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Search Results: 1 - 10 of 155896 matches for " Ian H. Stevenson "
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On the Similarity of Functional Connectivity between Neurons Estimated across Timescales
Ian H. Stevenson,Konrad P. K?rding
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0009206
Abstract: A central objective in neuroscience is to understand how neurons interact. Such functional interactions have been estimated using signals recorded with different techniques and, consequently, different temporal resolutions. For example, spike data often have sub-millisecond resolution while some imaging techniques may have a resolution of many seconds. Here we use multi-electrode spike recordings to ask how similar functional connectivity inferred from slower timescale signals is to the one inferred from fast timescale signals. We find that functional connectivity is relatively robust to low-pass filtering—dropping by about 10% when low pass filtering at 10 hz and about 50% when low pass filtering down to about 1 Hz—and that estimates are robust to high levels of additive noise. Moreover, there is a weak correlation for physiological filters such as hemodynamic or Ca2+ impulse responses and filters based on local field potentials. We address the origin of these correlations using simulation techniques and find evidence that the similarity between functional connectivity estimated across timescales is due to processes that do not depend on fast pair-wise interactions alone. Rather, it appears that connectivity on multiple timescales or common-input related to stimuli or movement drives the observed correlations. Despite this qualification, our results suggest that techniques with intermediate temporal resolution may yield good estimates of the functional connections between individual neurons.
Sensory Adaptation and Short Term Plasticity as Bayesian Correction for a Changing Brain
Ian H. Stevenson,Beau Cronin,Mriganka Sur,Konrad P. Kording
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0012436
Abstract: Neurons in the sensory system exhibit changes in excitability that unfold over many time scales. These fluctuations produce noise and could potentially lead to perceptual errors. However, to prevent such errors, postsynaptic neurons and synapses can adapt and counteract changes in the excitability of presynaptic neurons. Here we ask how neurons could optimally adapt to minimize the influence of changing presynaptic neural properties on their outputs. The resulting model, based on Bayesian inference, explains a range of physiological results from experiments which have measured the overall properties and detailed time-course of sensory tuning curve adaptation in the early visual cortex. We show how several experimentally measured short term plasticity phenomena can be understood as near-optimal solutions to this adaptation problem. This framework provides a link between high level computational problems, the properties of cortical neurons, and synaptic physiology.
Generalization of Stochastic Visuomotor Rotations
Hugo L. Fernandes, Ian H. Stevenson, Konrad P. Kording
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0043016
Abstract: Generalization studies examine the influence of perturbations imposed on one movement onto other movements. The strength of generalization is traditionally interpreted as a reflection of the similarity of the underlying neural representations. Uncertainty fundamentally affects both sensory integration and learning and is at the heart of many theories of neural representation. However, little is known about how uncertainty, resulting from variability in the environment, affects generalization curves. Here we extend standard movement generalization experiments to ask how uncertainty affects the generalization of visuomotor rotations. We find that although uncertainty affects how fast subjects learn, the perturbation generalizes independently of uncertainty.
Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task
Ian H. Stevenson ,Hugo L. Fernandes,Iris Vilares,Kunlin Wei,Konrad P. K?rding
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000629
Abstract: A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task.
Rewiring Neural Interactions by Micro-Stimulation
James M. Rebesco,Ian H. Stevenson,Konrad P. K?rding,Sara A. Solla,Lee E. Miller
Frontiers in Systems Neuroscience , 2010, DOI: 10.3389/fnsys.2010.00039
Abstract: Plasticity is a crucial component of normal brain function and a critical mechanism for recovery from injury. In vitro, associative pairing of presynaptic spiking and stimulus-induced postsynaptic depolarization causes changes in the synaptic efficacy of the presynaptic neuron, when activated by extrinsic stimulation. In vivo, such paradigms can alter the responses of whole groups of neurons to stimulation. Here, we used in vivo spike-triggered stimulation to drive plastic changes in rat forelimb sensorimotor cortex, which we monitored using a statistical measure of functional connectivity inferred from the spiking statistics of the neurons during normal, spontaneous behavior. These induced plastic changes in inferred functional connectivity depended on the latency between trigger spike and stimulation, and appear to reflect a robust reorganization of the network. Such targeted connectivity changes might provide a tool for rerouting the flow of information through a network, with implications for both rehabilitation and brain–machine interface applications.
Inter-Group Conflict in Health Care: UK Students’ Experiences of Bullying and the Need for Organisational Solutions
Keith Stevenson,Jacqueline Randle,Ian Grayling
Online Journal of Issues in Nursing , 2006,
Abstract: This paper addresses bullying of United Kingdom (UK) nursing students whilst on work placement as a specific issue of inter-group difficulty that currently affects nurses and students working in the UK National Health Service. The authors begin by discussing the concept of bullying and sharing the types of bullying reported in two recent studies involving UK nursing students. Both studies illustrate the effects that negative workplace experiences can have on new entrants to the profession. After reviewing various individual solutions which have been recommended for reducing bullying, they suggest that the most effective solution is for health care organisations offering placement training to become much more proactive in creating a culture that will not tolerate bullying behaviour by staff at any level. The literature suggests bullying is a phenomenon affecting workplaces in many countries. Thus the issues described in this article, and the solutions offered have relevance to a variety of health care settings.
Functional Connectivity and Tuning Curves in Populations of Simultaneously Recorded Neurons
Ian H. Stevenson ,Brian M. London,Emily R. Oby,Nicholas A. Sachs,Jacob Reimer,Bernhard Englitz,Stephen V. David,Shihab A. Shamma,Timothy J. Blanche,Kenji Mizuseki,Amin Zandvakili,Nicholas G. Hatsopoulos,Lee E. Miller,Konrad P. Kording
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002775
Abstract: How interactions between neurons relate to tuned neural responses is a longstanding question in systems neuroscience. Here we use statistical modeling and simultaneous multi-electrode recordings to explore the relationship between these interactions and tuning curves in six different brain areas. We find that, in most cases, functional interactions between neurons provide an explanation of spiking that complements and, in some cases, surpasses the influence of canonical tuning curves. Modeling functional interactions improves both encoding and decoding accuracy by accounting for noise correlations and features of the external world that tuning curves fail to capture. In cortex, modeling coupling alone allows spikes to be predicted more accurately than tuning curve models based on external variables. These results suggest that statistical models of functional interactions between even relatively small numbers of neurons may provide a useful framework for examining neural coding.
Nonequilibrium electron rings for synchrotron radiation production
Hywel Owen,Peter H. Williams,Scott Stevenson
Physics , 2013, DOI: 10.1103/PhysRevLett.110.154801
Abstract: Electron storage rings used for the production of synchrotron radiation (SR) have an output photon brightness that is limited by the equilibrium beam emittance. By using interleaved injection and ejection of bunches from a source with repetition rate greater than 1 kHz, we show that it is practicable to overcome this limit in rings of energy ~1 GeV. Sufficiently short kicker pulse lengths enable effective currents of many milliamperes, which can deliver a significant flux of diffraction-limited soft X-ray photons. Thus, either existing SR facilities may be adapted for non-equilibrium operation, or the technique applied to construct SR rings smaller than their storage ring equivalent.
Spontaneous reconnection at a separator current layer. II. Nature of the waves and flows
Julie E. H. Stevenson,Clare E. Parnell
Physics , 2015,
Abstract: Sudden destabilisations of the magnetic field, such as those caused by spontaneous reconnection, will produce waves and/or flows. Here, we investigate the nature of the plasma motions resulting from spontaneous reconnection at a 3D separator. In order to clearly see the perturbations generated by the reconnection, we start from a magnetohydrostatic equilibrium containing two oppositely-signed null points joined by a generic separator along which lies a twisted current layer. The nature of the magnetic reconnection initiated in this equilibrium as a result of an anomalous resistivity is discussed in detail in \cite{Stevenson15_jgra}. The resulting sudden loss of force balance inevitably generates waves that propagate away from the diffusion region carrying the dissipated current. In their wake a twisting stagnation-flow, in planes perpendicular to the separator, feeds flux back into the original diffusion site (the separator) in order to try to regain equilibrium. This flow drives a phase of slow weak impulsive-bursty reconnection that follows on after the initial fast-reconnection phase.
Spontaneous reconnection at a separator current layer. I. Nature of the reconnection
Julie E. H. Stevenson,Clare E. Parnell
Physics , 2015,
Abstract: Magnetic separators, which lie on the boundary between four topologically-distinct flux domains, are prime locations in three-dimensional magnetic fields for reconnection, especially in the magnetosphere between the planetary and interplanetary magnetic field and also in the solar atmosphere. Little is known about the details of separator reconnection and so the aim of this paper, which is the first of two, is to study the properties of magnetic reconnection at a single separator. Three-dimensional, resistive magnetohydrodynamic numerical experiments are run to study separator reconnection starting from a magnetohydrostatic equilibrium which contains a twisted current layer along a single separator linking a pair of opposite-polarity null points. The resulting reconnection occurs in two phases. The first is short involving rapid-reconnection in which the current at the separator is reduced by a factor of around 2.3. Most ($75\%$) of the magnetic energy is converted during this phase, via Ohmic dissipation, directly into internal energy, with just $0.1\%$ going into kinetic energy. During this phase the reconnection occurs along most of the separator away from its ends (the nulls), but in an asymmetric manner which changes both spatially and temporally over time. The second phase is much longer and involves slow impulsive-bursty reconnection. Again Ohmic heating dominates over viscous damping. Here, the reconnection occurs in small localised bursts at random anywhere along the separator.
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