Gaze intersection points reveal the onset of visual processing during eye and head movement.

This study explored the dynamics of steady-state visual evoked potentials (SSVEPs) amid unrestricted head and eye movements using immersive virtual reality (VR) to concurrently record eye and head movement data with a 64-channel electroencephalogram (EEG) during a visual fixation task. Employing a dual-condition approach-eye-shifting and head-turning-the trials were time-locked to stimulus onset, Gaze Intersection Point (GIP) onset, and fixation onset. Eye and head velocity, Canonical Correlation Analysis (CCA) correlation, and Inter-Trial Coherence (ITC) were computed across the trial duration.

"Blue Sky Effect": Contextual Influences on Pupil Size During Naturalistic Visual Search.

Pupil size is influenced by cognitive and non-cognitive factors. One of the strongest modulators of pupil size is scene luminance, which complicates studies of cognitive pupillometry in environments with complex patterns of visual stimulation. To help understand how dynamic visual scene statistics influence pupil size during an active visual search task in a visually rich 3D virtual environment (VE), we analyzed the correlation between pupil size and intensity changes of image pixels in the red, green, and blue (RGB) channels within a large window (~14 degrees) surrounding the gaze position over time.

Dissociable mappings of tonic and phasic pupillary features onto cognitive processes involved in mental arithmetic.

Pupil size modulations have been used for decades as a window into the mind, and several pupillary features have been implicated in a variety of cognitive processes. Thus, a general challenge facing the field of pupillometry has been understanding which pupil features should be most relevant for explaining behavior in a given task domain. In the present study, a longitudinal design was employed where participants completed 8 biweekly sessions of a classic mental arithmetic task for the purposes of teasing apart the relationships between tonic/phasic pupil features (baseline, peak amplitude, peak latency) and two task-related cognitive processes including mental processing load (indexed by math question difficulty) and decision making (indexed by response times).

The Benefits and Challenges of Implementing Motivational Features to Boost Cognitive Training Outcome.

In the current literature, there are a number of cognitive training studies that use N-back tasks as their training vehicle; however, the interventions are often bland, and many studies suffer from considerable attrition rates. An increasingly common approach to increase participant engagement has been the implementation of motivational features in training tasks; yet, the effects of such "gamification" on learning have been inconsistent. To shed more light on those issues, here, we report the results of a training study conducted at two Universities in Southern California.

The Influence of Feedback on Task-Switching Performance: A Drift Diffusion Modeling Account.

Task-switching is an important cognitive skill that facilitates our ability to choose appropriate behavior in a varied and changing environment. Task-switching training studies have sought to improve this ability by practicing switching between multiple tasks. However, an efficacious training paradigm has been difficult to develop in part due to findings that small differences in task parameters influence switching behavior in a non-trivial manner.

Pupillometry as a glimpse into the neurochemical basis of human memory encoding.

Neurochemical systems are well studied in animal learning; however, ethical issues limit methodologies to explore these systems in humans. Pupillometry provides a glimpse into the brain's neurochemical systems, where pupil dynamics in monkeys have been linked with locus coeruleus (LC) activity, which releases norepinephrine (NE) throughout the brain. Here, we use pupil dynamics as a surrogate measure of neurochemical activity to explore the hypothesis that NE is involved in modulating memory encoding.

Uncertainty in fast task-irrelevant perceptual learning boosts learning of images in women but not men.

A key tenet of models of reinforcement learning is that learning is most desirable in the times of maximum uncertainty. Here we examine the role of uncertainty in the paradigm of fast task-irrelevant perceptual learning (fast-TIPL), where stimuli that are consistently presented at relevant points in times (e.g.