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Adaptation in face animacy perception: An event-related potential study.

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The study reveals a "face animacy aftereffect" (FAAE): adapting to real faces biases perception towards inanimate, while adapting to artificial faces biases towards animate. This highlights how AI blurs real and artificial face distinctions.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Artificial Intelligence

Background:

  • The distinction between real and artificial faces is blurring due to AI.
  • Perception of animacy in faces is a growing area of interest.
  • Understanding how humans perceive animacy is crucial in the age of AI.

Purpose of the Study:

  • To investigate the perception of animacy in faces using an adaptation paradigm.
  • To explore the psychological and neural mechanisms underlying face animacy perception.
  • To examine the impact of adapting to real versus artificial faces on subsequent animacy judgments.

Main Methods:

  • A morphing continuum of real and artificial faces was created.
  • Participants judged face animacy after adapting to either a real or an artificial face.
  • Electroencephalography (EEG) was used to record event-related potentials (ERPs).

Main Results:

  • The face animacy aftereffect (FAAE) was observed: adaptation to real faces led to judging ambiguous faces as inanimate, and vice versa.
  • EEG analysis showed modulations in late positive potential (LPP) amplitude and N250r/LPP latencies.
  • Neural responses differed based on whether subsequent faces were congruent or incongruent with the adaptation stimulus.

Conclusions:

  • The FAAE demonstrates a clear perceptual bias influenced by adaptation to face animacy.
  • Modulations in LPP and N250r/LPP serve as neural correlates for face animacy adaptation.
  • These findings provide insights into the neural basis of distinguishing real from artificial faces.