8,558 research outputs found
Adaptations in physiological and neuronal function during diet-induced obesity
Obesity significantly increases the risk of developing chronic conditions including type II diabetes, cardiovascular disease, and some cancers. The rate of obesity has tripled globally since 1975, which is in part due to the sudden prevalence and overconsumption of palatable high-fat diets (HFDs). Obesity profoundly perturbs the neural control of energy balance, affecting diverse cell types within the hypothalamus. However, an incomplete understanding of how HFD impacts the regulation of energy balance hinders our ability to more effectively treat obesity.
In this thesis, I describe the physiological and neuronal response to HFD feeding in rodents. We identified that HFD exposure elevates the body weight set point, which is initially driven by a transient hyperphagia. This hyperphagia coincides with increased excitatory transmission to lateral hypothalamic orexin (ORX) neurons, which regulate acute food intake. This suggests that ORX neurons may be involved in the initial hyperphagia, implicating them in the development of obesity. As HFD prolongs, body weight gain slows and reaches a new steady state regardless of age at the start, duration of feeding, or palatability of the diet. This sustained weight coincides with increased synaptic contacts to melanin-concentrating hormone (MCH) neurons, which promote weight gain and food intake, likely contributing to the maintenance of obesity.
The molecular mechanism underlying the establishment of a new set point remains elusive. During HFD feeding, the presence of a chronic low-grade
hypothalamic inflammation exacerbates weight gain, therefore we reasoned that inflammatory factors could modulate appetite-promoting neurons to maintain a new set point. We found that the inflammatory mediator prostaglandin E2 (PGE2) activate MCH neurons via its EP2 receptor (EP2R). Suppressing PGE2-EP2R on MCH neurons partially protects against excess weight gain and fat accumulation in the liver during HFD feeding. This mechanism could contribute to the maintenance of an elevated body weight set point in during diet-induced obesity.
Without long-term treatment options in face of the increasing rates of obesity, we are in desperate need of novel interventions. In the future, we hope that targeting EP2R on MCH neurons can lower body weight set point and aid in combatting obesity
Spiking Neural Network for Ultra-low-latency and High-accurate Object Detection
Spiking Neural Networks (SNNs) have garnered widespread interest for their
energy efficiency and brain-inspired event-driven properties. While recent
methods like Spiking-YOLO have expanded the SNNs to more challenging object
detection tasks, they often suffer from high latency and low detection
accuracy, making them difficult to deploy on latency sensitive mobile
platforms. Furthermore, the conversion method from Artificial Neural Networks
(ANNs) to SNNs is hard to maintain the complete structure of the ANNs,
resulting in poor feature representation and high conversion errors. To address
these challenges, we propose two methods: timesteps compression and
spike-time-dependent integrated (STDI) coding. The former reduces the timesteps
required in ANN-SNN conversion by compressing information, while the latter
sets a time-varying threshold to expand the information holding capacity. We
also present a SNN-based ultra-low latency and high accurate object detection
model (SUHD) that achieves state-of-the-art performance on nontrivial datasets
like PASCAL VOC and MS COCO, with about remarkable 750x fewer timesteps and 30%
mean average precision (mAP) improvement, compared to the Spiking-YOLO on MS
COCO datasets. To the best of our knowledge, SUHD is the deepest spike-based
object detection model to date that achieves ultra low timesteps to complete
the lossless conversion.Comment: 14 pages, 10 figure
Study of neural circuits using multielectrode arrays in movement disorders
Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: RodrÃguez Allué, Manuel JoséNeurodegenerative movement-related disorders are characterized by a progressive degeneration and loss of neurons, which lead to motor control impairment. Although the precise mechanisms underlying these conditions are still unknown, an increasing number of studies point towards the analysis of neural networks and functional connectivity to unravel novel insights. The main objective of this work is to understand cellular mechanisms related to dysregulated motor control symptoms in movement disorders, such as Chorea-Acanthocytosis (ChAc), by employing multielectrode arrays to analyze the electrical activity of neuronal networks in mouse models. We found no notable differences in cell viability between neurons with and without VPS13A knockdown, that is the only gene known to be implicated in the disease, suggesting that the absence of VPS13A in neurons may be partially compensated by other proteins. The MEA setup used to capture the electrical activity from neuron primary cultures is described in detail, pointing out its specific characteristics. At last, we present the alternative backup approach implemented to overcome the challenges faced during the research process and to explore the advanced algorithms for signal processing and analysis.
In this report, we present a thorough account of the conception and implementation of our research, outlining the multiple limitations that have been encountered all along the course of the project. We provide a detailed analysis on the project’s economical and technical feasibility, as well as a comprehensive overview of the ethical and legal aspects considered during the execution
Endogenous analgesic systems and neuropathic pain
Purpose: Neuropathic pain is a debilitating condition that deeply affects quality of life and is a major socioeconomic burden. The endogenous analgesic system can be modelled by assessing responses to stress known as stress induced analgesia. Quite often, the anticipation of pain is a major source of fear and anxiety for chronic pain sufferers, leading to or compounding stress and anxiety related disorders. Thus, responses to conditioned fear were modelled utilising a fear conditioned analgesia protocol on an animal model of neuropathic pain.
Methods: Electric foot-shock stimulation was used as a stressor to activate the endogenous analgesic system in C57BL/6 mice. Neuropathic pain was modelled via the chronic constriction injury method. The resultant analgesia from the stressor was measured by two thermal pain assays: the hotplate and Hargreaves test, engaging unique supraspinal and spinal pain pathways. The immediate response to stress was the experimentally produced stress induced analgesia. A two-day fear conditioning protocol was setup to assess fear conditioned analgesia. The engagement of endogenous opioids and cannabinoids were tested via systemic administrations of drugs. The neuronal activity within the PAG was assessed using c-fos immunohistochemistry.
Results: Stress induced analgesia induced by brief continuous footshock was largely mediated by endogenous opioids. By contrast, both opioids and cannabinoids mediated the analgesia induced by intermittent footshock. Extended continuous footshock produced supramaximal responses which prevented the assessment of endogenous opioids and cannabinoids. The immediate response to stress was opioid mediated whilst both endogenous opioid and cannabinoids was necessary to mediate fear expression and fear conditioned analgesia. Neuropathic pain disrupts the stress response but interestingly did not alter fear expression. Neuronal activity within the PAG was increased with neuropathic pain mice
Exploring the Modulation of Motor Cortical Excitability by Duration of Transcranial Direct Current Stimulation
The motor cortex(MC) was important in human learning and memory, and the level of cortical excitability is a way of assessing its state. To non-invasively modulate cortical excitability, transcranial direct current stimulation (tDCS) is a widely employed technique. tDCS can be utilized to either enhance or inhibit motor MC excitability. However, in most studies, the optimal duration effect of tDCS on cortical excitability has been neglected. Additionally, there are no systematic analysis of tDCS and cortical excitability indexes. To bridge these gaps, we designed an experiment to systematically analyze the duration of tDCS and MC excitability it triggered.
We recruited 5 healthy, right-handed subjects. They don’t have history of psychiatric disorders. Throughout the 30-minute tDCS stimulation at 1 mA, we continuously applied TMS to characterize the motor evoked potential.
Our experiment revealed the following: applying 1 mA tDCS to the participants for 30 minutes effectively increases cortical excitability, and this effect can last for at least 30 minutes after stimulation. We then analysed cortical excitability by measuring the motor-evoked potentials (MEPs) induced by TMS during the tDCS stimulation process. We found that the relationship between cortical excitability and tDCS duration does not appear to be linear. Instead, two peaks were observed at 2-5 minutes and 15-25 minutes, respectively. A decrease in cortical excitability was observed at 26-28 minutes. Finally, we analysed the response of different participants to tDCS and found that individuals vary in their response to tDCS. Additionally, the relationship between cortical excitability and tDCS duration is inconsistent across different individuals
Scale-free avalanches in arrays of FitzHugh-Nagumo oscillators
The activity in the brain cortex remarkably shows a simultaneous presence of
robust collective oscillations and neuronal avalanches, where intermittent
bursts of pseudo-synchronous spiking are interspersed with long periods of
quiescence. The mechanisms allowing for such a coexistence are still a matter
of an intensive debate. Here, we demonstrate that avalanche activity patterns
can emerge in a rather simple model of an array of diffusively coupled neural
oscillators with multiple timescale local dynamics in vicinity of a canard
transition. The avalanches coexist with the fully synchronous state where the
units perform relaxation oscillations. We show that the mechanism behind the
avalanches is based on an inhibitory effect of interactions, which may quench
the spiking of units due to an interplay with the maximal canard. The avalanche
activity bears certain heralds of criticality, including scale-invariant
distributions of event sizes. Furthermore, the system shows an increased
sensitivity to perturbations, manifested as critical slowing down and a reduced
resilience.Comment: 9 figure
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