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Yeh MS, Li T, Huang J, Liu Z. Comparing conventional and action video game training in visual perceptual learning. Sci Rep 2024; 14:27864. [PMID: 39537636 PMCID: PMC11561280 DOI: 10.1038/s41598-024-71987-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 08/30/2024] [Indexed: 11/16/2024] Open
Abstract
Action video game (AVG) playing has been found to transfer to a variety of laboratory tasks in visual cognition. More recently, it has even been found to transfer to low-level visual "psychophysics tasks. This is unexpected since such low-level tasks have traditionally been found to be largely "immune" to transfer from another task, or even from the same task but a different stimulus attribute, e.g., motion direction. In this study, we set out to directly quantify transfer efficiency from AVG training to motion discrimination. Participants (n = 65) trained for 20 h on either a first-person active shooting video game, or a motion direction discrimination task with random dots. They were tested before, midway, and after training with the same motion task and an orientation discrimination task that had been shown to receive transfer from AVG training, but not from motion training. A subsequent control group (n = 18) was recruited to rule out any test-retest effect, by taking the same tests with the same time intervals, but without training. We found that improvement in motion discrimination performance was comparable between the AVG training and control groups, and less than the motion discrimination training group. We could not replicate the AVG transfer to orientation discrimination, but this was likely due to the fact that our participants were practically at chance for this task at all test points. Our study found no evidence, in either accuracy or reaction time, that AVG training transferred to motion discrimination. Overall, our results suggest that AVG training transferred little to lower-level visual skills, refining understanding of the mechanisms by which AVGs may affect vision. Protocol registration The accepted stage 1 protocol for this study can be found on the Open Science Framework at https://osf.io/zdv9c/?view_only=5b3b0c161dad448d9d1d8b14ce91ab11 . The stage 1 protocol for this Registered Report was accepted in principle on 01/12/22. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ZDV9C.
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Affiliation(s)
- Maggie S Yeh
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Tan Li
- Department of Psychology, Hebei Normal University, Shijiazhuang, China
| | - Jinfeng Huang
- Department of Psychology, Hebei Normal University, Shijiazhuang, China.
| | - Zili Liu
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
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Donato R, Pavan A, Cavallin G, Ballan L, Betteto L, Nucci M, Campana G. Mechanisms Underlying Directional Motion Processing and Form-Motion Integration Assessed with Visual Perceptual Learning. Vision (Basel) 2022; 6:vision6020029. [PMID: 35737415 PMCID: PMC9229663 DOI: 10.3390/vision6020029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/17/2022] [Accepted: 05/27/2022] [Indexed: 11/18/2022] Open
Abstract
Dynamic Glass patterns (GPs) are visual stimuli commonly employed to study form–motion interactions. There is brain imaging evidence that non-directional motion induced by dynamic GPs and directional motion induced by random dot kinematograms (RDKs) depend on the activity of the human motion complex (hMT+). However, whether dynamic GPs and RDKs rely on the same processing mechanisms is still up for dispute. The current study uses a visual perceptual learning (VPL) paradigm to try to answer this question. Identical pre- and post-tests were given to two groups of participants, who had to discriminate random/noisy patterns from coherent form (dynamic GPs) and motion (RDKs). Subsequently, one group was trained on dynamic translational GPs, whereas the other group on RDKs. On the one hand, the generalization of learning to the non-trained stimulus would indicate that the same mechanisms are involved in the processing of both dynamic GPs and RDKs. On the other hand, learning specificity would indicate that the two stimuli are likely to be processed by separate mechanisms possibly in the same cortical network. The results showed that VPL is specific to the stimulus trained, suggesting that directional and non-directional motion may depend on different neural mechanisms.
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Affiliation(s)
- Rita Donato
- Dipartimento di Psicologia Generale, University of Padova, Via Venezia 8, 35131 Padova, Italy; (L.B.); (M.N.); (G.C.)
- Human Inspired Technology Research Centre, University of Padova, Via Luzzati 4, 35121 Padova, Italy;
- Proaction Laboratory, Faculty of Psychology and Educational Sciences, University of Coimbra, Colégio de Jesus, Rua Inácio Duarte 65, 3000-481 Coimbra, Portugal
- CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Rua Colégio Novo, 3000-115 Coimbra, Portugal
- Correspondence: (R.D.); (A.P.)
| | - Andrea Pavan
- Dipartimento di Psicologia, University of Bologna, Viale Berti Pichat, 5, 40127 Bologna, Italy
- Correspondence: (R.D.); (A.P.)
| | - Giovanni Cavallin
- Dipartimento di Matematica, University of Padova, Via Trieste 63, 35121 Padova, Italy;
| | - Lamberto Ballan
- Human Inspired Technology Research Centre, University of Padova, Via Luzzati 4, 35121 Padova, Italy;
- Dipartimento di Matematica, University of Padova, Via Trieste 63, 35121 Padova, Italy;
| | - Luca Betteto
- Dipartimento di Psicologia Generale, University of Padova, Via Venezia 8, 35131 Padova, Italy; (L.B.); (M.N.); (G.C.)
| | - Massimo Nucci
- Dipartimento di Psicologia Generale, University of Padova, Via Venezia 8, 35131 Padova, Italy; (L.B.); (M.N.); (G.C.)
- Human Inspired Technology Research Centre, University of Padova, Via Luzzati 4, 35121 Padova, Italy;
| | - Gianluca Campana
- Dipartimento di Psicologia Generale, University of Padova, Via Venezia 8, 35131 Padova, Italy; (L.B.); (M.N.); (G.C.)
- Human Inspired Technology Research Centre, University of Padova, Via Luzzati 4, 35121 Padova, Italy;
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The effect of initial performance on motion perception improvements is modulated by training method. Atten Percept Psychophys 2021; 84:179-187. [PMID: 34657999 DOI: 10.3758/s13414-021-02381-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2021] [Indexed: 12/20/2022]
Abstract
Repeated practice of a perceptual task, termed "perceptual learning," can improve visual performance. Previously, the training thresholds were determined in two ways. One is that the stimulus corresponding to a certain level in individually set psychometric functions was selected as the training threshold. The other is that the certain stimulus was selected as the training threshold without consideration of individual differences. However, little is known about how the two training methods modulate perceptual learning. This study aimed to evaluate the effect of initial performance on patterns of motion perceptual learning under two methods-individually set or group averaged-for setting the training threshold. Thirty-six observers were randomly divided into individual and group thresholds. Psychometric functions, with the percentage correct as a function of coherence, were measured using the coherent motion direction identification task. For the individual threshold, each observer was trained at individualized coherence level, targeting 60% correct for each observer's psychometric function. For the group threshold, each observer was trained at one coherence level, targeting 60% correct in the group-averaged psychometric function. The threshold was reduced after training with the method of constant stimulus in both groups, indicating improvements following perceptual learning. Furthermore, observers with a poorer initial performance exhibited greater learning gains independent of the training method. Importantly, the correlation between the initial performance and learning gains was larger in the individual threshold than in the group threshold, suggesting the influence of the initial performance on the learning amount depends on the training method.
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Long-term training reduces the responses to the sound-induced flash illusion. Atten Percept Psychophys 2021; 84:529-539. [PMID: 34518970 DOI: 10.3758/s13414-021-02363-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/25/2021] [Indexed: 11/08/2022]
Abstract
The sound-induced flash illusion (SiFI) is a robust auditory-dominated multisensory integration phenomenon that is used as a reliable indicator to assess multisensory integration. Previous studies have indicated that the SiFI effect is correlated with perceptual sensitivity. However, to date, there is no consensus regarding how it corresponds to sensitivity with long-term training. The present study adopted the classic SiFI paradigm with feedback training to investigate the effect of a week of long-term training on the SiFI effect. Both the training group and control group completed a pretest and a posttest before and after the perceptual training; however, only the training group was required to complete 7-day behavioral training. The results showed that (1) long-term training could reduce the response of fission and fusion illusions by improving perceptual sensitivity and that (2) there was a "plateau effect" that emerged during the training stage, which tended to stabilize by the fifth day. These findings demonstrated that the SiFI effect could be modified with long-term training by ameliorating perceptual sensitivity, especially in terms of the fission illusion. Therefore, the present study supplements perceptual training in SiFI domains and provides evidence that the SiFI could be used as an assessment intervention to improve the efficiency of multisensory integration.
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Battaglini L, Oletto CM, Contemori G, Barollo M, Ciavarelli A, Casco C. Perceptual learning improves visual functions in patients with albinistic bilateral amblyopia: A pilot study. Restor Neurol Neurosci 2021; 39:45-59. [PMID: 33554927 DOI: 10.3233/rnn-201043] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Several visual functions are impaired in patients with oculocutaneous albinism (OCA) associated to albinistic bilateral amblyopia (ABA). OBJECTIVE In this study, we aimed at exploring whether perceptual learning (PL) can improve visual functions in albinism. METHOD Six patients and six normal sighted controls, were trained in a contrast detection task with lateral masking. Participants were asked to choose which of the two intervals contained a foveally presented low-contrast Gabor patch. Targets were presented between higher contrast collinear flankers with equal spatial frequency. When increasing target-to-flanker distance, lateral interactions effect normally switches from inhibition to facilitation, up to no effect. RESULTS Our findings showed that before PL, only controls showed facilitation. After PL, results suggest that facilitatory lateral interactions are found both in controls as well as in albino patients. These results suggest that PL could induce higher processing efficiency at early cortical level. Moreover, PL positive effect seems to transfer to higher-level visual functions, but results were not very consistent among tasks (visual acuity, contrast sensitivity function, hyperacuity and foveal crowding). CONCLUSIONS Although a small sample size was tested, our findings suggest a rehabilitative potential of PL in improving visual functions in albinism.
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Affiliation(s)
- Luca Battaglini
- Department of General Psychology, University of Padova, Padova, Italy.,Neuro.Vis.U.S. Laboratory, University of Padova, Padova, Italy.,Department of Physics and Astronomy "Galileo Galilei", University of Padova, via Marzolo, Padova, Italy
| | | | - Giulio Contemori
- Department of General Psychology, University of Padova, Padova, Italy.,Neuro.Vis.U.S. Laboratory, University of Padova, Padova, Italy
| | - Michele Barollo
- Neuro.Vis.U.S. Laboratory, University of Padova, Padova, Italy.,Dipartimento dei Beni Culturali, University of Padova, Padova, Italy
| | - Ambra Ciavarelli
- Department of General Psychology, University of Padova, Padova, Italy.,Neuro.Vis.U.S. Laboratory, University of Padova, Padova, Italy
| | - Clara Casco
- Department of General Psychology, University of Padova, Padova, Italy.,Neuro.Vis.U.S. Laboratory, University of Padova, Padova, Italy
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Xi J, Zhang P, Jia WL, Chen N, Yang J, Wang GT, Dai Y, Zhang Y, Huang CB. Multi-Stage Cortical Plasticity Induced by Visual Contrast Learning. Front Neurosci 2020; 14:555701. [PMID: 33408602 PMCID: PMC7779615 DOI: 10.3389/fnins.2020.555701] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 11/25/2020] [Indexed: 11/30/2022] Open
Abstract
Perceptual learning, the improved sensitivity via repetitive practice, is a universal phenomenon in vision and its neural mechanisms remain controversial. A central question is which stage of processing is changed after training. To answer this question, we measured the contrast response functions and electroencephalography (EEG) before and after ten daily sessions of contrast detection training. Behavioral results showed that training substantially improved visual acuity and contrast sensitivity. The learning effect was significant at the trained condition and partially transferred to control conditions. Event-related potential (ERP) results showed that training reduced the latency in both early and late ERPs at the trained condition. Specifically, contrast-gain-related changes were observed in the latency of P1, N1-P2 complex, and N2, which reflects neural changes across the early, middle, and high-level sensory stages. Meanwhile, response-gain-related changes were found in the latency of N2, which indicates stimulus-independent effect in higher-level stages. In sum, our findings indicate that learning leads to changes across different processing stages and the extent of learning and transfer may depend on the specific stage of information processing.
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Affiliation(s)
- Jie Xi
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Pan Zhang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Center for Neural Science, New York University, New York, NY, United States
| | - Wu-Li Jia
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- School of Education Science, Huaiyin Normal University, Huaian, China
| | - Nihong Chen
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing, China
- THU-IDG/McGovern Institute for Brain Research, Beijing, China
| | - Jia Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ge-Tong Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yun Dai
- Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China
- The Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu, China
| | - Yudong Zhang
- Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China
- The Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu, China
| | - Chang-Bing Huang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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