Dynamics of Gamma Bursts in Local Field Potentials

被引:15
作者
Greenwood, Priscilla E. [1 ]
McDonnell, Mark D. [2 ]
Ward, Lawrence M. [3 ,4 ]
机构
[1] Univ British Columbia, Dept Math, Vancouver, BC V6T 1Z4, Canada
[2] Univ S Australia, Inst Telecommun Res, Computat & Theoret Neurosci Lab, Mawson Lakes, SA 5001, Australia
[3] Univ British Columbia, Dept Psychol, Vancouver, BC V6T 1Z4, Canada
[4] Univ British Columbia, Brain Res Ctr, Vancouver, BC V6T 1Z4, Canada
关键词
CORTICAL OSCILLATIONS; V1; CORTEX; INHIBITION; FREQUENCY; SYNCHRONIZATION; NETWORKS; NEURONS; SYSTEMS; SPARSE; NOISE;
D O I
10.1162/NECO_a_00688
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this letter, we provide a stochastic analysis of, and supporting simulation data for, a stochastic model of the generation of gamma bursts in local field potential (LFP) recordings by interacting populations of excitatory and inhibitory neurons. Our interest is in behavior near a fixed point of the stochastic dynamics of the model. We apply a recent limit theorem of stochastic dynamics to probe into details of this local behavior, obtaining several new results. We show that the stochastic model can be written in terms of a rotation multiplied by a two-dimensional standard Ornstein-Uhlenbeck (OU) process. Viewing the rewritten process in terms of phase and amplitude processes, we are able to proceed further in analysis. We demonstrate that gamma bursts arise in the model as excursions of the modulus of the OU process. The associated pair of stochastic phase and amplitude processes satisfies their own pair of stochastic differential equations, which indicates that large phase slips occur between gamma bursts. This behavior is mirrored in LFP data simulated from the original model. These results suggest that the rewritten model is a valid representation of the behavior near the fixed point for a wide class of models of oscillatory neural processes.
引用
收藏
页码:74 / 103
页数:30
相关论文
共 47 条
[1]  
[Anonymous], ARXIV12094027V1
[2]   Sustained oscillations for density dependent Markov processes [J].
Baxendale, Peter H. ;
Greenwood, Priscilla E. .
JOURNAL OF MATHEMATICAL BIOLOGY, 2011, 63 (03) :433-457
[3]   ESTIMATING AND INTERPRETING THE INSTANTANEOUS FREQUENCY OF A SIGNAL .1. FUNDAMENTALS [J].
BOASHASH, B .
PROCEEDINGS OF THE IEEE, 1992, 80 (04) :520-538
[4]   Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity [J].
Börgers, C ;
Kopell, N .
NEURAL COMPUTATION, 2003, 15 (03) :509-538
[5]  
Borodin A.N., 2002, Handbook of Brownian Motion-Facts and Formulae, V2
[6]   What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance [J].
Brunel, N ;
Wang, XJ .
JOURNAL OF NEUROPHYSIOLOGY, 2003, 90 (01) :415-430
[7]   Fast global oscillations in networks of integrate-and-fire neurons with low firing rates [J].
Brunel, N ;
Hakim, V .
NEURAL COMPUTATION, 1999, 11 (07) :1621-1671
[8]   Is Gamma-Band Activity in the Local Field Potential of V1 Cortex a "Clock" or Filtered Noise? [J].
Burns, Samuel P. ;
Xing, Dajun ;
Shapley, Robert M. .
JOURNAL OF NEUROSCIENCE, 2011, 31 (26) :9658-9664
[9]   Mechanisms of Gamma Oscillations [J].
Buzsaki, Gyoergy ;
Wang, Xiao-Jing .
ANNUAL REVIEW OF NEUROSCIENCE, VOL 35, 2012, 35 :203-225
[10]   The origin of extracellular fields and currents - EEG, ECoG, LFP and spikes [J].
Buzsaki, Gyoergy ;
Anastassiou, Costas A. ;
Koch, Christof .
NATURE REVIEWS NEUROSCIENCE, 2012, 13 (06) :407-420