Evaluating persistence of shape information using a matching protocol

Ernest Greene; Michael J. Hautus; Ernest Greene; Michael J. Hautus

doi:10.3934/Neuroscience.2018.1.81

AIMS Neuroscience

2018, Volume 5, Issue 1: 81-96. doi: 10.3934/Neuroscience.2018.1.81

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Research article

Evaluating persistence of shape information using a matching protocol

Ernest Greene ^{1
,
,},
Michael J. Hautus ²

1.
Department of Psychology, University of Southern California, Los Angeles, USA
2.
School of Psychology, University of Auckland, Auckland, New Zealand

Received: 12 October 2017 Accepted: 09 January 2018 Published: 03 February 2018

Many laboratories have studied persistence of shape information, the goal being to better understand how the visual system mediates recognition of objects. Most have asked for recognition of known shapes, e.g., letters of the alphabet, or recall from an array. Recognition of known shapes requires access to long-term memory, so it is not possible to know whether the experiment is assessing short-term encoding and working memory mechanisms, or has encountered limitations on retrieval from memory stores. Here we have used an inventory of unknown shapes, wherein a string of discrete dots forms the boundary of each shape. Each was displayed as a target only once to a given respondent, with recognition being tested using a matching task. Analysis based on signal detection theory was used to provide an unbiased estimate of the probability of correct decisions about whether comparison shapes matched target shapes. Four experiments were conducted, which found the following: a) Shapes were identified with a high probability of being correct with dot densities ranging from 20% to 4%. Performance dropped only about 10% across this density range. b) Shape identification levels remained very high with up to 500 milliseconds of target and comparison shape separation. c) With one-at-a-time display of target dots, varying the total time for a given display, the proportion of correct decisions dropped only about 10% even with a total display time of 500 milliseconds. d) With display of two complementary target subsets, also varying the total time of each display, there was a dramatic decline of proportion correct that reached chance levels by 500 milliseconds. The greater rate of decline for the two-pulse condition may be due to a mechanism that registers when the number of dots is sufficient to create a shape summary. Once a summary is produced, the temporal window that allows shape information to be added may be more limited.
- shape recognition,
- shape encoding,
- visual persistence,
- working memory
Citation: Ernest Greene, Michael J. Hautus. Evaluating persistence of shape information using a matching protocol[J]. AIMS Neuroscience, 2018, 5(1): 81-96. doi: 10.3934/Neuroscience.2018.1.81

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Abstract

Many laboratories have studied persistence of shape information, the goal being to better understand how the visual system mediates recognition of objects. Most have asked for recognition of known shapes, e.g., letters of the alphabet, or recall from an array. Recognition of known shapes requires access to long-term memory, so it is not possible to know whether the experiment is assessing short-term encoding and working memory mechanisms, or has encountered limitations on retrieval from memory stores. Here we have used an inventory of unknown shapes, wherein a string of discrete dots forms the boundary of each shape. Each was displayed as a target only once to a given respondent, with recognition being tested using a matching task. Analysis based on signal detection theory was used to provide an unbiased estimate of the probability of correct decisions about whether comparison shapes matched target shapes. Four experiments were conducted, which found the following: a) Shapes were identified with a high probability of being correct with dot densities ranging from 20% to 4%. Performance dropped only about 10% across this density range. b) Shape identification levels remained very high with up to 500 milliseconds of target and comparison shape separation. c) With one-at-a-time display of target dots, varying the total time for a given display, the proportion of correct decisions dropped only about 10% even with a total display time of 500 milliseconds. d) With display of two complementary target subsets, also varying the total time of each display, there was a dramatic decline of proportion correct that reached chance levels by 500 milliseconds. The greater rate of decline for the two-pulse condition may be due to a mechanism that registers when the number of dots is sufficient to create a shape summary. Once a summary is produced, the temporal window that allows shape information to be added may be more limited.

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