Fast Readout of Object Identity from Macaque Inferior Temporal Cortex

Hung, Chou P.; Kreiman, Gabriel; Poggio, Tomaso; DiCarlo, James J.

doi:10.1126/science.1117593

Cited by 754 publications

(793 citation statements)

References 32 publications

(40 reference statements)

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“…Neurons here respond to stimuli from large parts of the visual field, and they code for complex shapes similar to the face parts represented by the Assembly Layer (Tanaka 1996(Tanaka , 2003. The fact that information about object position and scale can be read out from IT neurons (Hung et al 2005), which disagrees with the assumptions made by pure pooling-models, points to the possibility of our control units residing there as well. Of course, in the cortex the mapping from V1 to IT does not happen directly, but via intermediate stages like V2 and V4.…”

Section: Discussioncontrasting

confidence: 42%

“…While this idea contradicts the textbook view that the dorsal stream takes care of object position and the ventral stream is only responsible for object identity, there is growing evidence that these roles are not as separate as previously thought. Hung et al (2005) have found that object position and scale can be read out from neurons in inferotemporal cortex (a high area of the ventral stream), while Konen and Kastner (2008) report representations of object identity in the dorsal stream.…”

Section: Physiological Background Of Dynamic Routingmentioning

confidence: 99%

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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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Section: Discussioncontrasting

confidence: 42%

Section: Physiological Background Of Dynamic Routingmentioning

confidence: 99%

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

Wolfrum¹

2010

Studies in Computational Intelligence

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“…In humans, multivariate pattern analysis (MVPA) of non‐invasive electrophysiological data has shown potential to achieve a similar level of sensitivity, demonstrating rapid categorization along the ventral stream (Cauchoix, Barragan‐Jason, Serre, & Barbeau, 2014; Isik, Meyers, Leibo, & Poggio, 2014; Ramkumar, Hansen, Pannasch, & Loschky, 2016). Fast decoding of object category was achieved at ∼100 ms from small neuronal populations in primates (Hung & Poggio, 2005) and from invasively recorded responses in human visual cortex (Li & Lu, 2009). Furthermore, recent applications of MVPA to electrophysiological data have resolved face identity processing to early latencies (50–70 ms after stimulus onset; Davidesco et al, 2014; Nemrodov et al, 2016; Vida, Nestor, Plaut, & Behrmann, 2017).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces

Dima

Perry

Messaritaki

et al. 2018

Human Brain Mapping

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Recognizing emotion in faces is important in human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry and neutral faces. Using time‐resolved decoding of sensor‐level data, we show that responses to angry faces can be discriminated from happy and neutral faces as early as 90 ms after stimulus onset and only 10 ms later than faces can be discriminated from scrambled stimuli, even in the absence of differences in evoked responses. Time‐resolved relevance patterns in source space track expression‐related information from the visual cortex (100 ms) to higher‐level temporal and frontal areas (200–500 ms). Together, our results point to a system optimised for rapid processing of emotional faces and preferentially tuned to threat, consistent with the important evolutionary role that such a system must have played in the development of human social interactions.

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“…Many physiological studies assume that animals classify stimuli as we do (Hung et al 2005;Kreiman et al 2006) or explicitly train animals on categories chosen by experimenters (Freedman et al 2001). Finally, many investigations have focused on the visual system, using patterns that are relatively stable over time.…”

Section: Introductionmentioning

confidence: 99%

Differential Influence of Frequency, Timing, and Intensity Cues in a Complex Acoustic Categorization Task

Nagel

McLendon

Doupe

2010

Journal of Neurophysiology

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Nagel KI, McLendon HM, Doupe AJ. Differential influence of frequency, timing, and intensity cues in a complex acoustic categorization task. J Neurophysiol 104: 1426 -1437, 2010. First published July 7, 2010 doi:10.1152/jn.00028.2010. Songbirds, which, like humans, learn complex vocalizations, provide an excellent model for the study of acoustic pattern recognition. Here we examined the role of three basic acoustic parameters in an ethologically relevant categorization task. Female zebra finches were first trained to classify songs as belonging to one of two males and then asked whether they could generalize this knowledge to songs systematically altered with respect to frequency, timing, or intensity. Birds' performance on song categorization fell off rapidly when songs were altered in frequency or intensity, but they generalized well to songs that were changed in duration by Ͼ25%. Birds were not deaf to timing changes, however; they detected these tempo alterations when asked to discriminate between the same song played back at two different speeds. In addition, when birds were retrained with songs at many intensities, they could correctly categorize songs over a wide range of volumes. Thus although they can detect all these cues, birds attend less to tempo than to frequency or intensity cues during song categorization. These results are unexpected for several reasons: zebra finches normally encounter a wide range of song volumes but most failed to generalize across volumes in this task; males produce only slight variations in tempo, but females generalized widely over changes in song duration; and all three acoustic parameters are critical for auditory neurons. Thus behavioral data place surprising constraints on the relationship between previous experience, behavioral task, neural responses, and perception. We discuss implications for models of auditory pattern recognition.

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Fast Readout of Object Identity from Macaque Inferior Temporal Cortex

Cited by 754 publications

References 32 publications

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

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

Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces

Differential Influence of Frequency, Timing, and Intensity Cues in a Complex Acoustic Categorization Task

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