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How We Remember (Brain Mechanisms of Episodic Memory)

List Price: $70.00
SKU:
9780262525336
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  • Product Details

    Author:
    Michael E. Hasselmo
    Format:
    Paperback
    Pages:
    378
    Publisher:
    MIT Press (August 16, 2013)
    Language:
    English
    ISBN-13:
    9780262525336
    ISBN-10:
    026252533X
    Weight:
    25.4oz
    Dimensions:
    7.13" x 9" x 0.83"
    Case Pack:
    20
    File:
    RandomHouse-PRH_Book_Company_PRH_PRT_Onix_full_active_D20260405T170602_155746831-20260405.xml
    Folder:
    RandomHouse
    List Price:
    $70.00
    As low as:
    $53.90
    Publisher Identifier:
    P-RH
    Discount Code:
    A
    QuickShip:
    Yes
    Audience:
    General/trade
    Country of Origin:
    United States
    Pub Discount:
    65
    Imprint:
    The MIT Press
  • Overview

    A novel perspective on the biological mechanisms of episodic memory, focusing on the encoding and retrieval of spatiotemporal trajectories.

    Episodic memory proves essential for daily function, allowing us to remember where we parked the car, what time we walked the dog, or what a friend said earlier. In How We Remember, Michael Hasselmo draws on recent developments in neuroscience to present a new model describing the brain mechanisms for encoding and remembering such events as spatiotemporal trajectories. He reviews physiological breakthroughs on the regions implicated in episodic memory, including the discovery of grid cells, the cellular mechanisms of persistent spiking and resonant frequency, and the topographic coding of space and time. These discoveries inspire a theory for understanding the encoding and retrieval of episodic memory not just as discrete snapshots but as a dynamic replay of spatiotemporal trajectories, allowing us to "retrace our steps" to recover a memory.

    In the main text of the book, he presents the model in narrative form, accessible to scholars and advanced undergraduates in many fields. In the appendix, he presents the material in a more quantitative style, providing mathematical descriptions appropriate for advanced undergraduates and graduate students in neuroscience or engineering.