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In JoVE (1)
Other Publications (3)
Articles by Joseph Snider in JoVE
JoVE Bioengineering
Adaptation of a Haptic Robot in a 3T fMRI
1Institute for Neural Computation, University of California, 2Department of Radiology, University of California, 3Department of Cognitive Science and Program in Neurosciences, University of California
The adaptation and use of a haptic robot in a 3T fMRI is described.
Other articles by Joseph Snider on PubMed
Intracellular Actin-based Transport: How Far You Go Depends on How Often You Switch
Intracellular molecular motor-driven transport is essential for such diverse processes as mitosis, neuronal function, and mitochondrial transport. Whereas there have been in vitro studies of how motors function at the single-molecule level, and in vivo studies of the structure of filamentary networks, studies of how the motors effectively use the networks for transportation have been lacking. We investigate how the combined system of myosin-V motors plus actin filaments is used to transport pigment granules in Xenopus melanophores. Experimentally, we characterize both the actin filament network, and how this transport is altered in response to external signals. We then develop a theoretical formalism to explain these changes. We show that cells regulate transport by controlling how often granules switch from one filament to another, rather than by altering individual motor activity at the single-molecule level, or by relying on structural changes in the network.
A Universal Property of Axonal and Dendritic Arbors
Axonal and dendritic arbors can be characterized statistically by their spatial density function, a function that specifies the probability of finding a branch of a particular arbor at each point in a neural circuit. Based on an analysis of over a thousand arbors from many neuron types in various species, we have discovered an unexpected simplicity in arbor structure: all of the arbors we have examined, both axonal and dendritic, can be described by a Gaussian density function truncated at about two standard deviations. Because all arbors are characterized by density functions with this single functional form, only four parameters are required to specify an arbor's size and shape: the total length of its branches and the standard deviations of the Gaussian in three orthogonal directions. This simplicity in arbor structure can have implications for the developmental wiring of neural circuits.
Optimal Random Search for a Single Hidden Target
A single target is hidden at a location chosen from a predetermined probability distribution. Then, a searcher must find a second probability distribution from which random search points are sampled such that the target is found in the minimum number of trials. Here it will be shown that if the searcher must get very close to the target to find it, then the best search distribution is proportional to the square root of the target distribution regardless of dimension. For a Gaussian target distribution, the optimum search distribution is approximately a Gaussian with a standard deviation that varies inversely with how close the searcher must be to the target to find it. For a network where the searcher randomly samples nodes and looks for the fixed target along edges, the optimum is either to sample a node with probability proportional to the square root of the out-degree plus 1 or not to do so at all.
