9 found
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  1.  4
    The simultaneous type, serial token model of temporal attention and working memory.Howard Bowman & Brad Wyble - 2007 - Psychological Review 114 (1):38-70.
  2.  44
    Strategic regulation of cognitive control by emotional salience: a neural network model.Bradley Wyble, Dinkar Sharma & Howard Bowman - 2008 - Cognition and Emotion 22 (6):1019-1051.
  3.  3
    Effect of tDCS Over the Right Inferior Parietal Lobule on Mind-Wandering Propensity.Sean Coulborn, Howard Bowman, R. Chris Miall & Davinia Fernández-Espejo - 2020 - Frontiers in Human Neuroscience 14.
  4.  76
    PITL2MONA: Implementing a Decision Procedure for Propositional Interval Temporal Logic.Rodolfo Gómez & Howard Bowman - 2004 - Journal of Applied Non-Classical Logics 14 (1-2):105-148.
    Interval Temporal Logic is a finite-time linear temporal logic with applications in hardware verification, temporal logic programming and specification of multimedia documents. Due to the logic's non-elementary complexity, efficient ITL-based verification tools have been difficult to develop, even for propositional subsets. MONA is an efficient implementation of an automata-based decision procedure for the logic WS1S. Despite the non-elementary complexity of WS1S, MONA has been successfully applied in problems such as hardware synthesis, protocol verification and theorem proving. Here we consider a (...)
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  5.  21
    Placing meta-stable states of consciousness within the predictive coding hierarchy: The deceleration of the accelerated prediction error.Amirali Shirazibeheshti, Jennifer Cooke, Srivas Chennu, Ram Adapa, David K. Menon, Seyed Ali Hojjatoleslami, Adrien Witon, Ling Li, Tristan Bekinschtein & Howard Bowman - 2018 - Consciousness and Cognition 63:123-142.
  6.  11
    Illusions of integration are subjectively impenetrable: Phenomenological experience of Lag 1 percepts during dual-target RSVP.Luca Simione, Elkan G. Akyürek, Valentina Vastola, Antonino Raffone & Howard Bowman - 2017 - Consciousness and Cognition 51:181-192.
  7.  4
    Understanding visual attention with RAGNAROC: A reflexive attention gradient through neural AttRactOr competition.Brad Wyble, Chloe Callahan-Flintoft, Hui Chen, Toma Marinov, Aakash Sarkar & Howard Bowman - 2020 - Psychological Review 127 (6):1163-1198.
    A quintessential challenge for any perceptual system is the need to focus on task-relevant information without being blindsided by unexpected, yet important information. The human visual system incorporates several solutions to this challenge, one of which is a reflexive covert attention system that is rapidly responsive to both the physical salience and the task-relevance of new information. This paper presents a model that simulates behavioral and neural correlates of reflexive attention as the product of brief neural attractor states that are (...)
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  8.  4
    On the limits of evidence accumulation of the preconscious percept.Alberto Avilés, Howard Bowman & Brad Wyble - 2020 - Cognition 195 (C):104080.
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  9.  57
    Attention is more than prediction precision.Howard Bowman, Marco Filetti, Brad Wyble & Christian Olivers - 2013 - Behavioral and Brain Sciences 36 (3):206-208.
    A cornerstone of the target article is that, in a predictive coding framework, attention can be modelled by weighting prediction error with a measure of precision. We argue that this is not a complete explanation, especially in the light of ERP (event-related potentials) data showing large evoked responses for frequently presented target stimuli, which thus are predicted.
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