We review evidence for partially segregated networks of brain areas that carry out different attentional functions. One system, which includes parts of the intraparietal cortex and superior frontal cortex, is involved in preparing and applying goal-directed (top-down) selection for stimuli and responses. This system is also modulated by the detection of stimuli. The other system, which includes the temporoparietal cortex and inferior frontal cortex, and is largely lateralized to the right hemisphere, is not involved in top-down selection. Instead, this system is specialized for the detection of behaviourally relevant stimuli, particularly when they are salient or unexpected. This ventral frontoparietal network works as a 'circuit breaker' for the dorsal system, directing attention to salient events. Both attentional systems interact during normal vision, and both are disrupted in unilateral spatial neglect.

Control of goal-directed and stimulus-driven attention in the brain

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Attention and Effort

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components - not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

/pdf/perceptual-symbol-systems-4spsk97r61.pdf

Perceptual symbol systems.

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this "hierarchical prediction machine" approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency.

/pdf/whatever-next-predictive-brains-situated-agents-and-the-epj56cs868.pdf

Whatever next? Predictive brains, situated agents, and the future of cognitive science

These experiments use functional magnetic resonance imaging (fMRI) to reveal neural activity uniquely associated with perception of biological motion. We isolated brain areas activated during the viewing of point-light figures, then compared those areas to regions known to be involved in coherent-motion perception and kinetic-boundary perception. Coherent motion activated a region matching previous reports of human MT/MST complex located on the temporo-parieto-occipital junction. Kinetic boundaries activated a region posterior and adjacent to human MT previously identified as the kinetic-occipital (KO) region or the lateral-occipital (LO) complex. The pattern of activation during viewing of biological motion was located within a small region on the ventral bank of the occipital extent of the superior-temporal sulcus (STS). This region is located lateral and anterior to human MT/MST, and anterior to KO. Among our observers, we localized this region more frequently in the right hemisphere than in the left. This was true regardless of whether the point-light figures were presented in the right or left hemifield. A small region in the medial cerebellum was also active when observers viewed biological-motion sequences. Consistent with earlier neuroimaging and single-unit studies, this pattern of results points to the existence of neural mechanisms specialized for analysis of the kinematics defining biological motion.

/pdf/brain-areas-involved-in-perception-of-biological-motion-1h8vne119v.pdf

Brain Areas Involved in Perception of Biological Motion

Humans, being highly social creatures, rely heavily on the ability to perceive what others are doing and to infer from gestures and expressions what others may be intending to do. These perceptual skills are easily mastered by most, but not all, people, in large part because human action readily communicates intentions and feelings. In recent years, remarkable advances have been made in our understanding of the visual, motoric, and affective influences on perception of human action, as well as in the elucidation of the neural concomitants of perception of human action. This article reviews those advances and, where possible, draws links among those findings.

/pdf/perception-of-human-motion-2h7r5z9wbq.pdf

Perception of Human Motion

http://www.psy.vanderbilt.edu/faculty/blake/PDFs/GB_Neuron_2002.pdf

Brain Areas Active during Visual Perception of Biological Motion

When the two eyes view discrepant monocular stimuli, stable single vision gives way to alternating periods of monocular dominance; this is the well-known but little understood phenomenon of binocular rivalry. This article develops a neural theory of binocular rivalry that treats the phenomenon as the default outcome when binocular correspondence cannot be established. The theory posits the existence of monocular and binocular neurons arrayed within a functional processing module, with monocular neurons playing a crucial role in signaling the stimulus conditions instigating rivalry and generating inhibitory signals to implement suppression. Suppression is conceived as a local process happening in parallel over the entire cortical representation of the binocular visual field. The strength of inhibition causing suppression is related to the size of the pool of monocular neurons innervated by the suppressed eye, and the duration of a suppression phase is attributed to the strength of excitation generated by the suppressed stimulus. The theory is compared with three other contemporary theories of binocular rivalry. The article closes with a discussion of some of the unresolved problems related to the theory.

https://www.psy.gla.ac.uk/~martinl/Assets/MCMPS/Blake_89.pdf

A Neural Theory of Binocular Rivalry

http://www.psy.vanderbilt.edu/tonglab/publications/TongMengBlake_TICS2006.pdf

Randolph Blake

Papers

Brain Areas Involved in Perception of Biological Motion

Perception of Human Motion

Brain Areas Active during Visual Perception of Biological Motion

A Neural Theory of Binocular Rivalry

Neural bases of binocular rivalry.