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The dynamic ability of neuronal dendrites to shape and integrate synaptic responses is the hallmark of information processing in the brain. Effectively studying this phenomenon requires concurrent measurements at multiple sites on live neurons. Substantial progress has been made by optical imaging systems that combine confocal and multiphoton microscopy(More)
Patterned networks of hippocampal neurons were generated on peptide-coated gold substrates prepared by microscope projection photolithography and microcontact printing. A 19 amino acid peptide fragment of laminin A (PA22-2) that includes the IKVAV cell adhesion domain was used to direct patterns of cell adhesion in primary culture. Microscale grid patterns(More)
We discuss methods for fast spatiotemporal smoothing of calcium signals in dendritic trees, given single-trial, spatially localized imaging data obtained via multi-photon microscopy. By analyzing the dynamics of calcium binding to probe molecules and the effects of the imaging procedure, we show that calcium concentration can be estimated up to an affine(More)
Voltage propagation through neurons is a complicated process dependent on the concentrations and kinetics of ion channels, as well as the morphology of the dendrites. The task of recording the level of activation within different parts of the neuron is challenging, given the small size of the constituent structures, and the fast timescale of the signals.(More)
Understanding what triggers synaptic strength modifications in vivo remains a key problem in cellular neuroscience. Recent fast scanning multi-photon microscopy techniques [1] support the role of calcium as a key biochemical effector, signaling the coincident occurrence of back-propagating action potentials (bAPs) and excitatory post-synaptic potentials(More)
Supporting Information for: Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees Eftychios A. Pnevmatikakis1∗, Keith Kelleher2†, Rebecca Chen, Peter Saggau, Krešimir Josić, Liam Paninski 1 Department of Statistics and Center for Theoretical Neuroscience, Columbia University, New York, NY, USA 2 Department of Mathematics, University of(More)
Changes in neural connectivity are thought to underlie the most permanent forms of memory in the brain. We consider two models, derived from the clusteron (Mel, Adv Neural Inf Process Syst 4:35-42, 1992), to study this method of learning. The models show a direct relationship between the speed of memory acquisition and the probability of forming appropriate(More)
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