感觉系统
计算机科学
人口
神经编码
编码(社会科学)
灵活性(工程)
人工智能
刺激(心理学)
预测编码
信息集成
背景(考古学)
计算模型
机器学习
上下文模型
适应性行为
感觉线索
人工神经网络
任务(项目管理)
信息处理
沟通
编码(内存)
信息论
作者
Jonas Terlau,Silke Ethofer,Georgios Naros,Yvonne Fonken,Jack J. Lin,Robert T. Knight,Randolph F. Helfrich
标识
DOI:10.1073/pnas.2520444122
摘要
Cognitive flexibility relies on the continuous accumulation and integration of sensory evidence to guide adaptive behavior. In natural environments, behaviorally relevant information unfolds sequentially over time and is constantly evaluated against prior knowledge, task rules, and current demands. Integration of these inputs poses a computational challenge: How is temporally unfolding, predictive information integrated into a stable representation, while preserving the discriminability and flexibility to map individual stimuli to competing context-specific actions? Using large-scale human intracranial electroencephalography, we assessed how neural population activity integrates behaviorally relevant information across multiple sensory events that sequentially unfold over time and jointly determine the current context. The results uncover that the population geometry supports the emergence of conjunctive coding subspaces that integrate prior information with current sensory evidence and jointly define the temporal context that mediates behavioral benefits. Evidence accumulation diversifies the population responses distributed across the cortex, increasing the representational space that embeds context-dependent stimulus-action mappings. Hence, context-dependent sensory coding might constitute the neural basis underlying adaptive human behavior. In sum, these results demonstrate how neural population activity balances integrating predictive information with preserving stimulus discriminability to enable flexibility, while minimizing interference.
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