Neural population codes

In many regions of the brain, information is represented by patterns of activity occurring over populations of neurons. Understanding the encoding of information in neural population activity is important both for grasping the fundamental computations underlying brain function, and for interpreting signals that may be useful for the control of prosthetic devices. We concentrate on the representation of information in neurons with Poisson spike statistics, in which information is contained in the average spike firing rate. We analyze the properties of population codes in terms of the tuning functions that describe individual neuron behavior. The discussion centers on three computational questions: first, what information is encoded in a population; second, how does the brain compute using populations; and third, when is a population optimal? To answer these questions, we discuss several methods for decoding population activity in an experimental setting. We also discuss how computation can be performed within the brain in networks of interconnected populations. Finally, we examine questions of optimal design of population codes that may help to explain their particular form and the set of variables that are best represented. We show that for population codes based on neurons that have a Poisson distribution of spike probabilities, the behavior and computational properties of the code can be understood in terms of the tuning properties of individual cells.     

Approximate Bayesian computation in population genetics

We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summary statistics, and then substituting the observed summary statistics into the regression equation. The method combines many of the advantages of Bayesian statistical inference with the computational efficiency of methods based on summary statistics. A key advantage of the method is that the nuisance parameters are automatically integrated out in the simulation step, so that the large numbers of nuisance parameters that arise in population genetics problems can be handled without difficulty. Simulation results indicate computational and statistical efficiency that compares favorably with those of alternative methods previously proposed in the literature. We also compare the relative efficiency of inferences obtained using methods based on summary statistics with those obtained directly from the data using MCMC.     

Information processing with population codes

Information is encoded in the brain by populations or clusters of cells, rather than by single cells. This encoding strategy is known as population coding. Here we review the standard use of population codes for encoding and decoding information, and consider how population codes can be used to support neural computations such as noise removal and nonlinear mapping. More radical ideas about how population codes may directly represent information about stimulus uncertainty are also discussed.     

Neural ensembles in navigation: From single cells to population codes

The brain can represent behaviorally relevant information through the firing of individual neurons as well as the coordinated firing of ensembles of neurons. Neurons in the hippocampus and associated cortical regions participate in a variety of types of ensembles to support navigation. These ensemble types include single cell codes, population codes, time-compressed sequences, behavioral sequences, and engrams. We present the physiological basis and behavioral relevance of ensemble firing. We discuss how these traditional definitions of ensembles can constrain or expand potential analyses due to the underlying assumptions and abstractions made. We highlight how coding can change at the ensemble level while underlying single cell codes remain intact. Finally, we present how ensemble definitions could be broadened to better understand the full complexity of the brain.     

A stitch in time: Efficient computation of genomic DNA melting bubbles

Background  

It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses the challenge that a generic search through all combinations of bubble starts and ends is quadratic.     

Neural correlations, population coding and computation

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.     

Note on the computation of critical effective population sizes.

This work extends the work of Whitlock in examining the critical effective population sizes from the fixation of both deleterious and beneficial mutations under drift and selection to prevent mutation breakdown of the population. The validity of approximations for the probability of fixation depends on the nature of the assumed distribution for the fitness effect of both types of mutations. Using no approximation for the probability of fixation and assuming a heavy tailed fitness effect distribution, the current model indicates that the coefficients of variation for the fitness effect distributions of both types of mutations and the fitness effect distribution mean for the beneficial mutations are important predictors of the critical effective population size. The current model further predicts that very small populations can be sustained if the fitness effect variances for both types of mutations and the mean for beneficial mutations are large.     

Real time with Caspase-2

Comment on: Bouchier-Hayes L, et al. Mol Cell 2009;35:830-40.     

Neural coding of categories: information efficiency and optimal population codes

This paper deals with the analytical study of coding a discrete set of categories by a large assembly of neurons. We consider population coding schemes, which can also be seen as instances of exemplar models proposed in the literature to account for phenomena in the psychophysics of categorization. We quantify the coding efficiency by the mutual information between the set of categories and the neural code, and we characterize the properties of the most efficient codes, considering different regimes corresponding essentially to different signal-to-noise ratio. One main outcome is to find that, in a high signal-to-noise ratio limit, the Fisher information at the population level should be the greatest between categories, which is achieved by having many cells with the stimulus-discriminating parts (steepest slope) of their tuning curves placed in the transition regions between categories in stimulus space. We show that these properties are in good agreement with both psychophysical data and with the neurophysiology of the inferotemporal cortex in the monkey, a cortex area known to be specifically involved in classification tasks.     

Hydraulic residence time computation for constructed wetland design

Hydraulic residence time (HRT) is one of the key design parameters controlling the removal efficiency of contaminants and nutrients in stormwater and wastewater wetlands. The paper presents a new approach to the estimation of HRT using the variable residence time (VART) model. The VART model is employed to simulate the major processes (including advection, dispersion, and transient storage of contaminants/nutrients in vegetated zones) affecting HRT and thereby to produce a hydraulic residence time distribution (HRTD) for a design wetland. The HRTD in combination with a moment-based method is then utilized to find a mean design HRT for the design wetland. Methods for estimation of parameters governing the HRTD are proposed. The new approach to HRT computation is demonstrated through a case study for the Tres Rios Demonstration (TRD) Wetlands in Arizona, USA. Modeling results show that the design HRTs for the Hayfield wetland (H1) and the Cobble wetlands (C1 and C2) are 4.04, 4.66, and 2.65 days, respectively. The computed HRTs agree well with those reported by previous studies, confirming the efficacy of the new approach to hydraulic design of constructed wetlands.     

Two-sex population dynamics in space: effects of gestation time on persistence.

Most single-species population models assume either that one sex dominates the growth dynamics (usually the female), or that the life cycles of the two sexes are identical; however, sexual differences in ontogenetic features can render this assumption invalid. Further, the interaction between sexes is necessarily nonlinear, and the dependence of dynamic behavior on sexual interactions can be complicated. Here we examine a two-sex population model, related to the well-known logistic model, with explicit sexual interactions. The model is bistable and, by the addition of diffusion, admits traveling wave solutions. Dominance of states via this spatial dynamic are examined. A simple condition for neutral dominance is obtained; sexual interactions inhibit the dominance of the nonzero population, making persistence more difficult.     

Real time ultrasonic monitoring of hepatic cryosurgery

Cryosurgery has a number of advantages that make it particularly appealing in the treatment of liver cancer. However, a major problem in the clinical application of hepatic cryosurgery is the lack of a precise means of monitoring the freezing process in situ. Preliminary investigations on simulated tissue have shown that standard ultrasonography is capable of accurately determining the amount of frozen material during a cryosurgical procedure. To extend these results to living tissue, cryosurgery was performed, in vivo, on the livers of four mongrel dogs. An ultrasound imaging device using a new intraoperative ultrasound transducer monitored the entire process in real time. The results indicate that the entire freezing and thawing cycle can be monitored easily using real time ultrasound. During freezing, the solidification interface can be seen to move through the tissue allowing clear imaging of the cryolesion. After complete thawing, the cryolesion became less echogenic than before freezing and was therefore distinguishable under ultrasound. Postsurgical pathologic examination showed excellent correlation between the lesion size and its ultrasonic image.     

Real time imaging of human progenitor neurogenesis

Human neural progenitors are increasingly being employed in drug screens and emerging cell therapies targeted towards neurological disorders where neurogenesis is thought to play a key role including developmental disorders, Alzheimer's disease, and depression. Key to the success of these applications is understanding the mechanisms by which neurons arise. Our understanding of development can provide some guidance but since little is known about the specifics of human neural development and the requirement that cultures be expanded in vitro prior to use, it is unclear whether neural progenitors obey the same developmental mechanisms that exist in vivo. In previous studies we have shown that progenitors derived from fetal cortex can be cultured for many weeks in vitro as undifferentiated neurospheres and then induced to undergo neurogenesis by removing mitogens and exposing them to supportive substrates. Here we use live time lapse imaging and immunocytochemical analysis to show that neural progenitors use developmental mechanisms to generate neurons. Cells with morphologies and marker profiles consistent with radial glia and recently described outer radial glia divide asymmetrically and symmetrically to generate multipolar intermediate progenitors, a portion of which express ASCL1. These multipolar intermediate progenitors subsequently divide symmetrically to produce CTIP2(+) neurons. This 3-cell neurogenic scheme echoes observations in rodents in vivo and in human fetal slice cultures in vitro, providing evidence that hNPCs represent a renewable and robust in vitro assay system to explore mechanisms of human neurogenesis without the continual need for fresh primary human fetal tissue. Knowledge provided by this and future explorations of human neural progenitor neurogenesis will help maximize the safety and efficacy of new stem cell therapies by providing an understanding of how to generate physiologically-relevant cell types that maintain their identities when placed in diagnostic or transplantation environments.     

Real time evaluation of overranging in helical computed tomography

Overranging or overscanning increases the dose delivered to patients undergoing helical Computed Tomography examinations. In order to reduce it, nowadays most of the multidetector tomographs close the X-ray beam aperture at the scan extremes. This technical innovation, usually referred to as dynamic or adaptive collimation, also influences the overranging assessment methods. In particular, the film free approach proposed in previous studies is not suitable for these modern tomographs. The present study aims to introduce a new method of estimating overranging with real time dosimetry, even suitable for tomographs equipped with adaptive collimation. The approach proposed is very easy to implement and time saving because only a pencil chamber is required. It is also equivalent in precision and in accuracy to the film based one, considered an absolute benchmark.