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A context-sensitive and non-linguistic approach to abstract concepts.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2022

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Inner speech.

Peter Langland-Hassan¹

¹Department of Philosophy, University of Cincinnati, Cincinnati, Ohio, USA.

Wiley Interdisciplinary Reviews. Cognitive Science

|September 19, 2020

Summary

Inner speech, or "talking in your head," supports abstract thought and executive functions. New AI methods translate inner speech neural signals, opening doors for novel applications and interventions.

Area of Science:

Cognitive Science
Neuroscience
Philosophy of Mind

Background:

Inner speech, also known as verbal thought, is a fundamental aspect of human consciousness.
It plays crucial roles in abstract thinking, metacognition, memory, and executive functions.
Its neural underpinnings and cognitive functions are increasingly understood.

Purpose of the Study:

To explore the multifaceted roles of inner speech in cognition.
To investigate the relationship between inner speech and auditory verbal hallucinations (AVHs) in schizophrenia.
To introduce novel AI-driven methods for decoding inner speech.

Main Methods:

Review of existing cognitive and neuroscientific research on inner speech.
Analysis of the proposed link between inner speech and AVHs.

Keywords:

inner speech, language, auditory verbal hallucination, metacognition, inner voice

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Description of recent advancements in artificial intelligence for translating neural and neuromuscular signals of inner speech.

Main Results:

Inner speech is vital for higher-order cognitive processes.
A common hypothesis suggests AVHs arise from misattributing self-generated inner speech to external sources.
AI can translate neural signatures of inner speech into audible speech.

Conclusions:

Inner speech is a complex cognitive phenomenon with significant implications for understanding thought and consciousness.
The AI-driven translation of inner speech signals offers potential for new therapeutic interventions.
Further research is needed to fully elucidate the mechanisms and applications of inner speech decoding.