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Introduction to Cognitive Psychology01:20

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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Neurodynamical Computing at the Information Boundaries of Intelligent Systems.

Joseph D Monaco1, Grace M Hwang2

  • 1Dept of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD USA.

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|August 12, 2024
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Summary
This summary is machine-generated.

Biological intelligence remains elusive for artificial intelligence. This perspective proposes a shift from brain-as-computer models to a dynamical systems approach, integrating embodied cognition and perceptual control theory for a new understanding of neural computation.

Keywords:
Artificial intelligenceComputational neuroscienceDynamical systemsEmbodied cognitionPerceptual control theoryRobotics

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Artificial Intelligence

Background:

  • Current artificial intelligence (AI) models lack key features of biological intelligence.
  • Cognitivist brain-as-computer theories present methodological and epistemic biases.
  • Existing frameworks fail to fully capture the complexity of neural mechanisms.

Purpose of the Study:

  • To challenge prevailing AI and cognitive science paradigms.
  • To propose an alternative framework for understanding biological intelligence.
  • To bridge theoretical gaps in computational neuroscience.

Main Methods:

  • Synthesizing historical approaches to intelligent systems.
  • Integrating dynamical systems theory and perceptual control theory.
  • Reconceptualizing cell assemblies as reentrant dynamical flows.

Main Results:

  • Identified limitations in cognitivist and brain-as-computer theories.
  • Proposed cell assemblies as a minimal supraneuronal organizational level.
  • Highlighted the role of embodiment and situational embedding in neural computation.

Conclusions:

  • A shift towards embodied cognition and dynamical systems is necessary for AI and neuroscience.
  • Reentrant dynamical flows (cell assemblies) offer a neurodynamical base layer for computation.
  • This integrated approach can overcome neurosymbolic stalemates in AI research.