Fluctuations and information filtering in coupled populations of spiking neurons with adaptation

Finite-sized populations of spiking elements are fundamental to brain function, but also used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasi-renewal description of neurons with adaptation. We derive an integral equation with colored noise that governs the stochastic dynamics of the population activity in response to time-dependent stimulation and calculate the spectral density in the asynchronous state. We show that systems of coupled populations with adaptation can generate a frequency band in which sensory information is preferentially encoded. The theory is applicable to fully as well as randomly connected networks, and to leaky integrate-and-fire as well as to generalized spiking neurons with adaptation on multiple time scales

Cogentrification sociale et économique : La colocalisation de la main-d’oeuvre et des emplois de services aux entreprises à Montréal, 1996-2001

Plusieurs études se sont penchées sur l’évolution de la localisation des emplois de services aux entreprises. Une hypothèse qui n’a pas encore été pleinement explorée est celle selon laquelle ce secteur chercherait à s’implanter à proximité des quartiers résidentiels où réside sa main-d’oeuvre. Notre étude démontre qu’il semble effectivement y avoir une certaine colocalisation, mais que celle-ci affecte principalement la main-d’oeuvre résidant à proximité du centre-ville. Ici, on trouve que les nouveaux emplois de services aux entreprises tendent à se localiser à proximité des quartiers déjà habités par leurs employés. Ceci nous permet d’avancer l’hypothèse d’une cogentrification : d’abord résidentielle, alors que certains professionnels se sont, depuis une vingtaine d’années, réapproprié des quartiers péricentraux de Montréal. Ensuite économique, tandis que les emplois de bureau en services aux entreprises se sont localisés vers ces mêmes quartiers.Many studies are currently investigating the localization of business services jobs and its development. One hypothesis, which has been insufficiently researched to date, is that this sector tends to locate in the vicinity of residential neighbourhoods where its workforce lives. This study demonstrates that though colocalization does exist to some extent, it mainly affects workers living close to the downtown area. It has been discovered that new business services jobs tend to locate in close proximity to areas already inhabited by employees in the business services sector. We can therefore hypothesize that cogentrification is primarily residential. A number of professional workers have returned to live in Montreal’s pericentral neighbourhoods over the past twenty years. Cogentrification is also economic, insofar as business services office jobs have gravitated toward these same areas during the same period

Silences, Spikes and Bursts: Three-Part Knot of the Neural Code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labeling action potentials emitted at a particularly high frequency with a metonym -- bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.Comment: 15 pages, 4 figure

The Dynamics of Adapting Neurons

How do neurons dynamically encode and treat information? Each neuron communicates with its distinctive language made of long silences intermitted by occasional spikes. The spikes are prompted by the pooled effect of a population of pre-synaptic neurons. To understand the operation made by single neurons is to create a quantitative description of their dynamics. The results presented in this thesis describe the necessary elements for a quantitative description of single neurons. Almost all chapters can be unified under the theme of adaptation. Neuronal adaptation plays an important role in the transduction of a given stimulation into a spike train. The work described here shows how adaptation is brought by every spike in a stereotypical fashion. The spike-triggered adaptation is then measured in three main types of cortical neurons. I analyze in detail how the different adaptation profiles can reproduce the diversity of firing patterns observed in real neurons. I also summarize the most recent results concerning the spike-time prediction in real neurons, resulting in a well-founded single-neuron model. This model is then analyzed to understand how populations can encode time-dependent signals and how time-dependent signals can be decoded from the activity of populations. Finally, two lines of investigation in progress are described, the first expands the study of spike-triggered adaptation on longer time scales and the second extends the quantitative neuron models to models with active dendrites

Développement d’un modèle par éléments finis anisotrope pour une simulation réaliste de l’alliage de AA6082 extrudé

L’alliage d’aluminium AA6082-T6 extrudé présente des propriétés mécaniques intéressantes pour utilisation dans les boîtes-tampons (crash box) de véhicules automobiles. Cependant, cet alliage possède des propriétés mécaniques fortement anisotropes, ce qui rend la simulation difficile. En collaboration avec le Centre des Technologies de l’Aluminium du Saguenay (CNRC-CTA), ce projet vise à modéliser par éléments finis le comportement mécanique anisotrope du AA6082-T6 lors d’essais d’écrasement. Dans un premier temps, les paramètres d’anisotropie du matériau sont établis par différents essais mécaniques. Par la suite, une loi de comportement anisotrope est développée afin de représenter l’anisotropie du matériau. Ensuite, des simulations d’essais de traction par éléments finis sont réalisées pour démontrer que la loi représente bien l’anisotropie. Finalement, des simulations d’essais d’écrasement de tube sont réalisées afin d'évaluer l’amélioration obtenue en tenant compte de l’anisotropie

Firing patterns in the adaptive exponential integrate-and-fire model

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulation

Firing patterns in the adaptive exponential integrate-and-fire model

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations

How Good are Neuron Models?

Opinions strongly diverge on what constitutes a good model of a neuron. Two lines of thought on this have coexisted for a long time: detailed biophysical models (of the style proposed in 1952 by the physiologists Alan Hodgkin and Andrew Huxley) that describe ion channels on the tree-like spatial structure of the neuronal cell, and simple "integrate-and-fire" models based on the much older insight that pulsatile electrical activity (known as an action potential or spike) is a threshold process. Electrophysiologists generally prefer the biophysical models, familiar with the notion of ion channels that open and close (and hence, alter neuronal activity) depending on environmental conditions. Theoreticians, by contrast, typically prefer simple neuron models with few parameters that are amenable to mathematical analysis. Earlier this year, following previous attempts at model comparison on a smaller scale, the International Neuroinformatics Coordinating Facility (INCF) launched an international competition that allowed a quantitative comparison of neuron models