a-gaze-contingent-display-framework-for-perceptual-learning-research

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Macular degeneration (MD) is one of the leading causes of vision impairment in the Western world. Patients with MD tend to develop spontaneous eye ...

University of Alabama at Birmingham

The functionality of central vision is different from peripheral vision. Central vision is used for fixation and has higher acuity, making it useful for everyday activities such as reading and object identification. The central and peripheral representations in primary visual cortex (V1) also differ in how higher-order processing areas modulate their responses. For example, attention and expectation are top-down processes (i.e., high-order cognitive functions) that influence visual information processing during behavioral tasks. This top-down control is different for central vs. peripheral vision. Since functional networks can influence visual information processing in different ways, networks (such as the Fronto-Parietal (FPN), Default Mode (DMN), and Cingulo-Opercular (CON)) likely differ in how they connect to representations of the visual field across V1. Prior work indicated the central representing portion of V1 was more functionally connected to regions belonging to the FPN, and the far-peripheral representing portion of V1 was more functionally connected to regions belonging to the DMN. Our goals were (1) Assess the reproducibility and generalizability of retinotopic effects on functional connections between V1 and functional networks. (2) Extend this work to understand structural connections of central vs. peripheral representations in V1. (3) Examine the overlapping eccentricity differences in functional and structural connections of V1. (4) Examine the major white matter tracks connecting central V1 to frontal regions. We used resting-state BOLD fMRI and DWI to examine whether portions of V1 that represent different visual eccentricities differ in their functional and structural connectivity to functional networks. All data were acquired and minimally preprocessed by the Human Connectome Project. We identified central and far-peripheral representing regions from a retinotopic template. Functional connectivity was measured by correlated activity between V1 and functional networks, and structural connectivity was measured by probabilistic tractography and converted to track probability. In both modalities, differences between V1 eccentricity segment connections were compared by paired, two-tailed t-test. A spatial permutation approach was used to determine the statistical significance of the spatial overlap between modalities. The identified spatial overlap was then used in a deterministic tractography approach to identify the white matter pathways connecting the overlap to central V1. We found (1) Centrally representing portions of V1 are more strongly functionally connected to frontal regions than are peripherally representing portions of V1, (2) Structural connections also show stronger connections between central V1 and frontal regions, (3) Patterns of structural and functional connections overlaps in the lateral frontal cortex, (4) This lateral frontal overlap is connected to central V1 via the IFOF. In summary, the work's main contribution is a greater understanding of higher-order functional networks' connectivity to V1. There are stronger structural connections to central representations in V1, particularly for lateral frontal regions, implying that the functional relationship between central V1 and frontal regions is built upon direct, long-distance connections via the IFOF. Overlapping structural and functional connections reflect differences in V1 eccentricities, with central V1 preferentially connected to attention-associated regions. Understanding how V1 is functionally and structurally connected to higher-order brain areas contributes to our understanding of how the human brain processes visual information and forms a baseline for understanding any modifications in processing that might occur with training or experience.

Frontal cortical regions associated with attention connect more strongly to central than peripheral V1.

The homozygous LAMC3 gene mutation is associated with severe bilateral smoothening and thickening of the lateral occipital cortex . Despite this and further significant changes in gray matter structure, a patient harboring this mutation exhibited a range of remarkably intact perceptual abilities . One possible explanation of this perceptual sparing could be that the white matter structural integrity and functional connectivity in relevant pathways remained intact. To test this idea, we used diffusion tensor and functional magnetic resonance imaging to investigate functional connectivity in resting-state networks in major structural pathways involved in object perception and visual attention and corresponding microstructural integrity in a patient with homozygous LAMC3 mutation and sex, age, education, and socioeconomically matched healthy control group. White matter microstructural integrity results indicated widespread disruptions in both intra- and interhemispheric structural connections except inferior longitudinal fasciculus. With a few exceptions, the functional connectivity between the patient's adjacent gray matter regions of major white matter tracts of interest was conserved. In addition, functional localizers for face, object, and place areas showed similar results with a representative control, providing an explanation for the patient's intact face, place, and object recognition abilities. To generalize this finding, we also compared functional connectivity between early visual areas and face, place, and object category-selective areas, and we found that the functional connectivity of the patient was not different from the control group. Overall, our results provided complementary information about the effects of LAMC3 gene mutation on the human brain including intact temporo-occipital structural and functional connectivity that are compatible with preserved perceptual abilities.

Cortical connectivity in the face of congenital structural changes-A case of homozygous LAMC3 mutation.

The visual cortex has been a heavily studied region in neuroscience due to many factors, not the least of which is its well-defined retinotopic organization. This organization makes it possible to predict the general location of cortical regions that stimuli will activate during visual tasks. However, the precise and accurate mapping of these regions in human patients takes time, effort, and participant compliance that can be difficult in many patient populations. In humans, this retino-cortical mapping has typically been done using functional localizers which maximally activate the area of interest, and then the activation profile is thresholded and converted to a binary mask region of interest (ROI). An alternative method involves performing population receptive field (pRF) mapping of the whole visual field and choosing vertices whose pRF centers fall within the stimulus. This method ignores the spatial extent of the pRF which changes dramatically between central and peripheral vision. Both methods require a dedicated functional scan and depend on participants' stable fixation. The aim of this project was to develop a user-friendly method that can transform a retinal object of interest (for example, an image, a retinal lesion, or a preferred locus for fixation) from retinal space to its expected representation on the cortical surface without a functional scan. We modeled the retinal representation of each cortical vertex as a 2D Gaussian with a location and spatial extent given by a previously published retinotopic atlas. To identify how affected any cortical vertex would be by a given retinal object, we took the product of the retinal object with the Gaussian pRF of that cortical vertex. Normalizing this value gives the expected response of a given vertex to the retinal object. This method was validated using BOLD data obtained using a localizer with discrete visual stimuli, and showed good agreement to predicted values. Cortical localization of a visual stimulus or retinal defect can be obtained using our publicly available software, without a functional scan. Our software may benefit research with disease populations who have trouble maintaining stable fixation.

A method for mapping retinal images in early visual cortical areas.

Magnetic resonance imaging (MRI) scanners at ultra-high magnetic fields have become available to use in humans, thus enabling researchers to investigate the human brain in detail. By increasing the spatial resolution, ultra-high field MR allows both structural and functional characterization of cortical layers. Techniques that can differentiate cortical layers, such as histological studies and electrode-based measurements have made critical contributions to the understanding of brain function, but these techniques are invasive and thus mainly available in animal models. There are likely to be differences in the organization of circuits between humans and even our closest evolutionary neighbors. Thus research on the human brain is essential. Ultra-high field MRI can observe differences between cortical layers, but is non-invasive and can be used in humans. Extensive previous literature has shown that neuronal connections between brain areas that transmit feedback and feedforward information terminate in different layers of the cortex. Layer-specific functional MRI (fMRI) allows the identification of layer-specific hemodynamic responses, distinguishing feedback and feedforward pathways. This capability has been particularly important for understanding visual processing, as it has allowed researchers to test hypotheses concerning feedback and feedforward information in visual cortical areas. In this review, we provide a general overview of successful ultra-high field MRI applications in vision research as examples of future research.

Laminar functional magnetic resonance imaging in vision research.

Late-stage macular degeneration (MD) often causes retinal lesions depriving an individual of central vision, forcing them to learn to use peripheral vision for daily tasks. To compensate, many patients develop a preferred retinal locus (PRL), an area of peripheral vision used more often than equivalent regions of spared vision. Thus, associated portions of cortex experience increased use, while portions of cortex associated with the lesion are deprived of sensory input. Prior research has not well examined the degree to which structural plasticity depends on the amount of use across the visual field. Cortical thickness, neurite density, and orientation dispersion were measured at portions of cortex associated with the PRL, the retinal lesion, and a control region in participants with MD as well as age-matched, gender-matched, and education-matched controls. MD participants had significantly thinner cortex in both the cortical representation of the PRL (cPRL) and the control region, compared with controls, but no significant differences in thickness, neurite density, or orientation dispersion were found between the cPRL and the control region as functions of disease or onset. This decrease in thickness is driven by a subset of early-onset participants whose patterns of thickness, neurite density, and neurite orientation dispersion are distinct from matched control participants. These results suggest that people who develop MD earlier in adulthood may undergo more structural plasticity than those who develop it late in life.

Cortical plasticity in central vision loss: Cortical thickness and neurite structure.

Alterations in P300 amplitude and latency, as well as neuropsychological tests, are informative to detect early signs of the affected high cognitive processing in Mild Cognitive Impairment (MCI). In the present study, we examined P300 latency and amplitude elicited by visual oddball paradigm in 20 participants with MCI and age, education, and sex-matched healthy controls from frontal, central, and parietal midline electrodes. We performed a mixed-design ANOVA to compare P300 amplitude and latency between groups during target and non-target stimulus presentation. We also assessed the correlation between our electrophysiology findings and neuropsychological tests. Our results indicated that in healthy individuals P300 is elicited earlier in target stimulus processing compared to non-target stimulus processing. On the contrary, in the MCI group, P300 latency was increased during target processing compared to non-target stimulus processing. Moreover, P300 latency in target processing is prolonged in the MCI group compared to controls. Also, our correlation results showed a significant correlation between P300 peak latency and amplitude, and attention required cognitive tasks. In conclusion, our results provide evidence that high-order cognitive processes that are involved in stimulus processing slows down in individuals with MCI due to the high working memory demand for neural processing.

Cognitive load associates prolonged P300 latency during target stimulus processing in individuals with mild cognitive impairment.

Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how removal of input changes brain function. However, an important question yet to be answered is: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. When central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with some portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. Specifically, we examined functional connectivity between category-selective visual areas and the cortical representation of three areas of the retina: the lesioned area, a preferentially used region of the intact retina, and a non-preferentially used region. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that the long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development.

Article	Year
Frontal cortical regions associated with attention connect more strongly to central than peripheral V1. NeuroImage\| PubMed ID: 34111516	2021
Cortical connectivity in the face of congenital structural changes-A case of homozygous LAMC3 mutation. Brain and behavior\| PubMed ID: 34124859	2021
A method for mapping retinal images in early visual cortical areas. NeuroImage\| PubMed ID: 34798232	2021
Laminar functional magnetic resonance imaging in vision research. Frontiers in neuroscience\| PubMed ID: 36267240	2022
Cortical plasticity in central vision loss: Cortical thickness and neurite structure. Human brain mapping\| PubMed ID: 37195035	2023
Cognitive load associates prolonged P300 latency during target stimulus processing in individuals with mild cognitive impairment. Scientific reports\| PubMed ID: 37743392	2023
Impact of Deprivation and Preferential Usage on Functional Connectivity Between Early Visual Cortex and Category-Selective Visual Regions. Human brain mapping\| PubMed ID: 39575904	2024

Pinar Demirayak

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