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The evolution of cerebral imaging technologies combined with specific image processing algorithms contribute to improving our knowledge of the brain functioning, in particular regarding visual perception. This thesis contributes to current understanding implied in visual motion perception in humans, based on complementary information brought by different Magnetic Resonance Imaging (MRI) modalities. The first part of this work focuses on functional MRI (fMRI) identification of low-level visual areas. We detail the fMRI retinotopic mapping procedure we developed, from the stimulus design to the final anatomo-functional analysis. A specific functional localization of the hMT/V5+ complex is also obtained with a block design. These methods, optimized according to some stimulation parameters, allow the extraction of individually defined and homogeneous Regions Of Interest (ROI). In the second part, we characterize functionally these previously identified low-level visual areas. Based on the recent fMR-Adaptation paradigm, which allows to investigate the sensitivity of a cortical region to quantitative variations of a given feature, we demonstrate a functional differentiation across areas regarding their relative sensitivity to visual direction of motion. Lastly, we combine fMRI and Diffusion Tensor MRI (DTI) to study the anatomical connectivity within the low-level visual cortex. Based on state of the art white matter fibers mapping algorithms, this characterization gives insights on the network of areas implied, among others, in visual motion processing.
Foremost neurophysiologists and psychophysicists provide pertinent information on the nature of representation at the earliest stages as this will constrain the disposition of all subsequent processing. This processing is discussed in several different types of visual perception.
This book presents a collection of articles reflecting state-of-the-art research in visual perception, specifically concentrating on neural correlates of perception. Each section addresses one of the main topics in vision research today. Volume 1 Fundamentals of Vision: Low and Mid-Level Processes in Perception covers topics from receptive field analyses to shape perception and eye movements. A variety of methodological approaches are represented, including single-neuron recordings, fMRI and optical imaging, psychophysics, eye movement characterization and computational modelling. The contributions will provide the reader with a valuable perspective on the current status of vision research, and more importantly, with critical insight into future research directions and the discoveries yet to come. · Provides a detailed breakdown of the neural and psychophysical bases of Perception · Presents never-before-published original discoveries · Includes multiple full-color illustrations
Motion processing is an essential piece of the complex brain machinery that allows us to reconstruct the 3D layout of objects in the environment, to break camouflage, to perform scene segmentation, to estimate the ego movement, and to control our action. Although motion perception and its neural basis have been a topic of intensive research and modeling the last two decades, recent experimental evidences have stressed the dynamical aspects of motion integration and segmentation. This book presents the most recent approaches that have changed our view of biological motion processing. These new experimental evidences call for new models emphasizing the collective dynamics of large population of neurons rather than the properties of separate individual filters. Chapters will stress how the dynamics of motion processing can be used as a general approach to understand the brain dynamics itself.
Animals use vision to traverse novel cluttered environments with apparent ease. Evidence suggests that the mammalian brain integrates visual motion cues across a number of remote but interconnected brain regions that make up a visual motion pathway. Although much is known about the neural circuitry that is concerned with motion perception in the Primary Visual Cortex (V1) and the Middle Temporal area (MT), little is known about how relevant perceptual variables might be represented in higher-order areas of the motion pathway, and how neural activity in these areas might relate to the behavioral dynamics of locomotion.The main goal of this dissertation is to investigate the computational principles that the mammalian brain might be using to organize low-level motion signals into distributed representations of perceptual variables, and how neural activity in the motion pathway might mediate behavior in reactive navigation tasks. I first investigated how the aperture problem, a fundamental conceptual challenge encountered by all low-level motion systems, can be solved in a spiking neural network model of V1 and MT (consisting of 153,216 neurons and 40 million synapses), relying solely on dynamics and properties gleaned from known electrophysiological and neuroanatomical evidence, and how this neural activity might influence perceptual decision-making. Second, when used with a physical robot performing a reactive navigation task in the real world, I found that the model produced behavioral trajectories that closely matched human psychophysics data. Essential to the success of these studies were software implementations that could execute in real time, which are freely and openly available to the community. Third, using ideas from the efficient-coding and free-energy principles, I demonstrated that a variety of response properties of neurons in the dorsal sub-region of the Medial Superior Temporal area (MSTd) area could be derived from MT-like input features. This finding suggests that response properties such as 3D translation and rotation selectivity, complex motion perception, and heading selectivity might simply be a by-product of MSTd neurons performing dimensionality reduction on their inputs. The hope is that these studies will not only further our understanding of how the brain works, but also lead to novel algorithms and brain-inspired robots capable of outperforming current artificial systems.
For the successful recognition of objective, `real' motion based on visual cues it is necessary to take self-induced motion signals into account, such as those induced by eye-movements. During a series of fMRI studies we measured responses of visual and parietal regions to motion cues derived from (a) retinal motion, (b) eyemovements (visual pursuit) and (c) objective, (real) motion. We show that the recently described cingulate sulcus visual area (CSv) is not, as implied before, primarily driven by 3D self-motion cues but favoured 2D translational coherent motion over 3D expanding flow fields. Further, we found that V3A is capable of integrating retinal motion with eye-movements, thus allowing V3A to respond to object motion independent of retinal motion. This allowed us to define a new functional localizer for area V3A. Finally, we showed that activity in the foveal representation of the early visual cortex is driven by a combination of retinal input and by error signals as hypothesized by of Rao and Ballard (1999) for predictive coding. Taken together, this work provides evidence that regions V3A and CSv are key regions concerning visual self-motion processing and that early visual regions might be modulated by feedback from higher motion processing regions.
The brain's ability to detect movement within the retinal image is crucial not only for determining the trajectories of moving objects, but also for identifying and interpreting image motion resulting from eye and head movements. This book summarizes our knowledge of how information about image motion is encoded in the brain. Key Features * Valuable reference source for those involved in the rapidly expanding area of motion perception * Strong emphasis on integration of physiological, computation, and psychophysical approaches * Topics include: * Principles of local motion detection * Inputs to local motion detectors * Integration of motion signals * Higher-order interpretation of motion * Motion detection and eye movements
The Cambridge Handbook of Applied Perception Research covers core areas of research in perception with an emphasis on its application to real-world environments. Topics include multisensory processing of information, time perception, sustained attention, and signal detection, as well as pedagogical issues surrounding the training of applied perception researchers. In addition to familiar topics, such as perceptual learning, the Handbook focuses on emerging areas of importance, such as human-robot coordination, haptic interfaces, and issues facing societies in the twenty-first century (such as terrorism and threat detection, medical errors, and the broader implications of automation). Organized into sections representing major areas of theoretical and practical importance for the application of perception psychology to human performance and the design and operation of human-technology interdependence, it also addresses the challenges to basic research, including the problem of quantifying information, defining cognitive resources, and theoretical advances in the nature of attention and perceptual processes.