Task-uninformative visual stimuli improve auditory spatial discrimination in humans but not the ideal observer
Autoři:
Madeline S. Cappelloni aff001; Sabyasachi Shivkumar aff003; Ralf M. Haefner aff003; Ross K. Maddox aff001
Působiště autorů:
Biomedical Engineering, University of Rochester, Rochester, New York, United States of America
aff001; Del Monte Institute for Neuroscience, University of Rochester, Rochester, New York, United States of America
aff002; Brain and Cognitive Sciences, University of Rochester, Rochester, New York, United States of America
aff003; Center for Visual Science, University of Rochester, Rochester, New York, United States of America
aff004; Neuroscience, University of Rochester, Rochester, New York, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0215417
Souhrn
In order to survive and function in the world, we must understand the content of our environment. This requires us to gather and parse complex, sometimes conflicting, information. Yet, the brain is capable of translating sensory stimuli from disparate modalities into a cohesive and accurate percept with little conscious effort. Previous studies of multisensory integration have suggested that the brain’s integration of cues is well-approximated by an ideal observer implementing Bayesian causal inference. However, behavioral data from tasks that include only one stimulus in each modality fail to capture what is in nature a complex process. Here we employed an auditory spatial discrimination task in which listeners were asked to determine on which side they heard one of two concurrently presented sounds. We compared two visual conditions in which task-uninformative shapes were presented in the center of the screen, or spatially aligned with the auditory stimuli. We found that performance on the auditory task improved when the visual stimuli were spatially aligned with the auditory stimuli—even though the shapes provided no information about which side the auditory target was on. We also demonstrate that a model of a Bayesian ideal observer performing causal inference cannot explain this improvement, demonstrating that humans deviate systematically from the ideal observer model.
Klíčová slova:
Biology and life sciences – Neuroscience – Sensory perception – Vision – Sensory cues – Psychophysics – Cognitive science – Cognitive psychology – Attention – Decision making – Cognition – Psychology – Behavior – Social sciences
Zdroje
1. Ernst MO, Banks MS. Humans integrate visual and haptic information in a statistically optimal fashion. Nature. 2002;415(6870):429–433. doi: 10.1038/415429a 11807554
2. Körding KP, Beierholm U, Ma WJ, Quartz S, Tenenbaum JB, Shams L. Causal Inference in Multisensory Perception. PLOS ONE. 2007;2(9):e943. doi: 10.1371/journal.pone.0000943 17895984
3. Battaglia PW, Jacobs RA, Aslin RN. Bayesian integration of visual and auditory signals for spatial localization. JOSA A. 2003;20(7):1391–1397. doi: 10.1364/JOSAA.20.001391 12868643
4. Alais D, Burr D. The Ventriloquist Effect Results from Near-Optimal Bimodal Integration. Current Biology. 2004;14(3):257–262. doi: 10.1016/j.cub.2004.01.029 14761661
5. Shams L, Ma WJ, Beierholm U. Sound-induced flash illusion as an optimal percept. NeuroReport. 2005;16(17):1923. doi: 10.1097/01.wnr.0000187634.68504.bb 16272880
6. Bresciani JP, Dammeier F, Ernst MO. Vision and touch are automatically integrated for the perception of sequences of events. Journal of Vision. 2006;6(5):2–2. doi: 10.1167/6.5.2
7. Wozny DR, Beierholm UR, Shams L. Human trimodal perception follows optimal statistical inference. Journal of Vision. 2008;8(3):24–24. doi: 10.1167/8.3.24 18484830
8. Beierholm UR, Quartz SR, Shams L. Bayesian priors are encoded independently from likelihoods in human multisensory perception. Journal of Vision. 2009;9(5):23–23. doi: 10.1167/9.5.23 19757901
9. Hospedales T, Vijayakumar S. Multisensory Oddity Detection as Bayesian Inference. PLOS ONE. 2009;4(1):e4205. doi: 10.1371/journal.pone.0004205 19145254
10. Girshick AR, Banks MS. Probabilistic combination of slant information: Weighted averaging and robustness as optimal percepts. Journal of vision. 2009;9(9):8.1–820. doi: 10.1167/9.9.8
11. Rohe T, Noppeney U. Cortical Hierarchies Perform Bayesian Causal Inference in Multisensory Perception. PLOS Biology. 2015;13(2):e1002073. doi: 10.1371/journal.pbio.1002073 25710328
12. Rohe T, Noppeney U. Distinct Computational Principles Govern Multisensory Integration in Primary Sensory and Association Cortices. Current Biology. 2016;26(4):509–514. doi: 10.1016/j.cub.2015.12.056 26853368
13. Maddox RK, Atilgan H, Bizley JK, Lee AK. Auditory selective attention is enhanced by a task-irrelevant temporally coherent visual stimulus in human listeners. eLife. 2015;4. doi: 10.7554/eLife.04995 25654748
14. Atilgan H, Town SM, Wood KC, Jones GP, Maddox RK, Lee AKC, et al. Integration of Visual Information in Auditory Cortex Promotes Auditory Scene Analysis through Multisensory Binding. Neuron. 2018;97(3):640–655.e4. doi: 10.1016/j.neuron.2017.12.034 29395914
15. Eramudugolla R, Kamke MR, Soto-Faraco S, Mattingley JB. Perceptual load influences auditory space perception in the ventriloquist aftereffect. Cognition. 2011;118(1):62–74. doi: 10.1016/j.cognition.2010.09.009 20979992
16. Howard IP, Templeton WB. Human spatial orientation. Human spatial orientation. Oxford, England: John Wiley & Sons; 1966.
17. Slutsky DA, Recanzone GH. Temporal and spatial dependency of the ventriloquism effect. NeuroReport. 2001;12(1):7. doi: 10.1097/00001756-200101220-00009 11201094
18. Blau V, Atteveldt NV, Formisano E, Goebel R, Blomert L. Task-irrelevant visual letters interact with the processing of speech sounds in heteromodal and unimodal cortex. European Journal of Neuroscience. 2008;28(3):500–509. doi: 10.1111/j.1460-9568.2008.06350.x 18702722
19. Lovelace CT, Stein BE, Wallace MT. An irrelevant light enhances auditory detection in humans: a psychophysical analysis of multisensory integration in stimulus detection. Cognitive Brain Research. 2003;17(2):447–453. doi: 10.1016/S0926-6410(03)00160-5 12880914
20. Soto-Faraco S, Navarra J, Alsius A. Assessing automaticity in audiovisual speech integration: evidence from the speeded classification task. Cognition. 2004;92(3):B13–B23. doi: 10.1016/j.cognition.2003.10.005 15019556
21. Larson E, Lee AKC. The cortical dynamics underlying effective switching of auditory spatial attention. NeuroImage. 2013;64:365–370. doi: 10.1016/j.neuroimage.2012.09.006 22974974
22. Best V, Gallun FJ, Ihlefeld A, Shinn-Cunningham BG. The influence of spatial separation on divided listening. The Journal of the Acoustical Society of America. 2006;120(3):1506–1516. doi: 10.1121/1.2234849 17004472
23. Gallun FJ, Mason CR, Kidd G. Task-dependent costs in processing two simultaneous auditory stimuli. Perception & Psychophysics. 2007;69(5):757–771. doi: 10.3758/BF03193777
24. Talsma D, Doty TJ, Woldorff MG. Selective Attention and Audiovisual Integration: Is Attending to Both Modalities a Prerequisite for Early Integration? Cerebral Cortex. 2007;17(3):679–690. doi: 10.1093/cercor/bhk016 16707740
25. Bizley JK, Maddox RK, Lee AKC. Defining Auditory-Visual Objects: Behavioral Tests and Physiological Mechanisms. Trends in Neurosciences. 2016;39(2):74–85. doi: 10.1016/j.tins.2015.12.007 26775728
26. Bizley JK, Jones GP, Town SM. Where are multisensory signals combined for perceptual decision-making? Current Opinion in Neurobiology. 2016;40:31–37. doi: 10.1016/j.conb.2016.06.003 27344253
27. Wozny DR, Beierholm UR, Shams L. Probability Matching as a Computational Strategy Used in Perception. PLOS Computational Biology. 2010;6(8):e1000871. doi: 10.1371/journal.pcbi.1000871 20700493
28. Algazi VR, Duda RO, Thompson DM, Avendano C. The CIPIC HRTF database. In: Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575). New Platz, NY, USA: IEEE; 2001. p. 99–102. Available from: http://ieeexplore.ieee.org/document/969552/.
29. Martin R, McAnally K. Interpolation of head-related transfer functions. Defence Science and Technology Organization Ednburgh (Australia) Air Operations Div; 2007.
30. Blaser E, Pylyshyn ZW, Holcombe AO. Tracking an object through feature space. Nature. 2000;408(6809):196–. doi: 10.1038/35041567 11089972
31. Acerbi L, Ma WJ. Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search. In: Advances in Neural Information Processing Systems; 2017. p. 1836–1846.
Článek vyšel v časopise
PLOS One
2019 Číslo 9
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Je libo čepici místo mozkového implantátu?
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
- Nová metoda odlišení nádorové tkáně může zpřesnit resekci glioblastomů
Nejčtenější v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy