Chapter 14 Coding of stimulus invariances by inferior temporal neurons
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Cited by (51)
Attention to distinguishing features in object recognition: An interactive-iterative framework
2018, CognitionCitation Excerpt :Despite many other differences, classic theories of object recognition (e.g., Biederman, 1987; Marr & Nishihara, 1978; Poggio & Edelman, 1990; Reisenhuber & Poggio, 1999; Tarr & Bülthoff, 1995; Tarr & Pinker, 1989; Ullman, 1989) are generally united in what might be called the orthodox view—that object recognition is based primarily on a bottom-up analysis of the visual input; recognition is achieved when some temporary representation of the input image matches a stored object representation. The functional architecture of the visual cortex—the increase in the receptive field size and in representational complexity from lower to higher areas in the cortex (Maunsell & Newsome, 1987; Vogels & Orban, 1996)—has been pointed to as consistent with the bottom-up view. Also, findings that the processes involved in object recognition are sometimes remarkably fast, occurring within 100–200 ms of stimulus presentation (e.g., Thorpe, Fize, & Marlot, 1996), have been taken by some researchers as evidence that object recognition can occur largely with feed-forward processing alone (e.g., Wallis & Rolls, 1997; but see Evans & Treisman, 2005).
Dynamic gamma frequency feedback coupling between higher and lower order visual cortices underlies perceptual completion in humans
2014, NeuroImageCitation Excerpt :Taken together, these findings accord with the suggestion that not only brain regions for cue invariant object/face recognition such as ventral visual cortex (Haxby et al., 1999; Kanwisher and Yovel, 2006; Malach et al., 1995) but also spatial attention relevant parietal brain regions (Corbetta et al., 1998; Fernandez-Duque and Posner, 2001) are crucial for perceptual closure and that this process occurs about 230 ms to 400 ms after stimulus onset. Within the classical view of visual system hierarchy, simple geometric lines and shapes that form complex objects are processed in lower order visual cortex, whereas higher order areas within the ventral visual stream (Mishkin et al., 1983) code invariant object and category information (e.g. Vogels and Orban, 1996) based on feedforward communication from early visual cortex (for a review of these models see Hochstein and Ahissar, 2002). However, recent models of conscious visual perception suggest reverse hierarchical processing (for a review see Hochstein and Ahissar, 2002) whereby higher order visual areas in the ventral and dorsal streams provide top-down feedback to early visual cortex (i.e., predictive coding — Friston, 2003; Rao and Ballard, 1999).
Right fusiform response patterns reflect visual object identity rather than semantic similarity
2013, NeuroImageCitation Excerpt :Invariance is a key characteristic of shape processing in LO (Kanwisher, 1997; Liu et al., 2008; Malach et al., 1995; Schacter et al., 1995). In the monkey brain, relative shape preference in IT is invariant for cue (luminance, relative motion or texture), size or location (Vogels and Orban, 1996). Position-tolerant identity information can be derived from inferior temporal (IT) neuronal activity (Hung et al., 2005; Tanaka, 2003).
Visual System
2012, The Human Nervous System, Third EditionUnsupervised natural visual experience rapidly reshapes size-invariant object representation in inferior temporal cortex
2010, NeuronCitation Excerpt :At the highest stage of this stream, the inferior temporal cortex (IT), a tolerant object representation is obtained in which individual IT neurons have a preference for some objects (“selectivity”) over others, and this rank-order preference is largely maintained across identity-preserving image transformations (Ito et al., 1995; Logothetis and Sheinberg, 1996; Tanaka, 1996; Vogels and Orban, 1996). Though most IT neurons are not strictly “invariant” (DiCarlo and Maunsell, 2003; Ito et al., 1995; Logothetis and Sheinberg, 1996; Vogels and Orban, 1996), reasonably sized populations of these so-called “tolerant” neurons can support object recognition tasks (Afraz et al., 2006; Hung et al., 2005; Li et al., 2009). However, we do not yet understand how IT neurons construct this tolerant response phenomenology.
Location-specific deviant responses to object sequences in macaque inferior temporal cortex
2024, Scientific Reports