Evidence from retractor bulbi EMG for linearized motor control of conditioned nictitating membrane responses

Time course of the rabbit's conditioned nictitating membrane movements during acquisition, extinction, and reacquisition

The present experiment tested whether or not the time course of a conditioned eyeblink response, particularly its duration, would expand and contract, as the magnitude of the conditioned response (CR) changed massively during acquisition, extinction, and reacquisition. The CR duration remained largely constant throughout the experiment, while CR onset and peak time occurred slightly later during extinction. The results suggest that computational models can account for these results by using two layers of plasticity conforming to the sequence of synapses in the cerebellar pathways that mediate eyeblink conditioning.

Decorrelation learning in the cerebellum: computational analysis and experimental questions

Many cerebellar models use a form of synaptic plasticity that implements decorrelation learning. Parallel fibers carrying signals positively correlated with climbing-fiber input have their synapses weakened (long-term depression), whereas those carrying signals negatively correlated with climbing input have their synapses strengthened (long-term potentiation). Learning therefore ceases when all parallel-fiber signals have been decorrelated from climbing-fiber input. This is a computationally powerful rule for supervised learning and can be cast in a spike-timing dependent plasticity form for comparison with experimental evidence. Decorrelation learning is particularly well suited to sensory prediction, for example, in the reafference problem where external sensory signals are interfered with by reafferent signals from the organism's own movements, and the required circuit appears similar to the one found to mediate classical eye blink conditioning. However, for certain stimuli, avoidance is a much better option than simple prediction, and decorrelation learning can also be used to acquire appropriate avoidance movements. One example of a stimulus to be avoided is retinal slip that degrades visual processing, and decorrelation learning appears to play a role in the vestibulo-ocular reflex that stabilizes gaze in the face of unpredicted head movements. Decorrelation learning is thus suitable for both sensory prediction and motor control. It may also be well suited for generic spatial and temporal coordination, because of its ability to remove the unwanted side effects of movement. Finally, because it can be used with any kind of time-varying signal, the cerebellum could play a role in cognitive processing.

An agonist-antagonist cerebellar nuclear system controlling eyelid kinematics during motor learning

The presence of two antagonistic groups of deep cerebellar nuclei neurons has been reported as necessary for a proper dynamic control of learned motor responses. Most models of cerebellar function seem to ignore the biomechanical need for a double activation–deactivation system controlling eyelid kinematics, since most of them accept that, for closing the eyelid, only the activation of the orbicularis oculi (OO) muscle (via the red nucleus to the facial motor nucleus) is necessary, without a simultaneous deactivation of levator palpebrae motoneurons (via unknown pathways projecting to the perioculomotor area). We have analyzed the kinetic neural commands of two antagonistic types of cerebellar posterior interpositus neuron (IPn) (types A and B), the electromyographic (EMG) activity of the OO muscle, and eyelid kinematic variables in alert behaving cats during classical eyeblink conditioning, using a delay paradigm. We addressed the hypothesis that the interpositus nucleus can be considered an agonist–antagonist system controlling eyelid kinematics during motor learning. To carry out a comparative study of the kinetic–kinematic relationships, we applied timing and dispersion pattern analyses. We concluded that, in accordance with a dominant role of cerebellar circuits for the facilitation of flexor responses, type A neurons fire during active eyelid downward displacements—i.e., during the active contraction of the OO muscle. In contrast, type B neurons present a high tonic rate when the eyelids are wide open, and stop firing during any active downward displacement of the upper eyelid. From a functional point of view, it could be suggested that type B neurons play a facilitative role for the antagonistic action of the levator palpebrae muscle. From an anatomical point of view, the possibility that cerebellar nuclear type B neurons project to the perioculomotor area—i.e., more or less directly onto levator palpebrae motoneurons—is highly appealing.

Learning stimulus intervals--adaptive timing of conditioned purkinje cell responses

Classical conditioning of motor responses, such as the eyeblink response, is an experimental model of associative learning and of adaptive timing of movements. A conditioned blink will have its maximum amplitude near the expected onset of the unconditioned blink-eliciting stimulus and it adapts to changes in the interval between the conditioned and unconditioned stimuli. Previous studies have shown that an eyeblink conditioning protocol can make cerebellar Purkinje cells learn to pause in response to the conditioned stimulus. According to the cerebellar cortical conditioning model, this conditioned Purkinje cell response drives the overt blink. If so, the model predicts that the temporal properties of the Purkinje cell response reflect the overt behaviour. To test this prediction, in vivo recordings of Purkinje cell activity were performed in decerebrate ferrets during conditioning, using direct stimulation of cerebellar mossy and climbing fibre afferents as conditioned and unconditioned stimuli. The results show that Purkinje cells not only develop a change in responsiveness to the conditioned stimulus. They also learn a particular temporal response profile where the timing, not only of onset and maximum but also of offset, is determined by the temporal interval between the conditioned and unconditioned stimuli.

Adaptive timing of motor output in the mouse: the role of movement oscillations in eyelid conditioning

To survive, animals must learn to control their movements with millisecond-level precision, and adjust the kinematics if conditions, or task requirements, change. Here, we examine adaptive timing of motor output in mice, using a simple eyelid conditioning task. Mice were trained to blink in response to a light stimulus that was always followed by a corneal air-puff at a constant time interval. Different mice were trained with different intervals of time separating the onset of the light and the air-puff. As in previous work in other animal species, mice learned to control the speed of the blink, such that the time of maximum eyelid closure matched the interval used during training. However, we found that the time of maximum eyelid speed was always in the first 100 ms after movement onset and did not scale with the training interval, indicating that adaptive timing is not accomplished by slowing down (or speeding up) the eyelid movement uniformly throughout the duration of the blink. A new analysis, specifically designed to examine the kinematics of blinks in single trials, revealed that the underlying control signal responsible for the eyelid movement is made up of oscillatory bursts that are time-locked to the light stimulus at the beginning of the blink, becoming desynchronized later on. Furthermore, mice learn to blink at different speeds and time the movement appropriately by adjusting the amplitude, but not the frequency of the bursts in the eyelid oscillation.

Timing in trace conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus): scalar, nonscalar, and adaptive features

Using interstimulus intervals (ISIs) of 125, 250, and 500 msec in trace conditioning of the rabbit nictitating membrane response, the offset times and durations of conditioned responses (CRs) were collected along with onset and peak latencies. All measures were proportional to the ISI, but only onset and peak latencies conformed to the criterion for scalar timing. Regarding the CR's possible protective overlap of the unconditioned stimulus (US), CR duration increased with ISI, while the peak's alignment with the US declined. Implications for models of timing and CR adaptiveness are discussed.

Sensory prediction or motor control? Application of marr-albus type models of cerebellar function to classical conditioning

Marr-Albus adaptive filter models of the cerebellum have been applied successfully to a range of sensory and motor control problems. Here we analyze their properties when applied to classical conditioning of the nictitating membrane response in rabbits. We consider a system-level model of eyeblink conditioning based on the anatomy of the eyeblink circuitry, comprising an adaptive filter model of the cerebellum, a comparator model of the inferior olive and a linear dynamic model of the nictitating membrane plant. To our knowledge, this is the first model that explicitly includes all these principal components, in particular the motor plant that is vital for shaping and timing the behavioral response. Model assumptions and parameters were systematically investigated to disambiguate basic computational capacities of the model from features requiring tuning of properties and parameter values. Without such tuning, the model robustly reproduced a range of behaviors related to sensory prediction, by displaying appropriate trial-level associative learning effects for both single and multiple stimuli, including blocking and conditioned inhibition. In contrast, successful reproduction of the real-time motor behavior depended on appropriate specification of the plant, cerebellum and comparator models. Although some of these properties appear consistent with the system biology, fundamental questions remain about how the biological parameters are chosen if the cerebellar microcircuit applies a common computation to many distinct behavioral tasks. It is possible that the response profiles in classical conditioning of the eyeblink depend upon operant contingencies that have previously prevailed, for example in naturally occurring avoidance movements.

Memory consolidation in the cerebellar cortex

Several forms of learning, including classical conditioning of the eyeblink, depend upon the cerebellum. In examining mechanisms of eyeblink conditioning in rabbits, reversible inactivations of the control circuitry have begun to dissociate aspects of cerebellar cortical and nuclear function in memory consolidation. It was previously shown that post-training cerebellar cortical, but not nuclear, inactivations with the GABA_A agonist muscimol prevented consolidation but these findings left open the question as to how final memory storage was partitioned across cortical and nuclear levels. Memory consolidation might be essentially cortical and directly disturbed by actions of the muscimol, or it might be nuclear, and sensitive to the raised excitability of the nuclear neurons following the loss of cortical inhibition. To resolve this question, we simultaneously inactivated cerebellar cortical lobule HVI and the anterior interpositus nucleus of rabbits during the post-training period, so protecting the nuclei from disinhibitory effects of cortical inactivation. Consolidation was impaired by these simultaneous inactivations. Because direct application of muscimol to the nuclei alone has no impact upon consolidation, we can conclude that post-training, consolidation processes and memory storage for eyeblink conditioning have critical cerebellar cortical components. The findings are consistent with a recent model that suggests the distribution of learning-related plasticity across cortical and nuclear levels is task-dependent. There can be transfer to nuclear or brainstem levels for control of high-frequency responses but learning with lower frequency response components, such as in eyeblink conditioning, remains mainly dependent upon cortical memory storage.

Recruitment in retractor bulbi muscle during eyeblink conditioning: EMG analysis and common-drive model

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.

Dynamics of primate oculomotor plant revealed by effects of abducens microstimulation

Despite their importance for deciphering oculomotor commands, the mechanics of the extraocular muscles and orbital tissues (oculomotor plant) are poorly understood. In particular, the significance of plant nonlinearities is uncertain. Here primate plant dynamics were investigated by measuring the eye movements produced by stimulating the abducens nucleus with brief pulse trains of varying frequency. Statistical analysis of these movements indicated that the effects of stimulation lasted about 40 ms after the final pulse, after which the eye returned passively toward its position before stimulation. Behavior during the passive phase could be approximated by a linear plant model, corresponding to Voigt elements in series, with properties independent of initial eye position. In contrast, behavior during the stimulation phase revealed a sigmoidal relation between stimulation frequency and estimated steady-state tetanic tension, together with a frequency-dependent rate of tension increase, that appeared very similar to the nonlinearities previously found for isometric-force production in primate lateral rectus muscle. These results suggest that the dynamics of the oculomotor plant have an approximately linear component related to steady-state viscoelasticity and a nonlinear component related to changes in muscle activation. The latter may in part account for the nonlinear relations observed between eye-movement parameters and single-unit firing patterns in the abducens nucleus. These findings point to the importance of recruitment as a simplifying factor for motor control with nonlinear plants.