In the cerebellar network, a precise relationship between plasticity and neuronal discharge has been predicted. However, the potential generation of persistent changes in Purkinje cell (PC) spike discharge as a consequence of plasticity following natural stimulation patterns has not been clearly determined. Here, we show that facial tactile stimuli organized in theta-patterns can induce stereotyped N-methyl-D-aspartate (NMDA) and gamma-aminobutyric acid (GABA-A) receptor-dependent changes in PCs and molecular layer interneurons (MLIs) firing: invariably, all PCs showed a long-lasting increase (Spike-Related Potentiation or SR-P) and MLIs a long-lasting decrease (Spike-Related Suppression or SR-S) in baseline activity and spike response probability. These observations suggests that tactile sensory stimulation engages multiple long-term plastic changes that are distributed along the mossy fiber-parallel fiber (MF-PF) pathway and operate synergistically to potentiate spike generation in PCs. In contrast, theta-pattern electrical stimulation (ES) of PFs indistinctly induced SR-P and SR-S both in PCs and MLIs, suggesting that tactile sensory stimulation preordinates plasticity upstream of the PF-PC synapse. All these effects occurred in the absence of complex spike changes, supporting the theoretical prediction that PC activity is potentiated when the MF-PF system is activated in the absence of conjunctive climbing fiber (CF) activity.

A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit information faithfully and linearly in the frequency range of the vestibular-ocular reflex. This was achieved most simply if the model neurons had a firing rate at least twice the highest required frequency of modulation, but lower rates were also adequate provided a population of neurons was utilized, especially in combination with push-pull coding. The exact number of neurons required for faithful transmission depended on the precise values of firing rate and noise. The model neurons were also able to combine excitatory and inhibitory signals linearly, and could be replaced by a simpler (modified) integrate-and-fire neuron in the case of high tonic firing rates. These findings suggest that granule cells can in principle code modulated firing-rate inputs in a linear manner, and are thus consistent with the high-level adaptive-filter model of the cerebellar microcircuit.

A bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a humanoid NAO robot in real time. The learning properties of the system have been challenged in a classic cerebellum-driven paradigm, a perturbed upper limb reaching protocol. The neurophysiological principles used to develop the model succeeded in driving an adaptive motor control protocol with baseline, acquisition, and extinction phases. The spiking neural network model showed learning behaviours similar to the ones experimentally measured with human subjects in the same task in the acquisition phase, while resorted to other strategies in the extinction phase. The model processed in real-time external inputs, encoded as spikes, and the generated spiking activity of its output neurons was decoded, in order to provide the proper correction on the motor actuators. Three bidirectional long-term plasticity rules have been embedded for different connections and with different time scales. The plasticities shaped the firing activity of the output layer neurons of the network. In the perturbed upper limb reaching protocol, the neurorobot successfully learned how to compensate for the external perturbation generating an appropriate correction. Therefore, the spiking cerebellar model was able to reproduce in the robotic platform how biological systems deal with external sources of error, in both ideal and real (noisy) environments.

The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model and a biophysically-detailed model of the network were used to study signal recoding in the granular layer and to test observations like center-surround organization and time-window hypothesis in addition to effects of induced plasticity. Simulations suggest that simple neuron models may be used to abstract timing phenomenon in large networks, however detailed models were needed to reconstruct population coding via evoked local field potentials (LFP) and for simulating changes in synaptic plasticity. Our results also indicated that spatio-temporal code of the granular network is mainly controlled by the feed-forward inhibition from the Golgi cell synapses. Spike amplitude and total number of spikes were modulated by LTP and LTD. Reconstructing granular layer evoked-LFP suggests that granular layer propagates the nonlinearities of individual neurons. Simulations indicate that granular layer network operates a robust population code for a wide range of intervals, controlled by the Golgi cell inhibition and is regulated by the post-synaptic excitability.

Neurons in vertebrate central nervous systems initiate and conduct sodium action potentials in distinct subcellular compartments that differ architecturally and electrically. Here, we report several unanticipated passive and active properties of the cerebellar granule cell's unmyelinated axon. Whereas spike initiation at the axon initial segment relies on sodium channel (Nav)-associated fibroblast growth factor homologous factor (FHF) proteins to delay Nav inactivation, distal axonal Navs show little FHF association or FHF requirement for high-frequency transmission, velocity and waveforms of conducting action potentials. In addition, leak conductance density along the distal axon is estimated as <1% that of somatodendritic membrane. The faster inactivation rate of FHF-free Navs together with very low axonal leak conductance serves to minimize ionic fluxes and energetic demand during repetitive spike conduction and at rest. The absence of FHFs from Navs at nodes of Ranvier in the central nervous system suggests a similar mechanism of current flux minimization along myelinated axons.

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

The brain functions can be reversibly modulated by the action of general anesthetics. Despite a wide number of pharmacological studies, an extensive analysis of the cellular determinants of anesthesia at the microcircuits level is still missing. Here, by combining patch-clamp recordings and mathematical modeling, we examined the impact of sevoflurane, a general anesthetic widely employed in the clinical practice, on neuronal communication. The cerebellar microcircuit was used as a benchmark to analyze the action mechanisms of sevoflurane while a biologically realistic mathematical model was employed to explore at fine grain the molecular targets of anesthetic analyzing its impact on neuronal activity. The sevoflurane altered neurotransmission by strongly increasing GABAergic inhibition while decreasing glutamatergic NMDA activity. These changes caused a notable reduction of spike discharge in cerebellar granule cells (GrCs) following repetitive activation by excitatory mossy fibers (mfs). Unexpectedly, sevoflurane altered GrCs intrinsic excitability promoting action potential generation. Computational modelling revealed that this effect was triggered by an acceleration of persistent sodium current kinetics and by an increase in voltage dependent potassium current conductance. The overall effect was a reduced variability of GrCs responses elicited by mfs supporting the idea that sevoflurane shapes neuronal communication without silencing neural circuits.

Long-term synaptic plasticity is thought to provide the substrate for adaptive computation in brain circuits but very little is known about its spatiotemporal organization. Here, we combined multi-spot two-photon laser microscopy in rat cerebellar slices with realistic modeling to map the distribution of plasticity in multi-neuronal units of the cerebellar granular layer. The units, composed by ~300 neurons activated by ~50 mossy fiber glomeruli, showed long-term potentiation concentrated in the core and long-term depression in the periphery. This plasticity was effectively accounted for by an NMDA receptor and calcium-dependent induction rule and was regulated by the inhibitory Golgi cell loops. Long-term synaptic plasticity created effective spatial filters tuning the time-delay and gain of spike retransmission at the cerebellum input stage and provided a plausible basis for the spatiotemporal recoding of input spike patterns anticipated by the motor learning theory.

This study highlights the importance of looking beyond the main effect of movement to study alterations in functional response in the presence of central nervous system pathologies such as multiple sclerosis (MS). Data show that MS selectively affects regional BOLD (blood oxygenation level dependent) responses to variable grip forces (GF). It is known that the anterior and posterior BA 4 areas (BA 4a and BA 4p) are anatomically and functionally distinct. It has also been shown in healthy volunteers that there are linear (first order, typical of BA 4a) and nonlinear (second to fourth order, typical of BA 4p) BOLD responses to different levels of GF applied during a dynamic motor paradigm. After modeling the BOLD response with a polynomial expansion of the applied GFs, the particular case of BA 4a and BA 4p were investigated in healthy volunteers (HV) and MS subjects. The main effect of movement (zeroth order) analysis showed that the BOLD signal is greater in MS compared with healthy volunteers within both BA 4 subregions. At higher order, BOLD-GF responses were similar in BA 4a but showed a marked alteration in BA 4p of MS subjects, with those with greatest disability showing the greatest deviations from the healthy response profile. Therefore, the different behaviors in HV and MS could only be uncovered through a polynomial analysis looking beyond the main effect of movement into the two BA 4 subregions. Future studies will investigate the source of this pathophysiology, combining the present fMRI paradigm with blood perfusion and nonlinear neuronal response analysis.

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.

Previous studies have used fMRI to address the relationship between grip force (GF) applied to an object and BOLD response. However, whilst the majority of these studies showed a linear relationship between GF and neural activity in the contralateral M1 and ipsilateral cerebellum, animal studies have suggested the presence of non-linear components in the GF-neural activity relationship. Here, we present a methodology for assessing non-linearities in the BOLD response to different GF levels, within primary motor as well as sensory and cognitive areas and the cerebellum. To be sensitive to complex forms, we designed a feasible grip task with five GF targets using an event-related visually guided paradigm and studied a cohort of 13 healthy volunteers. Polynomial functions of increasing order were fitted to the data.

Growing neuroimaging and clinical evidence suggests that the cerebellum plays a critical role in perception. In the auditory domain, the cerebellum seems to be important in different aspects of music and sound processing. Here we investigated the possible causal role of the cerebellum in two auditory tasks, a pitch discrimination and a timbre discrimination task. Specifically, participants performed a pitch and a timbre discrimination task prior and after receiving offline low frequency transcranical magnetic stimulation (TMS) over their (right) cerebellum.

Signal elaboration in the cerebellum mossy fiber input pathway presents controversial aspects, especially concerning gain regulation and the spot-like (rather than beam-like) appearance of granular to molecular layer transmission. By using voltage-sensitive dye imaging in rat cerebellar slices (Mapelli et al., 2010), we found that mossy fiber bursts optimally excited the granular layer above approximately 50 Hz and the overlaying molecular layer above approximately 100 Hz, thus generating a cascade of high-pass filters. NMDA receptors enhanced transmission in the granular, while GABA-A receptors depressed transmission in both the granular and molecular layer. Burst transmission gain was controlled through a dynamic frequency-dependent involvement of these receptors. Moreover, while high-frequency transmission was enhanced along vertical lines connecting the granular to molecular layer, no high-frequency enhancement was observed along the parallel fiber axis in the molecular layer. This was probably due to the stronger effect of Purkinje cell GABA-A receptor-mediated inhibition occurring along the parallel fibers than along the granule cell axon ascending branch. The consequent amplification of burst responses along vertical transmission lines could explain the spot-like activation of Purkinje cells observed following punctuate stimulation in vivo.

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

The dysfunction of cholinergic neurons is a typical hallmark in Alzheimer's disease (AD). Previous findings demonstrated that high density of cholinergic receptors is found in the thalamus and the cerebellum compared with the cerebral cortex and the hippocampus. We aimed at investigating whether activation of the cerebello-thalamo-cortical pathway by means of cerebellar theta burst stimulation (TBS) could modulate central cholinergic functions evaluated in vivo by using the neurophysiological determination of Short-Latency Afferent Inhibition (SLAI). We tested the SLAI circuit before and after administration of cerebellar continuous TBS (cTBS) in 12 AD patients and in 12 healthy age-matched control subjects (HS). We also investigated potential changes of intracortical circuits of the contralateral primary motor cortex (M1) by assessing short intracortical inhibition (SICI) and intracortical facilitation (ICF). SLAI was decreased in AD patients compared to HS. Cerebellar cTBS partially restored SLAI in AD patients at later inter-stimulus intervals (ISIs), but did not modify SLAI in HS. SICI and ICF did not differ in the two groups and were not modulated by cerebellar cTBS. These results demonstrate that cerebellar magnetic stimulation is likely to affect mechanisms of cortical cholinergic activity, suggesting that the cerebellum may have a direct influence on the cholinergic dysfunction in AD.

Cerebellar neurones show complex and differentiated mechanisms of action potential generation that have been proposed to depend on peculiar properties of their voltage-dependent Na+ currents. In this study we analysed voltage-dependent Na(+) currents of rat cerebellar granule cells (GCs) by performing whole-cell, patch-clamp experiments in acute rat cerebellar slices. A transient Na+ current (I(NaT)) was always present and had the properties of a typical fast-activating/inactivating Na+ current. In addition to I(NaT), robust persistent (I(NaP)) and resurgent (I(NaR)) Na+ currents were observed. I(NaP) peaked at approximately -40 mV, showed half-maximal activation at approximately -55 mV, and its maximal amplitude was about 1.5% of that of I(NaT). I(NaR) was elicited by repolarizing pulses applied following step depolarizations able to activate/inactivate I(NaT), and showed voltage- and time-dependent activation and voltage-dependent decay kinetics. The conductance underlying I(NaR) showed a bell-shaped voltage dependence, with peak at -35 mV. A significant correlation was found between GC I(NaR) and I(NaT) peak amplitudes; however, GCs expressing I(NaT) of similar size showed marked variability in terms of I(NaR) amplitude, and in a fraction of cells I(NaR) was undetectable. I(NaT), I(NaP) and I(NaR) could be accounted for by a 13-state kinetic scheme comprising closed, open, inactivated and blocked states. Current-clamp experiments carried out to identify possible functional correlates of I(NaP) and/or I(NaR) revealed that in GCs single action potentials were followed by depolarizing afterpotentials (DAPs). In a majority of cells, DAPs showed properties consistent with I(NaR) playing a role in their generation. Computer modelling showed that I(NaR) promotes DAP generation and enhances high-frequency firing, whereas I(NaP) boosts near-threshold firing activity. Our findings suggest that special properties of voltage-dependent Na+ currents provides GCs with mechanisms suitable for shaping activity patterns, with potentially important consequences for cerebellar information transfer and computation.

The Human Brain Project (HBP) is a European flagship project with a 10-year horizon aiming to understand the human brain and to translate neuroscience knowledge into medicine and technology. To achieve such aims, the HBP explores the multilevel complexity of the brain in space and time; transfers the acquired knowledge to brain-derived applications in health, computing, and technology; and provides shared and open computing tools and data through the HBP European brain research infrastructure. We discuss how the HBP creates a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating perspectives on societal benefits.

The induction of long-term potentiation and depression (LTP and LTD) is thought to trigger gene expression and protein synthesis, leading to consolidation of synaptic and neuronal changes. However, while LTP and LTD have been proposed to play important roles for sensori-motor learning in the cerebellum granular layer, their association with these mechanisms remained unclear. Here, we have investigated phosphorylation of the cAMP-responsive element binding protein (CREB) and activation of the immediate early gene c-Fos pathway following the induction of synaptic plasticity by theta-burst stimulation (TBS) in acute cerebellar slices. LTP and LTD were localized using voltage-sensitive dye imaging (VSDi). At two time points following TBS (15 min and 120 min), corresponding to the early and late phases of plasticity, slices were fixed and processed to evaluate CREB phosphorylation (P-CREB) and c-FOS protein levels, as well as Creb and c-Fos mRNA expression. High levels of P-CREB and Creb/c-Fos were detected before those of c-FOS, as expected if CREB phosphorylation triggered gene expression followed by protein synthesis. No differences between control slices and slices stimulated with TBS were observed in the presence of an N-methyl-D-aspartate receptor (NMDAR) antagonist. Interestingly, activation of the CREB/c-Fos system showed a relevant degree of colocalization with long-term synaptic plasticity. These results show that NMDAR-dependent plasticity at the cerebellum input stage bears about transcriptional and post-transcriptional processes potentially contributing to cerebellar learning and memory consolidation.

Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls-HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.

This work presents the first simulation of a large-scale, bio-physically constrained cerebellum model performed on neuromorphic hardware. A model containing 97,000 neurons and 4.2 million synapses is simulated on the SpiNNaker neuromorphic system. Results are validated against a baseline simulation of the same model executed with NEST, a popular spiking neural network simulator using generic computational resources and double precision floating point arithmetic. Individual cell and network-level spiking activity is validated in terms of average spike rates, relative lead or lag of spike times, and membrane potential dynamics of individual neurons, and SpiNNaker is shown to produce results in agreement with NEST. Once validated, the model is used to investigate how to accelerate the simulation speed of the network on the SpiNNaker system, with the future goal of creating a real-time neuromorphic cerebellum. Through detailed communication profiling, peak network activity is identified as one of the main challenges for simulation speed-up. Propagation of spiking activity through the network is measured, and will inform the future development of accelerated execution strategies for cerebellum models on neuromorphic hardware. The large ratio of granule cells to other cell types in the model results in high levels of activity converging onto few cells, with those cells having relatively larger time costs associated with the processing of communication. Organizing cells on SpiNNaker in accordance with their spatial position is shown to reduce the peak communication load by 41%. It is hoped that these insights, together with alternative parallelization strategies, will pave the way for real-time execution of large-scale, bio-physically constrained cerebellum models on SpiNNaker. This in turn will enable exploration of cerebellum-inspired controllers for neurorobotic applications, and execution of extended duration simulations over timescales that would currently be prohibitive using conventional computational platforms.