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Although Renshaw cells (RCs) were discovered over half a century ago,

Although Renshaw cells (RCs) were discovered over half a century ago, their precise role in recurrent inhibition and ability to modulate motoneuron excitability have yet to be established. in motoneurons and reduce the frequency of spikes generated by excitatory inputs. This was CW069 supplier confirmed experimentally by showing that excitation of a single RC or selective activation of the recurrent inhibitory Rabbit Polyclonal to Cyclin L1 pathway to generate equivalent inhibitory conductances both suppress motoneuron firing. We conclude that recurrent inhibition is remarkably effective, in that a single action potential from one RC is sufficient to silence a motoneuron. Although our results may differ from previous indirect observations, they underline a need for a reevaluation of the role that RCs perform in one of the first neuronal circuits to be discovered. mice were perfused with 4% formaldehyde. The L5 spinal segment was removed and cut into 50-m-thick transverse sections with a vibrating blade microtome (VT1000, Leica Microsystems). Sections were incubated for 48 h at 4C in a mixture of primary antibodies consisting of rabbit anti-calbindin (1:1000, Swant), goat CW069 supplier anti-VAChT (1:1000; Millipore), and guinea-pig anti-GFP (1:1000) (Takasaki et al., 2010). These were revealed with species-specific secondary antibodies raised in donkey and conjugated to DyLight 649 (1:500) or Rhodamine Red (1:100) (both from Jackson ImmunoResearch Laboratories), or Alexa-488 (1:500; Invitrogen). Sections were scanned with a Zeiss LSM710 confocal microscope (with Argon multiline, 405 nm diode, 561 nm solid state, and CW069 supplier 633 nm HeNe lasers) through a 40 oil-immersion lens (NA 1.3), with the pinhole set to 1 1 Airy unit. reconstruction. Slices were fixed in 4% formaldehyde for 12 h. They were incubated overnight in streptavidin conjugated to Rhodamine Red (1:1000; Jackson ImmunoResearch Laboratories) and scanned with the confocal microscope to allow reconstruction of labeled neurons with Neurolucida. The slice was then embedded in agar and cut into 50 m serial sections. Each section was reincubated with avidin-rhodamine and rescanned to allow identification of processes deep within the slice that CW069 supplier were not revealed in the initial scans. The interneuron axon could usually be identified unequivocally because it could be followed to its origin. However, in a few cases, axon collaterals of the interneuron were intermingled with those of the motoneuron; and to confirm its identity, we immunostained for EGFP (which was present in the interneuron axon, but not the motoneuron axon) as described above. Electrophysiological analysis and simulations. Estimation of the quantal parameters was performed using Bayesian quantal analysis (BQA) as described previously (Bhumbra and Beato, 2013). Like multiple-probability fluctuation analysis (Silver, 2003), BQA yields estimates of the quantal parameters from postsynaptic responses observed at different release probabilities. Our technique simultaneously models the profiles of every amplitude distribution of responses at all observed probabilities of release. This approach has the advantage that reliable estimates of the quantal parameters can be obtained from small datasets (Bhumbra and Beato, 2013). Electrotonic analysis was performed based on the data acquired from CW069 supplier the anatomical reconstructions of motoneurons, the location of visualized synaptic contacts, and the quantal size. We simulated the electrotonic properties of reconstructed motoneurons and the effects of inhibitory conductances by using the NEURON simulation environment (Hines and Carnevale, 1997). Each motoneuron reconstruction was imported as a Neurolucida file using NEURONs graphical user interface and inspected for integrity. The reconstructed data, comprising the geometric configuration of neuronal segments represented as connected truncated cone frusta, were then exported into the native NEURON format. The Python application programming interface for NEURON (Hines et al., 2009) was used for subsequent electrotonic analysis. The membrane properties of somal and axonal sections were modeled according to active HodgkinCHuxley channel properties with all sections, including dendritic compartments, set to a fixed specific capacitance (Cm = 1 pF cm?2) and axial resistivity (Ra = 100 cm). Active conductances for sodium and potassium channels were set to gNa = 0.2 S cm?2 and gK = 0.035 S cm2 (Dai et al., 2002) with respective reversal potentials of ENa = 40 mV and EK = ?77 mV. The after-hyperpolarization was modeled using a voltage-dependent calcium conductance to activate a calcium-dependent potassium conductance, with peak values set to gCa = 0.03 mS cm?2 and gK(Ca) = 0.03 S cm?2, respectively (Powers et al., 2012). Passive leak conductances were modeled with a reversal potential of ?70 mV, with the soma 50-fold leakier than the dendrites (Taylor and Enoka,.