Visual Population Codes: Toward a Common Multivariate Framework for Cell Recording and Functional Imaging (Hardcover)

Nikolaus Kriegeskorte, Gabriel Kreiman

  • 出版商: MIT
  • 出版日期: 2011-11-04
  • 售價: $2,128
  • 貴賓價: 9.8$2,085
  • 語言: 英文
  • 頁數: 656
  • 裝訂: Hardcover
  • ISBN: 0262016249
  • ISBN-13: 9780262016247
  • 相關分類: 人工智慧大數據 Big-dataData Science
  • 立即出貨(限量) (庫存=2)

相關主題

商品描述

Vision is a massively parallel computational process, in which the retinal image is transformed over a sequence of stages so as to emphasize behaviorally relevant information (such as object category and identity) and deemphasize other information (such as viewpoint and lighting). The processes behind vision operate by concurrent computation and message passing among neurons within a visual area and between different areas. The theoretical concept of "population code" encapsulates the idea that visual content is represented at each stage by the pattern of activity across the local population of neurons. Understanding visual population codes ultimately requires multichannel measurement and multivariate analysis of activity patterns. Over the past decade, the multivariate approach has gained significant momentum in vision research. Functional imaging and cell recording measure brain activity in fundamentally different ways, but they now use similar theoretical concepts and mathematical tools in their modeling and analyses. With a focus on the ventral processing stream thought to underlie object recognition, this book presents recent advances in our understanding of visual population codes, novel multivariate pattern-information analysis techniques, and the beginnings of a unified perspective for cell recording and functional imaging. It serves as an introduction, overview, and reference for scientists and students across disciplines who are interested in human and primate vision and, more generally, in understanding how the brain represents and processes information.

商品描述(中文翻譯)

視覺是一個大規模並行的計算過程,透過一系列階段的轉換,強調行為相關的資訊(例如物體類別和身份),並減弱其他資訊(例如視角和光線)。視覺背後的過程通過視覺區域內和不同區域之間的神經元之間的並行計算和信息傳遞來運作。"族群編碼"的理論概念將視覺內容表示為當地神經元族群的活動模式。理解視覺族群編碼最終需要多通道測量和多變量活動模式分析。在過去的十年中,多變量方法在視覺研究中取得了顯著的動力。功能成像和細胞記錄以根本不同的方式測量腦部活動,但它們現在在建模和分析中使用相似的理論概念和數學工具。本書聚焦於被認為是物體識別基礎的腦部腹側處理流程,介紹了對視覺族群編碼的最新進展、新穎的多變量模式信息分析技術,以及細胞記錄和功能成像的統一觀點的開端。它作為一本介紹、概述和參考,針對對人類和靈長類視覺感興趣的科學家和學生,以及對了解大腦如何表示和處理信息感興趣的跨學科人士。