Fast Synchronization of Perpetual Grouping in Laminar Visual Cortical Circuits

Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints on which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

THE ROLE OF ACOUSTIC CAVITATION IN ENHANCED ULTRASOUND-INDUCED HEATING IN A TISSUE-MIMICKING PHANTOM

A complete understanding of high-intensity focused ultrasound-induced temperature changes in tissue requires insight into all potential mechanisms for heat deposition. Applications of therapeutic ultrasound often utilize acoustic pressures capable of producing cavitation activity. Recognizing the ability of bubbles to transfer acoustic energy into heat generation, a study of the role bubbles play in tissue hyperthermia becomes necessary. These bubbles are typically less than 50μm. This dissertation examines the contribution of bubbles and their motion to an enhanced heating effect observed in a tissue-mimicking phantom. A series of experiments established a relationship between bubble activity and an enhanced temperature rise in the phantom by simultaneously measuring both the temperature change and acoustic emissions from bubbles. It was found that a strong correlation exists between the onset of the enhanced heating effect and observable cavitation activity. In addition, the likelihood of observing the enhanced heating effect was largely unaffected by the insonation duration for all but the shortest of insonation times, 0.1 seconds. Numerical simulations were used investigate the relative importance of two candidate mechanisms for heat deposition from bubbles as a means to quantify the number of bubbles required to produce the enhanced temperature rise. The energy deposition from viscous dissipation and the absorption of radiated sound from bubbles were considered as a function of the bubble size and the viscosity of the surrounding medium. Although both mechanisms were capable of producing the level of energy required for the enhanced heating effect, it was found that inertial cavitation, associated with high acoustic radiation and low viscous dissipation, coincided with the the nature of the cavitation best detected by the experimental system. The number of bubbles required to account for the enhanced heating effect was determined through the numerical study to be on the order of 150 or less.

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.