual-task would influence the quality of gait and affect episodic long-term memory. Twenty-one participants (22.

Physical Activity and Children's Episodic Memory: A Meta-Analysis.

Purpose: The purpose of this review was to evaluate the effects of physical activity on children's free recall, cued recall, and recognition episodic memory and to explore potential moderating factors.

Methods: The following databases were searched: PubMed, ERIC, APA Psych Info, CINHAL, SPORTDiscus, and Google Scholar. Studies were included if: (1) participants were aged 4-18 years, (2) participants were typically developed, (3) participants were randomized to groups, (4) interventions employed gross movements, (5) sedentary group was used for control, (6) memory tests were quantitative, and (7) employed acute or chronic intervention.

The effects of physical activity timing and complexity on episodic memory: A randomized controlled trial.

The role of two types of acute physical activity (PA) bouts were assessed on young adults' free-recall and recognition memory in two experiments, which differed in the temporal relation of PA and word encoding. Before or following training on the Rey Auditory Verbal Learning Task, participants performed a simple two-step dance, a complex four-step dance, or remained seated. Hypotheses proposed that PA prior to encoding and complex PA would enhance PA's mnemonic benefits.

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it.