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21 results

Page 1 of 2

  • 6 - Human Intelligence and Network Neuroscience
  • from Part II - Theories, Models, and Hypotheses
  • Edited by Aron K. Barbey, University of Illinois, Urbana-Champaign, Sherif Karama, McGill University, Montréal, Richard J. Haier, University of California, Irvine
  • Book: The Cambridge Handbook of Intelligence and Cognitive Neuroscience
  • Published online: 11 June 2021
  • Print publication: 01 July 2021, pp 102-122
  • View extract

    Summary

    Flexibility is central to human intelligence and is made possible by the brain’s remarkable capacity to reconfigure itself – to continually update prior knowledge on the basis of new information and to actively generate internal predictions that guide adaptive behavior and decision making. Rather than lying dormant until stimulated, contemporary research conceives of the brain as a dynamic and active inference generator that anticipates incoming sensory inputs, forming hypotheses about that world that can be tested against sensory signals that arrive in the brain (Clark, 2013; Friston, 2010). Plasticity is therefore critical for the emergence of human intelligence, providing a powerful mechanism for updating prior beliefs, generating dynamic predictions about the world, and adapting in response to ongoing changes in the environment (Barbey, 2018). This perspective provides a catalyst for contemporary research on human intelligence, breaking away from the classic view that general intelligence (g) originates from individual differences in a fixed set of cortical regions or a singular brain network (for reviews, see Haier, 2017; Posner & Barbey, 2020).

The Cambridge Handbook of Intelligence and Cognitive Neuroscience
  • The Cambridge Handbook of Intelligence and Cognitive Neuroscience
  • Edited by Aron K. Barbey, Sherif Karama, Richard J. Haier
  • Published online: 11 June 2021
  • Print publication: 01 July 2021
  • View description
    This handbook introduces the reader to the thought-provoking research on the neural foundations of human intelligence. Written for undergraduate or graduate students, practitioners, and researchers in psychology, cognitive neuroscience, and related fields, the chapters summarize research emerging from the rapidly developing neuroscience literature on human intelligence. The volume focusses on theoretical innovation and recent advances in the measurement, modelling, and characterization of the neurobiology of intelligence differences, especially from brain imaging studies. It summarizes fundamental issues in the characterization and measurement of general intelligence, and surveys multidisciplinary research consortia and large-scale data repositories for the study of general intelligence. A systematic review of neuroimaging methods for studying intelligence is provided, including structural and diffusion-weighted MRI techniques, functional MRI methods, and spectroscopic imaging of metabolic markers of intelligence.
  • 25 - Moral Reasoning: A Network Neuroscience Perspective
  • from Part III - Intentionality-Based Forms of the Imagination
    • By
  • Edited by Anna Abraham, University of Georgia
  • Book: The Cambridge Handbook of the Imagination
  • Published online: 26 May 2020
  • Print publication: 18 June 2020, pp 406-424
  • View extract

    Summary

    Through imagining possible actions and considering their consequences, we are able to reason about the morality of behavior – judging whether an action is morally right or wrong. Neuroscience research indicates that moral reasoning depends on a complex, broadly distributed network of brain regions that interact in a both cooperative and competitive manner. Understanding the underlying neurobiology that governs how these regions dynamically interact to produce patterns of behavior is therefore of interest to the field. Currently, prominent theories suggest that moral judgments (consequentialist or deontological) are the product of two distinct cognitive systems (i.e. a dual-process framework). Network neuroscience, an emerging field that measures and interprets brain activity through the framework of modern network science, is positioned to expand our understanding of this dual-process framework by examining how topological properties of networks influence consequentialist and deontological reasoning, and how these two processing systems interact in order to imagine hypothetical scenarios during complex deontological reasoning tasks. In this chapter, we review evidence from neuroscience that bears on our understanding of the dual-process moral reasoning framework and advance a network neuroscience perspective on the neurobiological substrates that underlie it.

  • Base-rate respect: From ecological rationality to dual processes
  • Aron K. Barbey, Steven A. Sloman
  • Journal: Behavioral and Brain Sciences / Volume 30 / Issue 3 / June 2007
  • Published online by Cambridge University Press: 29 October 2007, pp. 241-254
  • View abstract

    The phenomenon of base-rate neglect has elicited much debate. One arena of debate concerns how people make judgments under conditions of uncertainty. Another more controversial arena concerns human rationality. In this target article, we attempt to unpack the perspectives in the literature on both kinds of issues and evaluate their ability to explain existing data and their conceptual coherence. From this evaluation we conclude that the best account of the data should be framed in terms of a dual-process model of judgment, which attributes base-rate neglect to associative judgment strategies that fail to adequately represent the set structure of the problem. Base-rate neglect is reduced when problems are presented in a format that affords accurate representation in terms of nested sets of individuals.

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