Neurosciences Commons^™

Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman

Undergraduate Research Posters

Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …

Open Neuroscience Initiative, Austin Lim

College of Science and Health Full Text Publications

The Open Neuroscience Initiative is a free-to-use textbook

This project began as a means to overcoming the financial burden that face undergraduate neuroscience students when buying textbooks. By compiling and writing a completely free-to-access textbook that covers the foundations of a typical college introduction to neuroscience course, students would have one less obstacle to overcome in their educational career, allowing them to focus their valuable time and attention on learning rather than finances. To make this project a reality, I began with a humble tweet in May 2019 that managed to gain a tiny bit of traction among the neuroscience …

Neural Coding And Decoding, Alexander Dimitrov

Systems Science Friday Noon Seminar Series

Methods based on Rate Distortion theory have been successfully used to cluster stimuli and neural responses in order to study neural codes at a level of detail supported by the amount of available data. They approximate the joint stimulus-response distribution by quantizing paired stimulus-response observations into smaller reproductions of the stimulus and response spaces. An optimal quantization is found by maximizing an information-theoretic cost function subject to both equality and inequality constraints, in hundreds to thousands of dimensions. This analytical approach has several advantages over other current approaches:

• it yields the most informative approximation of the encoding scheme given the …