Non-Markovian systems, phenomenology, and the challenges of capturing meaning and context - comment on Parr, Pezzulo, and Friston (2025) [0.03%]
非马尔可夫系统、现象学以及捕捉意义和背景的挑战——对Parr，Pezzulo和Friston（2025）的评论
Mahault Albarracin,Dalton A R Sakthivadivel
Mahault Albarracin
Paying attention to process [0.03%]
重视过程
Ryan Singh,Alexander Tschantz,Christopher L Buckley
Ryan Singh
Elliot Murphy
Elliot Murphy
How deep will you go? Hierarchy in predictive coding and transformers [0.03%]
预测编码和变压器中的层次结构：你愿意深入到什么程度？
Jeffrey F Queißer,Henrique Oyama,Jun Tani
Jeffrey F Queißer
Beyond individuals: Collective predictive coding for memory, attention, and the emergence of language [0.03%]
超越个体：记忆、注意以及语言涌现的集体预测编码理论
Tadahiro Taniguchi
Tadahiro Taniguchi
Berfin Bastug,Urte Roeber,Erich Schröger
Berfin Bastug
The brain learns statistical regularities in sensory sequences, enhancing behavioral performance for predictable stimuli while impairing behavioral performance for unpredictable stimuli. While previous research has shown that violations of ...
Thomas Parr,Giovanni Pezzulo,Karl Friston
Thomas Parr
This paper asks what predictive processing models of brain function can learn from the success of transformer architectures. We suggest that the reason transformer architectures have been successful is that they implicitly commit to a non-M...
Visuo-spatial working memory abilities modulate mental rotation: Evidence from event-related potentials [0.03%]
工作记忆容量影响思维旋转的脑电研究
Binglei Zhao,Sergio Della Sala,Elena Gherri
Binglei Zhao
In the present study, we investigated whether differences in spatial working memory (SWM) abilities - assessed through the Corsi block task (CBT) - impact the processes of mental rotation (MR) engaged during a classic letter rotation task. ...
The diversity of possible constitutive components in cognitive neurosciences [0.03%]
认知神经科学研究中可能的构成成分的多样性
Loïc P Heurley
Loïc P Heurley
I aim to discuss which constitutive components are essential for explaining how the mind works. Rather than focusing on some specific components, I emphasize their diversity. Thus, I seek to complement the recent mechanistic proposal by und...
Advancing mechanistic explanations through natural and artificial embodied cognitive systems [0.03%]
基于自然和人工具身认知系统的机制解释研究进展
Fernando Marmolejo-Ramos,Julian Tejada,Alejandra Ciria et al.
Fernando Marmolejo-Ramos et al.
Mougenot and Matheson propose that mechanistic models can explain behavior by describing the complex interactions among components of the brain, body, and environment as an integrated system, which aligns with embodied cognition. However, w...