Disentangling objects' contextual associations from perceptual and conceptual attributes using time-resolved neural...

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Visual Perception

Background:

• Humans integrate object knowledge (perceptual, conceptual, contextual) for recognition.
• Temporal dynamics of perceptual and conceptual object properties in neural signals are studied.
• Unique neural representation of contextual associations remains unclear.

Purpose of the Study:

• To investigate how the brain processes perceptual, conceptual, and contextual dimensions of object knowledge over time.
• To determine if and when contextual associations are uniquely represented in neural signals.
• To explore the temporal dynamics of object knowledge representation using electroencephalography (EEG).

Main Methods:

• Representational similarity analysis (RSA) applied to EEG data.
• Behavioral models of perceptual, conceptual, and contextual properties derived from human similarity judgments of 190 object concepts (images/words).
• Correlation of behavioral models with neural patterns from two EEG datasets during passive object viewing.

Main Results:

• Perceptual features dominated early EEG responses to object images.
• Conceptual features emerged later in the neural signal.
• Contextual associations were reflected in neural patterns but largely overlapped with conceptual models, indicating limited unique representation during passive viewing.

Conclusions:

• The brain integrates perceptual and conceptual information for visual object processing.
• Contextual attributes of objects may not be uniquely represented under passive viewing conditions.
• High-temporal-resolution EEG combined with behavioral models advances understanding of object knowledge encoding.