Stochasticity and Variability: Insights from Single-Cell Dynamics

Author(s):  
Kumar Selvarajoo
Keyword(s):  
2007 ◽  
Vol 19 (3) ◽  
pp. 249-258 ◽  
Author(s):  
S HENRICKSON ◽  
U VONANDRIAN

Cell Cycle ◽  
2010 ◽  
Vol 9 (8) ◽  
pp. 1504-1510 ◽  
Author(s):  
Ying V. Zhang ◽  
Brian S. White ◽  
David I. Shalloway ◽  
Tudorita Tumbar

2004 ◽  
Vol 16 (11) ◽  
pp. 2351-2378 ◽  
Author(s):  
Andrea Benucci ◽  
Paul F.M.J. Verschure ◽  
Peter König

Physiological experiments demonstrate the existence of weak pairwise correlations of neuronal activity in mammalian cortex (Singer, 1993). The functional implications of this correlated activity are hotly debated (Roskiesetal., 1999).Nevertheless, it is generally considered a wide spread feature of cortical dynamics. In recent years, another line of research has attracted great interest: the observation of a bimodal distribution of the membrane potential defining up states and down states at the single cell level (Wilson & Kawaguchi, 1996; Steriade, Contreras, & Amzica, 1994; Contreras & Steriade, 1995; Steriade, 2001). Here we use a theoretical approach to demonstrate that the latter phenomenon is a natural consequence of the former. In particular, we show that weak pairwise correlations of the inputs to a compartmental model of a layer V pyramidal cell can induce bimodality in its membrane potential. We show how this relationship can account for the observed increase of the power in the γ frequency band during up states, as well as the increase in the standard deviation and fraction of time spent in the depolarized state (Anderson, Lampl, Reichova, Carandini, & Ferster, 2000). In order to quantify the relationship between the correlation properties of a cortical network and the bistable dynamics of single neurons, we introduce a number of new indices. Subsequently, we demonstrate that a quantitative agreement with the experimental data can be achieved, introducing voltage-dependent mechanisms in our neuronal model such as Ca2+- and Ca2+-dependent K+ channels. In addition, we show that the up states and down states of the membrane potential are dependent on the dendritic morphology of cortical neurons. Furthermore, bringing together network and single cell dynamics under a unified view allows the direct transfer of results obtained in one context to the other and suggests a new experimental paradigm: the use of specific intracellular analysis as a powerful tool to reveal the properties of the correlation structure present in the network dynamics.


Biochemistry ◽  
2017 ◽  
Vol 57 (1) ◽  
pp. 108-116 ◽  
Author(s):  
Jongchan Yeo ◽  
Andrew B. Dippel ◽  
Xin C. Wang ◽  
Ming C. Hammond

2016 ◽  
Vol 113 (12) ◽  
pp. 3251-3256 ◽  
Author(s):  
Mikihiro Hashimoto ◽  
Takashi Nozoe ◽  
Hidenori Nakaoka ◽  
Reiko Okura ◽  
Sayo Akiyoshi ◽  
...  

Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a “speed limit” for proliferation.


2013 ◽  
Vol 4 (1) ◽  
Author(s):  
Isabella Santi ◽  
Neeraj Dhar ◽  
Djenet Bousbaine ◽  
Yuichi Wakamoto ◽  
John D. McKinney

2013 ◽  
Vol 144 (5) ◽  
pp. S-464
Author(s):  
Nobukatsu Horita ◽  
Kiichiro Tsuchiya ◽  
Shuji Hibiya ◽  
Keita Fukushima ◽  
Yoshihito Kano ◽  
...  

2007 ◽  
Vol 9 (8) ◽  
pp. S113-S121 ◽  
Author(s):  
E Eriksson ◽  
J Scrimgeour ◽  
A Granéli ◽  
K Ramser ◽  
R Wellander ◽  
...  

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