Rett syndrome begins to appear in affected females at the age of 6 to 25 months. They begin loosing voluntary control of hand movements and their communication skills deteriorate. Rett syndrome has been shown to be associated with mutations in the MECP2 gene, which is known to encode a protein called the Methyl-CpG-Binding Protein 2 (MeCP2).
Evidence has suggested that the loss of MeCP2 protein during a critical period in the early months of life leads to Rett syndrome. Research reported this month in Science (“Adult neural function requires MeCP2” published July 8, 2011) shows that normal adults may express Rett syndrome like symptoms if the MeCP2 protein is no longer expressed.
The report is significant for our understanding of the genetic influence of brain function leading to Rett syndrome since it points to a role of the MeCP2 protein in the ongoing maintenance of normal brain function rather than a transient influence during an early critical period. Both the infant and mature brain depend on the MeCP2 protein to function normally. Just what the mechanism (or mechanisms) of the ongoing influence is, is the critical next step in understanding and treating this disease.
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 SenseLabModelDB repository (see Note below).
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 SenseLabModelDB repository posting. This recent contribution continues Dr. Gordon Sheperd’s commendable efforts to provide open access to neuroscience data and tools.
This video tours the micro-circuitry of the cerebral cortex in the mouse’s whisker (technically vibrissae) system. Whisker’s are used in active touching by rodents and have functional similarities with our hands. The green structures are pyramidal neurons, the blue structures are axons and dendrites, and the red structures are synapses. The video was created by Dr. Stephen Smith’s research team at the Stanford University School of Medicine.
During the 1950s electron microscopy enabled us to peer into micro-circuitry where the majority of signal processing probably takes place in the brain. This was a major step forward in understanding brain structure and function that resulted in the empirical confirmation of the chemical synapse. However, revealing the rules of functional connectivity at the micron level was painful at best and was mostly beyond our capabilities. New techniques are now enabling us to begin unlocking the mysteries of connectivity and signal processing at the micron level in the brain (see “Other related blog posts” below). New research that contributes to revealing the structure and function of brain micro-circuitry was recently reported in the paper “Functional specificity of local synaptic connections in neocortical networks” (published May 5, 2011 in Nature).
The research team recorded responses to visual stimuli in every neuron found in a 285 micrometers by 285 micrometers by 90 micrometers volume of mouse brain that spanned layers 2/3 in the primary visual cortex. They presented oriented grating patterns that drifted in different directions and, in addition, they presented natural visual scenes from film clips. Finally, the team individually recorded the simultaneous electrical activity from up to four identified neurons. This enabled them to determine if the neurons were synaptically connected.
The results show that connections between neighboring neurons (less than 50 micrometers apart) are highly specific (not random). Visually driven neurons were more likely to connect with each other and the probability of connection increased with increases in the similarity of their responses to visual stimuli. Furthermore, neurons with similar responses to natural scenes showed more robust probabilities of being synaptically connected than neurons with similar responses to drifting gratings. These data are crucial for constraining our models of brain function. It will be important to determine to what extent the findings are specific to the species (mouse) and/or brain region (layers 2/3 visual cortex) explored and to what extent they my be stated as general principles of brain structure and functional organization.
