Model-Based and Model-Free Control Predicts Alcohol Consumption Developmental Trajectory in Young Adults: A 3-Year Prospective Study.

BACKGROUND: A shift from goal-directed toward habitual control has been associated with alcohol dependence. Whether such a shift predisposes to risky drinking is not yet clear. We investigated how goal-directed and habitual control at age 18 predict alcohol use trajectories over the course of 3 years. METHODS: Goal-directed and habitual control, as informed by model-based (MB) and model-free (MF) learning, were assessed with a two-step sequential decision-making task during functional magnetic resonance imaging in 146 healthy 18-year-old men. Three-year alcohol use developmental trajectories were based on either a consumption score from the self-reported Alcohol Use Disorders Identification Test (assessed every 6 months) or an interview-based binge drinking score (grams of alcohol/occasion; assessed every year). We applied a latent growth curve model to examine how MB and MF control predicted the drinking trajectory. RESULTS: Drinking behavior was best characterized by a linear trajectory. MB behavioral control was negatively associated with the development of the binge drinking score; MF reward prediction error blood oxygen level-dependent signals in the ventromedial prefrontal cortex and the ventral striatum predicted a higher starting point and steeper increase of the Alcohol Use Disorders Identification Test consumption score over time, respectively. CONCLUSIONS: We found that MB behavioral control was associated with the binge drinking trajectory, while the MF reward prediction error signal was closely linked to the consumption score development. These findings support the idea that unbalanced MB and MF control might be an important individual vulnerability in predisposing to risky drinking behavior

Do horizontal propulsive forces influence the nonlinear structure of locomotion?

<p>Abstract</p> <p>Background</p> <p>Several investigations have suggested that changes in the nonlinear gait dynamics are related to the neural control of locomotion. However, no investigations have provided insight on how neural control of the locomotive pattern may be directly reflected in changes in the nonlinear gait dynamics. Our simulations with a passive dynamic walking model predicted that toe-off impulses that assist the forward motion of the center of mass influence the nonlinear gait dynamics. Here we tested this prediction in humans as they walked on the treadmill while the forward progression of the center of mass was assisted by a custom built mechanical horizontal actuator.</p> <p>Methods</p> <p>Nineteen participants walked for two minutes on a motorized treadmill as a horizontal actuator assisted the forward translation of the center of mass during the stance phase. All subjects walked at a self-select speed that had a medium-high velocity. The actuator provided assistive forces equal to 0, 3, 6 and 9 percent of the participant's body weight. The largest Lyapunov exponent, which measures the nonlinear structure, was calculated for the hip, knee and ankle joint time series. A repeated measures one-way analysis of variance with a t-test post hoc was used to determine significant differences in the nonlinear gait dynamics.</p> <p>Results</p> <p>The magnitude of the largest Lyapunov exponent systematically increased as the percent assistance provided by the mechanical actuator was increased.</p> <p>Conclusion</p> <p>These results support our model's prediction that control of the forward progression of the center of mass influences the nonlinear gait dynamics. The inability to control the forward progression of the center of mass during the stance phase may be the reason the nonlinear gait dynamics are altered in pathological populations. However, these conclusions need to be further explored at a range of walking speeds.</p

Amino Acid Requirements in Critically Ill Patients with Acute Kidney Injury Treated with Continuous Renal Replacement Therapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90284/1/phco.28.5.600.pd

Solving Navigational Uncertainty Using Grid Cells on Robots

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments

Dynamical Mean-Field Theory

The dynamical mean-field theory (DMFT) is a widely applicable approximation scheme for the investigation of correlated quantum many-particle systems on a lattice, e.g., electrons in solids and cold atoms in optical lattices. In particular, the combination of the DMFT with conventional methods for the calculation of electronic band structures has led to a powerful numerical approach which allows one to explore the properties of correlated materials. In this introductory article we discuss the foundations of the DMFT, derive the underlying self-consistency equations, and present several applications which have provided important insights into the properties of correlated matter.Comment: Chapter in "Theoretical Methods for Strongly Correlated Systems", edited by A. Avella and F. Mancini, Springer (2011), 31 pages, 5 figure

Expression of B-RAF V600E in Type II Pneumocytes Causes Abnormalities in Alveolar Formation, Airspace Enlargement and Tumor Formation in Mice

Growth factor induced signaling cascades are key regulatory elements in tissue development, maintenance and regeneration. Perturbations of these cascades have severe consequences, leading to developmental disorders and neoplastic diseases. As a major function in signal transduction, activating mutations in RAF family kinases are the cause of human tumorigenesis, where B-RAF V600E has been identified as the prevalent mutant. In order to address the oncogenic function of B-RAF V600E, we have generated transgenic mice expressing the activated oncogene specifically in lung alveolar epithelial type II cells. Constitutive expression of B-RAF V600E caused abnormalities in alveolar epithelium formation that led to airspace enlargements. These lung lesions showed signs of tissue remodeling and were often associated with chronic inflammation and low incidence of lung tumors. The inflammatory cell infiltration did not precede the formation of the lung lesions but was rather accompanied with late tumor development. These data support a model where the continuous regenerative process initiated by oncogenic B-RAF-driven alveolar disruption provides a tumor-promoting environment associated with chronic inflammation

Cognitive and memory training in adults at risk of dementia: A Systematic Review

<p>Abstract</p> <p>Background</p> <p>Effective non-pharmacological cognitive interventions to prevent Alzheimer's dementia or slow its progression are an urgent international priority. The aim of this review was to evaluate cognitive training trials in individuals with mild cognitive impairment (MCI), and evaluate the efficacy of training in memory strategies or cognitive exercises to determine if cognitive training could benefit individuals at risk of developing dementia.</p> <p>Methods</p> <p>A systematic review of eligible trials was undertaken, followed by effect size analysis. Cognitive training was differentiated from other cognitive interventions not meeting generally accepted definitions, and included both cognitive exercises and memory strategies.</p> <p>Results</p> <p>Ten studies enrolling a total of 305 subjects met criteria for cognitive training in MCI. Only five of the studies were randomized controlled trials. Meta-analysis was not considered appropriate due to the heterogeneity of interventions. Moderate effects on memory outcomes were identified in seven trials. Cognitive exercises (relative effect sizes ranged from .10 to 1.21) may lead to greater benefits than memory strategies (.88 to -1.18) on memory.</p> <p>Conclusions</p> <p>Previous conclusions of a lack of efficacy for cognitive training in MCI may have been influenced by not clearly defining the intervention. Our systematic review found that cognitive exercises can produce moderate-to-large beneficial effects on memory-related outcomes. However, the number of high quality RCTs remains low, and so further trials must be a priority. Several suggestions for the better design of cognitive training trials are provided.</p

Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions

Novel image–novel location object recognition task sensitive to age-related cognitive decline in nondemented elderly

Traditional tests used in the clinic to identify dementia, such as the mini-mental state examination (MMSE), are useful to identify severe cognitive impairments but might be less sensitive to detect more subtle age-related cognitive changes. Previously, the novel image–novel location (NINL) object recognition test was shown to be sensitive to detect effects of apolipoprotein E4, a risk factor for developing age-related cognitive decline and Alzheimer’s disease, in nondemented elderly. In the present longitudinal study, performance on the MMSE and the NINL tests were compared over a 4-year period. Individual NINL scores over this period were highly correlated. In addition, while MMSE scores did not change over the 4-year period, NINL scores did. In a final testing session of a subset of the participants, NINL scores correlated with logical memory and word recall lists, cognitive tasks used to detect dementia in the clinic, as well as clinical dementia rating scales. These results support that the NINL might be a valuable tool to assess age-related cognitive decline