Work

Temporal dynamics of integration and individuation: Insights from temporal averaging and crowding

Year: 2025

Type: article

Abstract: Individuating a single item presented within a continuous sequence of items requires segregating its signal from that of the other items. In contrast, representing a global aspect of the sequence, such as its average orientation, involves integration of information across time. Individuation and integration allow us to focus on individual events while maintaining an overall perception of our environment. To examine the relations between temporal averaging and individuation, we measured orientation averaging over short and long timescales using the same stimuli and orientation-estimation procedure previously used to measure individuation. Participants reported the average orientation of a sequence of three oriented items separated by either short (SOAs<150 ms) or long intervals (SOAs>150 ms). Analysis of the error distribution and mixture-modeling revealed distinct patterns of results for the different tasks and timescales, but also some similarities, particularly for the short timescale. In this timescale, the relative contribution of each individual item to the final response was similar across tasks, indicating the involvement of low-level factors operating regardless of the task. With the long timescale, the two tasks showed dissociable pattern across all performance aspects, except guessing rate, indicating that long-scale individuation and averaging engage mainly higher-level, task-related processes. Importantly, regardless of timescale, estimation errors in these tasks were best described by different models: in integration they primarily reflected unequal weighting of the averaged items, whereas in individuation they reflected imprecise target encoding with occasional misreports of distractors. Together, the findings reveal dissociable dynamics for integration and individuation.

Source: Cognition

DOI: 10.1016/j.cognition.2025.106374

Authors: Ilanit Hochmitz, Yaffa Yeshurun, Amit Yashar

Institution: University of Haifa

Language: English

Topic: Visual perception and processing mechanisms

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,910

Funder: Israel Science Foundation