Biorobotics/Biomechanics

Spinal cord

Modelling

Neuron

Brain

Analytics

Intracellular

Cerebellum

For three decades our founders challenged the common consensus of one of the biggest scientific questions of our time: How does the brain work?

IntuiCell | Research

Born in the intersection
of AI and Neuroscience.

IntuiCell is a Lund University spin-off with presence in Lund and Stockholm. 

For three decades our founders challenged the common consensus 
of one of the biggest scientific questions of our time:

Today, we apply those groundbreaking neurophysiological insights 
to redesign artificial intelligence. Creating AI that is 

Explore our contrarian research on the mechanisms by which the 
brain predicts the world.

Research

CO Norrsken House
Birger Jarlsgatan 57C
SE-113 56 Stockholm

About

AI isn't actually intelligent. IntuiCell already is.

IntuiCell

The original chapter on adaptive-filter models addressed the issue of how far such models were consistent with experimental evidence. Here we consider one particularly important kind of evidence, that concerning the nature of the synaptic plasticity that underlies cerebellar learning. The basic decorrelation learning rule employed by the adaptive-filter model can be translated into spike timing-dependent plasticity form, in which temporal coincidence of parallel fiber and climbing fiber spikes produces LTD at parallel fiber synapses on Purkinje cells, and noncoincidence produces LTP. Although this appears at first sight to be consistent with extensive evidence demonstrating the existence of LTD, other studies have raised serious issues about its functional role. For example, Schonewille et al. (Neuron 70:43–50, 2011) demonstrated that mutant mice unable to sequester Purkinje cell AMPA receptors – the mechanism thought to underlie LTD – did indeed lack LTD, but showed no evidence of impaired learning of typical “cerebellar” tasks such as adaptation of the vestibulo-ocular reflex or eyeblink conditioning. This discrepancy focusses attention on (i) the potential importance of LTP for the initial phases of cerebellar learning, and (ii) the problems posed by reliance on in vitro preparations. An important question concerning the latter is therefore whether the blockage of LTD demonstrated in the mutant mice by Schonewille et al. would also be found in vivo. Resolving this issue would clarify the role of the cerebellum in supervised learning in general, and the plausibility of adaptive-filter models in particular.

The original chapter on adaptive-filter models addressed the issue of how far such models were consistent with experimental evidence. 

Adaptive filter models

The compartmentalization of the cerebellum into modules is often used to discuss its function. What, exactly, can be considered a module, how do they operate, can they be subdivided and do they act individually or in concert are only some of the key questions discussed in this consensus paper. Experts studying cerebellar compartmentalization give their insights on the structure and function of cerebellar modules, with the aim of providing an up-to-date review of the extensive literature on this subject. Starting with an historical perspective indicating that the basis of the modular organization is formed by matching olivocorticonuclear connectivity, this is followed by consideration of anatomical and chemical modular boundaries, revealing a relation between anatomical, chemical, and physiological borders. In addition, the question is asked what the smallest operational unit of the cerebellum might be. Furthermore, it has become clear that chemical diversity of Purkinje cells also results in diversity of information processing between cerebellar modules. An additional important consideration is the relation between modular compartmentalization and the organization of the mossy fiber system, resulting in the concept of modular plasticity. Finally, examination of cerebellar output patterns suggesting cooperation between modules and recent work on modular aspects of emotional behavior are discussed. Despite the general consensus that the cerebellum has a modular organization, many questions remain. The authors hope that this joint review will inspire future cerebellar research so that we are better able to understand how this brain structure makes its vital contribution to behavior in its most general form.

The compartmentalization of the cerebellum into modules is often used to discuss its function.

Cerebellar Modules and Their Role as Operational Cerebellar Processing Units: A Consensus paper

For many decades, the predominant view in the cerebellar field has been that the olivocerebellar system’s primary function is to induce plasticity in the cerebellar cortex, specifically, at the parallel fiber-Purkinje cell synapse. However, it has also long been proposed that the olivocerebellar system participates directly in motor control by helping to shape ongoing motor commands being issued by the cerebellum. Evidence consistent with both hypotheses exists; however, they are often investigated as mutually exclusive alternatives. In contrast, here, we take the perspective that the olivocerebellar system can contribute to both the motor learning and motor control functions of the cerebellum and might also play a role in development. We then consider the potential problems and benefits of it having multiple functions. Moreover, we discuss how its distinctive characteristics (e.g., low firing rates, synchronization, and variable complex spike waveforms) make it more or less suitable for one or the other of these functions, and why having multiple functions makes sense from an evolutionary perspective. We did not attempt to reach a consensus on the specific role(s) the olivocerebellar system plays in different types of movements, as that will ultimately be determined experimentally; however, collectively, the various contributions highlight the flexibility of the olivocerebellar system, and thereby suggest that it has the potential to act in both the motor learning and motor control functions of the cerebellum.

For many decades, the predominant view in the cerebellar field has been that the olivocerebellar system’s primary function is to induce plasticity in the cerebellar cortex, specifically, at the parallel fiber-Purkinje cell synapse.

The Roles of the Olivocerebellar Pathway in Motor Learning and Motor Control. A Consensus Paper

The existence of input plasticity in the deep cerebellar nuclear (DCN) cells of the adult cerebellum could have profound implications for our understanding of cerebellar function. Whereas the existence of plastic changes in mossy fiber (mf) synaptic responses in DCN neurons has been demonstrated in juvenile slices, there has so far been no direct demonstration of this form of plasticity in the adult cerebellum in vivo. In the present paper, we recorded from neurons in the anterior interposed nucleus (AIN) and stimulated the spinocerebellar tracts (SCT) directly or via the skin to obtain mf activation and the inferior olive to activate climbing fibers (cfs) in the nonanesthetized, adult, decerebrated cat. We used three different types of protocols that theoretically could be expected to induce plasticity, each of which involved episodically intense afferent activation lasting for 10 min. These were conjunctive mf-cf activation, which effectively induces plasticity in cortical neurons; mf and cf activation in a pattern resembling the protocol for inducing classical conditioning; and conjunctive activation of two excitatory mf inputs. None of these protocols had any statistically significant effect on the evoked responses in the AIN neurons. We conclude that the input plasticity for excitatory mfs in the AIN cells of the adult cerebellum in vivo is likely to be less effective than that of parallel fiber synaptic inputs in cerebellar cortical cells, at least in the timespan of 1 h.

The existence of input plasticity in the deep cerebellar nuclear (DCN) cells of the adult cerebellum could have profound implications for our understanding of cerebellar function.

No Medium-Term Spinocerebellar Input Plasticity in Deep Cerebellar Nuclear Neurons In Vivo?

Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear. This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamo-cortical system across a range of motor and cognitive functions. The paper includes theoretical and empirical contributions, which cover the following topics: recent evidence supporting the dynamical interplay between cerebellum, basal ganglia, and cortical areas in humans and other animals; theoretical neuroscience perspectives and empirical evidence on the reciprocal influences between cerebellum, basal ganglia, and cortex in learning and control processes; and data suggesting possible roles of the cerebellum in basal ganglia movement disorders. Although starting from different backgrounds and dealing with different topics, all the contributors agree that viewing the cerebellum, basal ganglia, and cortex as an integrated system enables us to understand the function of these areas in radically different ways. In addition, there is unanimous consensus between the authors that future experimental and computational work is needed to understand the function of cerebellar-basal ganglia circuitry in both motor and non-motor functions. The paper reports the most advanced perspectives on the role of the cerebellum within the cerebello-basal ganglia-thalamo-cortical system and illustrates other elements of consensus as well as disagreements and open questions in the field.

Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear.

Consensus paper: Towards a systems-level view of cerebellar function: The interplay between cerebellum, basal ganglia, and cortex

An accurate interpretation of the neuronal code readouts from behavioral recordings will be possible only when there is an understanding of the connectivity structure of the network under study and the format of the input that drives the circuitry. For the cerebellar cortex, this type of knowledge is comparatively advanced and can at least in some aspects be regarded as sufficient for predicting the behavioral modulations of a single neuron. The aim of this chapter is to review the state of knowledge about cerebellar neuronal codes and to pinpoint the remaining weak spots in our knowledge that prevent us from making predictions of the cerebellar neuronal code. It is concluded that, whereas the cerebellar neuronal circuitry in itself is highly characterized, there is an urgent need for characterizing the types and ranges of encoding in the mossy fiber systems. It is also concluded that cerebellar neuronal representations can be expected to be widely distributed, and the firing of individual cerebellar neurons is likely to represent only the bits and pieces of such distributed representations.

An accurate interpretation of the neuronal code readouts from behavioral recordings will be possible only when there is an understanding of the connectivity structure of the network under study and the format of the input that drives the circuitry.

Cerebellar Neuronal Codes---Perspectives from Intracellular Analysis In Vivo

The mechanism by which a learnt synaptic weight change can contribute to learning or adaptation of brain function is a type of credit assignment problem, which is a key issue for many parts of the brain. In the cerebellum, detailed knowledge not only of the local circuitry connectivity but also of the topography of different sources of afferent/external information makes this problem particularly tractable. In addition, multiple forms of synaptic plasticity and their general rules of induction have been identified. In this review, we will discuss the possible roles of synaptic and cellular plasticity at specific locations in contributing to behavioral changes. Focus will be on the parts of the cerebellum that are devoted to limb control, which constitute a large proportion of the cortex and where the knowledge of the external connectivity is particularly well known. From this perspective, a number of sites of synaptic plasticity appear to primarily have the function of balancing the overall level of activity in the cerebellar circuitry, whereas the locations at which synaptic plasticity leads to functional changes in terms of limb control are more limited. Specifically, the postsynaptic forms of long-term potentiation (LTP) and long-term depression (LTD) at the parallel fiber synapses made on interneurons and Purkinje cells, respectively, are the types of plasticity that mediate the widest associative capacity and the tightest link between the synaptic change and the external functions that are to be controlled.

The mechanism by which a learnt synaptic weight change can contribute to learning or adaptation of brain function is a type of credit assignment problem, which is a key issue for many parts of the brain. 

Cerebellar Synaptic Plasticity and the Credit Assignment Problem

Climbing fiber receptive fields are a physiological marker that have proven useful to delineate the details of the olivocerebellar circuitry. They have also proven useful as a point of reference to delineate the organization of other parts of the cerebellar circuitry. But what does the location of the climbing fiber receptive field imply and what is its relation to the presumed role of the cerebellum in coordination? Can we expect that all climbing fibers have a peripheral receptive field on the skin? In this short review, we aim to cover these issues.

Climbing fiber receptive fields are a physiological marker that have proven useful to delineate the details of the olivocerebellar circuitry. 

Climbing fiber receptive fields---organizational and functional aspects and relationship to limb coordination

We aimed to explore the cerebellar cortical inputs from two spinocerebellar pathways, the spinal border cell-component of the ventral spinocerebellar tract (SBC-VSCT) and the dorsal spinocerebellar tract (DSCT), respectively, in the sublobule C1 of the cerebellar posterior lobe. The two pathways were activated by electrical stimulation of the contralateral lateral funiculus (coLF) and the ipsilateral LF (iLF) at lower thoracic levels. Most granule cells in sublobule C1 did not respond at all but part of the granule cell population displayed high-intensity responses to either coLF or iLF stimulation. As a rule, Golgi cells and Purkinje cell simple spikes responded to input from both LFs, although Golgi cells could be more selective. In addition, a small population of granule cells responded to input from both the coLF and the iLF. However, in these cases, similarities in the temporal topography and magnitude of the responses suggested that the same axons were stimulated from the two LFs, i.e., that the axons of individual spinocerebellar neurons could be present in both funiculi. This was also confirmed for a population of spinal neurons located within known locations of SBC-VSCT neurons and dorsal horn (dh) DSCT neurons. We conclude that bilateral spinocerebellar responses can occur in cerebellar granule cells, but the VSCT and DSCT systems that provide the input can also be organized bilaterally. The implications for the traditional functional separation of VSCT and DSCT systems and the issue whether granule cells primarily integrate functionally similar information or not are discussed.

We aimed to explore the cerebellar cortical inputs from two spinocerebellar pathways, the spinal border cell-component of the ventral spinocerebellar tract (SBC-VSCT) and the dorsal spinocerebellar tract (DSCT), respectively, in the sublobule C1 of the cerebellar posterior lobe.

Properties of bilateral spinocerebellar activation of cerebellar cortical neurons

The spinocerebellar systems are essential for the brain in the performance of coordinated movements, but our knowledge about the spinocerebellar interactions is very limited. Recently, several crucial pieces of information have been acquired for the spinal border cell (SBC) component of the ventral spinocerebellar tract (VSCT), as well as the effects of SBC mossy fiber activation in granule cells of the cerebellar cortex. SBCs receive monosynaptic input from the reticulospinal tract (RST), which is an important driving system under locomotion, and disynaptic inhibition from Ib muscle afferents. The patterns of activity of RST neurons and Ib afferents under locomotion are known. The activity of VSCT neurons under fictive locomotion, i.e. without sensory feedback, is also known, but there is little information on how these neurons behave under actual locomotion and for cerebellar granule cells receiving SBC input this is completely unknown. But the available information makes it possible to simulate the interactions between the spinal and cerebellar neuronal circuitries with a relatively large set of biological constraints. Using a model of the various neuronal elements and the network they compose, we simulated the modulation of the SBCs and their target granule cells under locomotion and hence generated testable predictions of their general pattern of modulation under this condition. This particular system offers a unique opportunity to simulate these interactions with a limited number of assumptions, which helps making the model biologically plausible. Similar principles of information processing may be expected to apply to all spinocerebellar systems.

The spinocerebellar systems are essential for the brain in the performance of coordinated movements, but our knowledge about the spinocerebellar interactions is very limited.

Born in the intersection
of AI and Neuroscience.

IntuiCell is a Lund University spin-off with presence in Lund and Stockholm.

For three decades our founders challenged the common consensus
of one of the biggest scientific questions of our time:

How does the brain work?

Today, we apply those groundbreaking neurophysiological insights
to redesign artificial intelligence. Creating AI that is actually intelligent.

Explore our contrarian research on the mechanisms by which the
brain predicts the world.

All Publications.

Born in the intersectionof AI and Neuroscience.

IntuiCell is a Lund University spin-off with presence in Lund and Stockholm.

For three decades our founders challenged the common consensus of one of the biggest scientific questions of our time:

How does the brain work?

Today, we apply those groundbreaking neurophysiological insights to redesign artificial intelligence. Creating AI that is actually intelligent.

Explore our contrarian research on the mechanisms by which the brain predicts the world.

All Publications.

Born in the intersection
of AI and Neuroscience.

For three decades our founders challenged the common consensus
of one of the biggest scientific questions of our time:

Today, we apply those groundbreaking neurophysiological insights
to redesign artificial intelligence. Creating AI that is actually intelligent.

Explore our contrarian research on the mechanisms by which the
brain predicts the world.