Consorzio Interuniversitario per le Science Fisiche della Materia

Rome, Italy

Consorzio Interuniversitario per le Science Fisiche della Materia

Rome, Italy
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Garrido J.A.,University of Pavia | Garrido J.A.,Consorzio Interuniversitario per le Science Fisiche della Materia | Ros E.,University of Granada | D'Angelo E.,University of Pavia
Frontiers in Computational Neuroscience | Year: 2013

The way long-term synaptic plasticity regulates neuronal spike patterns is not completely understood. This issue is especially relevant for the cerebellum, which is endowed with several forms of long-term synaptic plasticity and has been predicted to operate as a timing and a learning machine. Here we have used a computational model to simulate the impact of multiple distributed synaptic weights in the cerebellar granular layer network. In response to mossy fiber bursts, synaptic weights at multiple connections played a crucial role to regulate spike number and positioning in granule cells. The weight at mossy fiber to granule cell synapses regulated the delay of the first spike and the weight at mossy fiber and parallel fiber to Golgi cell synapses regulated the duration of the time-window during which the first-spike could be emitted. Moreover, the weights of synapses controlling Golgi cell activation regulated the intensity of granule cell inhibition and therefore the number of spikes that could be emitted. First spike timing was regulated with millisecond precision and the number of spikes ranged from 0 to 3. Interestingly, different combinations of synaptic weights optimized either first-spike timing precision or spike number, efficiently controlling transmission and filtering properties. These results predict that distributed synaptic plasticity regulates the emission of quasi-digital spike patterns on the millisecond time scale and allows the cerebellar granular layer to flexibly control burst transmission along the mossy fiber pathway. © 2013 Garrido, Ros and D'angelo.


Luque N.R.,University of Granada | Garrido J.A.,Consorzio Interuniversitario per le Science Fisiche della Materia | Garrido J.A.,University of Pavia | Carrillo R.R.,University of Granada | And 2 more authors.
Frontiers in Computational Neuroscience | Year: 2014

The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network. © 2014 Luque, Garrido, Carrillo, D'Angelo and Ros.


Ramakrishnan K.B.,University of Pavia | Ramakrishnan K.B.,Consorzio Interuniversitario per le Science Fisiche della Materia | Voges K.,Erasmus University Rotterdam | De Propris L.,University of Pavia | And 3 more authors.
Frontiers in Cellular Neuroscience | Year: 2016

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. © 2016 Ramakrishnan, Voges, De Propris, De Zeeuw and D’Angelo.


Subramaniyam S.,University of Pavia | Subramaniyam S.,Consorzio Interuniversitario per le Science Fisiche della Materia | Perin P.,University of Pavia | Locatelli F.,University of Pavia | And 2 more authors.
Frontiers in Cellular Neuroscience | Year: 2014

Unipolar Brush Cells (UBCs) have been suggested to play a critical role in cerebellar functioning, yet the corresponding cellular mechanisms remain poorly understood. UBCs have recently been reported to generate, in addition to early-onset glutamate receptor-dependent synaptic responses, a late-onset response (LOR) composed of a slow depolarizing ramp followed by a spike burst (Locatelli et al., 2013). The LOR activates as a consequence of synaptic activity and involves an intracellular cascade modulating H- and TRP-current gating. In order to assess the LOR mechanisms, we have developed a UBC multi-compartmental model (including soma, dendrite, initial segment, and axon) incorporating biologically realistic representations of ionic currents and a cytoplasmic coupling mechanism regulating TRP and H channel gating. The model finely reproduced UBC responses to current injection, including a burst triggered by a low-threshold spike (LTS) sustained by CaLVA currents, a persistent discharge sustained by CaHVA currents, and a rebound burst following hyperpolarization sustained by H- and CaLVA-currents. Moreover, the model predicted that H- and TRP-current regulation was necessary and sufficient to generate the LOR and its dependence on the intensity and duration of mossy fiber activity. Therefore, the model showed that, using a basic set of ionic channels, UBCs generate a rich repertoire of bursts, which could effectively implement tunable delay-lines in the local microcircuit. © 2014 Subramaniyam, Solinas, Perin, Locatelli, Masetto and D'Angelo.


Mapelli J.,University of Pavia | Mapelli J.,Consorzio Interuniversitario per le Science Fisiche della Materia | Gandolfi D.,University of Pavia | Gandolfi D.,Consorzio Interuniversitario per le Science Fisiche della Materia | D'Angelo E.,University of Pavia
Frontiers in Cellular Neuroscience | Year: 2010

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 ~50 Hz and the overlaying molecular layer above ~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. © 2010 Mapelli, Gandolfi and D'Angelo.


D'Angelo E.,University of Pavia | D'Angelo E.,Consorzio Interuniversitario per le Science Fisiche della Materia
Journal of Integrative Neuroscience | Year: 2011

The rapid growth of cerebellar research is going to clarify several aspects of cellular and circuit physiology. However, the concepts about cerebellar mechanisms of function are still largely related to clinical observations and to models elaborated before the last discoveries appeared. In this paper, the major issues are revisited, suggesting that previous concepts can now be refined and modified. The cerebellum is fundamentally involved in timing and in controlling the ordered and precise execution of motor sequences. The fast reaction of the cerebellum to the inputs is sustained by specific cellular mechanisms ensuring precision on the millisecond scale. These include burstburst reconversion in the granular layer and instantaneous frequency modulation on the 100-Hz band in Purkinje and deep cerebellar nuclei cells. Precisely timed signals can be used for perceptron operations in Purkinje cells and to establish appropriate correlations with climbing fiber signals inducing learning at parallel fiber synapses. In the granular layer, plasticity turns out to be instrumental to timing, providing a conceptual solution to the discrepancy between cerebellar learning and timing. The granular layer sub-circuit can be tuned by long-term synaptic plasticity and synaptic inhibition to delay the incoming signals over a 100-ms range. For longer sequences, large circuit sections can be entrained into coherent activity in 100-ms cycles. These dynamic aspects, which have not been accounted for by original theories, could in fact represent the essence of cerebellar functioning. It is suggested that the cerebellum can, in this way, operate the realignment of temporally incongruent signals, allowing their binding and pattern recognition in Purkinje cells. The demonstration of these principles, their behavioral relevance and their relationship with internal model theories represent a challenge for future cerebellar research. © 2011 Imperial College Press.


Politano A.,University of Calabria | Politano A.,Autonomous University of Madrid | Marino A.R.,University of Calabria | Chiarello G.,University of Calabria | Chiarello G.,Consorzio Interuniversitario per le Science Fisiche della Materia
Journal of Chemical Physics | Year: 2010

High-resolution electron energy loss spectroscopy was used to study the coadsorption of alkali metals (Na, K) and oxygen on clean and CO-modified Ni(111) surfaces. We unambiguously show that on an alkali-precovered surface, the alkali-O bond was not formed upon O2 exposure. On the contrary, the alkali-O bond was readily observed by exposing to O2 the Ni(111) surface precovered with an alkali+CO phase. This enhanced oxidation rate of alkali metals in the presence of CO molecules was ascribed to the short-range CO-induced modification of the electronic charge of alkali-metal adatoms. © 2010 American Institute of Physics.


Tolu S.,University of Granada | Vanegas M.,University of Genoa | Luque N.R.,University of Granada | Garrido J.A.,Consorzio Interuniversitario per le Science Fisiche della Materia | Ros E.,University of Granada
Biological Cybernetics | Year: 2012

This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of themachine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs). © Springer-Verlag 2012.


Tolu S.,University of Granada | Vanegas M.,University of Genoa | Garrido J.A.,Consorzio Interuniversitario per le Science Fisiche della Materia | Luque N.R.,University of Granada | Ros E.,University of Granada
International Journal of Neural Systems | Year: 2013

In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs). © 2013 World Scientific Publishing Company.


Alfinito E.,University of Salento | Alfinito E.,Consorzio Interuniversitario per le Science Fisiche della Materia | Reggiani L.,Consorzio Interuniversitario per le Science Fisiche della Materia | Reggiani L.,University of Salento
Journal of Physics Condensed Matter | Year: 2013

By considering a set of experiments carried out on bacteriorhodopsin in vitro by Casuso et al (2007 Phys. Rev. E 76 041919), we extract the conductance as function of the applied voltage. The microscopic interpretation of experiments shows that charge transfer is ruled by a direct tunneling (DT) mechanism at low bias and by a Fowler-Nordheim (FN) tunneling mechanism at high bias. A nucleation region at the cross-over between the DT and FN regimes can be identified. A theoretical analysis of conductance fluctuations is performed by calculating the corresponding variance and the probability density functions (PDFs): these constitute a powerful indicator in order to understand the internal dynamics of the system. Conductance fluctuations are non-Gaussian and follow well the standard generalized Gumbel distributions G(a). In particular, at low bias, the PDFs are bimodal and can be resolved in at least a couple of G(a) functions with different values of the shape parameter a. The nucleation region is characterized by a single Gumbel distribution, G(1). At increasing bias, the G(1) distribution turns in a bimodal distribution. We discuss possible correlations between the voltage dependence of the G(a) and the microscopic mechanisms that determine the electrical response of the system. © 2013 IOP Publishing Ltd.

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