Biologically realistic simulation of a part of hippocampal CA3: Generation of testdata for the evaluation of spike detection algorithms (original) (raw)
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Intracellular features predicted by extracellular recordings in the hippocampus in vivo
Journal of neurophysiology, 2000
Multichannel tetrode array recording in awake behaving animals provides a powerful method to record the activity of large numbers of neurons. The power of this method could be extended if further information concerning the intracellular state of the neurons could be extracted from the extracellularly recorded signals. Toward this end, we have simultaneously recorded intracellular and extracellular signals from hippocampal CA1 pyramidal cells and interneurons in the anesthetized rat. We found that several intracellular parameters can be deduced from extracellular spike waveforms. The width of the intracellular action potential is defined precisely by distinct points on the extracellular spike. Amplitude changes of the intracellular action potential are reflected by changes in the amplitude of the initial negative phase of the extracellular spike, and these amplitude changes are dependent on the state of the network. In addition, intracellular recordings from dendrites with simultaneo...
INTRODUCTION: 1. Backpropagating spikes in pyramidal neurons follow an activation sequence. They contribute as much as 40% to the antidromic population spike amplitude. 2. Recent work showed the exact propagation of the depolarization of these back propagating spikes. 3. The strength and attenuation in a burst of backpropagating spikes varies between different neuronal types. 4. Dendritic branching and diameter are important for analyzing the genesis of MEG and EEG signals. 5. A net intracellular current dipole, Q, in each cell and each cell compartment can be calculated. METHODS: We take data from detailed computational models of pyramidal cells in the hippocampus. We then calculate the extracellular field that can be generated when a population of backpropagating spikes moves synchronously in a wave-like pattern. We use the mathematical formalism described in Gomez-Molina, Restrepo and Botero, 2015. The field in certain points is also calculated based on depolarizations that follows alpha and gabor functions. Computer simulations for discrete states vs. continuous functions are both run in MATLAB. Additional analysis was done using Python-NEURON for user-interfaces. We explore computationally what physiological variables are relevant for scaling and field wave- form. DISCUSSION: 1. Does the relative contribution of backpropagation vs. forward depolarizations depend on the population EPSP vs. pIPSP? 2. Can they explain the peak and valleys of the Sharp wave–ripple complexes? 3. In which conditions and scenarios the use of discrete states is a good simplification? PRELIMINARY CONCLUSION: For electrodes located at a long distant d from the source, the selection of source-model can be more important than the determination of the exact spatial position of the source in the dendrite. KEY WORDS: backpropagating action potential, pyramidal neurons, dendrites, extracellular potentials, waves, EEG Submitted by May/2016. PI, Initiative,development and Implementation: Juan Fernando Gomez Molina, International Group of Neuroscience, IGN. ACKNOWLEDGMENT. I am thankful to Dr. J. C. Bel for his advice and feedback and to Dr. R.M. for his assistance with software.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2010
Brain machine interfaces with chronically implanted microelectrode arrays for signal acquisition require algorithms for successful detection and classification of neural spikes. During the design of such algorithms, signals with a priori known characteristics need to be present. A common way to establish such signals is to model the recording environment, simulate the recordings and store ground truth about spiking activity for later comparison. In this paper, we present a statistical method to expand the spike libraries that are used in a previously presented simulation tool for the purpose described above. The method has been implemented and shown to successfully provide quick access to a large assembly of synthetic extracellular spikes with realistic characteristics. Simulations of extracellular recordings using synthesized spikes have shown to possess characteristics similar to those of in-vivo recordings in the cat cerebellum.
Spike library based simulator for extracellular single unit neuronal signals
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2009
A well defined set of design criteria is of great importance in the process of designing brain machine interfaces (BMI) based on extracellular recordings with chronically implanted micro-electrode arrays in the central nervous system (CNS). In order to compare algorithms and evaluate their performance under various circumstances, ground truth about their input needs to be present. Obtaining ground truth from real data would require optimal algorithms to be used, given that those exist. This is not possible since it relies on the very algorithms that are to be evaluated. Using realistic models of the recording situation facilitates the simulation of extracellular recordings. The simulation gives access to a priori known signal characteristics such as spike times and identities. In this paper, we describe a simulator based on a library of spikes obtained from recordings in the cat cerebellum and observed statistics of neuronal behavior during spontaneous activity. The simulator has pr...