1,721,022 research outputs found
Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations
No full textSeveral neuron types have been shown to exhibit (subthreshold) membrane potential resonance (MPR), defined as the occurrence of a peak in their voltage amplitude response to oscillatory input currents at a preferred (resonant) frequency. MPR has been investigated both experimentally and theoretically. However, whether MPR is simply an epiphenomenon or it plays a functional role for the generation of neuronal network oscillations and how the latent time scales present in individual, non-oscillatory cells affect the properties of the oscillatory networks in which they are embedded are open questions. We address these issues by investigating a minimal network model consisting of (i) a non-oscillatory linear resonator (band-pass filter) with 2D dynamics, (ii) a passive cell (low-pass filter) with 1D linear dynamics, and (iii) nonlinear graded synaptic connections (excitatory or inhibitory) with instantaneous dynamics. We demonstrate that (i) the network oscillations crucially depend on the presence of MPR in the resonator, (ii) they are amplified by the network connectivity, (iii) they develop relaxation oscillations for high enough levels of mutual inhibition/excitation, and (iv) the network frequency monotonically depends on the resonators resonant frequency. We explain these phenomena using a reduced adapted version of the classical phase-plane analysis that helps uncovering the type of effective network nonlinearities that contribute to the generation of network oscillations. We extend our results to networks having cells with 2D dynamics. Our results have direct implications for network models of firing rate type and other biological oscillatory networks (e.g, biochemical, genetic).Fil: Bel, Andrea Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: Rotstein, Horacio. New Jersey Institute of Technology; Estados Unidos. Rutgers University; Estados Unido
Bifurcaciones de equilibrios en un modelo no diferenciable para redes competitivas
Get PDFEn este trabajo estudiamos las propiedades de un modelo de redes neuronales conocido como modelocompetitivo lineal por sectores. Nos enfocamos en el caso más sencillo en el que el modelo puede exhibir oscilacionesgeneradas por un ciclo lı́mite: tres nodos interconectados. La presencia de este tipo de no-linealidades relativamentesimples le otorga a la red la capacidad de producir una dinámica compleja, pero a su vez matemáticamente tratable.Fil: Bel, Andrea Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Matemática; ArgentinaFil: Reartes, Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Matemática; ArgentinaFil: Rotstein, Horacio G.. New Jersey Institute of Technology; Estados UnidosCongreso de MAtemática Aplicada, Computacional e IndustrialComodoro RivadaviaArgentinaUniversidad Nacional de la Patagonia San Juan BoscoAsociación Argentina de Matemática Aplicada, Computacional e Industria
Periodic Solutions in Threshold-Linear Networks and Their Entrainment
No full textThreshold-linear networks (TLNs) are recurrent networks where the dynamics are threshold-linear (linearly rectified at zero). Mathematically, they consist of coupled nonsmooth ordinary differential equations. When the nodes in the network are assumed to be neurons or neuronal populations, TLNs represent firing rate models. We investigate the dynamics of a subclass of TLNs referred to as competitive TLNs where all the connections between different nodes are inhibitory. We prove the existence of periodic solutions in competitive TLNs with three nodes using a combination of mathematical analysis and numerical simulations. We calculate the analytical expressions of the periodic solutions, then we consider a reduced system of transcendental equations and apply a Kantorovich's convergence result to demonstrate the existence of these solutions. We then analyze the attributes (frequency and amplitude) of these periodic solutions as the model parameters vary. Finally, we study the entrainment properties of competitive TLNs in the oscillatory regime, by examining their response to external periodic inputs to one of the nodes in the network. We numerically determine the ranges of input amplitudes and frequencies for which competitive TLNs are able to follow the periodic input for three-node networks and larger networks with cyclic symmetry.Fil: Bel, Andrea Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: Cobiaga, Romina Pamela. Universidad Nacional del Sur. Departamento de Matemática; ArgentinaFil: Reartes, Walter. Universidad Nacional del Sur. Departamento de Matemática; ArgentinaFil: Rotstein, Horacio. Universidad Nacional del Sur. Departamento de Matemática; Argentina. New Jersey Institute of Technology; Estados Unidos. Rutgers University; Estados Unido
Feedback signal from motoneurons influences a rhythmic pattern generator
Get PDFMotoneurons are not mere output units of neuronal circuits that control motor behavior but participate in pattern generation. Research on the circuit that controls the crawling motor behavior in leeches indicated that motoneurons participate as modulators of this rhythmic motor pattern. Crawling results from successive bouts of elongation and contraction of the whole leech body. In the isolated segmental ganglia, dopamine can induce a rhythmic antiphasic activity of the motoneurons that control contraction (DE-3 motoneurons) and elongation (CV motoneurons). The study was performed in isolated ganglia where manipulation of the activity of specific motoneurons was performed in the course of fictive crawling (crawling). In this study, the membrane potential of CV was manipulated while crawling was monitored through the rhythmic activity of DE-3. Matching behavioral observations that show that elongation dominates the rhythmic pattern, the electrophysiological activity of CV motoneurons dominates the cycle. Brief excitation of CV motoneurons during crawling episodes resets the rhythmic activity of DE-3, indicating that CV feeds back to the rhythmic pattern generator. CV hyperpolarization accelerated the rhythm to an extent that depended on the magnitude of the cycle period, suggesting that CV exerted a positive feedback on the unit(s) of the pattern generator that controls the elongation phase. A simple computational model was implemented to test the consequences of such feedback. The simulations indicate that the duty cycle of CV depended on the strength of the positive feedback between CV and the pattern generator circuit.Fil: Rotstein, Horacio. New Jersey Institute of Technology; Estados UnidosFil: Schneider, Elisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Fisiología, Biología Molecular y Celular; ArgentinaFil: Szczupak, Lidia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Fisiología, Biología Molecular y Celular; Argentin
Frequency filter interactions in network of non-oscillatory cells
No full textResonance refers to the ability of dynamical systems to exhibit a peak in their amplitude response to oscillatory inputs at a preferred (resonant) frequency. In neuronal cir- cuits, resonance is typically measured by using the imped- ance amplitude profile Z defined as the absolute value of the quotient of the Fourier transforms of the output and the input. Resonance has been investigated in single neurons by many authors both experimentally and theoretically (Cichon & Gan, 2015 Apr; Sajikumar et al., 2014 Aug 19). Network resonance has received much less attention. Two important questions are (i) whether and under what condi- tions a network of neurons exhibits resonance in one or more neurons in response to inputs to one or more neurons, and (ii) whether and under what conditions the information is communicated between neurons in a frequency-dependent manner. In this project we address these issues by using a minimal network consisting of two passive cells (linear, non-reso- nant neurons) recurrently connected via graded synaptic inhibition or excitation and receiving oscillatory inputs in either one or the two nodes (Sezener et al., 2021). In order to investigate how network resonance emerges we extend the concept of impedance to nonlinear systems by comput- ing the peak-to-trough amplitudes normalized by the input amplitude. In order to investigate the communication of frequency-dependent information across neurons in the network we borrow the concept of the coupling coefficient from the gap junction literature. The coupling coefficient K, defined as the quotient between the postsynaptic and pre- synaptic membrane potentials of two electrically coupled neurons, is used to measure the strength of the connection in the presence of constant (DC) inputs. Here we extend this metrics to synaptically connected neurons and to the fre- quency domain. Linear networks (linear neurons and linear connectivity) can only show a low-pass filter K profile (K as a function of the input frequency). We show that the pres- ence of the more realistic nonlinear synaptic connectivity can produce band-pass K profiles. We note that the concept of communication of information we use here is different than the standard one used in information theory.Fil: Bel, Andrea Liliana. Universidad Nacional del Sur. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Unidad de Dirección. Comunicación Institucional; ArgentinaFil: Rotstein, Horacio G.. New Jersey Institute of Technology; Estados Unidos. Rutgers University; Estados Unidos30th Annual Computational Neuroscience MeetingMichiganEstados UnidosOrganization for Computational Neuroscience
Entrainment of competitive threshold-linear networks
No full textNeuronal oscillations are ubiquitous in the brain and emerge from the combined activity of the participating neurons (or nodes), the connec- tivity and the network topology. Recent neurotechnological advances have made it possible to interrogate neuronal circuits by perturbing one or more of its nodes. The response to periodic inputs has been used as a tool to identify the oscillatory properties of circuits and the flow of information in networks. However, a general theory that explains the underlying mechanisms and allows to make predictions is lacking beyond the single neuron level. Threshold-linear network (TLN) models describe the activity of con- nected nodes where the contribution of the connectivity terms is lin- ear above some threshold value (typically zero), while the network is disconnected below it. In their simplest description, the dynamics of the individual nodes are one-dimensional and linear. When the nodes in the network are neurons or neuronal populations, their activity can be interpreted as the firing rate, and therefore the TLNs represent fir- ing rate models [1]. Competitive threshold-linear networks (CTLNs) are a class of TLNs where the connectivity weights are all negative and there are no self- connections [2,3]. Inhibitory networks arise in many neuronal systems and have been shown to underlie the generation of rhythmic activity in cognition and motor behavior [4,5]. Despite their simplicity, TLNs and CTLNs produce complex behavior including multistability, peri- odic, quasi-periodic and chaotic solutions [2,3,6]. In this work, we consider CTLNs with three or more nodes and cyclic symmetry in which oscillatory solutions are observed. We first assume that an external oscillatory input is added to one of the nodes and, by defining a Poincaré map, we numerically study the response proper- ties of the CTLN networks. We determine the ranges of input ampli- tude and frequency in which the CTLN is able to follow the input (1:1 entrainment). For this we define local and global entrainment measures that convey different information. We then study how the entrainment properties of the CTLNs is affected by changes in (i) the time scale of each node, (ii) the number of nodes in the network, and (iii) the strength of the inhibitory connections. Finally, we extend our results to include other entrainment scenarios (e.g., 2:1) and other net- work topologies.Fil: Bel, Andrea Liliana. Universidad Nacional del Sur. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Unidad de Direccion; ArgentinaFil: Rotstein, Horacio. New Jersey Institute of Technology; Estados Unidos. Rutgers University; Estados UnidosFil: Reartes, Walter A.. Universidad Nacional del Sur. Departamento de Matemática; Argentina29th Annual Computacional Neuroscience MeetingOnlineEstados UnidosOrganization for Computational Neuroscience
Complex patterns in networks of hyperexcitable neurons
Get PDFComplex patterns in neuronal networks emerge from the cooperative activity of the participating neurons, synaptic connectivity and network topology. Several neuron types exhibit complex intrinsic dynamics due to the presence of nonlinearities and multiple time scales. In this paper we extend previous work on hyperexcitability of neuronal networks, a hallmark of epileptic brain seizure generation, which results from the net imbalance between excitation and inhibition and the ability of certain neuron types to exhibit abrupt transitions between low and high firing frequency regimes as the levels of recurrent AMPA excitation change. We examine the effect of different topologies and connection delays on the hyperexcitability phenomenon in networks having recurrent synaptic AMPA (fast) excitation (in the absence of synaptic inhibition) and demonstrate the emergence of additional time scales.Fil: Schindewolf, Craig. New Jersey Institute of Technology; Estados UnidosFil: Kim, Dongwook. New Jersey Institute of Technology; Estados UnidosFil: Bel, Andrea Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Matemática; ArgentinaFil: Rotstein, Horacio. New Jersey Institute of Technology; Estados Unido
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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