Ashutosh
@conscioustahoe.bsky.social
researcher @ genzel lab; teaching assistant @ neuromatch; computational cognitive science and behavioural science; language, memory and mental health; https://conscioustahoe.github.io
And slow fluctuation Ca+ spikes, 10-100ms that also contribute to the electric field outside neurons. What's interesting is that they can spread throughout the neuron, even crossing different layers of input. They are relatively large and long-lasting and can be measured outside the neuron.
October 23, 2023 at 7:59 PM
And slow fluctuation Ca+ spikes, 10-100ms that also contribute to the electric field outside neurons. What's interesting is that they can spread throughout the neuron, even crossing different layers of input. They are relatively large and long-lasting and can be measured outside the neuron.
Also read about fast potential Na+ spikes that generate the strongest currents across the neuronal membrane and contribute substantially to high frequency components of the LFP even though they happen in short bursts, 2ms because of the synchronous action potentials from many neurons.
October 23, 2023 at 7:50 PM
Also read about fast potential Na+ spikes that generate the strongest currents across the neuronal membrane and contribute substantially to high frequency components of the LFP even though they happen in short bursts, 2ms because of the synchronous action potentials from many neurons.
Upon sliding this kernel function over the manifold, we're essentially adding the values of the kernel function at different points, weighted by the data at those points to capture information about patterns or features on the manifold.
September 26, 2023 at 6:51 PM
Upon sliding this kernel function over the manifold, we're essentially adding the values of the kernel function at different points, weighted by the data at those points to capture information about patterns or features on the manifold.
And Instead of a grid, we have a "kernel function" to how to weight or combine information from nearby points on the manifold.
September 26, 2023 at 6:51 PM
And Instead of a grid, we have a "kernel function" to how to weight or combine information from nearby points on the manifold.
On a manifold, there's no Cartesian coordinates like (x, y). Instead, there's a local coordinate systems and at each point on the manifold, we describe how to measure distances and directions around that point. These help in defining the equivalent of the Cartesian coordinate.
September 26, 2023 at 6:51 PM
On a manifold, there's no Cartesian coordinates like (x, y). Instead, there's a local coordinate systems and at each point on the manifold, we describe how to measure distances and directions around that point. These help in defining the equivalent of the Cartesian coordinate.
Also, riemannian metric that are rules for measuring distances and angles on a manifold. And, geodesic which is the most efficient route between two points on a manifold.
September 25, 2023 at 8:38 PM
Also, riemannian metric that are rules for measuring distances and angles on a manifold. And, geodesic which is the most efficient route between two points on a manifold.
What I learned today about manifolds is basically a lot of prerequisite concepts like tangent vectors which are like little arrows that tell you how to move around on that curved surface on the manifold.
September 25, 2023 at 8:38 PM
What I learned today about manifolds is basically a lot of prerequisite concepts like tangent vectors which are like little arrows that tell you how to move around on that curved surface on the manifold.
Manifolds help represent high-dimensional data in a lower-dimensional space or latent space and diffusion models operate in the latent space which can be thought of as a representation of the data where the underlying structure is preserved.
September 25, 2023 at 8:37 PM
Manifolds help represent high-dimensional data in a lower-dimensional space or latent space and diffusion models operate in the latent space which can be thought of as a representation of the data where the underlying structure is preserved.
Also, riemannian metric that are rules for measuring distances and angles on a manifold. And, geodesic which is the most efficient route between two points on a manifold.
September 25, 2023 at 8:29 PM
Also, riemannian metric that are rules for measuring distances and angles on a manifold. And, geodesic which is the most efficient route between two points on a manifold.
What I learned today about manifolds is basically a lot of prerequisite concepts like tangent vectors which are like little arrows that tell you how to move around on that curved surface on the manifold.
September 25, 2023 at 8:27 PM
What I learned today about manifolds is basically a lot of prerequisite concepts like tangent vectors which are like little arrows that tell you how to move around on that curved surface on the manifold.