- Poster presentation
- Open Access
Noise-induced anti-correlated slow fluctuations in networks of neural populations
BMC Neuroscience volume 14, Article number: P214 (2013)
Coherent spontaneous fluctuations (< 0.1Hz) in fMRI blood-oxygen-level-dependent (BOLD) signal have been observed for a resting state of the human brain [1–4]. Functional connectivity analysis has identified clusters of brain areas exhibiting correlated fluctuations [1–4] and anti-correlation relationship between task-positive and task-negative areas [2–4]. In this study, we propose a model explaining the generation of slow fluctuations and the organization of the clusters. Based on the slowness and the anti-correlation relationship, we describe the brain as a network of neural populations which act as brain areas and prefer one of the two states, UP (active) state and DOWN (quiescent) state , and consider excitation-inducing or inhibition-inducing connections between brain areas. Without noise, this system can have multiple stable states in which each area can be in UP, DOWN, or intermediate state. Presence of noise can make the system slowly move from one stable state to other and this is manifested as organized slow fluctuations. We implement this mechanism using a Wilson-Cowan model [6, 7] with excitatory and inhibitory neurons constituting the neural populations. The neural activity is translated into BOLD signal through the Balloon-Windkessel hemodynamic model [8, 9]. With various networks with 2, 3, and 4 nodes, we show that the system without noise can have multiple stable states which are fixed points, and observe slow fluctuations and various organization including anti-correlated clusters. Similar behaviors are observed in the cases with random networks and modular networks. We analyze the functional connectivity in connection with the underlying networks.
Biswal B, Yetkin FZ, Haughton VM, Hyhe JS: Functional Connectivity in the Motor Cortex of Resting Human Brain Using Echo-Planar MRI. Magn Reson Med. 1995, 34: 537-541. 10.1002/mrm.1910340409.
Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA. 2005, 102: 9673-9678. 10.1073/pnas.0504136102.
Fox MD, Raichle ME: Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007, 8: 700-711. 10.1038/nrn2201.
Deco G, Jirsa VK, McIntosh AR: Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat Rev Neurosci. 2011, 12: 43-56.
Steriade M: Impact of Network Activities on Neuronal Properties in Corticothalamic Systems. J Neurophysiol. 2001, 86: 1-39.
Wilson HR, Cowan JD: Excitatory and inhibitory interactions in localized populations of model neurons. Biophys J. 1972, 12: 1-24.
Ermentrout GB, Terman DH: Mathematical Foundations of Neuroscience. 2010, New York: Springer
Friston KJ, Mechelli A, Turner R, Price CJ: Nonlinear responses in fMRI: the Balloon model, Volterra Kernels, and Other Hemodynamics. Neuroimage. 2000, 12: 466-477. 10.1006/nimg.2000.0630.
Friston KJ, Harrison L, Penny W: Dynamic causal modelling. Neuroimage. 2003, 19: 1273-1302. 10.1016/S1053-8119(03)00202-7.
DL and SK were supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2012R1A1A2043674).
About this article
Cite this article
Lee, D., Kim, S. & Ko, T. Noise-induced anti-correlated slow fluctuations in networks of neural populations. BMC Neurosci 14, P214 (2013) doi:10.1186/1471-2202-14-S1-P214
- Stable State
- Human Brain
- Brain Area
- Functional Connectivity
- Neural Activity