认知
代表(政治)
认知科学
感知
心理学
相似性(几何)
信息处理
人口
计算机科学
认知心理学
人工智能
神经科学
人口学
法学
社会学
图像(数学)
政治
政治学
作者
Nikolaus Kriegeskorte,Rogier A. Kievit
标识
DOI:10.1016/j.tics.2013.06.007
摘要
The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure.
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