The populations consist of current-based leaky integrate-and-fire model neurons with exponential synaptic currents and are randomly connected with connection probabilities according to the integrated connectivity map we derive in this article.
The experimental methods underlying both the anatomical and physiological connectivity maps provide connection probabilities for different cell types in different layers, but sample from different lateral spreads: The anatomical data correspond to a very large cortical surface area, parameterized by the sampling radius ra.
A "connectivity map" is defined by the 64 connection probabilities between the 8 considered cell types.
A measure with higher resolution is the discrepancy index ζ, which compares the connection probabilities of individual connections, provided both connectivity maps assign nonzero probabilities.
(G, H ) Cumulative distribution of connected and unconnected interneurons (left) and distribution of connection probabilities in respect to intersomatic distances (right) between interneurons and either NG2 cells (n = 13) or pyramidal neurons (n = 11) displaying at least one connection.
These relay cells emit Poissonian spike trains at a given rate in some prescribed time interval and are randomly connected to the cortex with the cell-type specific connection probabilities according to Binzegger et al. (2004); see Table 5.
We hypothesize that the emergence of coarseness clusters in layer 2 3 results from the feed forward connectivity patterns from lower cortical layers, possibly combined with higher connection probabilities between neurons belonging to the same coarseness cluster and dendritic amplification mechanisms (Lavzin et al., 2012).
We hypothesize that the differences in the mean connection probabilities are explained by differences in the methodology applied to obtain the connectivity maps: Physiological recordings in slices are usually restricted to a maximal lateral distance of the somata of around 100 μm (as reported in Thomson and Morris (2002) for the raw physiological map).
Two path finding algorithms are subsequently applied to derive connection probabilities.
These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain.
