Loredana Minini

Structural and Functional Changes across the Visual Cortex of a Patient with Visual Form Agnosia

Loss of shape recognition in visual-form agnosia occurs without equivalent losses in the use of vision to guide actions, providing support for the hypothesis of two visual systems (for “perception” and “action”). The human individual DF received a toxic exposure to carbon monoxide some years ago, which resulted in a persisting visual-form agnosia that has been extensively characterized at the behavioral level. We conducted a detailed high-resolution MRI study of DFs cortex, combining structural and functional measurements. We present the first accurate quantification of the changes in thickness across DFs occipital cortex, finding the most substantial loss in the lateral occipital cortex (LOC). There are reduced white matter connections between LOC and other areas. Functional measures show pockets of activity that survive within structurally damaged areas. The topographic mapping of visual areas showed that ordered retinotopic maps were evident for DF in the ventral portions of visual cortical areas V1, V2, V3, and hV4. Although V1 shows evidence of topographic order in its dorsal portion, such maps could not be found in the dorsal parts of V2 and V3. We conclude that it is not possible to understand fully the deficits in object perception in visual-form agnosia without the exploitation of both structural and functional measurements. Our results also highlight for DF the cortical routes through which visual information is able to pass to support her well-documented abilities to use visual information to guide actions.

Neural Modulation by Binocular Disparity Greatest in Human Dorsal Visual Stream

Although cortical activation to binocular disparity can be demonstrated throughout occipital and parietal cortices, the relative contributions to depth perception made by different human cortical areas have not been established. To investigate whether different regions are optimized for specific disparity ranges, we have measured the responses of occipital and parietal areas to different magnitudes of binocular disparity. Using stimuli consisting of sinusoidal depth modulations, we measured cortical activation when the stimuli were located at pedestal disparities of 0, 0.1, 0.35, and 0.7 degrees from fixation. Across all areas, occipital and parietal, there was an increase in BOLD signal with increasing pedestal disparity, compared with a plane at zero disparity. However, the greatest modulation of response by the different pedestals was found in the dorsal visual areas and the parietal areas. These differences contrast with the response to the zero disparity plane, compared with fixation, which is greatest in the early visual areas, smaller in the ventral and dorsal visual areas, and absent in parietal areas. Using the simultaneously acquired psychophysical data we also measured a greater response to correct than to incorrect trials, an effect that increased with rising pedestal disparity and was greatest in dorsal visual and parietal areas. These results illustrate that the dorsal stream, along both its occipital and parietal branches, can reliably discriminate a large range of disparities.

Responses to interocular disparity correlation in the human cerebral cortex.

Perceiving binocular depth relies on the ability of our visual system to precisely match corresponding features in the left and right eyes. Yet how the human brain extracts interocular disparity correlation is poorly understood.

A Self-Organizing Model of the Visual Development of Hand-Centred Representations

We show how hand-centred visual representations could develop in the primate posterior parietal and premotor cortices during visually guided learning in a self-organizing neural network model. The model incorporates trace learning in the feed-forward synaptic connections between successive neuronal layers. Trace learning encourages neurons to learn to respond to input images that tend to occur close together in time. We assume that sequences of eye movements are performed around individual scenes containing a fixed hand-object configuration. Trace learning will then encourage individual cells to learn to respond to particular hand-object configurations across different retinal locations. The plausibility of this hypothesis is demonstrated in computer simulations.

The Development of Hand-Centered Visual Representations in the Primate Brain: A Computer Modeling Study Using Natural Visual Scenes

Neurons that respond to visual targets in a hand-centered frame of reference have been found within various areas of the primate brain. We investigate how hand-centered visual representations may develop in a neural network model of the primate visual system called VisNet, when the model is trained on images of the hand seen against natural visual scenes. The simulations show how such neurons may develop through a biologically plausible process of unsupervised competitive learning and self-organization. In an advance on our previous work, the visual scenes consisted of multiple targets presented simultaneously with respect to the hand. Three experiments are presented. First, VisNet was trained with computerized images consisting of a realistic image of a hand and a variety of natural objects, presented in different textured backgrounds during training. The network was then tested with just one textured object near the hand in order to verify if the output cells were capable of building hand-centered representations with a single localized receptive field. We explain the underlying principles of the statistical decoupling that allows the output cells of the network to develop single localized receptive fields even when the network is trained with multiple objects. In a second simulation we examined how some of the cells with hand-centered receptive fields decreased their shape selectivity and started responding to a localized region of hand-centered space as the number of objects presented in overlapping locations during training increases. Lastly, we explored the same learning principles training the network with natural visual scenes collected by volunteers. These results provide an important step in showing how single, localized, hand-centered receptive fields could emerge under more ecologically realistic visual training conditions.

The visual development of hand-centered receptive fields in a neural network model of the primate visual system trained with experimentally recorded human gaze changes

ABSTRACT Neurons have been found in the primate brain that respond to objects in specific locations in hand-centered coordinates. A key theoretical challenge is to explain how such hand-centered neuronal responses may develop through visual experience. In this paper we show how hand-centered visual receptive fields can develop using an artificial neural network model, VisNet, of the primate visual system when driven by gaze changes recorded from human test subjects as they completed a jigsaw. A camera mounted on the head captured images of the hand and jigsaw, while eye movements were recorded using an eye-tracking device. This combination of data allowed us to reconstruct the retinal images seen as humans undertook the jigsaw task. These retinal images were then fed into the neural network model during self-organization of its synaptic connectivity using a biologically plausible trace learning rule. A trace learning mechanism encourages neurons in the model to learn to respond to input images that tend to occur in close temporal proximity. In the data recorded from human subjects, we found that the participant’s gaze often shifted through a sequence of locations around a fixed spatial configuration of the hand and one of the jigsaw pieces. In this case, trace learning should bind these retinal images together onto the same subset of output neurons. The simulation results consequently confirmed that some cells learned to respond selectively to the hand and a jigsaw piece in a fixed spatial configuration across different retinal views.

Geospatial statistics of high field functional MRI reveal topographical clustering for binocular stereo depth in early visual cortex

Significance statement Functional topography is present throughout the cerebral cortex, often in the form of columns or clusters of neurons with similar functional properties within identified cortical regions. Most of the evidence for these structures comes from work with non-human species. Using high-field strength magnetic resonance imaging in living human cortex, the search for this structure is frustrated by the presence of a background of local spatial correlations in the signal across the cortical surface. This structured background, which we term ‘neural dust’, is a form of noise that imposes a fundamental limit on the detection of clustering and topography. We apply a novel analysis approach that quantifies the background of spatial correlations, so that we achieve reliable identification of high-signal clusters of activation in the human cortex at a scale previously only visible with invasive optical imaging in animals. We searched specifically in visual cortex for correlates of binocular stereoscopic depth. We show both that signals for stereoscopic depth are clustered into specific zones within the cortex and that these signals occur within spatially extended cortical domains, which have similar preferences for the stereoscopic depth. The revealed structures are reliably identified in all subjects tested and in repeated testing of individual subjects. Our methods provide an objective approach for defining the size and locations of clusters of activation within functional images of neural activity. Abstract A characteristic principle of the organization of cerebral neocortex is the presence of clusters or columns of neurons with similar functional properties. Animals with forward-facing eyes exploit slight differences between the images in the two eyes to determine binocular depth using stereopsis. Evidence for an organized structure in human visual cortex for the representation of stereoscopic depth has proved elusive. Using 7-tesla functional MRI, with gradient-echo echo-planar imaging at 0.75 mm isotropic resolution and a novel analytical approach based on geospatial mapping methods, we find that clustered responses for disparity-defined depth can be clearly segregated from a background of spatially correlated signals in all subjects tested. High-signal clusters are associated with cortical domains as large as 12-15mm across the cortical surface, in which nearby points in the cortical map tend to respond to the same stereoscopic depth. These domains are found predominantly within visual cortical area V3A.

Human cortical responses to variations of the interocular correlation of binocular signals

The human visual system has an impressive ability to extract tiny differences from the left and right retinal images to produce the perception of depth. Moreover, the perception of depth is robust to a considerable amount of noise between the two images. Both these features of human vision contribute to the effectiveness of 3D imaging systems. Recent study of brain mechanisms for stereo has identified that there are multiple sites within the brain that respond to stereo depth, potentially implying that an effective 3D imaging system must deliver effective stimulation to multiple and differentiated brain systems. Here, we measure the neural responses of the visual cortex when tested a disparity-defined stimulus whose degree of interocular correlation was varied systematically. Neural responses were measured with functional magnetic resonance imaging (fMRI). This approach allowed us to obtain simultaneously measurements of the pattern of behavioral and neural responses to degraded binocular stimulation. Behavioral performance for the correct identification of binocular depth improved as expected with increasing degrees of binocular correlation. By comparison, the Blood Oxygen Level Dependent (BOLD) signal showed no consistent relationship with different levels of interocular correlation, although several of the visual cortical areas were strongly activated by the binocular stimuli. Preliminary analysis suggests that investigations of binocular vision that use fMRI need to adopt a multivariate approach to determine differences in neural responses to disparity-defined stimuli.