Neural differentiation is moderated by age in scene- but not face-selective cortical regions

The aging brain is characterized by neural dedifferentiation, an apparent decrease in the functional selectivity of category-selective cortical regions. Age-related reductions in neural differentiation have been proposed to play a causal role in cognitive aging. Recent findings suggest, however, that age-related dedifferentiation is not equally evident for all stimulus categories and, additionally, that the relationship between neural differentiation and cognitive performance is not moderated by age. In light of these findings, in the present experiment, younger and older human adults (males and females) underwent fMRI as they studied words paired with images of scenes or faces before a subsequent memory task. Neural selectivity was measured in two scene-selective (parahippocampal place area (PPA) and retrosplenial cortex (RSC)] and two face-selective [fusiform face area (FFA) and occipital face area (OFA)] regions using both a univariate differentiation index and multivoxel pattern similarity analysis. Both methods provided highly convergent results, which revealed evidence of age-related reductions in neural dedifferentiation in scene-selective but not face-selective cortical regions. Additionally, neural differentiation in the PPA demonstrated a positive, age-invariant relationship with subsequent source memory performance (recall of the image category paired with each recognized test word). These findings extend prior findings suggesting that age-related neural dedifferentiation is not a ubiquitous phenomenon, and that the specificity of neural responses to scenes is predictive of subsequent memory performance independently of age

Observational learning computations in neurons of the human anterior cingulate cortex

When learning from direct experience, neurons in the primate brain have been shown to encode a teaching signal used by algorithms in artificial intelligence: the reward prediction error (PE)—the difference between how rewarding an event is, and how rewarding it was expected to be. However, in humans and other species learning often takes place by observing other individuals. Here, we show that, when humans observe other players in a card game, neurons in their rostral anterior cingulate cortex (rACC) encode both the expected value of an observed choice, and the PE after the outcome was revealed. Notably, during the same task neurons recorded in the amygdala (AMY) and the rostromedial prefrontal cortex (rmPFC) do not exhibit this type of encoding. Our results suggest that humans learn by observing others, at least in part through the encoding of observational PEs in single neurons in the rACC

Electrical Field Flow Fractionation (EFFF) Using an Electrically Insulated Flow Channel

The present invention is an apparatus and a process for separation and resolution of particles suspended in, or molecules dissolved in, a sample mixture or solution using electrical field flow fractionation (EFFF). Fractionation of individual components in the mixture/solution is obtained by the interaction of particles/molecules with an electric field applied perpendicular to the flow direction, and externally to the fractionation channel. The plate electrodes are electrically isolated from the sample and carrier within a thin, non-permeable, insulating coating on the inside surfaces electrodes. This coating forms a barrier between the solution phase and the electric circuit used to generate the working electric field. The flow channel is formed by sandwiching a shaped insulating gasket between the two parallel plate electrodes. The side walls of the channel are defined then by the inside walls of the shaped, insulating gasket

Human choriogonadotropin and epoetin alfa in acute ischemic stroke patients (REGENESIS-LED trial).

IntroductionPreclinical studies suggest that growth factors in the early days after stroke improve final outcome. A prior study found three doses of human choriogonadotropin alfa followed by three doses of erythropoietin to be safe after stroke in humans. A proof of concept trial (REGENESIS) was initiated but placed on regulatory hold during review of an erythropoietin neuroprotective trial. Due to financial constraints, the trial was largely moved to India, using lower erythropoietin doses, as the REGENESIS-LED trial.MethodsEntry criteria included National Institutes of Health Stroke Scale 8-20, supratentorial ischemic stroke, and 24-48 h poststroke at start of therapy. Patients were randomized to three QOD doses of subcutaneous human choriogonadotropin alfa followed by three QD doses of intravenous erythropoietin (three escalating dose cohorts, 4000-20,000 IU/dose) vs. placebo. Primary outcomes were safety and neurological recovery.ResultsThe study was halted early by the sponsor after 96 enrollees. There was no significant difference across treatment groups in the proportion of patients experiencing death, serious adverse events, or any adverse event. There was no significant difference in National Institutes of Health Stroke Scale score change from baseline to Day 90 between placebo and active treatment, whether active cohorts were analyzed together or separately, and no exploratory secondary measure of neurological recovery showed a significant difference between groups.DiscussionAdministration of human choriogonadotropin alfa followed by erythropoietin is safe after a new ischemic stroke. At the doses studied, placebo and active groups did not differ significantly in neurological recovery. Study limitations, such as the use of multiple assessors, differences in rehabilitation care, and being underpowered to show efficacy, are discussed

Computational methods for higher real K-theory with applications to tmf

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2006.Includes bibliographical references (p. 67-69).We begin by present a new Hopf algebra which can be used to compute the tmf homology of a space or spectrum at the prime 3. Generalizing work of Mahowald and Davis, we use this Hopf algebra to compute the tmf homology of the classifying space of the symmetric group on three elements. We also discuss the E3 Tate spectrum of tmf at the prime 3. We then build on work of Hopkins and his collaborators, first computing the Adams-Novikov zero line of the homotopy of the spectrum eo4 at 5 and then generalizing the Hopf algebra for tmf to a family of Hopf algebras, one for each spectrum eop_l at p. Using these, and using a K(p - 1)-local version, we further generalize the Davis-Mahowald result, computing the eop_1 homology of the cofiber of the transfer map [...]. We conclude by computing the initial computations needed to understand the homotopy groups of the Hopkins-Miller real K-theory spectra for heights large than p- 1 at p. The basic computations are supplemented with conjectures as to the collapse of the spectral sequences used herein to compute the homotopy.by Michael Anthony Hill.Ph.D

Continuous cough monitoring using ambient sound recording during convalescence from a COPD exacerbation

Purpose Cough is common in chronic obstructive pulmonary disease (COPD) and is associated with frequent exacerbations and increased mortality. Cough increases during acute exacerbations (AE-COPD), representing a possible metric of clinical deterioration. Conventional cough monitors accurately report cough counts over short time periods. We describe a novel monitoring system which we used to record cough continuously for up to 45 days during AE-COPD convalescence. Methods This is a longitudinal, observational study of cough monitoring in AE-COPD patients discharged from a single teaching-hospital. Ambient sound was recorded from two sites in the domestic environment and analysed using novel cough classifier software. For comparison, the validated hybrid HACC/LCM cough monitoring system was used on days 1, 5, 20 and 45. Patients were asked to record symptoms daily using diaries. Results Cough monitoring data were available for 16 subjects with a total of 568 monitored days. Daily cough count fell significantly from mean±SEM 272.7±54.5 on day 1 to 110.9±26.3 on day 9 (p<0.01) before plateauing. The absolute cough count detected by the continuous monitoring system was significantly lower than detected by the hybrid HACC/LCM system but normalised counts strongly correlated (r=0.88, p<0.01) demonstrating an ability to detect trends. Objective cough count and subjective cough scores modestly correlated (r=0.46). Conclusions Cough frequency declines significantly following AE-COPD and the reducing trend can be detected using continuous ambient sound recording and novel cough classifier software. Objective measurement of cough frequency has the potential to enhance our ability to monitor the clinical state in patients with COPD

A Search for Time Variation of the Fine Structure Constant

A method offering an order of magnitude sensitivity gain is described for using quasar spectra to investigate possible time or space variation in the fine structure constant, alpha. Applying the technique to a sample of 30 absorption systems, spanning redshifts 0.5 < z< 1.6, obtained with the Keck I telescope, we derive limits on variations in alpha over a wide range of epochs. For the whole sample Delta(alpha)/alpha = -1.1 +/- 0.4 x 10^{-5}. This deviation is dominated by measurements at z > 1, where Delta(alpha)/alpha = -1.9 +/- 0.5 x 10^{-5}. For z < 1, Delta(alpha)/alpha = -0.2 +/- 0.4 x 10^{-5}, consistent with other known constraints. Whilst these results are consistent with a time-varying alpha, further work is required to explore possible systematic errors in the data, although careful searches have so far not revealed any.Comment: 4 pages, 1 figure, accepted for publication in Physical Review Letter

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural network weights. Conventional processing architectures are not well suited for simulating neural networks, often requiring large amounts of energy and time. Additionally, synapses in biological neural networks are not binary connections, but exhibit a nonlinear response function as neurotransmitters are emitted and diffuse between neurons. Inspired by neuroscience principles, we present a digital neuromorphic architecture, the Spiking Temporal Processing Unit (STPU), capable of modeling arbitrary complex synaptic response functions without requiring additional hardware components. We consider the paradigm of spiking neurons with temporally coded information as opposed to non-spiking rate coded neurons used in most neural networks. In this paradigm we examine liquid state machines applied to speech recognition and show how a liquid state machine with temporal dynamics maps onto the STPU-demonstrating the flexibility and efficiency of the STPU for instantiating neural algorithms.Comment: 8 pages, 4 Figures, Preprint of 2017 IJCN