Timecourse of neural signatures of object recognition

Johnson, Jeffrey S.; Olshausen, Bruno A.

doi:10.1167/3.7.4

Cited by 215 publications

(182 citation statements)

References 37 publications

(47 reference statements)

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“…The modulation of the frontal and posterior N100 response to artifacts is consistent with previous studies that compared the effect of animals and artifacts in visual categorization (Antal et al, 2000(Antal et al, , 2001Proverbio et al, 2007). Furthermore, our posterior N100, peaking around 200 ms, resembles the negative deflection over occipito-temporal areas (N200 or N150) reflecting selective attention effects in target decision tasks using animals (Codispoti et al, 2006;Johnson and Olshausen, 2003) and objects (Van Rullen and Thorpe, 2001). The N150 has been considered to reflect perceptual selection mechanisms devoted to high level features extraction (as those selected in visual categorization) (Codispoti et al, 2006) and, more importantly, it has been demonstrated not to be dependent on low level sensory analysis (Van Rullen and Thorpe, 2001).…”

Section: Discussionsupporting

confidence: 90%

Attractiveness and affordance shape tools neural coding: Insight from ERPs

Righi

Orlando

Marzi

2014

International Journal of Psychophysiology

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. The relation between attractiveness and motor affordance is a key topic in design and has not yet been investigated electrophysiologically. In this respect, action affordance and attractiveness represent two crucial dimensions in object processing (specifically for tools). In light of this evidence, Event Related Potentials (ERPs) enabled us to gain new insights into the time course of the interaction between these two dimensions during an explicit tool evaluation task. Behaviorally, tools that were judged as high affording and high attractive yielded faster response times than those judged as low affording and low attractive. The ERP results showed that early processes related to sensory gating and feature extraction (N100) were sensitive to both affordance and attractiveness; the P200 was dominated by affordance, indexing a facilitated access to motor action representation. The N300, P300 and the Late Positive Potential (LPP) showed enhanced responses for highly affording/attractive tools, reflecting the interconnection between attractiveness and affordance. Later responses were entirely affected by attractiveness, suggesting additional affective responses evoked by desirable tools. We are showing that things that are perceived as more functional and attractive have a privileged neural activation in the time course of tool evaluation, for the first time.

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Section: Discussionsupporting

confidence: 90%

Attractiveness and affordance shape tools neural coding: Insight from ERPs

Righi

Orlando

Marzi

2014

International Journal of Psychophysiology

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“…This difference in length could have resulted in a harder task -our participants took longer to respond to symbols, while in Araújo et al no stimulus type effect was observed on RTs -and therefore in a larger N1 component. This suggests a greater perceptual resource allocation for symbols than for letter strings, and is consistent with the fact that the N1 component is an index of perceptual processing: Increased visual processing demands are reflected by more negative values (e.g., Johnson & Olshausen, 2003;Kiefer, 2001;Tanaka, Luu, Weisbrod, & Kiefer, 1999). Yet, visual inspection of Fig.…”

Section: Discussionsupporting

confidence: 73%

Lexical and sublexical orthographic processing: An ERP study with skilled and dyslexic adult readers

Araújo

Faísca²,

Bramão

et al. 2015

Brain and Language

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a b s t r a c tThis ERP study investigated the cognitive nature of the P1-N1 components during orthographic processing. We used an implicit reading task with various types of stimuli involving different amounts of sublexical or lexical orthographic processing (words, pseudohomophones, pseudowords, nonwords, and symbols), and tested average and dyslexic readers. An orthographic regularity effect (pseudowords-nonwords contrast) was observed in the average but not in the dyslexic group. This suggests an early sensitivity to the dependencies among letters in word-forms that reflect orthographic structure, while the dyslexic brain apparently fails to be appropriately sensitive to these complex features. Moreover, in the adults the N1-response may already reflect lexical access: (i) the N1 was sensitive to the familiar vs. less familiar orthographic sequence contrast; (ii) and early effects of the phonological form (words-pseudohomophones contrast) were also found. Finally, the later N320 component was attenuated in the dyslexics, suggesting suboptimal processing in later stages of phonological analysis.

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“…This could be in the form that first there is a fast and unconscious feedforward sweep that is followed by more in-depth recurrent processing, only the latter leading to conscious perception (Lamme 2003). This is consistent with findings by Johnson and Olshausen (2003), who report two ERP signals related to object recognition, an early presentation-locked one, and a later signal that correlates in timing with the response times for recognition.…”

Section: Experimental Evidencesupporting

confidence: 89%

Information Routing, Correspondence Finding, and Object Recognition in the Brain

Wolfrum¹

2010

Studies in Computational Intelligence

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This work would not have been possible without the people I have had the honor of working with over the past years. First of all I want to thank Christoph von der Malsburg, whose scientific concepts have inspired large parts of this thesis, and who granted me enough freedom to follow my own research directions while at the same time providing motivation whenever this was necessary. I also thank Rudolf Mester for good discussions that helped me retain my engineering viewpoint on the interdisciplinary problems that I worked on. Discussions with Geoff Goodhill, Bruno Olshausen, Jochen Triesch, and Alan Yuille, among others, have shaped my thinking and had an important impact on this thesis.I thank Urs Bergmann, Jenia Jitsev, and Junmei Zhu for proof-reading parts of the thesis, and Jörg Lücke for good collaboration. The neurogroups at FIAS have provided a rich and stimulating environment, it has been fun working and thinking with you! I also thank all colleagues at FIAS for good company and the truly interdisciplinary interaction we had (e.g. at Hirschegg). Last but not least I owe this thesis to my parents, who planted curiosity and a desire for understanding in me that were stronger than the difficulties I met during this dissertation. iv

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Timecourse of neural signatures of object recognition

Cited by 215 publications

References 37 publications

Attractiveness and affordance shape tools neural coding: Insight from ERPs

Attractiveness and affordance shape tools neural coding: Insight from ERPs

Lexical and sublexical orthographic processing: An ERP study with skilled and dyslexic adult readers

Information Routing, Correspondence Finding, and Object Recognition in the Brain

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