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Explore the scaling exponent in the local field potential (LFP) of the human brain through compartmental models and membrane currents in pyramidal hippocampal cells. This study delves into the physical motivation behind power laws, electron shot noise, and stochastic variables. Discover the application of the Wiener-Kinchin theorem, white noise, and Brownian noise in neuronal activity analysis.
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Noise, Power Laws, and the Local Field Potential Sloan-Swartz 2008 Summer Meeting Joshua Milstein1, Florian Morman1,2, Itzhak Fried2 and Christof Koch1 1California Institute of Technology 2David Geffen School of Medicine and Semel Institute of Neuroscience and Human Behavior, University of California, Los Angeles
Scaling Exponent () N = 106 546 16 16 Physical Motivation Human Intracranial Recordings
Compartmental Model To generate the membrane currents Pyramidal hippocampal cell within rat CA1 3-D topological reconstruction • Hodgkin-Huxley Style Kinetics • Voltage dependent Na+, K+,Ca2+ currents • 12 different processes i (nA) NEURON Simulation Environment t (ms) Used to compare intracellular to extracellular recordings Henze (2000) & Gold (2006)
Scale Invariance: Number of Earthquakes/Year Earthquake Magnitude Power Laws Power/Slope
Electron Shot Noise Pulse Amplitude Time
Stochastic Variable: tk1 tk2 tk3 tk4 tk5 tk6 tk7 Time Neuron Shot Noise Spike Timing Pulse Shape
Autocorrelation Function Wiener-Kinchin Theorem: Power Spectrum Autocorrelation Function
Pulse Amplitude Time Contains All Time/Frequency Dependence Simple Case II: Sharp Spike
Binary Sequence: 10011010011010010001001100000100010111 White Noise Independent at each timestep
Autocorrelation Function: Power Spectrum: Brown(ian) Noise
Amplitude Timestep Spike Train White Noise ?!? Random Walk with a Threshold
Autocorrelation Function: Let and Telegraph Process
Summary Experimental Evidence for a Universal 1/f^2 Scaling in the LFP of Humans 2. Developed a Simple Mathematical Treatment for Understanding Power Laws in the LFP 3. Brownian Noise Can Arise From Single Neuron Activity Biophysical Examples: a. Sharp spikes followed by slow decay b. UP-DOWN states of activity ** Funded by the Swartz Foundation **