A continuous aggregated accumulation model of recognition judgments.

Area of Science:

• Cognitive Psychology
• Neuroscience
• Memory Research

Background:

• Recognition memory involves two processes: recollection (remember) and familiarity (know).
• Existing single-process and dual-process models struggle to explain the timing of these memory responses.
• A paradox exists: familiarity is faster than recollection, yet 'remember' responses are often faster than 'know' responses.

Purpose of the Study:

• To propose and test a new model of recognition memory that accounts for the time course of familiarity and recollection.
• To resolve the paradoxical timing differences between remember and know responses in recognition tasks.
• To quantitatively model the interplay of confidence, accuracy, and response type on reaction time.

Main Methods:

• Developed a novel dual-process model analyzing the detailed time course of recollection and familiarity.
• Incorporated factors like item familiarity, recollection strength, and response criteria into the model.
• Validated the model using a 12-parameter quantitative approach, comparing predicted and observed reaction times.

Main Results:

• The proposed model successfully explains why average 'know' response times can be slower than 'remember' response times.
• It accounts for 'know' responses driven by high familiarity (fast) and those with low familiarity/recollection (slow).
• The 12-parameter model demonstrated the best fit between expected and observed reaction times across tested models.

Conclusions:

• The new model provides a more comprehensive understanding of recognition memory by integrating temporal dynamics.
• It resolves the familiarity-recollection timing paradox by considering response categorization of low-familiarity, slow-recollection items.
• This framework offers a robust quantitative approach to studying recognition memory processes and their timing.