A Computational Model of Perceptual Fill-in Following Retinal Degeneration

A Computational Model for the Neural Representation and Estimation of the Binocular Vector Disparity from Convergent Stereo Image Pairs

The depth cue is a fundamental piece of information for artificial and living beings who interact with the surrounding environment in order to handle objects and to avoid obstacles: in such situations, the disparity patterns, which arise when agents fixate objects, are vector fields. We propose a biologically-inspired computational model to estimate dense horizontal and vertical disparity maps by exploiting the cortical paradigms of the primate visual system: in particular, we aim to model the disparity sensitivity of the V1–MT visual pathway. The proposed model is based on a first processing stage composed of a bank of spatial band-pass filters and a static nonlinearity, mimicking complex binocular cells. Then, subsequent pooling stages and decoding strategies allow the model to estimate the vector disparity, after having represented it as a population of MT-like units. We assess the proposed model by using standard benchmarking stereo images, the Middlebury dataset, and specific stereo images that have horizontal and vertical disparities, which characterize the stimuli produced by active vision systems. Moreover, we systemically analyze how the different processing stages affect the model performance, and we discuss their implications for the neural modeling.

Adult cortical plasticity studied with chronically implanted electrode arrays

The functional architecture of adult cerebral cortex retains a capacity for experience-dependent change. This is seen after focal binocular lesions as rapid changes in receptive field (RF) of the lesion projection zone (LPZ) in the primary visual cortex (V1). To study the dynamics of the circuitry underlying these changes longitudinally, we implanted microelectrode arrays in macaque (Macaca mulatta) V1, eliminating the possibility of sampling bias, which was a concern in previous studies. With this method, we observed a rapid initial recovery in the LPZ and, during the following weeks, 63-89% of the sites in the LPZ showed recovery of visual responses with significant position tuning. The RFs shifted ∼3° away from the scotoma. In the absence of a lesion, visual stimulation surrounding an artificial scotoma did not elicit visual responses, suggesting that the postlesion RF shifts resulted from cortical reorganization. Interestingly, although both spikes and LFPs gave consistent prelesion position tuning, only spikes reflected the postlesion remapping.

Death receptor 6 regulates adult experience-dependent cortical plasticity

Sensory experience alters cortical circuitry by parallel processes of axon outgrowth and pruning, but the mechanisms that control these rearrangements are poorly understood. Using in vivo 2-photon longitudinal imaging, we found a marked reduction in axonal pruning in somatosensory cortex of mice with a knock-out of the DR6 gene, which codes for Death Receptor 6. This effect was seen for both long-range horizontal excitatory connections and for the axons of inhibitory neurons. These results identify a new pathway governing axonal plasticity associated with experience-dependent changes in cortical maps.

A simple rule for dendritic spine and axonal bouton formation can account for cortical reorganization after focal retinal lesions

Lasting alterations in sensory input trigger massive structural and functional adaptations in cortical networks. The principles governing these experience-dependent changes are, however, poorly understood. Here, we examine whether a simple rule based on the neurons' need for homeostasis in electrical activity may serve as driving force for cortical reorganization. According to this rule, a neuron creates new spines and boutons when its level of electrical activity is below a homeostatic set-point and decreases the number of spines and boutons when its activity exceeds this set-point. In addition, neurons need a minimum level of activity to form spines and boutons. Spine and bouton formation depends solely on the neuron's own activity level, and synapses are formed by merging spines and boutons independently of activity. Using a novel computational model, we show that this simple growth rule produces neuron and network changes as observed in the visual cortex after focal retinal lesions. In the model, as in the cortex, the turnover of dendritic spines was increased strongest in the center of the lesion projection zone, while axonal boutons displayed a marked overshoot followed by pruning. Moreover, the decrease in external input was compensated for by the formation of new horizontal connections, which caused a retinotopic remapping. Homeostatic regulation may provide a unifying framework for understanding cortical reorganization, including network repair in degenerative diseases or following focal stroke.

The adult brain is less hard-wired than traditionally thought. About ten percent of synapses in the mature visual cortex is continually replaced by new ones (structural plasticity). This percentage greatly increases after lasting changes in visual input. Due to the topographically organized nerve connections from the retina in the eye to the primary visual cortex in the brain, a small circumscribed lesion in the retina leads to a defined area in the cortex that is deprived of input. Recent experimental studies have revealed that axonal sprouting and dendritic spine turnover are massively increased in and around the cortical area that is deprived of input. However, the driving forces for this structural plasticity remain unclear. Using a novel computational model, we examine whether the need for activity homeostasis of individual neurons may drive cortical reorganization after lasting changes in input activity. We show that homeostatic growth rules indeed give rise to structural and functional reorganization of neuronal networks similar to the cortical reorganization observed experimentally. Understanding the principles of structural plasticity may eventually lead to novel treatment strategies for stimulating functional reorganization after brain damage and neurodegeneration.

Adult visual cortical plasticity

The visual cortex has the capacity for experience-dependent change, or cortical plasticity, that is retained throughout life. Plasticity is invoked for encoding information during perceptual learning, by internally representing the regularities of the visual environment, which is useful for facilitating intermediate-level vision--contour integration and surface segmentation. The same mechanisms have adaptive value for functional recovery after CNS damage, such as that associated with stroke or neurodegenerative disease. A common feature to plasticity in primary visual cortex (V1) is an association field that links contour elements across the visual field. The circuitry underlying the association field includes a plexus of long-range horizontal connections formed by cortical pyramidal cells. These connections undergo rapid and exuberant sprouting and pruning in response to removal of sensory input, which can account for the topographic reorganization following retinal lesions. Similar alterations in cortical circuitry may be involved in perceptual learning, and the changes observed in V1 may be representative of how learned information is encoded throughout the cerebral cortex.

Decoding simulated neurodynamics predicts the perceptual consequences of age-related macular degeneration

Age-related macular degeneration (AMD) is the major cause of blindness in the developed world. Though substantial work has been done to characterize the disease, it is difficult to predict how the state of an individual's retina will ultimately affect their high-level perceptual function. In this paper, we describe an approach that couples retinal imaging with computational neural modeling of early visual processing to generate quantitative predictions of an individual's visual perception. Using a patient population with mild to moderate AMD, we show that we are able to accurately predict subject-specific psychometric performance by decoding simulated neurodynamics that are a function of scotomas derived from an individual's fundus image. On the population level, we find that our approach maps the disease on the retina to a representation that is a substantially better predictor of high-level perceptual performance than traditional clinical metrics such as drusen density and coverage. In summary, our work identifies possible new metrics for evaluating the efficacy of treatments for AMD at the level of the expected changes in high-level visual perception and, in general, typifies how computational neural models can be used as a framework to characterize the perceptual consequences of early visual pathologies.

Adaptive shape processing in primary visual cortex

The ability to derive meaning from complex sensory input requires the integration of information over space and time, as well as cognitive mechanisms to shape that integration. We studied these processes in the primary visual cortex (V1), where neurons are thought to integrate visual inputs along contours defined by an association field (AF). We recorded extracellularly from single cells in macaque V1 to map the AF, by using an optimization algorithm to find the contours that maximally activated individual cells. We combined the algorithm with a delayed-match-to-sample task, to test how the optimal contours might be molded by the monkey's expectation for particular cue shapes. We found that V1 neurons were selective for complex shapes, a property previously ascribed to higher cortical areas. Furthermore, the shape selectivity was reprogrammed by perceptual task: Over the whole network, the optimal modes of geometric selectivity shifted between distinct subsets of the AF, alternately representing different stimulus features known to predominate in natural scenes. Our results suggest a general model of cortical function, whereby horizontal connections provide a broad domain of potential associations, and top-down inputs dynamically gate these linkages to task switch the function of a network.

Vision restoration after brain and retina damage: the "residual vision activation theory"

Vision loss after retinal or cerebral visual injury (CVI) was long considered to be irreversible. However, there is considerable potential for vision restoration and recovery even in adulthood. Here, we propose the "residual vision activation theory" of how visual functions can be reactivated and restored. CVI is usually not complete, but some structures are typically spared by the damage. They include (i) areas of partial damage at the visual field border, (ii) "islands" of surviving tissue inside the blind field, (iii) extrastriate pathways unaffected by the damage, and (iv) downstream, higher-level neuronal networks. However, residual structures have a triple handicap to be fully functional: (i) fewer neurons, (ii) lack of sufficient attentional resources because of the dominant intact hemisphere caused by excitation/inhibition dysbalance, and (iii) disturbance in their temporal processing. Because of this resulting activation loss, residual structures are unable to contribute much to everyday vision, and their "non-use" further impairs synaptic strength. However, residual structures can be reactivated by engaging them in repetitive stimulation by different means: (i) visual experience, (ii) visual training, or (iii) noninvasive electrical brain current stimulation. These methods lead to strengthening of synaptic transmission and synchronization of partially damaged structures (within-systems plasticity) and downstream neuronal networks (network plasticity). Just as in normal perceptual learning, synaptic plasticity can improve vision and lead to vision restoration. This can be induced at any time after the lesion, at all ages and in all types of visual field impairments after retinal or brain damage (stroke, neurotrauma, glaucoma, amblyopia, age-related macular degeneration). If and to what extent vision restoration can be achieved is a function of the amount of residual tissue and its activation state. However, sustained improvements require repetitive stimulation which, depending on the method, may take days (noninvasive brain stimulation) or months (behavioral training). By becoming again engaged in everyday vision, (re)activation of areas of residual vision outlasts the stimulation period, thus contributing to lasting vision restoration and improvements in quality of life.

Rapid axonal sprouting and pruning accompany functional reorganization in primary visual cortex

The functional architecture of adult cerebral cortex retains a capacity for experience-dependent change. This is seen following focal binocular lesions, which induce rapid changes in receptive field size and position. To follow the dynamics of the circuitry underlying these changes, we imaged the intrinsic long-range horizontal connections within the lesion projection zone (LPZ) in adult macaque primary visual cortex. To image the same axons over time, we combined viral vector-mediated EGFP transfer and two-photon microscopy. The lesion triggered, within the first week, an approximately 2-fold outgrowth of axons toward the center of the LPZ. Over the subsequent month, axonal density declined due to a parallel process of pruning and sprouting but maintained a net increase relative to prelesion levels. The rate of turnover of axonal boutons also increased. The axonal restructuring recapitulates the pattern of exuberance and pruning seen in early development and correlates well with the functional changes following retinal lesions.