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Theoretical considerations on models of vestibular self-motion perception as inherent in computational frameworks of motion sickness
No full textThis study examines self-motion perception incorporated into motion sickness models. Research on modeling self-motion perception and motion sickness has advanced independently, though both are thought to share neural mechanisms, making the construction of a unified model opportune. Models based on the Subjective Vertical Conflict (SVC) theory, a refinement of the neural mismatch theory, have primarily focused on motion sickness, with limited validation for self-motion perception. Emerging studies have begun evaluating the perceptual validity of these models, suggesting that some models can reproduce perception in specific paradigms, while they often struggle to jointly capture motion perception and sickness. One prior study demonstrated that one of the SVC models could replicate illusory tilt during centrifugation, while others produced unrealistic responses, such as persistent tilt after motion cessation. In reality, under steady-state conditions such as being motionless, perceived motion is expected to settle to an appropriate state regardless of prior states. Based on the idea that this behavior is closely related to the equilibrium points and stability of the model dynamics, this study theoretically analyzed 6DoF-SVC models with a focus on them. Results confirmed that only one model ensures convergence from any state to a unique equilibrium point corresponding to plausible perception. In contrast, other SVC models and a conventional self-motion perception model converged to values dependent on earlier states. Further analysis showed that only this model captured both the somatogravic and Ferris wheel illusion. In conclusion, this 6DoF-SVC model unifies motion perception and sickness modeling, with theoretical convergence of the perceptual state.journal articl
Mapping Morphine's Antinociceptive Impact on the Ventral Tegmental Area During Nociceptive Stimulation: A Novel Microimaging Approach in a Neuropathic Pain Model
No full textThe neurobiology of chronic pain is complex and multifaceted, intertwining with the mesocorticolimbic system to regulate the behavioral and perceptional response to adverse stimuli. Specifically, the ventral tegmental area (VTA), the dopaminergic hub of the reward pathways located deep within the midbrain, is crucial for regulating the release of dopamine (DA) throughout the central nervous system (CNS). To better understand the nuances among chronic pain, VTA response, and therapeutics, implementing progressive approaches for mapping and visualizing the deep brain in real time during nociceptive stimulation is crucial. In this study, we utilize a fluorescence imaging platform with a genetically encoded calcium indicator (GCaMP6s) to directly visualize activity in the VTA during acute nociceptive stimulation in both healthy adult mice and adult mice with partial nerve ligation (PNL)-induced neuropathic pain. We also investigate the visualization of the analgesic properties of morphine. Deep brain imaging using our self-fabricated µ-complementary metal–oxide–semiconductor (CMOS) imaging device allows the tracking of the VTA’s response to adverse stimuli. Our findings show that nociceptive stimulation is associated with a reduction in VTA fluorescence activity, supporting the potential of this platform for visualizing pain-related responses in the central nervous system. Additionally, treatment with morphine significantly reduces the neuronal response caused by mechanical stimuli and is observable using the CMOS imaging platform, demonstrating a novel way to potentially assess and treat neuropathic pain.journal articl
Deep Learning Based Beamforming and Metasurface Design for Reconfigurable Intelligent Surface
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Investigation of polymer-polymer interactions for novel composites utilizing poly(trimethylene carbonate) and its derivatives bearing long-alkyl chain at side groups
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