
Javier G Orlandi- PhD
- Researcher at RIKEN
Javier G Orlandi
- PhD
- Researcher at RIKEN
About
29
Publications
4,460
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625
Citations
Introduction
Current institution
Additional affiliations
February 2019 - present
August 2016 - December 2018
October 2015 - July 2016
Publications
Publications (29)
Neuronal dynamics are fundamentally constrained by the underlying structural
network architecture, yet much of the details of this synaptic connectivity are
still unknown even in neuronal cultures in vitro. Here we extend a previous
approach based on information theory, the Generalized Transfer Entropy, to the
reconstruction of connectivity of simu...
At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining hi...
Choice information appears in multi-area brain networks mixed with sensory, motor, and cognitive variables. In the posterior cortex—traditionally implicated in decision computations—the presence, strength, and area specificity of choice signals are highly variable, limiting a cohesive understanding of their computational significance. Examining the...
Choice information appears in the brain as distributed signals with top-down and bottom-up components that together support decision-making computations. In sensory and associative cortical regions, the presence of choice signals, their strength, and area specificity are known to be elusive and changeable, limiting a cohesive understanding of their...
Choice information appears in the brain as distributed signals with top-down and bottom-up components that together support decision-making computations. In sensory and associative cortical regions, the presence of choice signals, their strength, and area specificity are known to be elusive and changeable, limiting a cohesive understanding of their...
Recent experiments have shown that the spontaneous activity of young dissociated neuronal cultures can be described as a process of highly inhomogeneous nucleation and front propagation due to the localization of noise activity, i.e., noise focusing. However, the basic understanding of the mechanisms of noise build-up leading to the nucleation rema...
Human pluripotent stem cells (hPSCs) are a powerful tool for modelling human development. In recent years, hPSCs have become central in cell-based therapies for neurodegenerative diseases given their potential to replace affected neurons. However, directing hPSCs into specific neuronal types is complex and requires an accurate protocol that mimics...
Background:
Network alterations underlying neurodegenerative diseases often precede symptoms and functional deficits. Thus, their early identification is central for improved prognosis. In Huntington's disease (HD), the cortico-striatal networks, involved in motor function processing, are the most compromised neural substrate. However, whether the...
Brownian ratchets are shown to feature a nontrivial vanishing-noise limit where the dynamics is reduced to a stochastic alternation between two deterministic circle maps (quasi-deterministic ratchets). Motivated by cooperative dynamics of molecular motors, here we solve exactly the problem of two interacting quasi-deterministic ratchets. We show th...
Many infectious processes, such as human diseases or computer viruses, spread across complex networks following directed links. While in some cases there exists a clear separation of timescales between the propagation of one outbreak and the initiation of the next, there are also processes for which this is not the case, such as zoonotic diseases....
Within the classical eye-blink conditioning, Purkinje cells within the cerebellum are known to suppress their tonic firing rates for a well defined time period in response to the conditional stimulus after training. The temporal profile of the drop in tonic firing rate, i.e., the onset and the duration, depend upon the time interval between the ons...
We studied effective connectivity in rat cortical cultures with various degrees of spatial aggregation, ranging from homogeneous networks to highly aggregated ones. We considered small cultures 3 mm in diameter and that contained about 2000 neurons. Spatial inhomogeneity favored an increase of metric correlations and connectivity among neighboring...
Neuronal avalanches have become an ubiquitous tool to describe the activity of large neuronal assemblies. The emergence of scale-free statistics with well-defined exponents has led to the belief that the brain might operate near a critical point. Yet not much is known in terms of how the different exponents arise or how robust they are. Using calci...
Huntington's disease (HD) is a fatal neurodegenerative disease with motor, cognitive and psychiatric impairment. Dysfunctions in HD models have been related to reduced levels of striatal brain-derived neurotrophic factor (BDNF) and imbalance between its receptors TrkB and p75(NTR). Thus, molecules with activity on the BDNF/TrkB/p75 system can have...
We introduce a novel random field Ising model, grounded on experimental observations, to assess the importance of metric correlations in cortical circuits in vitro. Metric correlations arise from both the finite axonal length and the heterogeneity in the spatial arrangement of neurons. The experiments consider the response of neuronal cultures to a...
We organized a Challenge to unravel the connectivity of simulated neuronal networks. The provided data was solely based on fluorescence time series of spontaneous activity in a network constituted by 1000 neurons. The task of the participants was to compute the effective connectivity between neurons, with the goal to reconstruct as accurately as po...
We introduce a coarse-grained stochastic model for the spontaneous activity of neuronal cultures to explain the phenomenon of noise focusing, which entails localization of the noise activity in excitable networks with metric correlations. The system is modeled as a continuum excitable medium with a state-dependent spatial coupling that accounts for...
This book illustrates the thrust of the scientific community to use machine learning concepts for tackling a complex problem: given time series of neuronal spontaneous activity, which is the underlying connectivity between the neurons in the network? The contributing authors also develop tools for the advancement of neuroscience through machine lea...
Induced pluripotent stem cell (iPSC) technology has been successfully used to recapitulate phenotypic traits of several human diseases in vitro. Patient-specific iPSC-based disease models are also expected to reveal early functional phenotypes, although this remains to be proved. Here, we generated iPSC lines from two patients with Sanfilippo type...
We organized a Challenge to unravel the connectivity of a simulated neuronal networks. The provided data were solely based on fluorescence time series of spontaneous activity in a network constituted by 1000 neurons. The task of the participants was to compute the effective connectivity between neurons, with the goal to approach as accurately as po...
We are organizing a challenge to reverse engineer the structure of neuronal networks from patterns of activity recorded with calcium fluorescence imaging. Unraveling the brain structure at the neuronal level at a large scale is an important step in brain science, with many ramifications in the comprehension of animal and human intelligence and lear...
Cultured neurons in vitro quickly connect to one another to establish a spontaneously active network within a week. The resulting neuronal network is characterized by a combination of excitatory and inhibitory integrate–and–fire units coupled through synaptic connections , and that interact in a highly nonlinear manner. The nonlinear behavior emerg...
There is a growing interest in reconstructing the structural connectivity of a neuronal circuit based on observing its activity. This would allow for the study of bulk network properties, like the degree distribution or the clustering index, as well as facilitate a better understanding of neuronal function.
In particular, a causality measure calle...
In vitro
neuronal networks of dissociated hippocampal or cortical tissues are one of the most attractive model systems for the physics and neuroscience communities. Cultured neurons grow and mature, develop axons and dendrites, and quickly connect to their neighbors to establish a spontaneously active network within a week. The resulting neuronal...
We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state...
We study channel transport across biomembranes. We propose a model that couples the diffusive dynamics with the gating process via a two-state ratchet mechanism. This gating process is governed by ATP binding and hydrolysis, and the process exhibits Michaelis-Menten enzymatic kinetics. The particle flow and permeability of the channel are studied b...
Màster en Biofísica Part I, curs 2007-2008. Part II la trobareu a: http://hdl.handle.net/2445/6722 We explore biological transport across membrane channels from a physical point of view. The main objective is to use the tools available to a physicist from non-equilibrium thermodynamics and apply them to a concrete biological problem. In this case,...
Màster en Biofísica Part II, 2008-2009. Part I la trobareu a: http://hdl.handle.net/2445/5801 We explore biological transport across membrane channels from a physical point of view. The main objective is to use the tools available to a physicist from non-equilibrium thermodynamics and apply them to a concrete biological problem. In this case, we fo...