Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, we consider various types of learning (perceptual, statistical, and rule/abstract) associated with vision in the past decades and argue that they represent differently specialized versions of the fundamental learning process, which must be captured in its entirety when applied to complex visual processes. We show why the generalized version of statistical learning can provide the appropriate setup for such a unified treatment of learning in vision, what computational framework best accommodates this kind of statistical learning, and what plausible neural scheme could feasibly implement this framework. Finally, we list the challenges that the field of statistical learning faces in fulfilling the promise of being the right vehicle for advancing our understanding of vision in its entirety.

József Fiser

Gábor Lengyel

Annual Review of Vision Science

视觉科学年度回顾回顾了视觉科学的进展，视觉科学是一组交叉学科，涉及心理学、神经科学、计算机科学、细胞生物学和遗传学以及临床医学。该杂志涵盖了广泛的主题和技术，包括光学、视网膜、中央视觉处理、视觉感知、眼球运动、视觉发育、视觉模型、计算机视觉，以及视觉疾病、功能障碍和视力恢复的机制。视觉研究是许多科学领域取得进展的核心，这本新期刊将探索和揭示将视觉研究与生物学、行为、计算、工程和医学联系起来的联系。

The Annual Review of Vision Science is an annual journal that focuses on the latest advancements in the field of vision science. Vision science is an interdisciplinary field that encompasses psychology, neuroscience, computer science, cell biology, genetics, and clinical medicine. This journal covers a wide range of topics and techniques, including optics, retina, central visual processing, visual perception, eye movements, visual development, visual modeling, computer vision, as well as the mechanisms of visual diseases, disorders, and vision restoration. Vision research plays a central role in the progress of many scientific fields, and this journal aims to explore and reveal the connections between vision research and biology, behavior, computation, engineering, and medicine.

《Annual Review of Vision Science》是一本专注于视觉科学领域的年度回顾期刊，涵盖了视觉科学的最新进展。视觉科学是一个跨学科的领域，涉及心理学、神经科学、计算机科学、细胞生物学、遗传学和临床医学等多个学科。该期刊讨论的主题和技术范围广泛，包括光学、视网膜、中央视觉处理、视觉感知、眼球运动、视觉发育、视觉模型、计算机视觉，以及视觉疾病、功能障碍和视力恢复的机制。视觉研究在多个科学领域的进展中扮演着核心角色，本期刊将探索和揭示视觉研究与生物学、行为、计算、工程和医学之间的联系。

Category	Quartile
医学	2
医学, 眼科学	1
医学, 神经科学	2

Statistical Learning in Vision

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