Details

Autor(en) / Beteiligte

• Delhaye, Emma
• D'Innocenzo, Giorgia
• Raposo, Ana
• Coco, Moreno I

Titel

The upside of cumulative conceptual interference on exemplar-level mnemonic discrimination

Ist Teil von

• Memory & cognition, 2024-05

Ort / Verlag

United States: Springer

Erscheinungsjahr

2024

Link zum Volltext

Quelle

Business Source Ultimate (EBSCOhost)

Beschreibungen/Notizen

• Although long-term visual memory (LTVM) has a remarkable capacity, the fidelity of its episodic representations can be influenced by at least two intertwined interference mechanisms during the encoding of objects belonging to the same category: the capacity to hold similar episodic traces (e.g., different birds) and the conceptual similarity of the encoded traces (e.g., a sparrow shares more features with a robin than with a penguin). The precision of episodic traces can be tested by having participants discriminate lures (unseen objects) from targets (seen objects) representing different exemplars of the same concept (e.g., two visually similar penguins), which generates interference at retrieval that can be solved if efficient pattern separation happened during encoding. The present study examines the impact of within-category encoding interference on the fidelity of mnemonic object representations, by manipulating an index of cumulative conceptual interference that represents the concurrent impact of capacity and similarity. The precision of mnemonic discrimination was further assessed by measuring the impact of visual similarity between targets and lures in a recognition task. Our results show a significant decrement in the correct identification of targets for increasing interference. Correct rejections of lures were also negatively impacted by cumulative interference as well as by the visual similarity with the target. Most interestingly though, mnemonic discrimination for targets presented with a visually similar lure was more difficult when objects were encoded under lower, not higher, interference. These findings counter a simply additive impact of interference on the fidelity of object representations providing a finer-grained, multi-factorial, understanding of interference in LTVM.