PubMed Health⌕ Search

PubMed · 16181438

Visual memory decay is deterministic.

Abstract

After observers see an object or pattern, their visual memory of what they have seen decays slowly over time. Nearly all current theories of vision assume that decay of short-term memory occurs because visual representations are progressively and randomly corrupted as time passes. We tested this assumption using psychophysical noise-masking methods, and we found that visual memory decays in a completely deterministic fashion. This surprising finding challenges current ideas about visual memory and sets a goal for future memory research: to characterize the deterministic "forgetting function" that describes how memories decay over time.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jason M Gold, Richard F Murray, Allison B Sekuler, Patrick J Bennett, Robert Sekuler. 2005. Visual memory decay is deterministic.. https://doi.org/10.1111/j.1467-9280.2005.01612.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

The effects of expanding patient choice of provider on waiting times: evidence from a policy experiment.

Long waiting times for inpatient treatment in the UK National Health Service have been a source of popular and political concern, and therefore a target for policy initiatives. In the London Patient Choice Project, patients at risk of breaching inpatient waiting time targets were offered the choice of an alternative hospital with a guaranteed shorter wait. This paper develops a simple theoretical model of the effect of greater patient choice on waiting times. It then uses a difference in difference econometric methodology to estimate the impact of the London choice project on ophthalmology waiting times. In line with the model predictions, the project led to shorter average waiting times in the London region and a convergence in waiting times amongst London hospitals.

Choice Behavior↗

Neural voting machines.

A "Winner-take-all" network is a computational mechanism for picking an alternative with the largest excitatory input. This choice is far from optimal when there is uncertainty in the strength of the inputs, and when information is available about how alternatives may be related. For some time, the Social Choice community has recognized that many other procedures will yield more robust winners. The Borda Count and the pair-wise Condorcet tally are among the most favored. If biological systems strive to optimize information aggregation, then it is of interest to examine the complexity of networks that implement these procedures. We offer two biologically feasible implementations that are relatively simple modifications of classical recurrent networks.

Choice Behavior↗