Neural Dynamics of an E-I Network

On Conditions for the Existence of Neural Ocsillations

We investigate the neural dynamics in an exicitatory-inhibitory neural nerwork (E-I network) with ReLU activation and Hebbian learning. By local bifurcation analysis, we find there are ten possible neural dynamical patterns between one excitatory neuron and one inhibitory neuron with all four types of synaptic connections. The unstable node never... [Read More]
Computational Neuroscience, Unsupervised Learning, Original Research

Real-Time Virtual Reality Streaming with Neural Super-Resolution

In this work, we tackle the problem of real-time virtual reality streaming in low-bandwidth network conditions. In low-bandwidth settings, VR streaming faces an inherent trade-off between responsiveness and image resolution, both of which are crucial to a high quality user experience. To overcome this trade-off, we propose to send low-resolution... [Read More]
Computer Vision, Virtual Reality, Deep Learning, Original Research

Mitochondrial Size Gradients in Cortical Neurons Suggested by 3D Electron Microscopy

Mitochondria play a crucial role in the functioning of neurons by synthesizing ATP and buffering intracellular Ca2+, both necessary for synaptic function. The morphology and location of mitochondria can provide insights into specialized function they perform in different parts of the neuron. We reconstruct 81,397 mitochondria within 180 pyramidal neurons... [Read More]
Neuroscience, Computer Vision, Deep Learning, Original Research

Can Machines Read Jmulbed Senetcnes?

This research is driven by our curiosity about the limits to which the current technology for natural language processing could be pushed: if humans are capable of reading jumbled sentences, can machines do? To answer this question, we evaluate the ability of state-of-the-art models to recognize and comprehend wordand character-level... [Read More]
Natural Language Processing, Deep Learning, Original Research