Decoding the activity of neuronal populations in macaque primary visual cortex

Visual function depends on the accuracy of signals carried by visual cortical neurons. Combining information across neurons should improve this accuracy because single neuron activity is variable. We examined the reliability of information inferred from populations of simultaneously recorded neurons in macaque primary visual cortex. We considered a decoding framework that computes the likelihood of visual stimuli from a pattern of population activity by linearly combining neuronal responses and tested this framework for orientation estimation and discrimination. We derived a simple parametric decoder assuming neuronal independence and a more sophisticated empirical decoder that learned the structure of the measured neuronal response distributions, including their correlated variability. The empirical decoder used the structure of these response distributions to perform better than its parametric variant, indicating that their structure contains critical information for sensory decoding. These results show how neuronal responses can best be used to inform perceptual decision-making

Indications for sharp continuous phase transitions at finite temperatures connected with the apparent metal-insulator transition in two-dimensional disordered systems

In a recent experiment, Lai et al. [Phys. Rev. B 75, 033314 (2007)] studied the apparent metal-insulator transition (MIT) of a Si quantum well structure tuning the charge carrier concentration $n$. They observed linear temperature dependences of the conductivity $\sigma(T,n)$ around the Fermi temperature and found that the corresponding $T \to 0$ extrapolation $\sigma_0(n)$ exhibits a sharp bend just at the MIT. Here, reconsidering the data published by Lai et al., it is shown that this sharp bend is related to a peculiarity of $\sigma(T=const.,n)$ clearly detectable in the whole $T$ range up to 4 K, the highest measuring temperature in that work. Since this peculiarity seems not to be smoothed out with increasing $T$ it may indicate a sharp continuous phase transition between the regions of apparent metallic and activated conduction to be present at finite temperature. Hints from the literature of such a behavior are discussed. Finally, a scaling analysis illuminates similarities to previous experiments and provides understanding of the shape of the peculiarity and of sharp peaks found in $d log_{10} \sigma / d n (n)$.Comment: Revised version (quantitative determination of exponent beta added), accepted for publication by Physical Review B. Revtex, 10 pages, 9 figure

From neuronal populations to behavior: a computational journey

Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable understanding of how the activity of a single neuron can be related to a specific behavior. However, it is still unclear how more complex behaviors are inferred from the responses of neuronal populations. This is a particularly timely problem because multi-neuronal recording techniques have recently become increasingly available, simultaneously spurring advances in the analysis of neuronal population data. These developments are, however, constrained by the challenges of combining theoretical and experimental approaches because both approaches have their unique set of constraints. A solution to this problem is to design computational models that are either derived or inspired by cortical computations

Brain–machine interface for eye movements

A number of studies in tetraplegic humans and healthy nonhuman primates (NHPs) have shown that neuronal activity from reach-related cortical areas can be used to predict reach intentions using brain–machine interfaces (BMIs) and therefore assist tetraplegic patients by controlling external devices (e.g., robotic limbs and computer cursors). However, to our knowledge, there have been no studies that have applied BMIs to eye movement areas to decode intended eye movements. In this study, we recorded the activity from populations of neurons from the lateral intraparietal area (LIP), a cortical node in the NHP saccade system. Eye movement plans were predicted in real time using Bayesian inference from small ensembles of LIP neurons without the animal making an eye movement. Learning, defined as an increase in the prediction accuracy, occurred at the level of neuronal ensembles, particularly for difficult predictions. Population learning had two components: an update of the parameters of the BMI based on its history and a change in the responses of individual neurons. These results provide strong evidence that the responses of neuronal ensembles can be shaped with respect to a cost function, here the prediction accuracy of the BMI. Furthermore, eye movement plans could be decoded without the animals emitting any actual eye movements and could be used to control the position of a cursor on a computer screen. These findings show that BMIs for eye movements are promising aids for assisting paralyzed patients

Predicting oculomotor behaviour from correlated populations of posterior parietal neurons

Oculomotor function critically depends on how signals representing saccade direction and eye position are combined across neurons in the lateral intraparietal (LIP) area of the posterior parietal cortex. Here we show that populations of parietal neurons exhibit correlated variability, and that using these interneuronal correlations yields oculomotor predictions that are more accurate and also less uncertain. The structure of LIP population responses is therefore essential for reliable read-out of oculomotor behaviour

Inferring eye position from populations of lateral intraparietal neurons

Understanding how the brain computes eye position is essential to unraveling high-level visual functions such as eye movement planning, coordinate transformations and stability of spatial awareness. The lateral intraparietal area (LIP) is essential for this process. However, despite decades of research, its contribution to the eye position signal remains controversial. LIP neurons have recently been reported to inaccurately represent eye position during a saccadic eye movement, and to be too slow to support a role in high-level visual functions. We addressed this issue by predicting eye position and saccade direction from the responses of populations of LIP neurons. We found that both signals were accurately predicted before, during and after a saccade. Also, the dynamics of these signals support their contribution to visual functions. These findings provide a principled understanding of the coding of information in populations of neurons within an important node of the cortical network for visual-motor behaviors

Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature

A wide variety of battery models are available, and it is not always obvious which model `best' describes a dataset. This paper presents a Bayesian model selection approach using Bayesian quadrature. The model evidence is adopted as the selection metric, choosing the simplest model that describes the data, in the spirit of Occam's razor. However, estimating this requires integral computations over parameter space, which is usually prohibitively expensive. Bayesian quadrature offers sample-efficient integration via model-based inference that minimises the number of battery model evaluations. The posterior distribution of model parameters can also be inferred as a byproduct without further computation. Here, the simplest lithium-ion battery models, equivalent circuit models, were used to analyse the sensitivity of the selection criterion to given different datasets and model configurations. We show that popular model selection criteria, such as root-mean-square error and Bayesian information criterion, can fail to select a parsimonious model in the case of a multimodal posterior. The model evidence can spot the optimal model in such cases, simultaneously providing the variance of the evidence inference itself as an indication of confidence. We also show that Bayesian quadrature can compute the evidence faster than popular Monte Carlo based solvers.Comment: 11 pages, 2 figures, accepted at IFAC202

In vitro assessment of the pharmacodynamic properties and the partitioning of OZ277/RBx-11160 in cultures of Plasmodium falciparum

Objectives: Using synchronous cultures of Plasmodium falciparum malaria, the stage sensitivity of the parasite to OZ277 (RBx-11160), the first fully synthetic antimalarial peroxide that has entered Phase II clinical trials, was investigated in vitro over a concentration range of 1× to 100× the IC50. Secondly, partitioning of OZ277 into P. falciparum-infected red blood cells (RBCs) and uninfected RBCs was studied in vitro by measuring its distribution between RBCs and plasma (R/P). Methods: The effects of timed in vitro exposure (1, 6, 12 or 24 h) to OZ277 were monitored by incorporation of [3H]hypoxanthine into parasite nucleic acids and by light-microscopic analysis of parasite morphology. Partitioning studies were performed with radiolabelled [14C]OZ277. Results: After 1 h of exposure to OZ277 at the highest concentration (100× the IC50) followed by removal of the compound, the hypoxanthine assay showed that growth of mature stages of P. falciparum was reduced to below 20%. Young ring forms were slightly less sensitive (43% growth). Similar stage-specific profiles were found for the antimalarial reference compounds artemether and chloroquine. Strong inhibition (≤6% growth) of all parasite stages was observed when the parasites were exposed to each of the three compounds for 6 h or longer. After removal of the compounds, the parasites did not recover, indicating that the observed growth inhibitions were cytotoxic rather than cytostatic. Pyrimethamine was confirmed to be active exclusively against young schizonts. Light-microscopic analysis also demonstrated the specificity of pyrimethamine against the schizont forms and showed that OZ277, artemether and chloroquine attenuated parasite growth more rapidly than did pyrimethamine. The R/P for OZ277 was 1.5 for uninfected RBCs and up to 270 for infected RBCs. Conclusions: The present study indicates similar stage-specific profiles for OZ277 and for the more well-established antimalarial agents artemether and chloroquine. Secondly, the study describes a significant accumulation of radiolabelled OZ277 in P. falciparum-infected RBC

Convergence of the stochastic Euler scheme for locally Lipschitz coefficients

Stochastic differential equations are often simulated with the Monte Carlo Euler method. Convergence of this method is well understood in the case of globally Lipschitz continuous coefficients of the stochastic differential equation. The important case of superlinearly growing coefficients, however, has remained an open question. The main difficulty is that numerically weak convergence fails to hold in many cases of superlinearly growing coefficients. In this paper we overcome this difficulty and establish convergence of the Monte Carlo Euler method for a large class of one-dimensional stochastic differential equations whose drift functions have at most polynomial growth.Comment: Published at http://www.springerlink.com/content/g076w80730811vv3 in the Foundations of Computational Mathematics 201

Microstructure of Silica in the Presence of Iron Oxide

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65543/1/j.1151-2916.1960.tb14328.x.pd