Figure 1. Neuron to neuron connectivity matrix for the whisker (vibrissae) related somatosensory cortex. The computations were carried out by and the image was generated using Octave. The matrix shows that layer 4 and 5a neurons provide excitatory input into layers 2/3 and layer layers 2/3 neurons provide excitatory input into layers 5a and 5b. This matrix was used for Figure 7e in the paper “Laminar Analysis of Excitatory Local Circuits in Vibrissal Motor and Sensory Cortical Areas” published January 4, 2011 in PLoS Biology.

Surprisingly little is known about detailed brain circuitry, which presumably underlies the dynamics of signal processing in the brain and, therefore, brain functions such as behavior and cognition. New techniques are helping to quantify specific features of brain circuits. A paper from earlier this year, “Laminar Analysis of Excitatory Local Circuits in Vibrissal Motor and Sensory Cortical Areas” (published January 4, 2011 in PLoS Biology), reports on a method that uses data from laser scanning photostimulation experiments to provide direct quantitative comparisons of excitatory connectivity amongst brain micro-circuits.

The authors obtained maps of local intracortical sources of excitatory synaptic input by recording the electrical activity of an individual neuron while exciting small clusters of neurons from various sites surrounding the recorded neuron using photostimulation to release caged glutamate. The validity and usefulness of the connectivity matrices they present rest on their accuracy of their calculations. Those interested in investigating or applying their methodology may download their data and calculations from the SenseLab ModelDB repository (see Note below).

Note: The data and code for deriving connectivity matrices is available from the SenseLab ModelDB repository. Versions for both Matlab and Octave, an open source alternative to Matlab, are available. Go to the “Laminar analysis of excitatory circuits in vibrissal motor and sensory cortex (Hooks et al. 2011)” record.

Note: When Octave tried to create graphic output of the connectivity matrix results my system couldn’t find gnuplot, which is apparently the default graphics setting for Octave. Octave is able to use the standard graphics library known as OpenGL. Tell your system to use OpenGL for its graphics by entering graphics_toolkit("fltk") at the Octave command prompt. Next load the Octave file mhconmatvalues20100928_octave.m by entering mhconmatvalues20100928_octave at the command prompt. Six figures should appear (see Figure 1 above).

The team used Matlab to carry out their analysis. Matlab is commonly used within the neuroscience community but, unfortunately, the software package is too expensive for most individuals to own. It’s fortunate that an open source alternative known as Octave is available. It’s also fortunate that this research team included an Octave version of their data and analysis file in their SenseLab ModelDB repository posting. This recent contribution continues Dr. Gordon Sheperd’s commendable efforts to provide open access to neuroscience data and tools.