Incremental Mutual Information: A New Method for Characterizing the Strength and Dynamics of Connections in Neuronal Circuits

Understanding the computations performed by neuronal circuits requires characterizing the strength and dynamics of the connections between individual neurons. This characterization is typically achieved by measuring the correlation in the activity of two neurons. We have developed a new measure for studying connectivity in neuronal circuits based on information theory, the incremental mutual information (IMI). By conditioning out the temporal dependencies in the responses of individual neurons before measuring the dependency between them, IMI improves on standard correlation-based measures in several important ways: 1) it has the potential to disambiguate statistical dependencies that reflect the connection between neurons from those caused by other sources (e. g. shared inputs or intrinsic cellular or network mechanisms) provided that the dependencies have appropriate timescales, 2) for the study of early sensory systems, it does not require responses to repeated trials of identical stimulation, and 3) it does not assume that the connection between neurons is linear. We describe the theory and implementation of IMI in detail and demonstrate its utility on experimental recordings from the primate visual system

ASPECTOS HIDRODINÂMICOS DA ENSEADA DA ARMAÇÃO DE ITAPOCOROY, SC.

This paper join available information of environmental variables which allow to assess the hydrodynamics of the Armação do Itapocoroy Bight. Data of current speed and direction, tide, wind, salinity, temperature, turbidity and the bathimetry were acquired at different occasions, although when they are evaluated together, they permit to build a preliminary picture about the holding capacity of this environment to maintain the mollusc aquaculture. The water renewal rate is of the order of some days, and the proximity of the Itajaí-açu River estuary mouth allow that the river plume enter in a regular bassis into the bight. The occasional storm waves from east, together with wind and tide currents, act in the remobilization of material generated by the mussel culture.Este trabalho reúne informações disponíveis de variávies ambientais que permitem realizar uma avaliação das condições hidrodinâmicas da enseada da Armação de Itapocoroy. Dados de velocidade e direção de correntes, maré, vento, salinidade, temperatura, turbidez e a batimetria foram obtidos em diferentes ocasiões, porém em conjunto permitem elaborar um quadro preliminar da capacidade de suporte deste ambiente para manter a atividade de cultivo de moluscos marinhos. A taxa de renovação de água é da ordem de alguns dias, e a proximidade da desembocadura do estuário do Rio Itajaí-açu faz com que a pluma deste regularmente avance para o interior da enseada. A ação ocasional de ondas de tempestade de leste, juntamente com correntes devido ao vento e à maré, atuam na remoção de detritos gerados pelos cultivos

Supramolecular Self-Assembly of Engineered Polyproline Helices

The ability to rationally design biomaterials to form desired supramolecular constructs presents an ever-growing research field, with many burgeoning works within recent years providing exciting results; however, there exists a broad expanse of promising avenues of research yet to be investigated. As such we have set out to make use of the polyproline helix as a rigid, tunable, and chiral ligand for the rational design and synthesis of supramolecular constructs. In this investigation, we show how an oligoproline tetramer can be specifically designed and functionalized, allowing predictable tuning of supramolecular interactions, to engineer the formation of supramolecular peptide frameworks with varying properties and, consequently, laying the groundwork for further studies utilizing the polyproline helix, with the ability to design desired supramolecular structures containing these peptide building blocks, having tunable structural features and functionalities

Exponential martingales and changes of measure for counting processes

We give sufficient criteria for the Dol\'eans-Dade exponential of a stochastic integral with respect to a counting process local martingale to be a true martingale. The criteria are adapted particularly to the case of counting processes and are sufficiently weak to be useful and verifiable, as we illustrate by several examples. In particular, the criteria allow for the construction of for example nonexplosive Hawkes processes as well as counting processes with stochastic intensities depending on diffusion processes

Single-neuron dynamics in human focal epilepsy

Epileptic seizures are traditionally characterized as the ultimate expression of monolithic, hypersynchronous neuronal activity arising from unbalanced runaway excitation. Here we report the first examination of spike train patterns in large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal spiking activity during seizure initiation and spread was highly heterogeneous, not hypersynchronous, suggesting complex interactions among different neuronal groups even at the spatial scale of small cortical patches. In contrast to earlier stages, seizure termination is a nearly homogenous phenomenon followed by an almost complete cessation of spiking across recorded neuronal ensembles. Notably, even neurons outside the region of seizure onset showed significant changes in activity minutes before the seizure. These findings suggest a revision of current thinking about seizure mechanisms and point to the possibility of seizure prevention based on spiking activity in neocortical neurons

Sensing with the Motor Cortex

The primary motor cortex is a critical node in the network of brain regions responsible for voluntary motor behavior. It has been less appreciated, however, that the motor cortex exhibits sensory responses in a variety of modalities including vision and somatosensation. We review current work that emphasizes the heterogeneity in sensorimotor responses in the motor cortex and focus on its implications for cortical control of movement as well as for brain-machine interface development

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Human seizures couple across spatial scales through travelling wave dynamics

Epilepsy—the propensity toward recurrent, unprovoked seizures—is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms—namely, the effects of an increased extracellular potassium concentration diffusing in space—that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures—and connecting these dynamics to specific biological mechanisms—promises new insights to treat this devastating disease