Event-related functional magnetic resonance imaging of reward-related brain circuitry in children and adolescents

BACKGROUND: Functional disturbances in reward-related brain systems are thought to play a role in the development of mood, impulse, and substance abuse disorders. Studies in non-human primates have identified brain regions, including the dorsal / ventral striatum and orbital-frontal cortex (OFC), in which neural activity is modulated by reward. Recent studies in adults have concurred with these findings by observing reward-contingent blood oxygen level dependant (BOLD) responses in these regions during functional magnetic resonance imaging (FMRI) paradigms. However no previous studies indicate whether comparable modulations of neural activity exist in the brain reward systems of children and adolescents. METHODS: We used event-related FMRI and a behavioral paradigm modeled on previous work in adults to study brain responses to monetary gains and losses in non-psychiatric children and adolescents as part of a program examining the neural substrates of anxiety and depression in youth. RESULTS: Regions and time-courses of reward-related activity were similar to those observed in adults with condition-dependent BOLD changes in the ventral striatum, lateral and medial OFC; specifically, these regions showed larger responses to positive than to negative feedback. CONCLUSIONS: These results provide further evidence for the value of event-related FMRI in examining reward systems of the brain, demonstrate the feasibility of this approach in children and adolescents, and establish a baseline from which to understand the pathophysiology of reward-related psychiatric disorders in youth

Inference of nonlinear state-space models for sandwich-type lateral flow immunoassay using extended Kalman filtering

Copyright [2011] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, a mathematical model for sandwichtype lateral flow immunoassay is developed via short available time series. A nonlinear dynamic stochastic model is considered that consists of the biochemical reaction system equations and the observation equation. After specifying the model structure, we apply the extend Kalman filter (EKF) algorithm for identifying both the states and parameters of the nonlinear state-space model. It is shown that the EKF algorithm can accurately identify the parameters and also predict the system states in the nonlinear dynamic stochastic model through an iterative procedure by using a small number of observations. The identified mathematical model provides a powerful tool for testing the system hypotheses and also inspecting the effects from various design parameters in a both rapid and inexpensive way. Furthermore, by means of the established model, the dynamic changes of the concentration of antigens and antibodies can be predicted, thereby making it possible for us to analyze, optimize and design the properties of lateral flow immunoassay devices.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of Fujian Province of China under Grants 2009J01280 and 2009J01281

Neuroelectronic interfacing with cultured multielectrode arrays toward a cultured probe

Efficient and selective electrical stimulation and recording of neural activity in peripheral, spinal, or central pathways requires multielectrode arrays at micrometer scale. ¿Cultured probe¿ devices are being developed, i.e., cell-cultured planar multielectrode arrays (MEAs). They may enhance efficiency and selectivity because neural cells have been grown over and around each electrode site as electrode-specific local networks. If, after implantation, collateral sprouts branch from a motor fiber (ventral horn area) and if they can be guided and contacted to each ¿host¿ network, a very selective and efficient interface will result. Four basic aspects of the design and development of a cultured probe, coated with rat cortical or dorsal root ganglion neurons, are described. First, the importance of optimization of the cell-electrode contact is presented. It turns out that impedance spectroscopy, and detailed modeling of the electrode-cell interface, is a very helpful technique, which shows whether a cell is covering an electrode and how strong the sealing is. Second, the dielectrophoretic trapping method directs cells efficiently to desired spots on the substrate, and cells remain viable after the treatment. The number of cells trapped is dependent on the electric field parameters and the occurrence of a secondary force, a fluid flow (as a result of field-induced heating). It was found that the viability of trapped cortical cells was not influenced by the electric field. Third, cells must adhere to the surface of the substrate and form networks, which are locally confined, to one electrode site. For that, chemical modification of the substrate and electrode areas with various coatings, such as polyethyleneimine (PEI) and fluorocarbon monolayers promotes or inhibits adhesion of cells. Finally, it is shown how PEI patterning, by a stamping technique, successfully guides outgrowth of collaterals from a neonatal rat lumbar spinal cord explant, after six days in cultur

Acetylcholine neuromodulation in normal and abnormal learning and memory: vigilance control in waking, sleep, autism, amnesia, and Alzheimer's disease

This article provides a unified mechanistic neural explanation of how learning, recognition, and cognition break down during Alzheimer's disease, medial temporal amnesia, and autism. It also clarifies whey there are often sleep disturbances during these disorders. A key mechanism is how acetylcholine modules vigilance control in cortical layer

Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting state study of attention, default mode and salience network connectivity

Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesized to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six minutes resting state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli

A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant 2009I0016