Assessing the Oral Health Needs of Public Housing Residents

Objectives: “Tooth Smart Healthy Start” is a randomized clinical trial which aims to reduce the incidence of early childhood caries (ECC) in Boston public housing residents as part of the NIH funded Northeast Center for Research to Evaluate and Eliminate Dental Disparities. The purpose of this project was to assess public housing stakeholders' perception of the oral health needs of public housing residents and their interest in replicating “Tooth Smart Healthy Start” in other public housing sites across the nation. Methods: The target population was the 180 attendees of the 2010 meeting of the Health Care for Residents of Public Housing National Conference. A ten question survey which assessed conference attendees' beliefs about oral health and its importance to public housing residents was distributed. Data was analyzed using SAS 9.1. Descriptive statistics were calculated for each variable and results were stratified by participants' roles. Results: Thirty percent of conference attendees completed the survey. The participants consisted of residents, agency representatives, and housing authority personnel. When asked to rank health issues facing public housing residents, oral health was rated as most important (42%) or top three (16%) by residents. The agency representatives and housing authority personnel rated oral health among the top three (33% and 58% respectively) and top five (36% and 25% respectively). When participants ranked the three greatest resident health needs out of eight choices, oral health was the most common response. Majority of the participants expressed interest in replicating the “Tooth Smart Healthy Start” program at their sites. Conclusion: All stakeholder groups identified oral health as one of the greatest health needs of residents in public housing. Furthermore, if shown to reduce ECC, there is significant interest in implementing the program amongst key public housing stakeholders across the nation.

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.