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J Neurophysiol 102: 2498-2513, 2009. First published August 12, 2009; doi:10.1152/jn.00204.2009
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RESEARCH-ARTICLE

Recruitment in Retractor Bulbi Muscle During Eyeblink Conditioning: EMG Analysis and Common-Drive Model

¹Department of Psychology, Sheffield University, Sheffield; ²Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom; and ³Department of Neurobiology and Behavior, State University of New York, Stony Brook, New York

Submitted 9 March 2009; accepted in final form 8 August 2009

ABSTRACT

To analyze properly the role of the cerebellum in classical conditioning of the eyeblink and nictitating membrane (NM) response, the control of conditioned response dynamics must be better understood. Previous studies have suggested that the control signal is linearly related to the CR as a result of recruitment within the accessory abducens motoneuron pool, which acts to linearize retractor bulbi muscle and NM response mechanics. Here we investigate possible recruitment mechanisms. Data came from simultaneous recordings of NM position and multiunit electromyographic (EMG) activity from the retractor bulbi muscle of rabbits during eyeblink conditioning, in which tone and periocular shock act as conditional and unconditional stimuli, respectively. Action potentials (spikes) were extracted and classified by amplitude. Firing rates of spikes with different amplitudes were analyzed with respect to NM response temporal profiles and total EMG spike firing rate. Four main regularities were revealed and quantified: 1) spike amplitude increased with response amplitude; 2) smaller spikes always appeared before larger spikes; 3) subsequent firing rates covaried for spikes of different amplitude, with smaller spikes always firing at higher rates than larger ones; and 4) firing-rate profiles were approximately Gaussian for all amplitudes. These regularities suggest that recruitment does take place in the retractor bulbi muscle during conditioned NM responses and that all motoneurons receive the same command signal (common-drive hypothesis). To test this hypothesis, a model of the motoneuron pool was constructed in which motoneurons had a range of intrinsic thresholds distributed exponentially, with threshold linearly related to EMG spike amplitude. Each neuron received the same input signal as required by the common-drive assumption. This simple model reproduced the main features of the data, suggesting that conditioned NM responses are controlled by a common-drive mechanism that enables simple commands to determine response topography in a linear fashion.

Abbreviations: CS, conditioned stimulus • US, unconditioned stimulus • CR, conditioned response • UR, unconditioned response • EMG, electromyogram • MN, motoneuron • MU, motor unit • MUAP, motor unit action potential • NM, nictitating membrane • RB, retractor bulbi • _k, base total-spike rate at which f_k becomes >0 • c_i, strength of motor unit i • f(t), total instantaneous EMG spike firing rate at time t • f_i(t), instantaneous firing rate of model neuron i at time t • _k(t), instantaneous firing rate of spike amplitude class k at time t • f_EMG, EMG sampling frequency • g_k, gradient of best-fit line for spike amplitude class k • G_i, intrinsic gain of a motoneuron • h_k, maximum of Gaussian-fit to firing rate for class k • I(t), common drive input current • I₀, peak input current for a single trial • I_max, maximum input current for data set • k, spike amplitude class • l, gradient of firing rate width _k with EMG amplitude _k • m, gradient of base firing rate b_k with EMG amplitude _k • n, number of time-bins in fit to spike rate • n_MN, total number of motoneurons in the pool • N, number of EMG spikes divided by width of time bin in fit to spike rate • N_class, number of spike amplitude classes • p, proportion of sampled motoneurons • q, exponent defining the proportion of small to large rheobase currents R_i • r², square of correlation coefficient • R_i, rheobase current of a motoneuron • R_max, highest rheobase current in motoneuron pool • s, exponent defining the proportion of small to large motor unit strengths c • t, time • t_EMG, times when EMG sampled • u, exponent of peak firing rate h_k with EMG amplitude _k • v, exponent of gradient g_k with EMG amplitude _k • , width of time bin in fit to spike rate • _max, maximum EMG spike amplitude • , EMG amplitude in midpoint of range for class k • ₀, EMG threshold for spike detection • _k, EMG threshold for spike detectionin the spike amplitude class number k • µ, mean time of Gaussian-fit to total firing rate f(t) • , width of Gaussian-fit to total firing rate f(t) • µ_k, mean time of Gaussian-fit to firing rate f_k(t) for class k • _k, width of Gaussian-fit to firing rate f_k(t) for class k