@article {49518,
	title = {Visual physiology of the layer 4 cortical circuit in silico.},
	journal = {PLoS Computational Biology},
	volume = {14},
	year = {2018},
	month = {2018 Nov 12},
	pages = {e1006535},
	abstract = {<p>Despite advances in experimental techniques and accumulation of large datasets concerning the composition and properties of the cortex, quantitative modeling of cortical circuits under in-vivo-like conditions remains challenging. Here we report and publicly release a biophysically detailed circuit model of layer 4 in the mouse primary visual cortex, receiving thalamo-cortical visual inputs. The 45,000-neuron model was subjected to a battery of visual stimuli, and results were compared to published work and new in vivo experiments. Simulations reproduced a variety of observations, including effects of optogenetic perturbations. Critical to the agreement between responses in silico and in vivo were the rules of functional synaptic connectivity between neurons. Interestingly, after extreme simplification the model still performed satisfactorily on many measurements, although quantitative agreement with experiments suffered. These results emphasize the importance of functional rules of cortical wiring and enable a next generation of data-driven models of in vivo neural activity and computations.</p>
},
	issn = {1553-7358},
	doi = {10.1371/journal.pcbi.1006535},
	author = {Arkhipov, Anton and Gouwens, Nathan W and Billeh, Yazan N and Gratiy, Sergey and Iyer, Ramakrishnan and Wei, Ziqiang and Xu, Zihao and Abbasi-Asl, Reza and Berg, Jim and Buice, Michael and Cain, Nicholas and da Costa, Nuno and de Vries, Saskia and Denman, Daniel and Durand, Severine and Feng, David and Jarsky, Tim and Lecoq, Jerome and Lee, Brian and Li, Lu and Mihalas, Stefan and Ocker, Gabriel K and Olsen, Shawn R and Reid, R Clay and Soler-Llavina, Gilberto and Sorensen, Staci A and Wang, Quanxin and Waters, Jack and Scanziani, Massimo and Koch, Christof}
}
@article {47899,
	title = {The influence of synaptic weight distribution on neuronal population dynamics.},
	journal = {PLoS computational biology},
	volume = {9},
	year = {2013},
	month = {2013 Oct},
	pages = {e1003248},
	abstract = {<p>The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.</p>
},
	keywords = {Action Potentials, Computer Simulation, Models, Neurological, Neurons, Synapses},
	issn = {1553-7358},
	doi = {10.1371/journal.pcbi.1003248},
	author = {Iyer, Ramakrishnan and Menon, Vilas and Buice, Michael and Koch, Christof and Mihalas, Stefan}
}
