720 research outputs found

    A simple transfer function for nonlinear dendritic integration

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    Relatively recent advances in patch clamp recordings and iontophoresis have enabled unprecedented study of neuronal post-synaptic integration (dendritic integration). Findings support a separate layer of integration in the dendritic branches before potentials reach the cell’s soma. While integration between branches obeys previous linear assumptions, proximal inputs within a branch produce threshold nonlinearity, which some authors have likened to the sigmoid function. Here we show the implausibility of a sigmoidal relation and present a more realistic transfer function in both an elegant artificial form and a biophysically derived form that further considers input locations along the dendritic arbor. As the distance between input locations determines their ability to produce nonlinear interactions, models incorporating dendritic topology are essential to understanding the computational power afforded by these early stages of integration. We use the biophysical transfer function to emulate empirical data using biophysical parameters and describe the conditions under which the artificial and biophysically derived forms are equivalent

    Perceived Stress Predicts Altered Reward and Loss Feedback Processing in Medial Prefrontal Cortex

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    Stress is a significant risk factor for the development of psychopathology, particularly symptoms related to reward processing. Importantly, individuals display marked variation in how they perceive and cope with stressful events, and such differences are strongly linked to risk for developing psychiatric symptoms following stress exposure. However, many questions remain regarding the neural architecture that underlies inter-subject variability in perceptions of stressors. Using functional magnetic resonance imaging (fMRI) during a Monetary Incentive Delay (MID) paradigm, we examined the effects of self-reported perceived stress levels on neural activity during reward anticipation and feedback in a sample of healthy individuals. We found that subjects reporting more uncontrollable and overwhelming stressors displayed blunted neural responses in medial prefrontal cortex (mPFC) following feedback related to monetary gains as well monetary losses. This is consistent with preclinical models that implicate the mPFC as a key site of vulnerability to the noxious effects of uncontrollable stressors. Our data help translate these findings to humans, and elucidate some of the neural mechanisms that may underlie stress-linked risk for developing reward-related psychiatric symptoms.Psycholog

    Integrating Landsat pixel composites and change metrics with lidar plots to predictively map forest structure and aboveground biomass in Saskatchewan, Canada

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    Forest inventory and monitoring programs are needed to provide timely, spatially complete (i.e. mapped), and verifiable information to support forest management, policy formulation, and reporting obligations. Satellite images, in particular data from the Landsat Thematic Mapper and Enhanced Thematic Mapper (TM/ETM +) sensors, are often integrated with field plots from forest inventory programs, leveraging the complete spatial coverage of imagery with detailed ecological information from a sample of plots to spatially model forest conditions and resources. However, in remote and unmanaged areas such as Canada's northern forests, financial and logistic constraints can severely limit the availability of inventory plot data. Additionally, Landsat spectral information has known limitations for characterizing vertical vegetation structure and biomass; while clouds, snow, and short growing seasons can limit development of large area image mosaics that are spectrally and phenologically consistent across space and time. In this study we predict and map forest structure and aboveground biomass over 37 million ha of forestland in Saskatchewan, Canada. We utilize lidar plots—observations of forest structure collected from airborne discrete-return lidar transects acquired in 2010—as a surrogate for traditional field and photo plots. Mapped explanatory data included Tasseled Cap indices and multi-temporal change metrics derived from Landsat TM/ETM + pixel-based image composites. Maps of forest structure and total aboveground biomass were created using a Random Forest (RF) implementation of Nearest Neighbor (NN) imputation. The imputation model had moderate to high plot-level accuracy across all forest attributes (R2 values of 0.42–0.69), as well as reasonable attribute predictions and error estimates (for example, canopy cover above 2 m on validation plots averaged 35.77%, with an RMSE of 13.45%, while unsystematic and systematic agreement coefficients (ACuns and ACsys) had values of 0.63 and 0.97 respectively). Additionally, forest attributes displayed consistent trends in relation to the time since and magnitude of wildfires, indicating model predictions captured the dominant ecological patterns and processes in these forests. Acknowledging methodological and conceptual challenges based upon the use of lidar plots from transects, this study demonstrates that using lidar plots and pixel compositing in imputation mapping can provide forest inventory and monitoring information for regions lacking ongoing or up-to-date field data collection programs

    The Balloon Analog Insurance Task (BAIT): A Behavioral Measure of Protective Risk Management

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    Prior methods used to assess individual differences related to risk have not focused on an important component of risk management: how willing individuals are to pay for or take actions to insure what they already have. It is not clear whether this type of protective risk management taps into the same individual differences as does risk taking propensity measured by existing risk taking tasks. We developed a novel task to assess protective risk management, the Balloon Analog Insurance Task (BAIT), which is modeled after the Balloon Analog Risk Task (BART). In the BAIT, individuals are forced to decide how much money they are willing to pay in order to insure a specific fraction of their prior winnings given changing but imprecise levels of risk of monetary loss. Participants completed the BART and BAIT for real monetary rewards, and completed six self report questionnaires. The amount of insurance purchased on the BAIT was positively correlated with scores on the Intolerance of Uncertainty Scale and on the Checking scale of the revised Obsessive Compulsive Inventory. Conversely, the amount of insurance purchased was negatively correlated with scores on the Domain Specific Risk Taking Questionnaire, and on the Psychopathic Personality Inventory (PPI). Furthermore, relationships between insurance purchased and these scales remained significant after controlling for the BART in linear regression analyses, and the BART was only a significant predictor for measures on one scale - the PPI. Our results reveal that behavior on the BAIT taps into a number of individual differences that are not related to behavior on another measure of risk taking. We propose that the BAIT may provide a useful complement to the BART in the assessment of risk management style

    A 'Performative' Social Movement: The Emergence of Collective Contentions within Collaborative Governance

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    The enmeshment of urban movements in networks of collaborative governance has been characterised as a process of co-option in which previously disruptive contentions are absorbed by regimes and reproduced in ways that do not threaten the stability of power relations. Applying a theoretical framework drawn from feminist philosopher Judith Butler this paper directs attention to the development of collective oppositional identities that remain embedded in conventional political processes. In a case study of the English tenants' movement, it investigates the potential of regulatory discourses that draw on market theories of performative voice to offer the collectivising narratives and belief in change that can generate the emotional identification of a social movement. The paper originates the concept of the ‘performative social movement’ to denote the contentious claims that continue to emerge from urban movements that otherwise appear quiescent

    Variables influencing the neural correlates of perceived risk of physical harm

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    Abstract Many human activities involve a risk of physical harm. However, not much is known about the specific brain regions involved in decision making regarding these risks. To explore the neural correlates of risk perception for physical harms, 19 participants took part in an event-related fMRI study while rating risky activities. The scenarios varied in level of potential harm (e.g., paralysis vs. stubbed toe), likelihood of injury (e.g., 1 chance in 100 vs. 1 chance in 1,000), and format (frequency vs. probability). Networks of brain regions were responsive to different aspects of risk information. Cortical language-processing areas, the middle temporal gyrus, and a region around the bed nucleus of stria terminalis responded more strongly to high-harm conditions. Prefrontal areas, along with subcortical ventral striatum, responded preferentially to highlikelihood conditions. Participants rated identical risks to be greater when information was presented in frequency format rather than probability format. These findings indicate that risk assessments for physical harm engage a broad network of brain regions that are sensitive to the severity of harm, the likelihood of risk, and the framing of risk information

    Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

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    Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file
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