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Browse project ideas by Polygence mentors
Epigenetic downregulations of the Vitamin D receptor gene in Multiple Sclerosis
Multiple Sclerosis (MS) is an autoimmune disease that affects the central nervous system (CNS) (Huang et al. 2017). Recent studies suggest that vitamin D deficiencies have risen as a central risk factor. The vitamin D receptor (VDR) is known to modulate immune tolerance to inflammatory responses in the CNS, which is correlated to MS susceptibility (Ao et al. 2021). Although high vitamin D levels provide capability for VDR activation, there are alternative factors that can accelerate MS development. This includes epigenetic mechanisms in the suppression of the VDR. Such epigenetic mechanisms, DNA methylation, histone modifications, and non-coding RNAs (ncRNAs), are recognised as regulators of VDR activity (Gasperini et al. 2023). For example, a silencing of VDR activity is noticed in patients with methylation in the promoter regions of the VDR. In a similar fashion, suppressive histone modifications leave VDR in a depressive state, allowing pro-inflammatory responses to activate. Additionally, ncRNAs, specifically microRNAs, directly silence VDR levels in MS patients. These interconnections found in epigenetic mechanisms in VDR downregulations and MS pathogenesis highlights how the VDR engenders conditions that prohibit inflammatory responses to weaken the CNS. This review serves to clarify the association between VDR downregulations and MS pathogenesis with emphasis on epigenetic control of VDR activity. By comprehensively analyzing epigenetic mechanisms in MS intervention, there are newfound opportunities for targeted epigenetic modulation as a therapeutic and preventive measure of MS.
Math, Neuroscience, Computer Science
The Link Between Depression and Neurodegeneration in Alzheimer’s Disease
Alzheimer’s Disease (AD) is often feared as a disease of losing memories, but what if depression could predict its arrival before memory loss proceeds? Affecting approximately 46.8 million people worldwide, Alzheimer’s is a progressive neurodegenerative disorder, one of the main causes of mortality and morbidity, especially among the elderly population (Sáiz-Vázquez et al., 2021). AD is the most prevalent type of dementia, accounting for 60 - 70% of all cases globally. It affects more than 50 million individuals worldwide, with incidence rising steadily due to global population aging. At the neuropathological level, AD is defined by two hallmark features: the extracellular aggregation of amyloid-beta (Aβ) plaques and the intracellular accumulation of hyperphosphorylated tau protein in the form of neurofibrillary tangles (NFTs). These protein aggregates are the main causes governing synaptic dysfunction, neuroinflammation, and widespread neuronal loss, particularly in regions essential for memory and cognition, such as the hippocampus and cerebral cortex. Despite decades of research, the precise mechanisms that drive AD pathogenesis remain shrouded in mystery, and there is currently no disease-modifying therapy.
Math, Neuroscience, Computer Science
The interplay between the amygdala and the hippocampus in the emotional processing of music and memories
For the human brain to analyze and understand music, there is a brilliant and meticulous symphony that orchestrates our ability to perceive a compilation of sounds as music. Starting as variations in air pressure received by the pinna at the outer ear, musical sounds are transmitted via the ossicles in the middle ear to the cochlea of the inner ear that harbor our sensory hair cells, which due to their mechanotransduction capabilities, transform the mechanical forces into electrical signaling that is then picked by the spiral ganglions transmitting the auditory message to various areas and pathways in the brain. While this cascade of events holds for every sound that enters our ears, why and how does music affect us? Why do specific songs trigger happiness while others unleash sad memories, and yet other songs bring relaxation or send shivers down our spines? In this work, we review the involvement of two major brain nuclei, the amygdala and the hippocampus, in the emotional processing of music. Among their many roles in the brain, these two nuclei had been shown to be heavily involved in enhancing emotional music memories and the euphoric response to music, interacting with one another to form long-lasting memories. This review gives an elaborate overview of the intricate interplay between the amygdala and the hippocampal neurons in the generation of the neural encoding of musical memories and their associated emotions.
Math, Neuroscience, Computer Science
Integrating Real-Time EEG Feedback with VR Systems: A Holistic Study in Neuroadaptive Interfaces
Background: Virtual Reality (VR) technology has great impact across various fields. Electroencephalography (EEG) feedback, on the other hand, measures brain activity and offers insights into cognitive and emotional states. Combining VR and real-time EEG feedback has become a popular area of research and creates adaptive, personalized systems that respond to the user’s brain activity. Objectives: This review aims to introduce neuroadaptive interfaces and provide an overview of the current state of research on integrating EEG feedback with VR technology. It seeks to explore the applications of EEG-VR systems, especially in therapeutic settings. The review identifies and examines key studies demonstrating the use of EEG-VR systems in neurological rehabilitation. Methods: The review involved a search of the official database of the National Institute of Health(NIH) and the Institute of Electrical and Electronics Engineers(IEEE). 38 papers were selected. The procedure and significance of EEG-VR are analyzed in detail using these papers. Results: EEG-VR systems have been shown to have a wide range of applications in modern medical settings. For example, it enhances pain management and improves neurosurgical practice in the treatment of mental health conditions. As demonstrated in the case studies, neuroadaptive interfaces adapt in real-time based on the user’s brain activity, providing a highly personalized and individualized experience and treatment.
Math, Neuroscience, Computer Science
Illuminating the Depths: The Neurobiology of Bioluminescence in Marine Life
Bioluminescence, the phenomenon of light production by living organisms through chemical reactions, illuminates the ocean’s depths much like stars adorn the night sky. This review explores the physiological control mechanisms behind marine bioluminescence across diverse taxa including Echinodermata, Cnidaria, Ctenophora, Arthropoda, Annelida, and Chordata. Organisms employ two main light-producing systems—luciferase-luciferin and photoprotein—housed in structures ranging from simple photocytes to complex photophores. Neurological and hormonal regulation finely tunes bioluminescent displays, which are crucial for understanding adaptive strategies of marine organisms and ecosystem health assessments. Despite advancements, gaps in electrophysiological and neurotransmitter studies persist, particularly in deep-sea species. Future research opportunities lie in developing noninvasive techniques for prolonged physiological studies, broadening comparative neurobiology across species, and elucidating neurotransmitter roles. Understanding these mechanisms not only unveils evolutionary adaptations but also informs bioengineering and conservation efforts, underscoring the enduring scientific interest and ecological significance of bioluminescence.
Math, Neuroscience, Computer Science
Understanding the Relationship Between Music and Neurodegenerative Diseases
Although it is speculated that music predates language, our understanding of the complicated and vast neural processes of music in the brain remains limited, especially concerning its effect on neurodegeneration. Music has a mainly positive effect on our mental well-being, a statement that is generally true for the average listener. However, the underlying mechanisms and reasons for this impact continue to be vague. This paper explores questions of “how” music impacts the development of neurodegenerative diseases and touches upon important questions of “why” understanding music on a neural basis is important. This paper argues that the fundamental qualities of music, namely melody, harmony, and rhythm, engage the brain’s predictive models, thereby activating its emotional and psychological perception; cognitive learning and memory; and physiological action. Consequently, this engagement activates all associated brain regions, leading to improvement in brain diseases that may lack activation in some of these regions. The attempt to understand music through a neural lens might seem counterproductive. After all, to advance our knowledge means to diminish the sense of novelty and amazement music is first viewed with. Historically, the tools used to analyze the brain were inadequate for finding meaningful conclusions about music’s relation with the brain. However, with the advent of advanced neuroimaging techniques such as fMRI and EEG, it has become clear that exploring music can help uncover deeper secrets about human emotions and mental health.
Math, Neuroscience, Computer Science
A Computational Model of the Dopaminergic and Pharmacological Modulations in the Subthalamopallidal Network of the Basal Ganglia
The basal ganglia, a large region comprising multiple complex subcortical nucleic areas interconnected in circuit systems, is crucial for regulating motor control, cognition, and reward processing. One such important system, the subthalamopallidal network, involves three specific cerebral areas: the globus pallidus, the subthalamic nucleus, and the dopaminergic substantia nigra pars compacta. This study focuses on computationally modeling the three components of the subthalamopallidal network to elucidate the neuron interactions and dopaminergic modulations of the substantia pars compacta and to highlight the effects of altering ion channel properties in the network. Simulations of substantia nigra pars compacta excitation on the network showed the importance of regulating firing and activity levels to maintain structured behavior throughout the other areas in the network. Manipulations of T-type low voltage-activated calcium channels and other ion properties revealed an important role of the T-type channel in regulating neuron firing throughout the network, suggesting potential pharmacological targets for neurodegenerative disorders like Parkinson’s disease. Despite alterations to many ion channels and the introduction of gradual neuronal dysfunction, the network showed robust tendencies. These findings contribute to understanding neural mechanisms in basal ganglia circuits and offer insights into the neurobiology and interactions between ion channels, individual neurons themselves, and whole networks communicating together in the human brain.
Math, Neuroscience, Computer Science
Computational Neuroscience Meets Down Syndrome: Bridging Molecular, Cellular, and Network Mechanisms
Trisomy 21 is the cause of Down syndrome (DS) and results in a wide range of neurobiological and cognitive impairments. This paper reviews the genetic, cellular, and network mechanisms underlying DS and explores the integration of computational models with neurobiological research to improve the understanding of DS’s phenotypic manifestations. This review discusses findings about DS’s gene overexpression, cellular alterations, structural brain changes, and manifestations. Additionally, it highlights computational models' roles in bridging the gap between neurobiological data and phenotypic manifestations. Despite significant advancements, there are many unknowns about DS, and computational models offer valuable insights into these complex interactions, guiding future research and the development of targeted interventions. This review highlights the importance of integrating computational approaches to enhance today’s understanding of DS and improve outcomes for affected individuals.
Math, Neuroscience, Computer Science
Temperature Induced Codimension-One and Codimension-Two Bifurcations in Hodgkin-Huxley Neurons
Temperature fluctuations can have detrimental effects on the firing pattern and electrical activity of biological neurons, eliciting diverse responses depending on the neuronal cell types and the underlying ion channels exhibited. Using the classical Hodgkin-Huxley (HH) model, we performed a comprehensive dynamical systems analysis to determine how temperature fluctuations alter neuronal excitability, spike morphology, and bifurcation structure. We first relied on experimentally-derived temperature coefficients, or Q10 values, associated with gating kinetics and conductances, and examined codimension-1 and codimension-2 bifurcations across a range of temperatures and standard HH parameters governing the intrinsic properties (firing frequency, spike amplitude, spike width, afterhyperpolarization (AHP), time-to-peak AHP, etc…) of the model HH neuron. Our analysis revealed that increasing temperature accelerates gating dynamics, leading to narrower and higher-frequency spikes but reduced amplitudes, and ultimately to a loss of sustained firing via temperature-induced depolarization block. We identified generalized Hopf (Bautin) bifurcations as critical boundaries beyond which the system becomes strictly monostable. Extending the model to independently scale sodium activation, sodium inactivation, and potassium activation kinetics showed that excitability is particularly sensitive to potassium gating dynamics. Our findings provide a quantitative framework for understanding temperature modulations of neuronal activity, highlighting how temperature reshapes the excitability landscape, unveiling the intricate interplays between the activation/inactivation kinetics of ion channels, and identifying key parameters governing temperature robustness in neuronal models.
Math, Neuroscience, Computer Science
Enhancing Alzheimer’s disease diagnostics: advances in non-invasive biomarker tests
Alzheimer’s disease (AD) is a neurodegenerative disease characterized by severe cognitive decline that progressively leads to dementia over time. This disease heavily affects the patient’s quality of life and often proving fatal. The progression of AD varies in different people, with survival time after diagnosis ranging from 4 to 8 years, with pathogenesis potentially starting a decade before symptom onset. Therefore, it is important to diagnose this disease early on in its pathogenesis to preserve patients’ quality of life with therapies and help the patient and their caretakers plan ahead for the future. However, the hallmark biomarkers of AD are proteotoxic proteins that mostly occur within the central nervous system, therefore current diagnosis methods such as cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), and positron emission tomography (PET) are invasive. Furthermore, they are expensive and can cost around several thousand dollars in the United States, making them unavailable to many people. Moreover, this disease may be caused by environmental factors, making it difficult to simply use genetic testing for diagnosis. These problems may discourage patients from getting diagnosed. Therefore, non-invasive and inexpensive methods in AD diagnosis are needed to improve and encourage diagnosis. This review summarizes non-invasive biomarkers that are currently being researched.
Math, Neuroscience, Computer Science