The human visual cortex.

By Kalanit Grill-Spector, Rafael Malach. 2004

1,291 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Neuroscience

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Citations in the corpus

CogView: Mastering Text-to-Image Generation via Transformers (2021, background): “…learn complex distributions to generate the overlapping and composite of different objects and features, which, like painting, is beyond basic visual functions (related to eyes and the V1–V4 in brain [22]), requiring a higher-level cognitive ability (more related to the angular gyrus in brain [3]).”
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning (2019, background): “Studies in neuroscience show that some areas in the brain are used for processing input signals e.g. visual cortices for images [20, 37], while other areas are responsible for logical thinking and reasoning [43].”
A Baseline for the Multivariate Comparison of Resting-State Networks (2011, result): “The visual system (VIS) is also represented by six components (ICs 46, 64, 67, 48, 39, and 59) in good agreement with the anatomical and functional delineations of occipital cortex (Grill-Spector and Malach, 2004).”
The neural basis of visual body perception (2007, background): “Given their distinct locations in the visual system, there might also be dissociations between the EBA and the FBA on one or more of these aspect”
TRoPICALS: a computational embodied neuroscience model of compatibility effects. (2010, background): “In the brain, the ventral pathway involves cortical areas performing high-level visual processing (Felleman & Van Essen, 1991; Van Essen et al., 2001; Grill-Spector & Malach, 2004).”
Explicit encoding of multimodal percepts by single neurons in the human brain. (2009, neutral): “But how does the brain recognize highly variable pictures as the same percept? Various studies have provided insights into how visual information is processed along the ‘‘ventral pathway,’’ via both single-cell recordings in monkeys [1, 2] and functional imaging in humans [3, 4].”
Decoding brain states from fMRI connectivity graphs (2011, background): “It is also known from visual mapping studies that spatial de-coherence breaks down into patterns with different functional specialisation (Grill-Spector and Malach, 2004).”
Human parietal cortex in action. (2006, background): “Object-selective areas Although the vast majority of human studies on object selectivity focused on areas within the ventral stream [47], neuroimaging has also revealed shape-selective activation for objects within the dorsal stream of both monkeys and humans [48].”
Mouth and Voice: A Relationship between Visual and Auditory Preference in the Human Superior Temporal Sulcus (2017, background): “The present study suggests a link between the organization of the pSTS into auditory, visual, and audiovisual patches and the organization of sensory cortex into regions preferring different stimulus categories (Grill-Spector and Malach, 2004).”
Intrinsically motivated action-outcome learning and goal-based action recall: a system-level bio-constrained computational model. (2013, background): “The ventral stream involves the inferior temporal cortex (ITC), which plays an important role in object identification (Grill-Spector and Malach, 2004), and the PFC (Fuster, 2008).”
Building the gist of a scene: the role of global image features in recognition. (2006, background): “Features of openness are shown in black and features of closedness are shown in white. mechanisms underlying human object recognition (Kanwisher, 2003; Grill-Spector and Malach, 2004) and its modeling (Riesenhuber and Poggio, 1999; Ullman et al., 2002; Torralba et al., 2004; Serre et al., 2005).”
Neurovisual Control in the Quake II Environment (2012, background): “The visual cortex's computational process is massively parallel [7], but an individual computer processor typically computes serially.”
Search for patterns of functional specificity in the brain: A nonparametric hierarchical Bayesian model for group fMRI data (2011, background): “In particular, fMRI studies have revealed a number of regions along the ventral visual pathway that demonstrate significant selectivity for certain categories of objects such as human faces, bodies, or places (Kanwisher, 2003; Grill-Spector and Malach, 2004).”