Comparación de métodos de caracterización de señales MER

En este documento presenta una comparación de los métodos propuestos para la caracterización de señales provenientes de microeléctrodos de registro (MER) para la identificación de zonas cerebrales que intervienen en la cirugía de la enfermedad de Parkinson. Los mejores porcentajes de acierto se obtienen utilizando como método de caracterización la transformada wavelet, 97.37% y 71.4% para 2 y 4 clases respectivamente.This document presents a microelectrode registers feature extraction methodologies comparison for brain zones identification found in Parkinson¿s disease surgery. Best results are obtained using wavelet transforms, 97.37% and 71.4% for 2 and 4 classes, respectively

Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks

Pattern separation is a fundamental function of the brain. The divergent feedforward networks thought to underlie this computation are widespread, yet exhibit remarkably similar sparse synaptic connectivity. Marr-Albus theory postulates that such networks separate overlapping activity patterns by mapping them onto larger numbers of sparsely active neurons. But spatial correlations in synaptic input and those introduced by network connectivity are likely to compromise performance. To investigate the structural and functional determinants of pattern separation we built models of the cerebellar input layer with spatially correlated input patterns, and systematically varied their synaptic connectivity. Performance was quantified by the learning speed of a classifier trained on either the input or output patterns. Our results show that sparse synaptic connectivity is essential for separating spatially correlated input patterns over a wide range of network activity, and that expansion and correlations, rather than sparse activity, are the major determinants of pattern separation

Activity-dependent release of Adenosine: a critical re-evaluation of mechanism

Adenosine is perhaps the most important and universal modulator in the brain. The current consensus is that it is primarily produced in the extracellular space from the breakdown of previously released ATP. It is also accepted that it can be released directly, as adenosine, during pathological events primarily by equilibrative transport. Nevertheless, there is a growing realization that adenosine can be rapidly released from the nervous system in a manner that is dependent upon the activity of neurons. We consider three competing classes of mechanism that could explain neuronal activity dependent adenosine release (exocytosis of ATP followed by extracellular conversion to adenosine; exocytotic release of an unspecified transmitter followed by direct non-exocytotic adenosine release from an interposed cell; and direct exocytotic release of adenosine) and outline discriminatory experimental tests to decide between them. We review several examples of activity dependent adenosine release and explore their underlying mechanisms where these are known. We discuss the limits of current experimental techniques in definitively discriminating between the competing models of release, and identify key areas where technologies need to advance to enable definitive discriminatory tests. Nevertheless, within the current limits, we conclude that there is evidence for a mechanism that strongly resembles direct exocytosis of adenosine underlying at least some examples of neuronal activity dependent adenosine release

Functional connectivity and neuronal dynamics: insights from computational methods

International audienceBrain functions rely on flexible communication between microcircuits in distinct cortical regions. The mechanisms underlying flexible information routing are still, however, largely unknown. Here, we hypothesize that the emergence of a multiplicity of possible information routing patterns is due to the richness of the complex dynamics that can be supported by an underlying structural network. Analyses of circuit computational models of interacting brain areas suggest that different dynamical states associated with a given connectome mechanistically implement different information routing patterns between system's components. As a result, a fast, network-wide and self-organized reconfiguration of information routing patterns-and Functional Connectivity networks, seen as their proxy-can be achieved by inducing a transition between the available intrinsic dynamical states. We present here a survey of theoretical and modelling results, as well as of sophisticated metrics of Functional Connectivity which are compliant with the daunting task of characterizing dynamic routing from neural data. Theory: Function follows dynamics, rather than structure Neuronal activity conveys information, but which target should this information be-pushed‖ to, or which source should new information be-pulled‖ from? The problem of dynamic information routing is ubiquitous in a distributed information processing system as the brain. Brain functions in general require the control of distributed networks of interregional communication on fast timescales compliant with behavior, but incompatible with plastic modifications of connectivity tracts (Bressler & Kelso, 2001; Varela et al., 2001). This argument led to notions of connectivity based on information exchange-or more generically, an-interaction‖-between brain regions or neuronal populations, rather than based on the underlying STRUCTURAL CONNECTIVITY (SC, i.e. anatomic). An entire zoo of data-driven metrics has been introduced in the literature and this chapter will review some of them. Notwithstanding, they track simple correlation, or directed causal influence (Friston, 2011) or information transfer (Wibral et al., 2014) between time-series of activity. Thes

Identification of Persistent and Resurgent Sodium Currents in Spiral Ganglion Neurons Cultured from the Mouse Cochlea

In spiral ganglion neurons (SGNs), the afferent single units of the auditory nerve, high spontaneous and evoked firing rates ensure preservation of the temporal code describing the key features of incoming sound. During postnatal development, the spatiotemporal distribution of ion channel subtypes contributes to the maturation of action potential generation in SGNs, and to their ability to generate spike patterns that follow rapidly changing inputs. Here we describe tetrodotoxin (TTX)-sensitive Na+ currents in SGNs cultured from mice, whose properties may support this fast spiking behavior. A subthreshold persistent Na+ current (INaP) and a resurgent Na+ current (INaR) both emerged prior to the onset of hearing and became more prevalent as hearing matured. Navβ4 subunits, which are proposed to play a key role in mediating INaR elsewhere in the nervous system, were immunolocalized to the first heminode where spikes are generated in the auditory nerve, and to perisomatic nodes of Ranvier. ATX-II, a sea anemone toxin that slows classical Na+ channel inactivation selectively, enhanced INaP five-fold and INaR three-fold in voltage clamp recordings. In rapidly-adapting SGNs under current clamp, ATX-II increased the likelihood of firing additional action potentials. The data identify INaP and INaR as novel regulators of excitability in SGNs, and consistent with their roles in other neuronal types, we suggest that these nonclassical Na+ currents may contribute to the control of refractoriness in the auditory nerve

Genetics and language: a neurobiological perspective on the missing link (-ing hypotheses)

The paper argues that both evolutionary and genetic approaches to studying the biological foundations of speech and language could benefit from fractionating the problem at a finer grain, aiming not to map genetics to “language”—or even subdomains of language such as “phonology” or “syntax”—but rather to link genetic results to component formal operations that underlie processing the comprehension and production of linguistic representations. Neuroanatomic and neurophysiological research suggests that language processing is broken down in space (distributed functional anatomy along concurrent pathways) and time (concurrent processing on multiple time scales). These parallel neuronal pathways and their local circuits form the infrastructure of speech and language and are the actual targets of evolution/genetics. Therefore, investigating the mapping from gene to brain circuit to linguistic phenotype at the level of generic computational operations (subroutines actually executable in these circuits) stands to provide a new perspective on the biological foundations in the healthy and challenged brain

Comparación de métodos de caracterización de señales mer

En este documento presenta una comparación de los métodos propuestos para la caracterización de señales provenientes de microeléctrodos de registro (MER) para la identificación de zonas cerebrales que intervienen en la cirugía de la enfermedad de Parkinson. Los mejores porcentajes de acierto se obtienenutilizando como método de caracterización la transformada wavelet, 97.37% y71.4% para 2 y 4 clases respectivamente

Somatosensory Signaling for Flight Control in the Echolocating Bat Eptesicus fuscus

Bats are the only mammals to have evolved powered flight. Their specialized hand-wings with elongated digits and a thin membrane spanning the digits not only enable flight, but give them unrivaled aerial maneuverability. Bat wing membrane is endowed with an array of microscopic hairs that are hypothesized to monitor airflow and provide sensory feedback to guide rapid motor adjustments for flight control. The goal of this thesis is to contribute to a broader understanding of the response properties of wing-associated tactile receptive fields, and the representation of aerodynamic feedback in the bat's nervous system. Using the big brown bat, Eptesicus fuscus, a series of neurophysiological experiments were performed where the primary somatosensory cortical (S1) responses to tactile and airflow stimulation of the wings were analyzed. Results demonstrate that the body surface is organized topographically across the surface of S1, with an overrepresentation of wings, head and foot. The wings have an inverted orientation compared to hand representation of terrestrial mammals, with tactile thresholds that are remarkably close to human fingertips. Airflow stimulation of the wings was achieved by brief puffs of air generated using a portable fluid dispensing system. By changing the intensity, duration and direction, airflow sensitive receptive fields were characterized based on responses of S1 neurons. Results reveal that neuronal responses are rapidly adapting, encompassing relatively large and overlapping receptive fields with well-defined centers. S1 responses are directionally selective, with a majority preferring reversed airflow. The onset latency of evoked activity decreases as a function of airflow intensity, with no effect on response magnitude. Furthermore, when dorsal and ventral wings surfaces are stimulated simultaneously, S1 responses are either inhibited or facilitated compared to either wing surface stimulation alone. This finding suggests that outputs from the two wing surfaces are integrated in a manner that reflects the interplay of aerodynamic forces experienced by the wings. To evaluate the central coding mechanisms of airflow sensing by bat wings, I applied an information theoretic framework to spike train data. Results indicate that the strength and direction of airflow can be encoded by the precise timing of spikes, where first post-stimulus spikes transmit bulk of the information, evidence for a latency code

Neural Circuit Dynamics and Ensemble Coding in the Locust and Fruit Fly Olfactory System

Raw sensory information is usually processed and reformatted by an organism’s brain to carry out tasks like identification, discrimination, tracking and storage. The work presented in this dissertation focuses on the processing strategies of neural circuits in the early olfactory system in two insects, the locust and the fruit fly. Projection neurons (PNs) in the antennal lobe (AL) respond to an odor presented to the locust’s antennae by firing in slow information-carrying temporal patterns, consistent across trials. Their downstream targets, the Kenyon cells (KCs) of the mushroom body (MB), receive input from large ensembles of transiently synchronous PNs at a time. The information arrives in slices of time corresponding to cycles of oscillatory activity originating in the AL. In the first part of the thesis, ensemble-level analysis techniques are used to understand how the AL-MB system deals with the problem of identifying odors across different concentrations. Individual PN odor responses can vary dramatically with concentration, but invariant patterns in PN ensemble responses are shown to allow odor identity to be extracted across a wide range of intensities by the KCs. Second, the sensitivity of the early olfactory system to stimulus history is examined. The PN ensemble and the KCs are found capable of tracking an odor in most conditions where it is pulsed or overlapping with another, but they occasionally fail (are masked) or reach intermediate states distinct from those seen for the odors presented alone or in a static mixture. The last part of the thesis focuses on the development of new recording techniques in the fruit fly, an organism with well-studied genetics and behavior. Genetically expressed fluorescent sensors of calcium offer the best available option to study ensemble activity in the fly. Here, simultaneous electrophysiology and two-photon imaging are used to estimate the correlation between G-CaMP, a popular genetically expressible calcium sensor, and electrical activity in PNs. The sensor is found to have poor temporal resolution and to miss significant spiking activity. More generally, this combination of electrophysiology and imaging enables explorations of functional connectivity and calibrated imaging of ensemble activity in the fruit fly.</p