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Disynaptic inhibition through somatostatin (SST) interneurons is a powerful potential mechanism for gain control in cortical circuits. However, excitatory drive to SST neurons is remarkably weak. Here we investigate the modulation of local pyramidal (Pyr) inputs onto SST interneurons of layer 2/3 in mouse barrel cortex, using in vitro and in vivo whole-cell recordings from Pyr-SST pairs with a combination of pharmacological screening and optogenetic activation of specific modulatory pathways. We show that presynaptic nicotinic acetylcholine receptor activation rapidly enhances local excitatory inputs onto SST neurons through PKA-dependent pathway. Precisely-timed, brief optogenetic activation of cholinergic fibers was sufficient to account for the enhancement of synaptic efficacy induced by pharmacological activation of Ach receptors. Importantly, these effects were synapse‑specific and did not occur at local excitatory connections between pyramidal neurons, indicating that cholinergic fibers selectively modulate synaptic transmission toward enhanced SST neurons-mediated inhibition. Our results show that brain state can selectively alter network function through the input‑specific modulation of specific synaptic motifs. FINANCIAL SUPPORT: This work was supported by the McKnight Foundation (ALB) and NIH R01NS088958 (ALB and JFAP), the National Science Centre, Poland (2015/18/E/ NZ4/00721; JUC), the European Research council (ERC-2015-CoG-682422; JFAP), the DFG (DFG-FOR-2143-Interneuron; JFAP), the Berlin Institute of Health (BIH; JFAP) and the European Union (FP7, 3x3Dimaging 323945; JFAP).
About 10% of neocortical pyramidal neurons in layer 2/3 are connected to each other with strong and reliable synapses, displaying near-zero failure rates under the condition of very low network activity. However, in vivo many cells, including inhibitory neurons, exhibit elevated spontaneous firing activity. Here we investigated the effect of network activity on connection probability, strength, and synapse reliability between layer 2/3 pyramidal neurons. Under the condition of network activity, failure rates are two-fold higher. We find that GABAB receptors are tonically active during spontaneous network activity and that these receptors profoundly influence release probability. Using optogenetic tools we examined what type of inhibitory neurons is responsible for GABAB inhibition. Our data suggest that neocortical networks may be dynamically rewired based upon presynaptic GABAB activation, and that this phenomenon may be state-dependent.
Fluorescence-based synapse detection enables dense, high-throughput and multichannel analysis of synapse properties and connections in brain tissue. Using fluorogen activating proteins (FAPs) or YFP coupled to a neuroligin tether, we have developed genetically-encoded reagents for fluorescence-labeling of post-synaptic sites. Sparse viral expression of YFP-post or FAP-post in mouse somatosensory (barrel) cortex enables compartment-specific quantitation of synapses across the surface of an individual neuron, as well as cell-type specific presynaptic input assignment. High-resolution, 3D confocal stacks were used for semi-automated, high-throughput assignment of YFP-post and FAP-post synaptic puncta across specific neuron cell-types. Using transgenic mice where specific subtypes of presynaptic inhibitory neurons were fluorescently-labeled with YFP, far red-fluorescence of FAP-post synaptic puncta and dTomato-filled postsynaptic pyramidal cells could be aligned to specific presynaptic partners using tricolor colocalization. Fluorescent post-synaptic puncta properties were evaluated to generate metrics reflecting synapse location, size, shape, and fluorescence intensity that could be used to differentiate synapses from different inhibitory sources. We used these quantitative metrics to evaluate changes in inhibitory inputs after sensory association training for pyramidal neurons in barrel cortex. Genetically-encoded fluorescence-based synaptic labeling reagents provide a powerful approach to enable high-throughput and automated analysis of synapse organization in brain tissue across development, learning, and disease states.
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