Or you could get more eggs, angular acceleration for the same amount of torque. This is point for this is 0.0.5, um and then so the benefit of using um want something with the least moment of inertia is you could get the same angular acceleration.

So, um, then we can say that based on these moment of inertia, eyes the eye of ah, from wheel is greater than I of a this which is greater than I of a spear just slightly right.

These are you need to average them down because some of the masses closer to the moment of to the axis of rotation. Every mass is equally far equally every mass at the radius. And also it's proportional but how much mass you have but for, say, mass and radius, You want to just think how foreign averages everything from the axis of rotation And it's for every mass. Moment of inertia is really a measure of the baton and exactly an average, but it's sort of an average position of the mass with respect to the center of the wheel. If you have all the mascot, the that the same radius that's gonna have a moment of inertia. I would definitely remember this one, though, because it's very fundamental. This has a moment of inertia to fit time r squared those you don't have to memorize. So, um, this has a moment of inertia of one.

Is so looking at the table, I actually remember them. And then Ah, well, so we want to make the moment of inertia. I guess I could draw the disc in perspective. I wonder how I could make it like a sphere and not like a disc. This probably want a rank moment of inertia for a sphere and a real with all the mass, the rim, and then a solid discs. Blocking spiking activity or NMDA receptor activation revealed that the clustering of synaptic inputs required neuronal activity, demonstrating a role of developmentally expressed spontaneous activity for connecting neurons with subcellular precision.Okay. Analysis of the spatiotemporal patterns of synaptic activity revealed a fine-scale connectivity rule: neighboring synapses (<16 μm intersynapse distance) are more likely to be coactive than synapses that are farther away from each other. Here, we used calcium imaging to record activity at many synapses of hippocampal pyramidal neurons simultaneously to establish the activity patterns in the majority of synapses of an entire cell. Such activity patterns have been described on the level of networks and cells, but the fine-structure of inputs received by an individual neuron during spontaneous network activity has not been studied. During brain development, before sensory systems become functional, neuronal networks spontaneously generate repetitive bursts of neuronal activity, which are typically synchronized across many neurons.

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