Interaction between Purkinje cells and inhibitory interneurons may create adjustable output waveforms to generate timed cerebellar output

Localization of long-term synaptic plasticity defects in cerebellar circuits using optokinetic reflex learning profile

Objective.Functional maps of the central nervous system attribute the coordination and control of many body movements directly or indirectly to the cerebellum. Despite this general picture, there is little information on the function of cerebellar neural components at the circuit level. The presence of multiple synaptic junctions and the synergistic action of different types of plasticity make it virtually difficult to determine the distinct contribution of cerebellar neural processes to behavioral manifestations. In this study, investigating the effect of long-term synaptic changes on cerebellar motor learning, we intend to provide quantitative criteria for localizing defects in the major forms of synaptic plasticity in the cerebellum.Approach.To this end, we develop a firing rate model of the cerebellar circuits to simulate learning of optokinetic reflex (OKR), one of the most well-known cerebellar-dependent motor tasks. In the following, by comparing the simulated OKR learning profile for normal and pathosynaptic conditions, we extract the learning features affected by long-term plasticity disorders. Next, conducting simulation with different massed (continuous with no rest) and spaced (interleaved with rest periods) learning paradigms, we estimate the detrimental impact of plasticity defects at corticonuclear synapses on short- and long-term motor memory.Main results.Our computational approach predicts a correlation between location and grade of the defect with some learning factors such as the rate of formation and retention of motor memory, baseline performance, and even cerebellar motor reserve capacity. Further, spacing analysis reveal the dependence of learning paradigm efficiency on the spatiotemporal characteristic of defect in the network. Indeed, defects in cortical memory formation and nuclear memory consolidation mainly harm massed and spaced learning, respectively. This result is used to design a differential assay for identifying the faulty phases of cerebellar learning.Significance.The proposed computational framework can help develop neural-screening systems and prepare meso-scale functional maps of the cerebellar circuits.

Neuronal processing of noxious thermal stimuli mediated by dendritic Ca(2+) influx in Drosophila somatosensory neurons

Adequate responses to noxious stimuli causing tissue damages are essential for organismal survival. Class IV neurons in Drosophila larvae are polymodal nociceptors responsible for thermal, mechanical, and light sensation. Importantly, activation of Class IV provoked distinct avoidance behaviors, depending on the inputs. We found that noxious thermal stimuli, but not blue light stimulation, caused a unique pattern of Class IV, which were composed of pauses after high-frequency spike trains and a large Ca²⁺ rise in the dendrite (the Ca²⁺ transient). Both these responses depended on two TRPA channels and the L-type voltage-gated calcium channel (L-VGCC), showing that the thermosensation provokes Ca²⁺ influx. The precipitous fluctuation of firing rate in Class IV neurons enhanced the robust heat avoidance. We hypothesize that the Ca²⁺ influx can be a key signal encoding a specific modality.

DOI:http://dx.doi.org/10.7554/eLife.12959.001

Animals often need to get away quickly from dangers in their environment, such as temperatures that are hot enough to damage their tissues. As such, an animal’s brain often encodes automatic ‘avoidance responses’ to signs of danger, which help the animal move away from harm.

The nervous system of a fruit fly larva, for example, contains a distinct class of neurons (known as class IV neurons) that respond specifically to high temperatures and ultraviolet or blue light. Both of these stimuli are potentially harmful, but the larvae escape from heat by rolling with a corkscrew-like motion, yet they turn their heads away from a source of ultraviolet or blue light. So, how does the same set of neurons orchestrate these two different types of behavior?

To answer this question, Terada, Matsubara, Onodera et al. measured the activity in the class IV neurons in two different ways. First, the levels of calcium ions in the neurons, which play a key role in neurons’ activity, were imaged using a calcium-sensitive biosensor. Second, electrodes were used to directly on the class IV neurons to record changes in their electrical activity.

The experiments showed that class IV neurons responded to heat by producing a characteristic burst of electrical activity followed by a pause, and that this pattern of electrical activity was accompanied by a large rise in the calcium signal. In contrast, the same neurons did not show this ‘burst and pause’ pattern of activity when the fruit fly larvae were exposed to ultraviolet/blue light. Instead, these conditions triggered much smaller changes in electrical activity. Further experiments then confirmed that the characteristic ‘burst and pause’ pattern of electrical activity was linked to the rolling motion observed when the larvae try to escape from heat.

These findings show how differing patterns of activity in the same neurons can be used to differentiate between different types of stimuli. Further work is now needed to explain how these two different patterns of activity in one set of neurons is translated by the fruit fly’s brain into different patterns of behavior.

DOI:http://dx.doi.org/10.7554/eLife.12959.002

The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model"

The subject of the effects of the active properties of the Purkinje cell dendrite on neuronal function has been an active subject of study for more than 40 years. Somewhat unusually, some of these investigations, from the outset have involved an interacting combination of experimental and model-based techniques. This article recounts that 40-year history, and the view of the functional significance of the active properties of the Purkinje cell dendrite that has emerged. It specifically considers the emergence from these efforts of what is arguably the first single cell "community" model in neuroscience. The article also considers the implications of the development of this model for future studies of the complex properties of neuronal dendrites.

Modeling possible effects of atypical cerebellar processing on eyeblink conditioning in autism

Autism is unique among other disorders in that acquisition of conditioned eyeblink responses is enhanced in children, occurring in a fraction of the trials required for control participants. The timing of learned responses is, however, atypical. Two animal models of autism display a similar phenotype. Researchers have hypothesized that these differences in conditioning reflect cerebellar abnormalities. The present study used computer simulations of the cerebellar cortex, including inhibition by the molecular layer interneurons, to more closely examine whether atypical cerebellar processing can account for faster conditioning in individuals with autism. In particular, the effects of inhibitory levels on delay eyeblink conditioning were simulated, as were the effects of learning-related synaptic changes at either parallel fibers or ascending branch synapses from granule cells to Purkinje cells. Results from these simulations predict that whether molecular layer inhibition results in an enhancement or an impairment of acquisition, or changes in timing, may depend on (1) the sources of inhibition, (2) the levels of inhibition, and (3) the locations of learning-related changes (parallel vs. ascending branch synapses). Overall, the simulations predict that a disruption in the balance or an overall increase of inhibition within the cerebellar cortex may contribute to atypical eyeblink conditioning in children with autism and in animal models of autism.

Evaluating the influence of motor control on selective attention through a stochastic model: the paradigm of motor control dysfunction in cerebellar patient

Attention allows us to selectively process the vast amount of information with which we are confronted, prioritizing some aspects of information and ignoring others by focusing on a certain location or aspect of the visual scene. Selective attention is guided by two cognitive mechanisms: saliency of the image (bottom up) and endogenous mechanisms (top down). These two mechanisms interact to direct attention and plan eye movements; then, the movement profile is sent to the motor system, which must constantly update the command needed to produce the desired eye movement. A new approach is described here to study how the eye motor control could influence this selection mechanism in clinical behavior: two groups of patients (SCA2 and late onset cerebellar ataxia LOCA) with well-known problems of motor control were studied; patients performed a cognitively demanding task; the results were compared to a stochastic model based on Monte Carlo simulations and a group of healthy subjects. The analytical procedure evaluated some energy functions for understanding the process. The implemented model suggested that patients performed an optimal visual search, reducing intrinsic noise sources. Our findings theorize a strict correlation between the "optimal motor system" and the "optimal stimulus encoders."

Neonatal ethanol exposure results in dose-dependent impairments in the acquisition and timing of the conditioned eyeblink response and altered cerebellar interpositus nucleus and hippocampal CA1 unit activity in adult rats

Exposure to ethanol in neonatal rats results in reduced neuronal numbers in the cerebellar cortex and deep nuclei of juvenile and adult animals. This reduction in cell numbers is correlated with impaired delay eyeblink conditioning (EBC), a simple motor learning task in which a neutral conditioned stimulus (CS; tone) is repeatedly paired with a co-terminating unconditioned stimulus (US; periorbital shock). Across training, cell populations in the interpositus (IP) nucleus model the temporal form of the eyeblink-conditioned response (CR). The hippocampus, though not required for delay EBC, also shows learning-dependent increases in CA1 and CA3 unit activity. In the present study, rat pups were exposed to 0, 3, 4, or 5 mg/kg/day of ethanol during postnatal days (PD) 4-9. As adults, CR acquisition and timing were assessed during 6 training sessions of delay EBC with a short (280 ms) interstimulus interval (ISI; time from CS onset to US onset) followed by another 6 sessions with a long (880 ms) ISI. Neuronal activity was recorded in the IP and area CA1 during all 12 sessions. The high-dose rats learned the most slowly and, with the moderate-dose rats, produced the longest CR peak latencies over training to the short ISI. The low dose of alcohol impaired CR performance to the long ISI only. The 3E (3 mg/kg/day of ethanol) and 5E (5 mg/kg/day of ethanol) rats also showed slower-than-normal increases in learning-dependent excitatory unit activity in the IP and CA1. The 4E (4 mg/kg/day of ethanol) rats showed a higher rate of CR production to the long ISI and enhanced IP and CA1 activation when compared to the 3E and 5E rats. The results indicate that binge-like ethanol exposure in neonatal rats induces long-lasting, dose-dependent deficits in CR acquisition and timing and diminishes conditioning-related neuronal excitation in both the cerebellum and hippocampus.

A computational mechanism for unified gain and timing control in the cerebellum

Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously.

Pharmacological tests of hypotheses for acquired pendular nystagmus

Acquired pendular nystagmus (APN) occurs with multiple sclerosis (MS) and oculopalatal tremor (OPT); distinct features of the nystagmus have led to the development of separate models for their pathogenesis. APN in MS has been attributed to instability in the neural integrator, which normally ensures steady gaze. APN in OPT may result from electrotonic coupling between neurons in the hypertrophied inferior olivary nucleus, which induces maladaptive learning in cerebellar cortex. We tested these two hypotheses by analyzing the effects of gabapentin, memantine, and baclofen on both forms of nystagmus. No drug changed the dominant frequency of either form of APN, but the variability of frequency was affected with gabapentin and memantine in patients with OPT. The amplitude of APN in both MS and OPT was reduced with gabapentin and memantine, but not baclofen. Analyzing the effects of drug therapies on ocular oscillations provides a novel approach to test models of nystagmus.

Model-founded explorations of the roles of molecular layer inhibition in regulating purkinje cell responses in cerebellar cortex: more trouble for the beam hypothesis

For most of the last 50 years, the functional interpretation for inhibition in cerebellar cortical circuitry has been dominated by the relatively simple notion that excitatory and inhibitory dendritic inputs sum, and if that sum crosses threshold at the soma the Purkinje cell generates an action potential. Thus, inhibition has traditionally been relegated to a role of sculpting, restricting, or blocking excitation. At the level of networks, this relatively simply notion is manifest in mechanisms like "surround inhibition" which is purported to "shape" or "tune" excitatory neuronal responses. In the cerebellum, where all cell types except one (the granule cell) are inhibitory, these assumptions regarding the role of inhibition continue to dominate. Based on our recent series of modeling and experimental studies, we now suspect that inhibition may play a much more complex, subtle, and central role in the physiological and functional organization of cerebellar cortex. This paper outlines how model-based studies are changing our thinking about the role of feed-forward molecular layer inhibition in the cerebellar cortex. The results not only have important implications for continuing efforts to understand what the cerebellum computes, but might also reveal important features of the evolution of this large and quintessentially vertebrate brain structure.

Behavioral characteristics, associative learning capabilities, and dynamic association mapping in an animal model of cerebellar degeneration

Young adult heterozygous Lurcher mice constitute an excellent model for studying the role of the cerebellar cortex in motor performance-including the acquisition of new motor abilities-because of the early postnatal degeneration of almost all of their Purkinje and granular cells. Wild-type and Lurcher mice were classically conditioned for eyelid responses using a delay paradigm with or without an electrolytic lesion in the interpositus nucleus. Although the late component of electrically evoked blink reflexes was smaller in amplitude and had a longer latency in Lurcher mice than that in controls, the two groups of animals presented similar acquisition curves for eyeblink conditioning. The lesion of the interpositus nucleus affected both groups of animals equally for the generation of reflex and conditioned eyelid responses. Furthermore, we recorded the multiunitary activity at the red and interpositus nuclei during the same type of associative learning. In both nuclei, the neural firing activity lagged the beginning of the conditioned response (determined by orbicularis oculi muscle response). Although red nucleus neurons and muscle activities presented a clear functional coupling (strong correlation and low asymmetry) across conditioning, the coupling between interpositus neurons and either red nucleus neurons or muscle activities was slightly significant (weak correlation and high asymmetry). Lurcher mice presented a nonlinear coupling (high asymmetry) between red nucleus neurons and muscle activities, with an evident compensatory adjustment in the correlation of firing between interpositus and red nuclei neurons (a coupling with low asymmetry), aimed probably at compensating the absence of cerebellar cortical neurons.

Oculopalatal tremor explained by a model of inferior olivary hypertrophy and cerebellar plasticity

The inferior olivary nuclei clearly play a role in creating oculopalatal tremor, but the exact mechanism is unknown. Oculopalatal tremor develops some time after a lesion in the brain that interrupts inhibition of the inferior olive by the deep cerebellar nuclei. Over time the inferior olive gradually becomes hypertrophic and its neurons enlarge developing abnormal soma-somatic gap junctions. However, results from several experimental studies have confounded the issue because they seem inconsistent with a role for the inferior olive in oculopalatal tremor, or because they ascribe the tremor to other brain areas. Here we look at 3D binocular eye movements in 15 oculopalatal tremor patients and compare their behaviour to the output of our recent mathematical model of oculopalatal tremor. This model has two mechanisms that interact to create oculopalatal tremor: an oscillator in the inferior olive and a modulator in the cerebellum. Here we show that this dual mechanism model can reproduce the basic features of oculopalatal tremor and plausibly refute the confounding experimental results. Oscillations in all patients and simulations were aperiodic, with a complicated frequency spectrum showing dominant components from 1 to 3 Hz. The model’s synchronized inferior olive output was too small to induce noticeable ocular oscillations, requiring amplification by the cerebellar cortex. Simulations show that reducing the influence of the cerebellar cortex on the oculomotor pathway reduces the amplitude of ocular tremor, makes it more periodic and pulse-like, but leaves its frequency unchanged. Reducing the coupling among cells in the inferior olive decreases the oscillation’s amplitude until they stop (at ∼20% of full coupling strength), but does not change their frequency. The dual-mechanism model accounts for many of the properties of oculopalatal tremor. Simulations suggest that drug therapies designed to reduce electrotonic coupling within the inferior olive or reduce the disinhibition of the cerebellar cortex on the deep cerebellar nuclei could treat oculopalatal tremor. We conclude that oculopalatal tremor oscillations originate in the hypertrophic inferior olive and are amplified by learning in the cerebellum.

Dynamic associations in the cerebellar-motoneuron network during motor learning

We assessed here true causal directionalities in cerebellar-motoneuron (MN) network associations during the classical conditioning of eyelid responses. For this, the firing activities of identified facial MNs and cerebellar interpositus (IP) nucleus neurons were recorded during the acquisition of this type of associative learning in alert behaving cats. Simultaneously, the eyelid conditioned response (CR) and the EMG activity of the orbicularis oculi (OO) muscle were recorded. Nonlinear association analysis and time-dependent causality method allowed us to determine the asymmetry, time delays, direction in coupling, and functional interdependences between neuronal recordings and learned motor responses. We concluded that the functional nonlinear association between the IP neurons and OO muscle activities was bidirectional and asymmetric, and the time delays in the two directions of coupling always lagged the start of the CR. Additionally, the strength of coupling depended inversely on the level of expression of eyeblink CRs, whereas causal inferences were significantly dependent on the phase information status. In contrast, the functional association between OO MNs and OO muscle activities was unidirectional and quasisymmetric, and the time delays in coupling were always of opposed signs. Moreover, information transfer in cerebellar-MN network associations during the learning process required a "driving common source" that induced the mere "modulating coupling" of the IP nucleus with the final common pathway for the eyelid motor system. Thus, it can be proposed that the cerebellum is always looking back and reevaluating its own function, using the information acquired in the process, to play a modulating-reinforcing role in motor learning.

Computational models of timing mechanisms in the cerebellar granular layer

A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum.