118 research outputs found
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 Ă©conomique : La colocalisation de la main-dâoeuvre et des emplois de services aux entreprises Ă MontrĂ©al, 1996-2001
Plusieurs Ă©tudes se sont penchĂ©es sur lâĂ©volution de la localisation des emplois de services aux entreprises. Une hypothĂšse qui nâa pas encore Ă©tĂ© pleinement explorĂ©e est celle selon laquelle ce secteur chercherait Ă sâimplanter Ă proximitĂ© des quartiers rĂ©sidentiels oĂč rĂ©side sa main-dâoeuvre. Notre Ă©tude dĂ©montre quâil semble effectivement y avoir une certaine colocalisation, mais que celle-ci affecte principalement la main-dâoeuvre rĂ©sidant Ă proximitĂ© du centre-ville. Ici, on trouve que les nouveaux emplois de services aux entreprises tendent Ă se localiser Ă proximitĂ© des quartiers dĂ©jĂ habitĂ©s par leurs employĂ©s. Ceci nous permet dâavancer lâhypothĂšse dâune cogentrification : dâabord rĂ©sidentielle, alors que certains professionnels se sont, depuis une vingtaine dâannĂ©es, rĂ©appropriĂ© des quartiers pĂ©ricentraux de MontrĂ©al. Ensuite Ă©conomique, tandis que les emplois de bureau en services aux entreprises se sont localisĂ©s vers ces mĂȘmes 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 Montrealâs 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
DĂ©veloppement dâun modĂšle par Ă©lĂ©ments finis anisotrope pour une simulation rĂ©aliste de lâalliage de AA6082 extrudĂ©
Lâalliage dâaluminium AA6082-T6 extrudĂ© prĂ©sente des propriĂ©tĂ©s mĂ©caniques intĂ©ressantes pour utilisation dans les boĂźtes-tampons (crash box) de vĂ©hicules automobiles. Cependant, cet alliage possĂšde des propriĂ©tĂ©s mĂ©caniques fortement anisotropes, ce qui rend la simulation difficile. En collaboration avec le Centre des Technologies de lâAluminium du Saguenay (CNRC-CTA), ce projet vise Ă modĂ©liser par Ă©lĂ©ments finis le comportement mĂ©canique anisotrope du AA6082-T6 lors dâessais dâĂ©crasement. Dans un premier temps, les paramĂštres dâanisotropie du matĂ©riau sont Ă©tablis par diffĂ©rents essais mĂ©caniques.
Par la suite, une loi de comportement anisotrope est dĂ©veloppĂ©e afin de reprĂ©senter lâanisotropie du matĂ©riau. Ensuite, des simulations dâessais de traction par Ă©lĂ©ments finis sont rĂ©alisĂ©es pour dĂ©montrer que la loi reprĂ©sente bien lâanisotropie. Finalement, des simulations dâessais dâĂ©crasement de tube sont rĂ©alisĂ©es afin d'Ă©valuer lâamĂ©lioration obtenue en tenant compte de lâanisotropie
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
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
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