Visual categorization shapes feature selectivity in the primate temporal cortex

By Natasha Sigala, Nikos K. Logothetis. Nature, 2002

600 citations recorded by the source corpus.

The way that we perceive and interact with objects depends on our previous experience with them. For example, a bird expert is more likely to recognize a bird as a sparrow, a sandpiper or a cockatiel than a non-expert. Neurons in the inferior temporal cortex have been shown to be important in the representation of visual objects; however, it is unknown which object features are represented and how these representations are affected by categorization training. Here we show that feature selectivity in the macaque inferior temporal cortex is shaped by categorization of objects on the basis of their visual features. Specifically, we recorded from single neurons while monkeys performed a categorization task with two sets of parametric stimuli. Each stimulus set consisted of four varying features, but only two of the four were important for the categorization task (diagnostic features). We found enhanced neuronal representation of the diagnostic features relative to the non-diagnostic ones. These findings demonstrate that stimulus features important for categorization are instantiated in the activity of single units (neurons) in the primate inferior temporal cortex.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/0bbd52aaddd00bc863c93d7b106db658c5c29402

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

Citations in the corpus

Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world (2013, background): “The anterior inferotemporal cortex exhibits such invariance (Bar et al., 2001; Sigala & Logothetis, 2002; Tanaka, Saito, Fukada, & Moriya, 1991).”
Reward modulates attention independently of action value in posterior parietal cortex (2009, unknown): “…visual and oculomotor system in operant tasks requiring conditional visuomotor learning (Chen and Wise, 1996; Asaad et al., 1998), categorization (Sigala and Logothetis, 2002; Freedman and Assad, 2006), decision making (Sugrue et al., 2004), or target selection (Bichot et al., 1996; Mruczek and…”
Deep Supervised Learning Using Local Errors (2017, background): “Single cell measurements in monkey area IT indicate broad tuning to a range of categories (Sigala and Logothetis, 2002; Kiani et al., 2007).”
Selectivity and tolerance (“invariance”) both increase as visual information propagates from cortical area V4 to IT (2010, background): “…to discriminate between different scrambled images; given the plasticity known to exist at higher stages of visual processing (Baker et al., 2002; Sigala and Logothetis, 2002; Kourtzi and DiCarlo, 2006; Li and DiCarlo, 2008), it remains an open question as to how well IT populations can encode…”
Recurrent Processing during Object Recognition (2013, background): “, 2010; Mahon and Caramazza, 2011) and task-relevant IT neural tunings (due to connectivity with higher-level cognitive systems; Sigala and Logothetis, 2002; Nestor et al., 2008).”
Experience-dependent sharpening of visual shape selectivity in inferior temporal cortex. (2005, unknown): “Keywords: categorization, inferior temporal cortex, learning, object recognition, vision”
Generalization and similarity in exemplar models of categorization: Insights from machine learning (2008, background): “In addition, the GCM, which does not lend itself easily to a neural interpretation, has inspired single-cell recordings in monkeys (Sigala, Gabbiani, & Logothetis, 2002; Sigala & Logothetis, 2002).”
Prefrontal cortex activity during flexible categorization (2010, background): “2002; Sigala and Logothetis, 2002; Freedman et al., 2003; Freedman and Assad, 2006;”
Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey (2008, background): “Monkey studies have reported IT responses that are correlated with categories (Vogels, 1999; Sigala and Logothetis, 2002; Baker et al., 2002; Tsao et al., 2003; Freedman et al., 2003; Kiani et al., 2005; Hung et al., 2005; Tsao et al., 2006; Afraz et al., 2006).”
Physiologically Inspired Model for the Visual Recognition of Transitive Hand Actions (2013, unknown): “…consistent with electro-physiological data showing view-dependent and view-independent shape-selective neurons, and an experience-dependent modulation of tuning properties of neurons in area IT (Kobatake et al., 1998; Sigala and Logothetis, 2002; Freedman et al., 2006; Suzuki and Tanaka, 2011).”
A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex (2005, result): “On the other hand, a recent experiment [Sigala and Logothetis, 2002] reported IT neuron tuning emphasizing category-relevant features over non-relevant features (but no explicit representation of the class boundary, unlike in [Freedman et al.”