Pupil response hazard rates predict perceived gaze durations

We investigated the mechanisms for evaluating perceived gaze-shift duration. Timing relies on the accumulation of endogenous physiological signals. Here we focused on arousal, measured through pupil dilation, as a candidate timing signal. Participants timed gaze-shifts performed by face stimuli in a Standard/Probe comparison task. Pupil responses were binned according to “Longer/Shorter” judgements in trials where Standard and Probe were identical. This ensured that pupil responses reflected endogenous arousal fluctuations opposed to differences in stimulus content. We found that pupil hazard rates predicted the classification of sub-second intervals (steeper dilation =“Longer” classifications). This shows that the accumulation of endogenous arousal signals informs gaze-shift timing judgements. We also found that participants relied exclusively on the 2nd stimulus to perform the classification, providing insights into timing strategies under conditions of maximum uncertainty. We observed no dissociation in pupil responses when timing equivalent neutral spatial displacements, indicating that a stimulus-dependent timer exploits arousal to time gaze-shifts

Temporal Accumulation and Decision Processes in the Duration Bisection Task Revealed by Contingent Negative Variation

The duration bisection paradigm is a classic task used to examine how humans and other animals perceive time. Typically, participants first learn short and long anchor durations and are subsequently asked to classify probe durations as closer to the short or long anchor duration. However, the specific representations of time and the decision rules applied in this task remain the subject of debate. For example, researchers have questioned whether participants actually use representations of the short and long anchor durations in the decision process rather than merely a response threshold that is derived from those anchor durations. Electroencephalographic (EEG) measures, like the contingent negative variation (CNV), can provide information about the perceptual and cognitive processes that occur between the onset of the timing stimulus and the motor response. The CNV has been implicated as an electrophysiological marker of interval timing processes such as temporal accumulation, representation of the target duration, and the decision that the target duration has been attained. We used the CNV to investigate which durations are involved in the bisection categorization decision. The CNV increased in amplitude up to the value of the short anchor, remained at a constant level until about the geometric mean (GM) of the short and long anchors, and then began to resolve. These results suggest that the short anchor and the GM of the short and long anchors are critical target durations used in the bisection categorization decision process. In addition, larger mean N1P2 amplitude differences were associated with larger amplitude CNVs, which may reflect the participant’s precision in initiating timing on each trial across a test session. Overall, the results demonstrate the value of using scalp-recorded EEG to address basic questions about interval timing

Development of a model on factors affecting instrumental activities of daily living in people with mild cognitive impairment - A Delphi study

Introduction: The level of function of instrumental activities of daily living (IADL) is crucial for a person's autonomy. A clear understanding of the nature of IADL and its limitations in people with mild cognitive impairment (MCI) is lacking. Literature suggests numerous possible influencing factors, e.g. cognitive function, but has not considered other domains of human functioning, such as environmental factors. Our aim was to develop a comprehensive model of IADL functioning that depicts the relevant influencing factors. Methods: We conducted a four-round online Delphi study with a sample of international IADL experts (N = 69). In the first round, panelists were asked to mention all possible relevant cognitive and physical function factors, as well as environmental and personal factors, that influence IADL functioning. In the subsequent rounds, panelists rated the relevance of these factors. Consensus was defined as: 1) ≥70% agreement between panelists on a factor, and 2) stability over two successive rounds. Results: Response rates from the four rounds were high (83 to 100%). In the first round, 229 influencing factors were mentioned, whereof 13 factors reached consensus in the subsequent rounds. These consensual factors were used to build a model of IADL functioning. The final model included: five cognitive function factors (i.e. memory, attention, executive function, and two executive function subdomains -problem solving / reasoning and organization / planning); five physical function factors (i.e. seeing functions, hearing functions, balance, gait / mobility functions and functional mobility functions); two environmental factors (i.e. social network / environment and support of social network / environment); and one personal factor (i.e. education). Conclusions: This study proposes a comprehensive model of IADL functioning in people with MCI. The results from this Delphi study suggest that IADL functioning is not merely affected by cognitive function factors, but also by physical function factors, environmental factors and personal factors. The multiplicity of factors mentioned in the first round also underlines the individuality of IADL functioning in people with MCI. This model may serve as a basis for future research in IADL functioning in people with MCI