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This study contrasts two consciousness theories, finding that "convergent" neurons, not "integrative" ones, better reflect conscious states, supporting the Global Neuronal Workspace theory over Integrated Information Theory.

Keywords:
complexityconsciousnessintegrated informationnoise correlationsprimary somatosensory cortexventral premotor

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Consciousness Studies

Background:

  • Prominent theories of consciousness, Global Neuronal Workspace (GNW) and Integrated Information Theory (IIT), emphasize complex neural networks for awareness.
  • GNW links subjective experience to frontoparietal network activity, while IIT focuses on network functional architecture.
  • Both theories often highlight the role of neural integration, but their specific predictions regarding neural activity and consciousness differ.

Purpose of the Study:

  • To test predictions derived from GNW and IIT mathematics regarding neural network properties and consciousness.
  • To functionally label neurons as 'convergent' or 'integrative' and analyze their behavior during induced loss of consciousness.
  • To directly contrast GNW and IIT within a single dataset of neuronal activity.

Main Methods:

  • Analysis of simultaneous neuronal recordings from primary somatosensory cortex (S1) and ventral premotor cortex (vPM) in nonhuman primates.
  • Stimulation with auditory, tactile, and audio-tactile stimuli during progressive anesthetization with propofol.
  • Functional labeling of neurons as convergent or integrative based on spiking responses, followed by characterization of their properties (neural complexity, noise correlation) during varying states of consciousness.

Main Results:

  • Contrary to IIT predictions, 'convergent' neurons exhibited more properties associated with consciousness (neural complexity, noise correlation) than 'integrative' neurons.
  • 'Convergent' neurons were more significantly impacted during the loss of consciousness compared to 'integrative' neurons.
  • Evidence supporting GNW was found, with 'neural ignition' (coactivation of S1 and vPM) being more frequent in conscious states.

Conclusions:

  • The study's findings support the Global Neuronal Workspace theory over Integrated Information Theory in explaining neural correlates of consciousness.
  • Convergent neuronal activity, rather than integrative activity as predicted by IIT, appears more closely linked to conscious states.
  • This research provides a direct, data-driven comparison of major consciousness theories using invasive electrophysiology.