Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal
| dc.contributor.author | Purohit, Pratik | |
| dc.contributor.author | Dutta, Prasun | |
| dc.contributor.author | Roy, Prasun K. | |
| dc.date.accessioned | 2024-02-08T10:15:06Z | |
| dc.date.available | 2024-02-08T10:15:06Z | |
| dc.date.issued | 2023-05-12 | |
| dc.description | This paper published with affiliation IIT (BHU), Varanasi in Open Access Mode. | en_US |
| dc.description.abstract | Introduction: Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space. Methods: We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex. Results: We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation. Conclusion: We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers. | en_US |
| dc.description.sponsorship | National Institutes of Health | en_US |
| dc.identifier.issn | 16625188 | |
| dc.identifier.uri | https://idr-sdlib.iitbhu.ac.in/handle/123456789/2845 | |
| dc.language.iso | en | en_US |
| dc.publisher | Frontiers Media S.A. | en_US |
| dc.relation.ispartofseries | Frontiers in Computational Neuroscience;17 | |
| dc.subject | autonomic nervous system | en_US |
| dc.subject | diffusion tensor imaging | en_US |
| dc.subject | grid cell | en_US |
| dc.subject | Hill equation | en_US |
| dc.subject | metric tensor | en_US |
| dc.subject | psilocybin | en_US |
| dc.subject | spatial perception | en_US |
| dc.subject | visual cortex | en_US |
| dc.title | Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal | en_US |
| dc.type | Article | en_US |
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