Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model

<div>Input variations in object representations. (a) Semantic overlap between 2 objects (left and right columns) consists in activating identical neurons in the two objects layers (black squares with red squares overlapping). Examples are given for 2, 5, and 10% overlaps. (b) Representation noise is introduced by randomly activating neurons each time an item is presented. For clarity, objects are shown as linear arrays of 256 neurons. 90 objects are presented for each noise level.</div>

Computational Intelligence and Neuroscience

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Figure 2: Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model 

Figure 2 | Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model 