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Related Experiment Video

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Perspectives on Neuroscience
26:41

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Published on: July 31, 2007

Predictive coding or evidence accumulation? False inference and neuronal fluctuations.

Guido Hesselmann1, Sepideh Sadaghiani, Karl J Friston

  • 1Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, Gif sur Yvette, France.

Plos One
|April 7, 2010
PubMed
Summary

Neural activity in sensory areas guides perceptual decisions toward accurate inference. This brain activity reflects the precision of prediction errors, aligning with predictive coding models.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Perception

Background:

  • Perceptual decisions rely on inferring external causes from sensory input.
  • Understanding the neural basis of these inferences is crucial for cognitive neuroscience.

Purpose of the Study:

  • To investigate how ongoing neural activity in sensory cortices influences perceptual decision-making.
  • To examine whether neural activity biases decisions towards correct inference or specific percepts.

Main Methods:

  • Two independent functional magnetic resonance imaging (fMRI) experiments using a sparse event-related design.
  • Visual experiment: forced-choice discrimination of motion coherence in random dot kinematograms.
  • Auditory experiment: free-response detection of near-threshold acoustic stimuli.

Main Results:

  • Neuronal activity in sensory areas (extrastriate visual, early auditory cortex) biased perceptual decisions towards correct inference.
  • Activity preceding correct detections (hits) was significantly higher than activity preceding misses or false alarms.
  • This pattern suggests neural activity reflects prediction error precision, not just sensory evidence or errors.

Conclusions:

  • Cortical activity in sensory brain regions plays a critical role in biasing perceptual decisions.
  • Findings support predictive coding models and the free-energy principle by linking neural activity to prediction error precision.
  • Neural signals in sensory areas contribute to the accuracy of perceptual inference.