Time course of classically conditioned Purkinje cell response is determined by initial part of conditioned stimulus

Accessible and reliable neurometric testing in humans using a smartphone platform

Tests of human brain circuit function typically require fixed equipment in lab environments. We have developed a smartphone-based platform for neurometric testing. This platform, which uses AI models like computer vision, is optimized for at-home use and produces reproducible, robust results on a battery of tests, including eyeblink conditioning, prepulse inhibition of acoustic startle response, and startle habituation. This approach provides a scalable, universal resource for quantitative assays of central nervous system function.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.

A computational passage-of-time model of the cerebellar Purkinje cell in eyeblink conditioning

The cerebellar Purkinje cell controlling eyeblinks can learn, remember, and reproduce the interstimulus interval in a classical conditioning paradigm. Given temporally separated inputs, the cerebellar Purkinje cell learns to pause its tonic inhibition of a motor pathway with high temporal precision so that an overt blink occurs at the right time. Most models place the passage-of-time representation in upstream network effects. Yet, bypassing the upstream network and directly stimulating the Purkinje cell's pre-synaptic fibers during conditioning still causes acquisition of a well-timed response. Additionally, while network models are sensitive to variance in the temporal structure of probe stimulation, in vivo findings suggest that the acquired Purkinje cell response is not. Such findings motivate alternative approaches to modeling neural function. Here, we present a proof-of-principle model of the passage-of-time which is internal to the Purkinje cell and is invariant to probe structure. The model is consistent with puzzling findings, accurately recapitulates Purkinje cell firing during classical conditioning and makes testable electrophysiological predictions.

Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit

The cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remains elusive. To tackle the issue, we developed an advanced computational modeling framework that allows us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome is generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation are used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation, inhibitory control, and long-term synaptic plasticity. Our simulations show how mossy fibers entrain the local neuronal microcircuit, boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of local microcircuit computation and of the neural correlates of behavior.

The Shape of Data: a Theory of the Representation of Information in the Cerebellar Cortex

This paper presents a model of rate coding in the cerebellar cortex. The pathway of input to output of the cerebellum forms an anatomically repeating, functionally modular network, whose basic wiring is preserved across vertebrate taxa. Each network is bisected centrally by a functionally defined cell group, a microzone, which forms part of the cerebellar circuit. Input to a network may be from tens of thousands of concurrently active mossy fibres. The model claims to quantify the conversion of input rates into the code received by a microzone. Recoding on entry converts input rates into an internal code which is homogenised in the functional equivalent of an imaginary plane, occupied by the centrally positioned microzone. Homogenised means the code exists in any random sample of parallel fibre signals over a minimum number. The nature of the code and the regimented architecture of the cerebellar cortex mean that the threshold can be represented by space so that the threshold can be met by the physical dimensions of the Purkinje cell dendritic arbour and planar interneuron networks. As a result, the whole population of a microzone receives the same code. This is part of a mechanism which orchestrates functionally indivisible behaviour of the cerebellar circuit and is necessary for coordinated control of the output cells of the circuit. In this model, fine control of Purkinje cells is by input rates to the system and not by learning so that it is in conflict with the for-years-dominant supervised learning model.

Bidirectional learning in upbound and downbound microzones of the cerebellum

Over the past several decades, theories about cerebellar learning have evolved. A relatively simple view that highlighted the contribution of one major form of heterosynaptic plasticity to cerebellar motor learning has given way to a plethora of perspectives that suggest that many different forms of synaptic and non-synaptic plasticity, acting at various sites, can control multiple types of learning behaviour. However, there still seem to be contradictions between the various hypotheses with regard to the mechanisms underlying cerebellar learning. The challenge is therefore to reconcile these different views and unite them into a single overall concept. Here I review our current understanding of the changes in the activity of cerebellar Purkinje cells in different 'microzones' during various forms of learning. I describe an emerging model that indicates that the activity of each microzone is bound to either increase or decrease during the initial stages of learning, depending on the directional and temporal demands of its downstream circuitry and the behaviour involved.

Kir3 channel blockade in the cerebellar cortex suppresses performance of classically conditioned Purkinje cell responses

In the eyeblink conditioning paradigm, cerebellar Purkinje cells learn to respond to the conditional stimulus with an adaptively timed pause in its spontaneous firing. Evidence suggests that the pause is elicited by glutamate released from parallel fibers and acting on metabotropic receptors (mGluR7) which initiates a delayed-onset suppression of firing. We suggested that G protein activation of hyperpolarizing K_ir3 channels (or ‘GIRK’, G protein-coupled inwardly-rectifying K⁺ channels) could be part of such a mechanism. Application of the K_ir3 antagonist Tertiapin-LQ locally in the superficial layers of the cerebellar cortex in decerebrate ferrets suppressed normal performance of Purkinje cell pause responses to the conditional stimulus. Importantly, there was no detectable effect on spontaneous firing. These findings suggest that intact functioning of K_ir3 channels in the cerebellar cortex is required for normal conditioned Purkinje cell responses.

A model for time interval learning in the Purkinje cell

Recent experimental findings indicate that Purkinje cells in the cerebellum represent time intervals by mechanisms other than conventional synaptic weights. These findings add to the theoretical and experimental observations suggesting the presence of intra-cellular mechanisms for adaptation and processing. To account for these experimental results we propose a new biophysical model for time interval learning in a Purkinje cell. The numerical model focuses on a classical delay conditioning task (e.g. eyeblink conditioning) and relies on a few computational steps. In particular, the model posits the activation by the parallel fiber input of a local intra-cellular calcium store which can be modulated by intra-cellular pathways. The reciprocal interaction of the calcium signal with several proteins forming negative and positive feedback loops ensures that the timing of inhibition in the Purkinje cell anticipates the interval between parallel and climbing fiber inputs during training. We systematically test the model ability to learn time intervals at the 150-1000 ms time scale, while observing that learning can also extend to the multiple seconds scale. In agreement with experimental observations we also show that the number of pairings required to learn increases with inter-stimulus interval. Finally, we discuss how this model would allow the cerebellum to detect and generate specific spatio-temporal patterns, a classical theory for cerebellar function.

Locating the engram: Should we look for plastic synapses or information-storing molecules?

Karl Lashley began the search for the engram nearly seventy years ago. In the time since, much has been learned but divisions remain. In the contemporary neurobiology of learning and memory, two profoundly different conceptions contend: the associative/connectionist (A/C) conception and the computational/representational (C/R) conception. Both theories ground themselves in the belief that the mind is emergent from the properties and processes of a material brain. Where these theories differ is in their description of what the neurobiological substrate of memory is and where it resides in the brain. The A/C theory of memory emphasizes the need to distinguish memory cognition from the memory engram and postulates that memory cognition is an emergent property of patterned neural activity routed through engram circuits. In this model, learning re-organizes synapse association strengths to guide future neural activity. Importantly, the version of the A/C theory advocated for here contends that synaptic change is not symbolic and, despite normally being necessary, is not sufficient for memory cognition. Instead, synaptic change provides the capacity and a blueprint for reinstating symbolic patterns of neural activity. Unlike the A/C theory, which posits that memory emerges at the circuit level, the C/R conception suggests that memory manifests at the level of intracellular molecular structures. In C/R theory, these intracellular structures are information-conveying and have properties compatible with the view that brain computation utilizes a read/write memory, functionally similar to that in a computer. New research has energized both sides and highlighted the need for new discussion. Both theories, the key questions each theory has yet to resolve and several potential paths forward are presented here.

Intrinsic memory of temporal intervals in cerebellar Purkinje cells

The general consensus for learning and memory, including in the cerebellum, is that modification of synaptic strength via long-term potentiation (LTP) or long-term depression (LTD) are the primary mechanisms for the formation of memories. Recent findings suggest additional cellular mechanisms - referred to as 'intrinsic plasticity' - where a neuron's membrane excitability intrinsically changes. These mechanisms act like a dimmer and alter neuronal responsiveness by adjusting response amplitudes and spike thresholds. Here, I argue that classical conditioning of cerebellar Purkinje cell responses reveals yet another cell-intrinsic learning mechanism which significantly differs from both changes in synaptic strength and changes in membrane excitability. When the conditional (CS) and unconditional stimuli (US) are delivered directly to the Purkinje cell's immediate pre-synaptic afferents, the parallel fibres and the climbing fibre, the cell learns to respond to the CS with a pause in its spontaneous firing that reflects the interval between the two stimuli. The pause response has a delayed onset and adaptively timed maximum, offset and duration, determined by the previously experienced CS-US interval. The timing is not dependent on any network-generated time-varying input. This implies the existence of a timing mechanism and a memory substrate that encodes the duration of the CS-US interval inside the Purkinje cell. Such temporal interval learning is not simply a change that causes more or less firing in response to an input. Here, I review these findings in relation to the standard theory of synaptic strength changes and the network interactions believed to be necessary for generating time codes.

Absence of Parallel Fibre to Purkinje Cell LTD During Eyeblink Conditioning

Long-term depression (LTD) of parallel fibre/Purkinje cell synapses has been the favoured explanation for cerebellar motor learning such as classical eyeblink conditioning. Previous evidence against this interpretation has been contested. Here we wanted to test whether a classical conditioning protocol causes LTD. We applied a conditioning protocol, using a train of electrical pulses to the parallel fibres as the conditional stimulus. In order to rule out indirect effects caused by antidromic granule cell activation or output from Purkinje cells that might produce changes in Purkinje cell responsiveness, we focused the analysis on the first pulse in the conditional stimulus, that is, before any indirect effects would have time to occur. Purkinje cells learned to respond with a firing pause to the conditional stimulus. Yet, there was no depression of parallel fibre excitation after training.

A cerebellar adaptation to uncertain inputs

Noise and variability are inherent and unavoidable features of neural processing. Despite this physiological challenge, brain systems function well, suggesting the existence of adaptations that cope with noise. We report a novel adaptation that the cerebellum implements to maintain correct responses in the face of ambiguous inputs. We found that under these conditions, the cerebellum used a probabilistic binary choice: Although the probability of behavioral response gradually increased or decreased depending on the degree of similarity between current and trained inputs, the size of response remained constant. That way the cerebellum kept responses adaptive to trained input corrupted by noise while minimizing false responses to novel stimuli. Recordings and analysis of Purkinje cells activity showed that the binary choice is made in the cerebellar cortex. Results from large-scale simulation suggest that internal feedback from cerebellar nucleus back to cerebellar cortex plays a critical role in implementation of binary choice.

Calcium Imaging Reveals Coordinated Simple Spike Pauses in Populations of Cerebellar Purkinje Cells

The brain's control of movement is thought to involve coordinated activity between cerebellar Purkinje cells. The results reported here demonstrate that somatic Ca²⁺ imaging is a faithful reporter of Na⁺-dependent "simple spike" pauses and enables us to optically record changes in firing rates in populations of Purkinje cells in brain slices and in vivo. This simultaneous calcium imaging of populations of Purkinje cells reveals a striking spatial organization of pauses in Purkinje cell activity between neighboring cells. The source of this organization is shown to be the presynaptic gamma-Aminobutyric acid producing (GABAergic) network, and blocking ionotropic gamma-Aminobutyric acid receptor (GABA_ARs) abolishes the synchrony. These data suggest that presynaptic interneurons synchronize (in)activity between neighboring Purkinje cells, and thereby maximize their effect on downstream targets in the deep cerebellar nuclei.

Establishment and transfer of classical eyeblink conditioning using electrical microstimulation of the hippocampus as the conditioned stimulus

The present experiment was designed to determine whether classical eyeblink conditioning (EBC) can be established by using electrical microstimulation of the hippocampus as a conditioned stimulus (CS) paired with an air-puff unconditioned stimulus (US). We intended to examine whether EBC transfer could occur when a CS was shifted between microstimulation of the hippocampus as a CS (Hip-CS) and tone as a CS (tone-CS) and to compare the difference in transfer effectiveness between delay EBC (dEBC) and trace EBC (tEBC). Eight groups of guinea pigs, including 4 experimental groups and 4 control groups, were included in the study. First, the experimental groups received either a Hip-CS or a tone-CS paired with a US; then, these groups were exposed to a shifted CS (tone-CS or Hip-CS) paired with the US. The control groups received the corresponding Hip-CS or tone-CS, which was, however, pseudo-paired with the US. The control groups were then shifted to the tone-CS (or Hip-CS) paired with the US. The results show that EBC can be successfully established when using microstimulation of the hippocampus as a CS paired with an air-puff US, and that the acquisition rates of EBC are higher in the experimental groups than in the control groups after switching from the Hip-CS to the tone-CS or vice versa, indicating the occurrence of learning transfer between EBC established with the Hip-CS and tone-CS. The present study also demonstrated that the EBC re-acquisition rates were remarkably higher in dEBC than in tEBC with both types of transfer, which suggests that the saving effect was more evident in dEBC than tEBC. These results significantly expand our knowledge of EBC transfer as well as the functional neural circuit underlying EBC transfer.

Learned response sequences in cerebellar Purkinje cells

Associative learning in the cerebellum has previously focused on single movements. In eyeblink conditioning, for instance, a subject learns to blink at the right time in response to a conditional stimulus (CS), such as a tone that is repeatedly followed by an unconditional corneal stimulus (US). During conditioning, the CS and US are transmitted by mossy/parallel fibers and climbing fibers to cerebellar Purkinje cells that acquire a precisely timed pause response that drives the overt blink response. The timing of this conditional Purkinje cell response is determined by the CS-US interval and is independent of temporal patterns in the input signal. In addition to single movements, the cerebellum is also believed to be important for learning complex motor programs that require multiple precisely timed muscle contractions, such as, for example, playing the piano. In the present work, we studied Purkinje cells in decerebrate ferrets that were conditioned using electrical stimulation of mossy fiber and climbing fiber afferents as CS and US, while alternating between short and long interstimulus intervals. We found that Purkinje cells can learn double pause responses, separated by an intermediate excitation, where each pause corresponds to one interstimulus interval. The results show that individual cells can not only learn to time a single response but that they also learn an accurately timed sequential response pattern.

Cerebellar learning modulates surface expression of a voltage-gated ion channel in cerebellar cortex

Numerous experiments using ex vivo electrophysiology suggest that mammalian learning and memory involves regulation of voltage-gated ion channels in terms of changes in function. Yet, little is known about learning-related regulation of voltage-gated ion channels in terms of changes in expression. In two experiments, we examined changes in cell surface expression of the voltage-gated potassium channel alpha-subunit Kv1.2 in a discrete region of cerebellar cortex after eyeblink conditioning (EBC), a well-studied form of cerebellar-dependent learning. Kv1.2 in cerebellar cortex is expressed almost entirely in basket cells, primarily in the axon terminal pinceaux (PCX) region, and Purkinje cells, primarily in dendrites. Cell surface expression of Kv1.2 was measured using both multiphoton microscopy, which allowed measurement confined to the PCX region, and biotinylation/western blot, which measured total cell surface expression. In the first experiment, rats underwent three sessions of EBC, explicitly unpaired stimulus exposure, or context-only exposure and the results revealed a decrease in Kv1.2 cell surface expression in the unpaired group as measured with microscopy but no change as measured with western blot. In the second experiment, the same three training groups underwent only one half of a session of training, and the results revealed an increase in Kv1.2 cell surface expression in the unpaired group as measured with western blot but no change as measured with microscopy. In addition, rats in the EBC group that did not express conditioned responses (CRs) exhibited the same increase in Kv1.2 cell surface expression as the unpaired group. The overall pattern of results suggests that cell surface expression of Kv1.2 is changed with exposure to EBC stimuli in the absence, or prior to the emergence, of CRs.

On the research of time past: the hunt for the substrate of memory

The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory.

Are Purkinje Cell Pauses Drivers of Classically Conditioned Blink Responses?

Several lines of evidence show that classical or Pavlovian conditioning of blink responses depends on the cerebellum. Recordings from cerebellar Purkinje cells that control the eyelid and the conditioned blink show that during training with a conditioning protocol, a Purkinje cell develops a pause response to the conditional stimulus. This conditioned cellular response has many of the properties that characterise the overt blink. The present paper argues that the learned Purkinje cell pause response is the memory trace and main driver of the overt conditioned blink and that it explains many well-known behavioural phenomena.

Mechanisms for motor timing in the cerebellar cortex

In classical eyeblink conditioning a subject learns to blink to a previously neutral stimulus. This conditional response is timed to occur just before an air puff to the eye. The learning is known to depend on the cerebellar cortex where Purkinje cells respond with adaptively timed pauses in their spontaneous firing. The pauses in the inhibitory Purkinje cells cause disinhibition of the cerebellar nuclei, which elicit the overt blinks. The timing of a Purkinje cell response was previously thought to require a temporal code in the input signal but recent work suggests that the Purkinje cells can learn to time their responses through an intrinsic mechanism that is activated by metabotropic glutamate receptors (mGluR7).

Inactivation of Cerebellar Cortical Crus II Disrupts Temporal Processing of Absolute Timing but not Relative Timing in Voluntary Movements

Several recent studies have demonstrated that the cerebellum plays an important role in temporal processing at the scale of milliseconds. However, it is not clear whether intrinsic cerebellar function involves the temporal processing of discrete or continuous events. Temporal processing during discrete events functions by counting absolute time like a stopwatch, while during continuous events it measures events at intervals. During the temporal processing of continuous events, animals might respond to rhythmic timing of sequential responses rather than to the absolute durations of intervals. Here, we tested the contribution of the cerebellar cortex to temporal processing of absolute and relative timings in voluntary movements. We injected muscimol and baclofen to a part of the cerebellar cortex of rats. We then tested the accuracy of their absolute or relative timing prediction using two timing tasks requiring almost identical reaching movements. Inactivation of the cerebellar cortex disrupted accurate temporal prediction in the absolute timing task. The rats formed two groups based on the changes to their timing accuracy following one of two distinct patterns which can be described as longer or shorter declines in the accuracy of learned intervals. However, a part of the cerebellar cortical inactivation did not affect the rats' performance of relative timing tasks. We concluded that a part of the cerebellar cortex, Crus II, contributes to the accurate temporal prediction of absolute timing and that the entire cerebellar cortex may be unnecessary in cases in which accurately knowing the absolute duration of an interval is not required for temporal prediction.

Motor Learning and the Cerebellum

Although our ability to store semantic declarative information can nowadays be readily surpassed by that of simple personal computers, our ability to learn and express procedural memories still outperforms that of supercomputers controlling the most advanced robots. To a large extent, our procedural memories are formed in the cerebellum, which embodies more than two-thirds of all neurons in our brain. In this review, we will focus on the emerging view that different modules of the cerebellum use different encoding schemes to form and express their respective memories. More specifically, zebrin-positive zones in the cerebellum, such as those controlling adaptation of the vestibulo-ocular reflex, appear to predominantly form their memories by potentiation mechanisms and express their memories via rate coding, whereas zebrin-negative zones, such as those controlling eyeblink conditioning, appear to predominantly form their memories by suppression mechanisms and express their memories in part by temporal coding using rebound bursting. Together, the different types of modules offer a rich repertoire to acquire and control sensorimotor processes with specific challenges in the spatiotemporal domain.

Relating cerebellar purkinje cell activity to the timing and amplitude of conditioned eyelid responses

How Purkinje cell (PC) activity may be altered by learning is central to theories of the cerebellum. Pavlovian eyelid conditioning, because of how directly it engages the cerebellum, has helped reveal many aspects of cerebellar learning and the underlying mechanisms. Theories of cerebellar learning assert that climbing fiber inputs control plasticity at synapses onto PCs, and thus PCs control the expression of learned responses. We tested this assertion by recording 184 eyelid PCs and 240 non-eyelid PCs during the expression of conditioned eyelid responses (CRs) in well trained rabbits. By contrasting the responses of eyelid and non-eyelid PCs and by contrasting the responses of eyelid PCs under conditions that produce differently timed CRs, we test the hypothesis that learning-related changes in eyelid PCs contribute to the learning and adaptive timing of the CRs. We used a variety of analyses to test the quantitative relationships between eyelid PC responses and the kinematic properties of the eyelid CRs. We find that the timing of eyelid PC responses varies systematically with the timing of the behavioral CRs and that there are differences in the magnitude of eyelid PC responses between larger-CR, smaller-CR, and non-CR trials. However, eyelid PC activity does not encode any single kinematic property of the behavioral CRs at a fixed time lag, nor does it linearly encode CR amplitude. Even so, the results are consistent with the hypothesis that learning-dependent changes in PC activity contribute to the adaptively timed expression of conditioned eyelid responses.

Theoretical considerations for understanding a Purkinje cell timing mechanism

In classical conditioning, cerebellar Purkinje cells learn an adaptively timed pause in spontaneous firing. This pause reaches its maximum near the end of the interstimulus interval. While it was thought that this timing was due to temporal patterns in the input signal and selective engagement of changes in synapse strength, we have shown Purkinje cells learn timed responses even when the conditional stimulus is delivered to its immediate afferents.¹ This shows that Purkinje cells have a cellular timing mechanism. The cellular models of intrinsic timing we are aware of are based on adapting the rise time of the concentration of a given ion. As an alternative, we here propose a selection mechanism in abstract terms for how a Purkinje cell could learn to respond at a particular time after an external trigger.

Memory trace and timing mechanism localized to cerebellar Purkinje cells

The standard view of the mechanisms underlying learning is that they involve strengthening or weakening synaptic connections. Learned response timing is thought to combine such plasticity with temporally patterned inputs to the neuron. We show here that a cerebellar Purkinje cell in a ferret can learn to respond to a specific input with a temporal pattern of activity consisting of temporally specific increases and decreases in firing over hundreds of milliseconds without a temporally patterned input. Training Purkinje cells with direct stimulation of immediate afferents, the parallel fibers, and pharmacological blocking of interneurons shows that the timing mechanism is intrinsic to the cell itself. Purkinje cells can learn to respond not only with increased or decreased firing but also with an adaptively timed activity pattern.

Human premotor areas parse sequences into their spatial and temporal features

Skilled performance is characterized by precise and flexible control of movement sequences in space and time. Recent theories suggest that integrated spatio-temporal trajectories are generated by intrinsic dynamics of motor and premotor networks. This contrasts with behavioural advantages that emerge when a trained spatial or temporal feature of sequences is transferred to a new spatio-temporal combination arguing for independent neural representations of these sequence features. We used a new fMRI pattern classification approach to identify brain regions with independent vs integrated representations. A distinct regional dissociation within motor areas was revealed: whereas only the contralateral primary motor cortex exhibited unique patterns for each spatio-temporal sequence combination, bilateral premotor areas represented spatial and temporal features independently of each other. These findings advocate a unique function of higher motor areas for flexible recombination and efficient encoding of complex motor behaviours.

DOI:http://dx.doi.org/10.7554/eLife.03043.001

Once a pianist has learned to play a song, he or she can nearly effortlessly reproduce the sequence of finger movements needed to play the song with a particular rhythm. A skilled pianist can also improvise, pairing the same keystrokes with a different rhythm or playing the same rhythm with a slightly different sequence of keys. This ability to flexibly modify and recombine sequences of physical movements in space and time enables humans to exhibit great creativity in music, language, and many other tasks that require motor skills. However, the underlying brain mechanisms that allow this flexibility are only beginning to be explored.

Some scientists have theorized that networks of brain cells in the parts of the brain that control movement store a sequence in time and space as one inseparable unit. However, this theory doesn't explain why pianists and other skilled individuals can separate and recombine the physical movements and timing of a sequence in new ways. An alternate idea is that the brain captures the information necessary to execute a series of physical movements separately from the timing at which the movements are to be carried out. This would allow these features to be put together in new ways.

Kornysheva and Diedrichsen taught a group of volunteers a series of finger movements paired with particular rhythms. Half the volunteers performed the task using their left hand and the other half with their right hand. After training the volunteers performed better when producing sequences they had been trained on, even in trials where either the rhythm or the finger sequence was slightly changed.

The volunteers were also asked to perform the trained movements while their brain activity was monitored in a functional magnetic resonance imaging (fMRI) machine. Kornysheva and Diedrichsen looked for areas that showed similar patterns of increases and decreases in activity whenever a particular sequence was performed. This identified areas that showed unique patterns for each trained sequence combination of finger movements and rhythm, which could be distinguished from areas where the activity patterns for sequences remained similar across rhythms or across finger movements.

Kornysheva and Diedrichsen found that a region of the brain that controls movement encodes sequences on the opposite side of the brain from the moving hand. In this part of the brain, the movement and timing were encoded together as one unit. However, in premotor areas—which are known to help individuals to plan movements—the timing and the finger movements appeared to be encoded separately in overlapping patches on both sides of the brain. This automatic separation appears to be a fundamental function of the premotor cortex, enabling behavioural flexibility and the storage of complex sequences of movements in space and time.

DOI:http://dx.doi.org/10.7554/eLife.03043.002

Changes in complex spike activity during classical conditioning

The cerebellar cortex is necessary for adaptively timed conditioned responses (CRs) in eyeblink conditioning. During conditioning, Purkinje cells acquire pause responses or "Purkinje cell CRs" to the conditioned stimuli (CS), resulting in disinhibition of the cerebellar nuclei (CN), allowing them to activate motor nuclei that control eyeblinks. This disinhibition also causes inhibition of the inferior olive (IO), via the nucleo-olivary pathway (N-O). Activation of the IO, which relays the unconditional stimulus (US) to the cortex, elicits characteristic complex spikes in Purkinje cells. Although Purkinje cell activity, as well as stimulation of the CN, is known to influence IO activity, much remains to be learned about the way that learned changes in simple spike firing affects the IO. In the present study, we analyzed changes in simple and complex spike firing, in extracellular Purkinje cell records, from the C3 zone, in decerebrate ferrets undergoing training in a conditioning paradigm. In agreement with the N-O feedback hypothesis, acquisition resulted in a gradual decrease in complex spike activity during the conditioned stimulus, with a delay that is consistent with the long N-O latency. Also supporting the feedback hypothesis, training with a short interstimulus interval (ISI), which does not lead to acquisition of a Purkinje cell CR, did not cause a suppression of complex spike activity. In contrast, observations that extinction did not lead to a recovery in complex spike activity and the irregular patterns of simple and complex spike activity after the conditioned stimulus are less conclusive.

Bidirectional plasticity of Purkinje cells matches temporal features of learning

Many forms of learning require temporally ordered stimuli. In Pavlovian eyeblink conditioning, a conditioned stimulus (CS) must precede the unconditioned stimulus (US) by at least about 100 ms for learning to occur. Conditioned responses are learned and generated by the cerebellum. Recordings from the cerebellar cortex during conditioning have revealed CS-triggered pauses in the firing of Purkinje cells that likely drive the conditioned blinks. The predominant view of the learning mechanism in conditioning is that long-term depression (LTD) at parallel fiber (PF)-Purkinje cell synapses underlies the Purkinje cell pauses. This raises a serious conceptual challenge because LTD is most effectively induced at short CS-US intervals, which do not support acquisition of eyeblinks. To resolve this discrepancy, we recorded Purkinje cells during conditioning with short or long CS-US intervals. Decerebrated ferrets trained with CS-US intervals ≥150 ms reliably developed Purkinje cell pauses, but training with an interval of 50 ms unexpectedly induced increases in CS-evoked spiking. This bidirectional modulation of Purkinje cell activity offers a basis for the requirement of a minimum CS-US interval for conditioning, but we argue that it cannot be fully explained by LTD, even when previous in vitro studies of stimulus-timing-dependent LTD are taken into account.

Number of spikes in climbing fibers determines the direction of cerebellar learning

Cerebellar learning requires context information from mossy fibers and a teaching signal through the climbing fibers from the inferior olive. Although the inferior olive fires in bursts, virtually all studies have used a teaching signal consisting of a single pulse. Following a number of failed attempts to induce cerebellar learning in decerebrate ferrets with a nonburst signal, we tested the effect of varying the number of pulses in the climbing fiber teaching signal. The results show that training with a single pulse in a conditioning paradigm in vivo does not result in learning, but rather causes extinction of a previously learned response.

Timing and cue competition in conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus)

Rabbits were classically conditioned using compounds of tone and light conditioned stimuli (CSs) presented with either simultaneous onsets (Experiment 1) or serial onsets (Experiment 2) in a delay conditioning paradigm. Training with the simultaneous compound reduced the likelihood of a conditioned response (CR) to the individual CSs (“mutual overshadowing”) but left CR timing unaltered. CR peaks were consistently clustered around the time of unconditioned stimulus (US) delivery. Training with the serial compound (CSA→CSB→US) reduced responding to CSB (“temporal primacy/information effect”) but this effect was prevented by prior CSB→US pairings. In both cases, serial compound training altered CR timing. On CSA→CSB test trials, the CRs were accelerated; the CR peaks occurred after CSB onset but well before the time of US delivery. Conversely, CRs on CSB– trials were decelerated; the distribution of CR peaks was variable but centered well after the US. Timing on CSB– trials was at most only slightly accelerated. The results are discussed with respect to processes of generalization and spectral timing applicable to the cerebellar and forebrain pathways in eyeblink preparations.

Interaction of temporal and ordinal representations in movement sequences

The production of movement sequences requires an accurate control of muscle activation in time. How does the nervous system encode the precise timing of these movements? One possibility is that the timing of movements (temporal sequence) is an emergent property of the dynamic state of the nervous system and therefore intimately linked to a representation of the sequence of muscle commands (ordinal sequence). Alternatively, timing may be represented independently of the motor effectors and would be transferable to a new ordinal sequence. Some studies have found that a learned temporal sequence cannot be transferred to a new ordinal sequence, thus arguing for an integrated representation. Others have observed temporal transfer across movement sequences and have advocated an independent representation of temporal information. Using a modified serial reaction time task, we tested alternative models of the representation of temporal structure and the interaction between the output of separate ordinal and temporal sequence representations. Temporal transfer depended on whether a novel ordinal sequence was fixed within each test block. Our results confirm the presence of an independent representation of temporal structure and advocate a nonlinear multiplicative neural interaction of temporal and ordinal signals in the production of movements.

Classical eyeblink conditioning using electrical stimulation of caudal mPFC as conditioned stimulus is dependent on cerebellar interpositus nucleus in guinea pigs

AIM

To determine whether electrical stimulation of caudal medial prefrontal cortex (mPFC) as conditioned stimulus (CS) paired with airpuff unconditioned stimulus (US) was sufficient for establishing eyeblink conditioning in guinea pigs, and whether it was dependent on cerebellar interpositus nucleus.

METHODS

Thirty adult guinea pigs were divided into 3 conditioned groups, and trained on the delay eyeblink conditioning, short-trace eyeblink conditioning, and long-trace eyeblink conditioning paradigms, respectively, in which electrical stimulation of the right caudal mPFC was used as CS and paired with corneal airpuff US. A pseudo conditioned group of another 10 adult guinea pigs was given unpaired caudal mPFC electrical stimulation and the US. Muscimol (1 μg in 1 μL saline) and saline (1 μL) were infused into the cerebellar interpositus nucleus of the animals through the infusion cannula on d 11 and 12, respectively.

RESULTS

The 3 eyeblink conditioning paradigms have been successfully established in guinea pigs. The animals acquired the delay and short-trace conditioned responses more rapidly than long-trace conditioned responses. Muscimol infusion into the cerebellar interpositus nucleus markedly impaired the expression of the 3 eyeblink conditioned responses.

CONCLUSION

Electrical stimulation of caudal mPFC is effective CS for establishing eyeblink conditioning in guinea pigs, and it is dependent on the cerebellar interpositus nucleus.

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.