Marked bias towards spontaneous synaptic inhibition distinguishes non-adapting from adapting layer 5 pyramidal neurons in the barrel cortex

Autor: Ion R. Popescu, Rebecca L. Voglewede, Ricardo Mostany, Kathy Q. Le, Rocío Palenzuela
Rok vydání: 2017
Předmět:
Zdroj: DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
instname
DDFV: Repositorio Institucional de la Universidad Francisco de Vitoria
Universidad Francisco de Vitoria
Scientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
Popis: Pyramidal neuron subtypes differ in intrinsic electrophysiology properties and dendritic morphology. However, do different pyramidal neuron subtypes also receive synaptic inputs that are dissimilar in frequency and in excitation/inhibition balance? Unsupervised clustering of three intrinsic parameters that vary by cell subtype – the slow afterhyperpolarization, the sag, and the spike frequency adaptation – split layer 5 barrel cortex pyramidal neurons into two clusters: one of adapting cells and one of non-adapting cells, corresponding to previously described thin- and thick-tufted pyramidal neurons, respectively. Non-adapting neurons presented frequencies of spontaneous inhibitory postsynaptic currents (sIPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) three- and two-fold higher, respectively, than those of adapting neurons. The IPSC difference between pyramidal subtypes was activity independent. A subset of neurons were thy1-GFP positive, presented characteristics of non-adapting pyramidal neurons, and also had higher IPSC and EPSC frequencies than adapting neurons. The sEPSC/sIPSC frequency ratio was higher in adapting than in non-adapting cells, suggesting a higher excitatory drive in adapting neurons. Therefore, our study on spontaneous synaptic inputs suggests a different extent of synaptic information processing in adapting and non-adapting barrel cortex neurons, and that eventual deficits in inhibition may have differential effects on the excitation/inhibition balance in adapting and non-adapting neurons. pre-print 3365 KB
Databáze: OpenAIRE