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Sacha Nelson

Publications and source records attributed to Sacha Nelson.

3 recordsLinked to original sources

The disease progression of Mecp2 mutant mice is affected by the level of BDNF expression.

Mutations in the MECP2 gene cause Rett syndrome (RTT). Bdnf is a MeCP2 target gene; however, its role in RTT pathogenesis is unknown. We examined Bdnf conditional mutant mice for RTT-relevant pathologies and observed that loss of BDNF caused smaller brain size, smaller CA2 neurons, smaller glomerulus size, and a characteristic hindlimb-clasping phenotype. BDNF protein level was reduced in Mecp2 mutant mice, and deletion of Bdnf in Mecp2 mutants caused an earlier onset of RTT-like symptoms. To assess whether this interaction was functional and potentially therapeutically relevant, we increased BDNF expression in the Mecp2 mutant brain with a conditional Bdnf transgene. BDNF overexpression extended the lifespan, rescued a locomotor defect, and reversed an electrophysiological deficit observed in Mecp2 mutants. Our results provide in vivo evidence for a functional interaction between Mecp2 and Bdnf and demonstrate the physiological significance of altered BDNF expression/signaling in RTT disease progression.

Action Potentials↗

Highly nonrandom features of synaptic connectivity in local cortical circuits.

How different is local cortical circuitry from a random network? To answer this question, we probed synaptic connections with several hundred simultaneous quadruple whole-cell recordings from layer 5 pyramidal neurons in the rat visual cortex. Analysis of this dataset revealed several nonrandom features in synaptic connectivity. We confirmed previous reports that bidirectional connections are more common than expected in a random network. We found that several highly clustered three-neuron connectivity patterns are overrepresented, suggesting that connections tend to cluster together. We also analyzed synaptic connection strength as defined by the peak excitatory postsynaptic potential amplitude. We found that the distribution of synaptic connection strength differs significantly from the Poisson distribution and can be fitted by a lognormal distribution. Such a distribution has a heavier tail and implies that synaptic weight is concentrated among few synaptic connections. In addition, the strengths of synaptic connections sharing pre- or postsynaptic neurons are correlated, implying that strong connections are even more clustered than the weak ones. Therefore, the local cortical network structure can be viewed as a skeleton of stronger connections in a sea of weaker ones. Such a skeleton is likely to play an important role in network dynamics and should be investigated further.

Animals↗