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Functional Specialization Across the Visual Cortex  

Erez Freud, Tzvi Ganel, and Galia Avidan

Vision is the most important sensory modality for humans, serving a range of fundamental daily behaviors from recognizing objects, people, places, and actions to navigation and visually guided interactions with objects and other individuals. One of the most prominent accounts of cortical functional specialization implies that the visual cortex is segregated into two pathways. The ventral pathway originates from the early visual cortex in the occipital lobe and projects to the inferior surface of the temporal cortex, and it mediates vision for perception. The dorsal pathway extends from the occipital lobe to the posterior portion of the parietal cortex, and it mediates vision for action. This key characterization of the visual system is supported by classic neuropsychological, behavioral, and neuroimaging evidence. Recent research offers new insights on the developmental trajectory of this dissociation as well as evidence for interactions between the two pathways. Importantly, an emerging hypothesis points to the existence of a third visual pathway located on the lateral surface of the ventral pathway and its potential roles in action recognition and social cognition.

Article

Visual Perception in the Human Brain: How the Brain Perceives and Understands Real-World Scenes  

Clemens G. Bartnik and Iris I. A. Groen

How humans perceive and understand real-world scenes is a long-standing question in neuroscience, cognitive psychology, and artificial intelligence. Initially, it was thought that scenes are constructed and represented by their component objects. An alternative view proposed that scene perception starts by extracting global features (e.g., spatial layout) first and individual objects in later stages. A third framework focuses on how the brain not only represents objects and layout but how this information combines to allow determining possibilities for (inter)action that the environment offers us. The discovery of scene-selective regions in the human visual system sparked interest in how scenes are represented in the brain. Experiments using functional magnetic resonance imaging show that multiple types of information are encoded in the scene-selective regions, while electroencephalography and magnetoencephalography measurements demonstrate links between the rapid extraction of different scene features and scene perception behavior. Computational models such as deep neural networks offer further insight by how training networks on different scene recognition tasks results in the computation of diagnostic features that can then be tested for their ability to predict activity in human brains when perceiving a scene. Collectively, these findings suggest that the brain flexibly and rapidly extracts a variety of information from scenes using a distributed network of brain regions.

Article

Visual Shape and Object Perception  

Anitha Pasupathy, Yasmine El-Shamayleh, and Dina V. Popovkina

Humans and other primates rely on vision. Our visual system endows us with the ability to perceive, recognize, and manipulate objects, to avoid obstacles and dangers, to choose foods appropriate for consumption, to read text, and to interpret facial expressions in social interactions. To support these visual functions, the primate brain captures a high-resolution image of the world in the retina and, through a series of intricate operations in the cerebral cortex, transforms this representation into a percept that reflects the physical characteristics of objects and surfaces in the environment. To construct a reliable and informative percept, the visual system discounts the influence of extraneous factors such as illumination, occlusions, and viewing conditions. This perceptual “invariance” can be thought of as the brain’s solution to an inverse inference problem in which the physical factors that gave rise to the retinal image are estimated. While the processes of perception and recognition seem fast and effortless, it is a challenging computational problem that involves a substantial proportion of the primate brain.