Temporal Dynamics of Decision-Making during Motion Perception in the Visual Cortex

How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical "decision neurons." A biophysically realistic model of interactions within and between Retina/LGN and cortical areas V1, MT, MST, and LIP, gated by basal ganglia, simulates dynamic properties of decision-making in response to ambiguous visual motion stimuli used by Newsome, Shadlen, and colleagues in their neurophysiological experiments. The model clarifies how brain circuits that solve the aperture problem interact with a recurrent competitive network with self-normalizing choice properties to carry out probablistic decisions in real time. Some scientists claim that perception and decision-making can be described using Bayesian inference or related general statistical ideas, that estimate the optimal interpretation of the stimulus given priors and likelihoods. However, such concepts do not propose the neocortical mechanisms that enable perception, and make decisions. The present model explains behavioral and neurophysiological decision-making data without an appeal to Bayesian concepts and, unlike other existing models of these data, generates perceptual representations and choice dynamics in response to the experimental visual stimuli. Quantitative model simulations include the time course of LIP neuronal dynamics, as well as behavioral accuracy and reaction time properties, during both correct and error trials at different levels of input ambiguity in both fixed duration and reaction time tasks. Model MT/MST interactions compute the global direction of random dot motion stimuli, while model LIP computes the stochastic perceptual decision that leads to a saccadic eye movement.National Science Foundation (SBE-0354378, IIS-02-05271); Office of Naval Research (N00014-01-1-0624); National Institutes of Health (R01-DC-02852

Task-Irrelevant Perceptual Learning Specific to the Contrast Polarity of Motion Stimuli

Studies of perceptual learning have focused on aspects of learning that are related to early stages of sensory processing. However, conclusions that perceptual learning results in low-level sensory plasticity are of great controversy, largely because such learning can often be attributed to plasticity in later stages of sensory processing or in the decision processes. To address this controversy, we developed a novel random dot motion (RDM) stimulus to target motion cells selective to contrast polarity, by ensuring the motion direction information arises only from signal dot onsets and not their offsets, and used these stimuli in conjunction with the paradigm of task-irrelevant perceptual learning (TIPL). In TIPL, learning is achieved in response to a stimulus by subliminally pairing that stimulus with the targets of an unrelated training task. In this manner, we are able to probe learning for an aspect of motion processing thought to be a function of directional V1 simple cells with a learning procedure that dissociates the learned stimulus from the decision processes relevant to the training task. Our results show learning for the exposed contrast polarity and that this learning does not transfer to the unexposed contrast polarity. These results suggest that TIPL for motion stimuli may occur at the stage of directional V1 simple cells.CELEST, an NSF Science of Learning Center (SBE-0354378); Defense Advanced Research Projects Agency SyNAPSE program (HR0011-09-3-0001, HR001-09-C-0011); National Science Foundation (BCS-0549036); National Institutes of Health (R21 EY017737

Applicability of structured telephone monitoring to follow up heart failure patients discharged from Muhimbili National Hospital, Tanzania

Background: Studies from developed countries have shown that home monitoring and follow up of heart failure (HF) patients by use of phone calls is cost-effective as it reduces re-admission and improves patients’ clinical status. This intervention has however not been tested in resource poor countries including Tanzania, and there are questions as to whether it is applicable in such situations. This study was carried out to determine the applicability of structured telephone monitoring of HF patients discharged from Muhimbili National Hospital in Dar es Salaam, Tanzania.   Methods: All heart failure patients admitted at the hospital’s Cardiovascular Medicine Department between August and December 2014 were consecutively recruited. Information on their clinical and demographic characteristics was collected and their mobile phone numbers recorded. Patients were then contacted through their phones on day 7, 14 and 30 post discharge and inquiry on their clinical status was made.Results: A total of 164 HF patients were admitted during the study period, of these 4 declined to participate, 3 could not establish a phone number and 26 died before discharge leaving 131 (79.9%) for follow-up. The mean age was 45±19 years and 56.5% were women. The proportion of patients that could be contacted through mobile phones were 96.2%, 94.7% and 93.9% on day 7, 14 and 30 post discharge, respectively. Over 90% of the contacted patients gave valuable information regarding their clinical status.Conclusion: Majority of HF patients can be contacted and provide valuable clinical information through mobile phones within a month post discharge from the national hospital in Tanzania.  Structured telephone monitoring could be used as a tool to follow up HF patients in a resource-poor country like Tanzania

Neuromodulated attention and goal-driven perception in uncertain domains.

In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive Excitation Backprop (c-EB) was used in two goal-driven perception tasks - one with pairs of noisy MNIST digits and the other with a robot in an action-based attention scenario. The first task included attending to even, odd, low, and high digits, whereas the second task included action goals, such as "eat", "work-on-computer", "read", and "say-hi" that led to attention to objects associated with those actions. The system needed to increase attention to target items and decrease attention to distractor items and background noise. Because the valid goal was unknown, an online learning model based on the cholinergic and noradrenergic neuromodulatory systems was used to predict a noisy goal (expected uncertainty) and re-adapt when the goal changed (unexpected uncertainty). This neurobiologically plausible model demonstrates how neuromodulatory systems can predict goals in uncertain domains and how attentional mechanisms can enhance the perception for that goal

The effect of inflation on financial development : evidence from selected developing countries

The main objectives of this research is to study the effect of inflation on financial development for 23 selected developing countries worldwide for the period 2000 to 2014. The dependent variable for financial sector performances is measured by credit provided to private sectors, and money supply(M2). Other controllable variables are, inflation which consumer price index, interest rate particular lending interest rate, and GDP per capita which measure economic growth of a particular country. This study employs panel data regression analysis of fixed effects and random effects models. Furthermore, the results show that, two independent variables was found having negative significant relationship with dependent variables, those variables are inflation and interest. While GDP per capita has negative significant relationship with money supply when used as a financial development measure. At the same time GDP per capita has positive significant relationship with credit as a measure of financial development

Association between body fat composition and blood pressure level among secondary school adolescents in Dar es Salaam, Tanzania

Introduction: excess body fat and high blood pressure (BP) are important risk factors for increased cardiovascular morbidity and mortality, and both may have their roots of occurrence in childhood and adolescence. The present study aimed at determining the association between body fat composition and BP level among adolescents in Tanzania. Methods: a cross-sectional study involving 5 randomly selected secondary schools within Dar es Salaam was conducted between June and November 2013. Structured questionnaires were used to collect information on demographic characteristics and other cardiovascular risk factors. BP, height, weight and waist circumference were measured following standard methods. Body fat was assessed by skinfold thickness and categorized as underfat, healthy, overfat or obese according to World Health Organization definitions. Hypertension was defined as BP ≥ 90th percentile for age, height and gender of the adolescent. Results: the study included 582 adolescents (mean age 16.5±1.8 years, 52.1% boys). The proportion of adolescents with overfat or obesity was 22.2%. Systolic, diastolic and combined hypertension was present in 17.5%, 5.5%, and 4.0% respectively. In the total population mean body fat percent correlated positively with diastolic BP and mean arterial pressure (MAP) but not with systolic BP. In multivariate analysis body mass index (β=0.21, p=0.008) and waist circumference (β=0.12, p=0.049), but not body fat percentage (β=-0.09, p=0.399) independently predicted higher MAP. Conclusion: body mass index predicts BP level better than body fat composition and should be used as a measure of increased risk for hypertension among adolescents

Anemia and Associated Risk Factors among People Living with Hiv in Dodoma Region, Central Tanzania

Background: Anemia is the most frequent hematologic abnormality of HIV disease and one of the most common manifestations of nutritional deficiency disorders in the world. In sub-Saharan Africa, about 70% of the world’s people living with HIV/AIDS, where the prevalence of anemia is higher than in developed countries. The aim of this study was to determine the prevalence and factors associated with anemia among people living with HIV at Dodoma regional hospital during 2013-2014. Methodology: A retrospective cross-section study conducted among PLWHIV at Dodoma Regional Hospital between 2015 and 2016. A total of 869 PLWHIV were enrolled. Data extraction sheet were used to collect Socio- demographics, immune-hematological data and ARV status from existing patient’s files (CTC 2 card). Double entry of data in Microsoft excel were done and transferred for analyzing using SPSS v.16. Results: Majority of them were females 648(74.6%)and 508(58.2%) were between 19-45years with mean age of 38.84(±14.09). 824(94. 8%) were on ARV; where 640(73.6%) are from urban. The overall prevalence of anaemia among PLHIV was 59.5% of which 56.6% of these were on ARV, and 2.9% were not on ARV. Age, sex and CD4+ counts < 200cell/µl were among factors associated with anemia among PLWHIV. Conclusion: Moderate anaemia was common in the study population. Screening and management of anemia along with the proper use Anti-retroviral therapy may decrease risk of anemia and the effect ARV on red blood cells. Haemoglobin measurements should be taken before initiation of ARV and routinely followed among ARV users

Concept-modulated model-based offline reinforcement learning for rapid generalization

The robustness of any machine learning solution is fundamentally bound by the data it was trained on. One way to generalize beyond the original training is through human-informed augmentation of the original dataset; however, it is impossible to specify all possible failure cases that can occur during deployment. To address this limitation we combine model-based reinforcement learning and model-interpretability methods to propose a solution that self-generates simulated scenarios constrained by environmental concepts and dynamics learned in an unsupervised manner. In particular, an internal model of the agent's environment is conditioned on low-dimensional concept representations of the input space that are sensitive to the agent's actions. We demonstrate this method within a standard realistic driving simulator in a simple point-to-point navigation task, where we show dramatic improvements in one-shot generalization to different instances of specified failure cases as well as zero-shot generalization to similar variations compared to model-based and model-free approaches