By Christof Koch

Neural community learn usually builds at the fiction that neurons are uncomplicated linear threshold devices, thoroughly neglecting the hugely dynamic and complicated nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: details Processing in unmarried Neurons demanding situations this idea, utilizing richly exact experimental and theoretical findings from mobile biophysics to give an explanation for the repertoire of computational capabilities to be had to unmarried neurons. the writer indicates how person nerve cells can multiply, combine, or hold up synaptic inputs and the way details will be encoded within the voltage around the membrane, within the intracellular calcium focus, or within the timing of person spikes.Key subject matters lined contain the linear cable equation; cable conception as utilized to passive dendritic bushes and dendritic spines; chemical and electric synapses and the way to regard them from a computational perspective; nonlinear interactions of synaptic enter in passive and lively dendritic timber; the Hodgkin-Huxley version of motion capability new release and propagation; part house research; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their position in info processing; the function of diffusion, buffering and binding of calcium, and different messenger platforms in details processing and garage; brief- and long term versions of synaptic plasticity; simplified types of unmarried cells; stochastic points of neuronal firing; the character of the neuronal code; and unconventional types of sub-cellular computation.Biophysics of Computation: info Processing in unmarried Neurons serves as an excellent textual content for complex undergraduate and graduate classes in mobile biophysics, computational neuroscience, and neural networks, and should entice scholars and execs in neuroscience, electric and laptop engineering, and physics.

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Extra info for Biophysics of Computation: Information Processing in Single Neurons

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These EPSPs and IPSPs are caused by so-called excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs), triggered by the spiking activity in the presynaptic cell. 6 illustrates some of the properties of a population of depolarizing synapses between the axons of granule cells, also called mossy fibers, and a CA3 hippocampal Fig. 5 SYNAPSES AMONG RETINAL NEURONS Electron microscopic photograph of a few square micrometers of tissue in the central portion of the retina in the monkey. Here a midget bipolar cell (MB) makes two ribbon synapses onto a midget ganglion cell (MG).

The reconstructions were carried out by a very laborious serial electron microscopic procedure. Notice the thin elongated, thomlike structures, dendritic spines. The vast majority of neuronal processes, whether axons or dendrites, possess such an elongated, cylindrical geometry. Studying the spread of electrical current in these structures is the subject of cable theory. (A) Cross section of a branching dendrite. (B) Three-dimensional view of another dendrite. The black blobs are excitatory synapses and the three clear blobs are inhibitory synapses.

2. We follow standard convention in using boldface variables for all vector quantities. 1 Basic Assumptions Underlying One-Dimensional Cable Theory 27 Fig. 2 ELECTRICAL STRUCTURE OF A CABLE (A) Idealized cylindrical axon or dendrite at the heart of one-dimensional cable theory. Almost all of the current inside the cylinder is longitudional due to geometrical (the radius is much smaller than the length of the cable) and electrical factors (the membrane covering the axon or dendrite possesses a very high resistivity compared to the intracellular cytoplasm).

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