The interlinking of alpha waves and visuospatial cognition in motor-based domains.

The manner in which we perceive and respond in accordance to the world is encompassed by our ability to process multimodal input stimuli. In other words, in order to perform any task, especially at a high degree of proficiency, high dependence is placed upon our ability to interact with, interpret, and visualize input stimuli from our environment, known as visuospatial cognition (Chueh et al., 2017). This article will explore and encapsulate the importance of visuospatial cognition, in terms of the link it has with the performance of tasks in various fields, such as artistry, musical performance, and athleticism. Alpha wave investigation will be discussed as a means of both identifying and characterizing the degree of performance within these domains. Findings from this investigation may be used as a modality to optimize performance in the explored domains (e.g., with Neurofeedback techniques). The limitations of using Electroencephalography (EEG) to support the enhancement of this task performance and the recommendations to elicit further research, will also be explored.

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.

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.

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.

Responses to interocular disparity correlation in the human cerebral cortex.

PURPOSE: 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. METHODS: We used functional magnetic resonance imaging (fMRI) to characterize brain regions involved in processing interocular disparity correlation. By varying the amount of interocular correlation of a disparity-defined random-dot-stereogram, we concomitantly controlled the perception of binocular depth and measured the percent Blood-Oxygenation-Level-Dependent (%BOLD)-signal in multiple regions-of-interest in the human occipital cortex and along the intra-parietal sulcus. RESULTS: A linear support vector machine classification analysis applied to cortical responses showed patterns of activation that represented different disparity correlation levels within regions-of-interest in the visual cortex. These also revealed a positive trend between the difference in disparity correlation and classification accuracy in V1, V3 and lateral occipital cortex. Classifier performance was significantly related to behavioural performance in dorsal visual area V3. Cortical responses to random-dot-stereogram stimuli were greater in the right compared to the left hemisphere. CONCLUSIONS: Our results show that multiple regions in the cerebral cortex are sensitive to changes in interocular disparity correlation, and that dorsal area V3 may play an important role in the early transformation of binocular disparity to depth perception.

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 DF's cortex, combining structural and functional measurements. We present the first accurate quantification of the changes in thickness across DF's 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.

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.

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.

Do rats use shape to solve "shape discriminations"?

Visual discrimination tasks are increasingly used to explore the neurobiology of vision in rodents, but it remains unclear how the animals solve these tasks: Do they process shapes holistically, or by using low-level features such as luminance and angle acuity? In the present study we found that when discriminating triangles from squares, rats did not use shape but instead relied on local luminance differences in the lower hemifield. A second experiment prevented this strategy by using stimuli-squares and rectangles-that varied in size and location, and for which the only constant predictor of reward was aspect ratio (ratio of height to width: a simple descriptor of "shape"). Rats eventually learned to use aspect ratio but only when no other discriminand was available, and performance remained very poor even at asymptote. These results suggest that although rats can process both dimensions simultaneously, they do not naturally solve shape discrimination tasks this way. This may reflect either a failure to visually process global shape information or a failure to discover shape as the discriminative stimulus in a simultaneous discrimination. Either way, our results suggest that simultaneous shape discrimination is not a good task for studies of visual perception in rodents.