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Search Results: 1 - 10 of 6124 matches for " Stefano Panzeri "
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The C = 1 Matrix Model Formulation of Two Dimensional Yang-Mills Theories
Stefano Panzeri
Physics , 1993, DOI: 10.1142/S0217732393002130
Abstract: We find the exact matrix model description of two dimensional Yang-Mills theories on a cylinder or on a torus and with an arbitrary compact gauge group. This matrix model is the singlet sector of a $c =1$ matrix model where the matrix field is in the fundamental representation of the gauge group. We also prove that the basic constituents of the theory are Sutherland fermions in the zero coupling limit, and this leads to an interesting connection between two dimensional gauge theories and one dimensional integrable systems. In particular we derive for all the classical groups the exact grand canonical partition function of the free fermion system corresponding to a two dimensional gauge theory on a torus.
Algorithms of causal inference for the analysis of effective connectivity among brain regions
Daniel Chicharro,Stefano Panzeri
Frontiers in Neuroinformatics , 2014, DOI: 10.3389/fninf.2014.00064
Abstract: In recent years, powerful general algorithms of causal inference have been developed. In particular, in the framework of Pearl’s causality, algorithms of inductive causation (IC and IC*) provide a procedure to determine which causal connections among nodes in a network can be inferred from empirical observations even in the presence of latent variables, indicating the limits of what can be learned without active manipulation of the system. These algorithms can in principle become important complements to established techniques such as Granger causality and Dynamic Causal Modeling (DCM) to analyze causal influences (effective connectivity) among brain regions. However, their application to dynamic processes has not been yet examined. Here we study how to apply these algorithms to time-varying signals such as electrophysiological or neuroimaging signals. We propose a new algorithm which combines the basic principles of the previous algorithms with Granger causality to obtain a representation of the causal relations suited to dynamic processes. Furthermore, we use graphical criteria to predict dynamic statistical dependencies between the signals from the causal structure. We show how some problems for causal inference from neural signals (e.g. measurement noise, hemodynamic responses, and time aggregation) can be understood in a general graphical approach. Focusing on the effect of spatial aggregation, we show that when causal inference is performed at a coarser scale than the one at which the neural sources interact, results strongly depend on the degree of integration of the neural sources aggregated in the signals, and thus characterize more the intra-areal properties than the interactions among regions. We finally discuss how the explicit consideration of latent processes contributes to understand Granger causality and DCM as well as to distinguish functional and effective connectivity.
Information carried by population spike times in the whisker sensory cortex can be decoded without knowledge of stimulus time
Stefano Panzeri,Mathew E. Diamond
Frontiers in Synaptic Neuroscience , 2010, DOI: 10.3389/fnsyn.2010.00017
Abstract: Computational analyses have revealed that precisely timed spikes emitted by somatosensory cortical neuronal populations encode basic stimulus features in the rat’s whisker sensory system. Efficient spike time based decoding schemes both for the spatial location of a stimulus and for the kinetic features of complex whisker movements have been defined. To date, these decoding schemes have been based upon spike times referenced to an external temporal frame – the time of the stimulus itself. Such schemes are limited by the requirement of precise knowledge of the stimulus time signal, and it is not clear whether stimulus times are known to rats making sensory judgments. Here, we first review studies of the information obtained from spike timing referenced to the stimulus time. Then we explore new methods for extracting spike train information independently of any external temporal reference frame. These proposed methods are based on the detection of stimulus-dependent differences in the firing time within a neuronal population. We apply them to a data set using single-whisker stimulation in anesthetized rats and find that stimulus site can be decoded based on the millisecond-range relative differences in spike times even without knowledge of stimulus time. If spike counts alone are measured over tens or hundreds of milliseconds rather than milliseconds, such decoders are much less effective. These results suggest that decoding schemes based on millisecond-precise spike times are likely to subserve robust and information-rich transmission of information in the somatosensory system.
Temporal correlations and neural spike train entropy
Simon R. Schultz,Stefano Panzeri
Physics , 2000, DOI: 10.1103/PhysRevLett.86.5823
Abstract: Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight upon the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower RMS error information estimates in comparison to a `brute force' approach.
The complexity of dynamics in small neural circuits
Diego Fasoli,Anna Cattani,Stefano Panzeri
Quantitative Biology , 2015,
Abstract: Mean-field theory is a powerful tool for studying large neural networks. However, when the system is composed of a few neurons, macroscopic differences between the mean-field approximation and the real behavior of the network can arise. Here we introduce a study of the dynamics of a small firing-rate network with excitatory and inhibitory populations, in terms of local and global bifurcations of the neural activity. Our approach is analytically tractable in many respects, and sheds new light on the finite-size effects of the system. In particular, we focus on the formation of multiple branching solutions of the neural equations through spontaneous symmetry-breaking, since this phenomenon increases considerably the complexity of the dynamical behavior of the network. For these reasons, branching points may reveal important mechanisms through which neurons interact and process information, which are not accounted for by the mean-field approximation.
The information content of Local Field Potentials: experiments and models
Alberto Mazzoni,Nikos K. Logothetis,Stefano Panzeri
Quantitative Biology , 2012,
Abstract: The LFPs is a broadband signal that captures variations of neural population activity over a wide range of time scales. The range of time scales available in LFPs is particularly interesting from the neural coding point of view because it opens up the possibility to investigate whether there are privileged time scales for information processing, a question that has been hotly debated over the last one or two decades.It is possible that information is represented by only a small number of specific frequency ranges, each carrying a separate contribution to the information representation. To shed light on this issue, it is important to quantify the information content of each frequency range of neural activity, and understand which ranges carry complementary or similar information.
Phase-of-firing code
Anna Cattani,Gaute T. Einevoll,Stefano Panzeri
Quantitative Biology , 2015,
Abstract: Definition. The phase-of-firing code is a neural coding scheme whereby neurons encode information using the time at which they fire spikes within a cycle of the ongoing oscillatory pattern of network activity. This coding scheme may allow neurons to use their temporal pattern of spikes to encode information that is not encoded in their firing rate.
Analysis of Slow (Theta) Oscillations as a Potential Temporal Reference Frame for Information Coding in Sensory Cortices
Christoph Kayser ,Robin A. A. Ince,Stefano Panzeri
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002717
Abstract: While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons
Alberto Mazzoni ,Stefano Panzeri,Nikos K. Logothetis,Nicolas Brunel
PLOS Computational Biology , 2008, DOI: 10.1371/journal.pcbi.1000239
Abstract: Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory–excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus–neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment.
Clinical results of the Harris-Galante cup implanted from 1986 to 1991
Antonio Croce,Emilio Mazza,Stefano Lucchina,Andrea Panzeri,Simone Gatti
Journal of Orthopaedics and Traumatology , 2000, DOI: 10.1007/s101950070014
Abstract: In the period 1986–1991, we performed 370 consecutive total hip arthroplasties (THA) using the Harris-Galante porus coated prosthesis. The characteristics of this component are: a fiber-mesh coating in pure Ti alloy that stimulates osteoinduction, a process of fusion of fiber-mesh to the metal back that reduces potential damage to the microstructure of the fibers with consequently less resistance to fatigue and a better primary stability guaranteed by fixation screws that stimulate osteoconduction. The average follow-up was 11.5 years. The follow-up was performed through a roentgenographic control at 3, 6 and 12 months and then once a year. Mineralometric evaluation with a Hoxologic QDR apparatus [1,2] permitted quantitative examination of the periprosthetic bonestock. A questionnaire was administered to examine the characteristics of pain and the ability to perform daily activities, to go upstairs, to walk distances, to sit the down and to put on socks and shoes. We found no vascular complications because of the use of Ti screws; the cup, after a primary fixation, ran into osteointegration in most cases. We did not find any aseptic loosening due to the inadequate primary press-fit or to screw breaking. We did not find any periprosthetic bone loss due to the migration of Ultra High Molecular Weight Polyethylene (UHMWPE) wear particles from holes of the shell. When aseptic loosening of the femoral stem and UHMWPE wear particle formation did occur, the metal back was perfectiyl osteointegrated and we only had to substitute the insert. The results are clinically interesting considering the long-term follow-up, the large number of patients and, technically, the type of fixation (line-to-line without press-fit), the semplicity of assembly of UHMWPE without any bone loss around the cup, the good fixation of cups even if badly implanted because of other difficulties in impanting them or for a wrong technique. In our opinion, our choice of implanting HG1 cups line-to-line was successful 10–15 years later.
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