Jason Gold Profile Picture

Jason Gold

  • jgold@indiana.edu
  • (812) 855-4635
  • Professor
    Psychological and Brain Sciences
  • Director of Undergraduate Studies
    Psychological and Brain Sciences

Field of study

  • Visual perception

Education

  • Ph.D., University of Toronto, 2001

Research interests

  • One of the most important abilities we possess is our capacity to detect, discriminate and identify objects in our environment. It is difficult to imagine navigating through the world without the ability to reliably detect objects in our path; or having social interactions without the ability to recognize other people's faces. These are tasks that we perform with ease and on a continual basis every day. But how does our visual system translate the array of light that reaches our eyes into an organized representation of meaningful objects embedded within complex scenes? My research is directed towards understanding some of these processes that are performed on visual patterns after the initial stages of sensory encoding. I am particularly interested in understanding what it is that limits our ability to use the information that is available to us when we are trying to detect or recognize visual patterns. My approach typically involves the use of a variety of psychophysical and signal-processing methods (such as ideal observer analysis and signal detection theory) to quantitatively characterize the mechanisms involved in various perceptual processes, such as perceptual learning, visual completion, face recognition and visual memory decay.

Representative publications

Inversion leads to quantitative, not qualitative, changes in face processing (2004)
Allison B Sekuler, Carl M Gaspar, Jason M Gold and Patrick J Bennett
Current Biology, 14 (5), 391-396

Humans are remarkably adept at recognizing objects across a wide range of views. A notable exception to this general rule is that turning a face upside down makes it particularly difficult to recognize 1, 2, 3. This striking effect has prompted speculation that inversion qualitatively changes the way faces are processed. Researchers commonly assume that configural cues strongly influence the recognition of upright, but not inverted, faces 3, 4, 5. Indeed, the assumption is so well accepted that the inversion effect itself has been taken as a hallmark of qualitative processing differences [6]. Here, we took a novel approach to understand the inversion effect. We used response classification 7, 8, 9, 10 to obtain a direct view of the perceptual strategies underlying face discrimination and to determine whether orientation effects can be explained by differential contributions of nonlinear processes. Inversion significantly …

Signal but not noise changes with perceptual learning (1999)
J Gold, PJ Bennett and AB Sekuler
Nature, 402 (6758), 176

Perceptual discrimination improves with practice. This ‘perceptual learning’is often specific to the stimuli presented during training 1, 2, 3, 4, 5, indicating that practice may alter the response characteristics of cortical sensory neurons 6, 7. Although much is known about how learning modifies cortical circuits 8, it remains unclear how these changes relate to behaviour. Different theories assume that practice improves discrimination by enhancing the signal 1, 9, 10, diminishing internal noise 11, 12 or both 13. Here, to distinguish among these alternatives, we fashioned sets of faces and textures whose signal strength could be varied, and we trained observers to identify these patterns embedded in noise. Performance increased by up to 400% across several sessions over several days. Comparisons of human performance to that of an ideal discriminator showed that learning increased the efficiency with which …

Identification of band-pass filtered letters and faces by human and ideal observers (1999)
Jason Gold, Patrick J Bennett and Allison B Sekuler
Vision research, 39 (21), 3537-3560

To better understand how the visual system makes use of information across spatial scales when identifying different kinds of complex patterns, we measured human and ideal contrast identification thresholds to estimate identification efficiency for 1- and 2-octave wide band-pass filtered letters and faces embedded in 2-D dynamic Gaussian noise. Varying stimulus center frequency from 1 to 70 c/object had different effects on letter and face identification efficiency. In the 2-octave conditions, identification efficiencies decreased by 0.25–0.5 log units for letters and 0.5–1.2 log units for faces as center frequency increased from 6.2 to 49.5 c/object, but only letters were identifiable at center frequencies below 6.2 c/object. In the 1-octave conditions, letter identification efficiencies increased by about 0.5 log units as center frequency increased from 1.1 to 2.2 c/object, and were nearly constant from 2.2 to 35 c/object. Letters …

Deriving behavioural receptive fields for visually completed contours (2000)
Jason M Gold, Richard F Murray, Patrick J Bennett and Allison B Sekuler
Current Biology, 10 (11), 663-666

The visual system is constantly faced with the problem of identifying partially occluded objects from incomplete images cast on the retinae. Phenomenologically, the visual system seems to fill in missing information by interpolating illusory and occluded contours at points of occlusion, so that we perceive complete objects. Previous behavioural 1, 2, 3, 4, 5, 6, 7 and physiological 8, 9, 10, 11, 12 studies suggest that the visual system treats illusory and occluded contours like luminance-defined contours in many respects. None of these studies has, however, directly shown that illusory and occluded contours are actually used to perform perceptual tasks. Here, we use a response-classification technique 13, 14, 15, 16, 17, 18, 19, 20 to answer this question directly. This technique provides pictorial representations — ‘classification images’ — that show which parts of a stimulus observers use to make perceptual decisions …

Characterizing perceptual learning with external noise (2004)
Jason M Gold, Allison B Sekuler and Partrick J Bennett
Cognitive Science, 28 (2), 167-207

Performance in perceptual tasks often improves with practice. This effect is known as ‘perceptual learning,’ and it has been the source of a great deal of interest and debate over the course of the last century. Here, we consider the effects of perceptual learning within the context of signal detection theory. According to signal detection theory, the improvements that take place with perceptual learning can be due to increases in internal signal strength or decreases in internal noise. We used a combination of psychophysical techniques (external noise masking and double‐pass response consistency) that involve corrupting stimuli with externally added noise to discriminate between the effects of changes in signal and noise as observers learned to identify sets of unfamiliar visual patterns. Although practice reduced thresholds by as much as a factor of 14, internal noise remained virtually fixed throughout training …

Discrete-slots models of visual working-memory response times (2013)
Christopher Donkin, Robert M Nosofsky, Jason M Gold and Richard M Shiffrin
Psychological Review, 120 (4), 873

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a …

The perception of a face is no more than the sum of its parts (2012)
Jason M Gold, Patrick J Mundy and Bosco S Tjan
Psychological science, 23 (4), 427-434

When you see a person’s face, how do you go about combining his or her facial features to make a decision about who that person is? Most current theories of face perception assert that the ability to recognize a human face is not simply the result of an independent analysis of individual features, but instead involves a holistic coding of the relationships among features. This coding is thought to enhance people’s ability to recognize a face beyond what would be expected if each feature were shown in isolation. In the study reported here, we explicitly tested this idea by comparing human performance on facial-feature integration with that of an optimal Bayesian integrator. Contrary to the predictions of most current notions of face perception, our findings showed that human observers integrate facial features in a manner that is no better than would be predicted by their ability to use each individual feature when shown …

The effect of the physical characteristics of cues and targets on facilitation and inhibition (2001)
Jay Pratt, Jamie Hillis and Jason M Gold
Psychonomic Bulletin & Review, 8 (3), 489-495

The present experiment was conducted in order to examine the role of cue—target discriminability on early occurring attentional cuing effects and late occurring inhibition of return (IOR). The experiment used a single target stimulus in conjunction with three different cue stimuli. The cues were the same as the target, different in color, shape, and luminance to the target, or did not spatially overlap with the target. At shorter stimulus onset asynchronies (SOAs; 100 and 200 msec), attentional cuing effects were only found with the nonoverlapping cues. However, at longer SOAs (400 and 800 msec), approximately equal IOR effects were found with all three types of cues. The results indicated that the physical characteristics of the cues and targets affected the pattern of reaction times at the shorter SOAs but not at the longer SOAs. The conclusion is that the biphasic pattern of early facilitation and late inhibition …

Troubles with bubbles (2004)
Richard F Murray and Jason M Gold
Vision Research, 44 (5), 461-470

The bubbles method is a recently developed variant of reverse correlation methods that have been used in psychophysics and physiology. We show mathematically that for the broad and important class of noisy linear observers, the bubbles method recovers much less information about how observers process stimuli than reverse correlation does. We also show experimentally that the unusual type of noise used in the bubbles method can drastically change human observers’ strategies in psychophysical tasks, which reduces the value of the information that is obtained from a bubbles experiment. We conclude that reverse correlation is generally preferable to the bubbles method in its present form, but we also give suggestions as to how the bubbles method could be modified to avoid the problems we discuss.

Visual memory decay is deterministic (2005)
Jason M Gold, Richard F Murray, Allison B Sekuler, Patrick J Bennett and Robert Sekuler
Psychological Science, 16 (10), 769-774

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.

The response of face-selective cortex with single face parts and part combinations (2012)
Lindsay R Arcurio, Jason M Gold and Thomas W James
Neuropsychologia, 50 (10), 2454-2459

A critical issue in object recognition research is how the parts of an object are analyzed by the visual system and combined into a perceptual whole. However, most of the previous research has examined how changes to object parts influence recognition of the whole, rather than recognition of the parts themselves. This is particularly true of the research on face recognition, and especially with questions related to the neural substrates. Here, we investigated patterns of BOLD fMRI brain activation with internal face parts (features) presented singly and in different combinations. A preference for single features over combinations was found in the occipital face area (OFA) as well as a preference for the two-eyes combination stimulus over other combination stimulus types. The fusiform face area (FFA) and lateral occipital cortex (LO) showed no preferences among the single feature and combination stimulus types. The …

The efficiency of dynamic and static facial expression recognition (2013)
Jason M Gold, Jarrett D Barker, Shawn Barr, Jennifer L Bittner, W Drew Bromfield, Nicole Chu ...
Journal of vision, 13 (5), 23-23

Abstract Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal (“ideal”) observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time. Our results suggest that the dynamic properties of human facial movements may play a surprisingly small role in people's ability to infer the emotional states of others from their facial expressions.

The efficiency of biological motion perception (2008)
Jason M Gold, Duje Tadin, Susan C Cook and Randolph Blake
Perception & Psychophysics, 70 (1), 88-95

Humans can readily perceive biological motion from point-light (PL) animations, which create an image of a moving human figure by tracing the trajectories of a small number of light points affixed to a moving human body. We have applied ideal observer analysis to a standard biological motion discrimination task involving either full-figure or PL displays. Contrary to current dogma, we find that PL animations can be rich in potential stimulus information but that human observers are remarkably inefficient at exploiting this information. Although our findings do not discount the utility of PL animation, they do provide a realistic measure of the computational challenge posed by biological motion perception.

The spatiotemporal properties of visual completion measured by response classification (2006)
Jason M Gold and Erin Shubel
Journal of Vision, 6 (4), 5-May

A constant problem faced by the visual system is the identification of partly occluded objects within the visual scene. Recent experiments have demonstrated that the visual system engages in a process of visual completion, where the hidden parts of objects are filled into the visual representation. Recent experiments have also suggested that there may be a time course to this completion process. Here, we examined the spatiotemporal properties of visual completion by having observers classify figures defined by either luminance-defined or illusory contours and then correlating their decisions with externally added spatiotemporal visual noise. This “response classification” technique allowed us to derive a spatiotemporal correlation map (a “classification movie”) that revealed the locations used by observers at each point in space and time during the stimulus presentation. We found that observers gradually became more influenced by noise at locations corresponding to illusory contours across the first 175 ms of stimulus presentation. Our results are consistent with the idea that there is a time course to the completion process on the order of∼ 175 ms.

Verbal labeling, gradual decay, and sudden death in visual short-term memory (2015)
Chris Donkin, Robert Nosofsky, Jason Gold and Richard Shiffrin
Psychonomic Bulletin & Review, 22 (1), 170-178

Zhang and Luck (Psychological Science, 20, 423–428, 2009) found that perceptual memories are lost over time via sudden death rather than gradual decay. However, they acknowledged that participants may have instead lost memory for the locations of objects. We required observers to recall only a single object. Although the paradigm eliminated the need to maintain object–location bindings, the possibility that observers would use verbal labels increased. To measure the precision of verbal labeling, we included explicit verbal-labeling and label-matching trials. We applied a model that measured the contributions of sudden death, gradual decay, and verbal labeling to recall. Our model-based evidence pointed to sudden death as the primary vehicle by which perceptual memories were lost. Crucially, however, the sudden-death hypothesis was favored only when the verbal-labeling component was …

Dissertation Committee Service

Dissertation Committee Service
Author Dissertation Title Committee
Alexander, Will A Real-Time Model of Attention (September 2006) Sporns, O. (Chair), Goldstone, R., Kruschke, J., Yaeger, L.
Blaha, Leslie A Dynamic Hebbian-style Model of Configural Learning (December 2010) Townsend, J. (Co-Chair), Busey, T. (Co-Chair), Gold, J,. Trosset, M.
Chalmers, David Toward a Theory of Consciousness (May 1993) Hofstadter, D. (Co-Chair), Dunn, J. (Co-Chair), van Gelder, T., Goldstone, R.
Desai, R. Modeling Interaction of Syntax and Semantics in Language Acquisition (December 2002) Gasser, M. (Co-Chair), Goldstone, R. (Co-Chair), Port, R., Smith, L.
Dimperio, Eric A Dynamic Model of Planning Behaviors in Multi-Stage Risky Decision Tasks (August 2009) Busemeyer, J., Goldstone, R., Kruschke, J., Scheutz, M.
Foundalis, Harry E. Phaeaco: A Cognitive Architecture Inspired by Bongard’s Problems (May 2006) Hofstadter, D. (Chair), Gasser, M., Goldstone, R., Leake, D.
Frey, Seth Complex Collective Dynamics in Human Higher-Level Reasoning. A Study Over Multiple Methods (August 2013) Goldstone, R. (Chair), Todd, P., Beer, R., Busemeyer, J.
Gokcesu, Bahriye S. Metaphor Processing and Polysemy (December 2007) Goldstone, R. (Co-Chair), Gasser, M. (Co-Chair), Gershkoff-Stowe L., Jones, M.
Hanania, Rima Selective Attention and Attention Shifting in Preschool Children (August 2009) Smith, L. (Co-Chair), Gershkoff-Stowe, L. (Co-Chair), Goldstone, R., Jones, S.
Hockema, S. A. Perception as Prediction (April 2004) Gasser, M. (Co-Chair), Smith, L. (Co-Chair), Goldstone, R., Port, R., Hummel, J.
Honey, Christopher Fluctuations & Flows in Large-Scale Brain Networks (April 2009) Townsend, J,. Goldstone, R. (Co-Chair), Beggs, J., Sporns, O. (Co-Chair)
Kachergis, George Earle Mechanisms for Cross-Situational Learning of Word-Referent Mappings: Empirical and Modeling Evidence (December 2012) Shiffrin, R. (Co-Chair), Yu, C. (Co-Chair), Goldstone, R., Jones, M., Kruschke, J.
Loehrlein, Aaron Priming Effects Associated with the Hierarchical Levels Of Classification Systems (March 2012) Jacob, E. (Co-Chair), Goldstone, R. (Co-Chair), Ekbia, H., Ding, Y.
Mahabal, Abhijit Seqsee: A Concept-Centered Architecture for Sequence Perception (March 2010) Hofstadter, D. (Chair), Gasser, M., Goldstone, R., Leake, D.
Mason, Winter Implicit Social Influence (August 2007) Smith, E. (Co-Chair), Goldstone, R. (Co-Chair), Tormala, Z., Sporns, O.
McGraw, G. E. Jr. Letter Spirit (Part One): Emergent High-Level Perception of Letters Using Fluid Concepts (September 1995) Hofstadter, D. R. (Chair), Gasser, M. Goldstone, R., Port, R. F., Rawlins, G. J. E.
Nelson, Angela Examining the Co-Evolution of Knowledge and Event Memory (August 2009) Shiffrin, R. (Co-Chair), Goldstone, R. (Co-Chair), Busey, T., James, K.
Paik, Jae H Fraction Concepts: A Complex System of Mappings (May 2005) Mix, K. (Co-Chair), Gasser, M., Goldstone, R. (Co-Chair), Smith, L.
Place, Skyler Non-Independent Mate Choice in Humans: Deciphering And Utilizing Information in a Social Environment (July 2010) Todd, P. (Co-Chair), Goldstone, R. (Co-Chair), Smith, E., Wasserman, S., West, M.
Recchia, Gabriel Investigating the Semantics of Abstract Concepts: Evidence From a Property Generation Game (December 2012) Jones, M. (Chair), Goldstone, R., Kubler, S., Todd, P.
Rehling, J. A. Letter Spirit (Part Two): Modeling Creativity in A Visual Domain (July 2001) Hofstadter, D. R. (Chair), Gasser, M., Goldstone, R., Port, R. F.
Roberts, Michael Human Collective Behavior: Complex systems properties of self-organizations, coordination, and emergent. (July 2008) Goldstone, R. (Co-Chair), Ostrom, E. (Co-Chair), Smith, E., Todd, P.
Ross, Travis Steering Social Behavior in Online Video Games: A Calibration and Test of The Rational Reconstruction of Norms in a Multiplayer Dungeon Crawl (November 2013) Castronova, E. (Chair), Lang, A., Goldstone, R., Weaver, A.
Sanborn, Adam Uncovering Mental Representations with Markov Chain Monte Carl (September 2007) R. Shiffrin (Chair), R. Nosofsky, J. Gold, M. Jones
Shayan, Shakila Emergence of Roles in English Canonical Transitive Construction (June 2008) Gasser, M. (Co-Chair), Gershkoff-Stowe, L. (Co-Chair), Leake, D., Goldstone, R., Smith, L.
Son, Ji Y. Forces of Contextualization and Decontextualization: A Look at Symbols, Experience, and Language (August 2007) Goldstone, R. (Co-Chair), Smith, L (Co-Chair), Gasser, M., Yu, C.
Stanton, Roger Dissociations of Classification: Evidence against the Multiple Learning-Systems Hypothesis (August 2007) Nosofsky, R. (Chair), Goldstone, R., James, T., Kruschke, J.
Tamara, Carolina Route Learning And Its Interaction With Visual Landmarks (May 2013) Timberlake, W. (chair), Crystal, J., Goldstone, R., Todd, P.
Theiner, Georg From Extened Minds to Group Minds: Rethinking The Boundaries Of The Mental (July 2008) O’Connor, T. (Co-Chair), Goldstone, R. (Co-Chair), Schmitt, R., Weinberg, J.
Thomas, Wisdom Incentives, Innovation, and Imitation: Social Learning in a Networked Group (August 2010) Goldstone, R. (Co-Chair), Ostrom, E. (Co-Chair), Collins, K., Gold, J., Smith, E.
Vigo, Ronaldo Mathematical Principles of Boolean Concept Learning (May 2008) Allen, C. (Co-Chair), Kruschke, J. (Co-Chair), Goldstone, R., Nosofsky, R., Townsend, J.
Weidemann, Christophe Identifying brief stimuli: Perceptual, preferential, and decisional aspects (August 2006) Shiffrin, R. (Chair), Gold, J., Goldstone, R., Todd, P.
Wild, Heather Applying Signal Detection Theory to Evoked Response Potentials For Understanding Mechanisms of Bias and Sensitivity in Face Detection Tasks (September 2006) Busey, T. (Co-Chair), Candy, R., Gold, J., Townsend, J. (Co-Chair)
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