parallel memories
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2019 ◽  
Vol 32 (15) ◽  
Author(s):  
Giulio Stramondo ◽  
Cătălin Bogdan Ciobanu ◽  
Cees Laat ◽  
Ana Lucia Varbanescu
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Author(s):  
Giulio Stramondo ◽  
Cătălin Bogdan Ciobanu ◽  
Ana Lucia Varbanescu ◽  
Cees de Laat
Keyword(s):  

Author(s):  
L. Stornaiuolo ◽  
M. Rabozzi ◽  
D. Sciuto ◽  
M. D. Santambrogio ◽  
G. Stramondo ◽  
...  
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2017 ◽  
Vol 114 (23) ◽  
pp. E4666-E4675 ◽  
Author(s):  
Martín Klappenbach ◽  
Ayelén Nally ◽  
Fernando Federico Locatelli

The neurobiology of learning and memory has been mainly studied by focusing on pure aversive or appetitive experiences. Here, we challenged this approach considering that real-life stimuli come normally associated with competing aversive and appetitive consequences and that interaction between conflicting information must be intrinsic part of the memory processes. We used Neohelice crabs, taking advantage of two well-described appetitive and aversive learning paradigms and combining them in a single training session to evaluate how this affects memory. We found that crabs build separate appetitive and aversive memories that compete during retrieval but not during acquisition. Which memory prevails depends on the balance between the strength of the unconditioned stimuli and on the motivational state of the animals. The results indicate that after a mix experience with appetitive and aversive consequences, parallel memories are established in a way that appetitive and aversive information is stored to be retrieved in an opportunistic manner.


2012 ◽  
Vol 22 (4-5) ◽  
pp. 574-613 ◽  
Author(s):  
MATTHEW NAYLOR ◽  
COLIN RUNCIMAN

AbstractA new version of a special-purpose processor for running lazy functional programs is presented. This processor – the Reduceron – exploits parallel memories and dynamic analyses to increase evaluation speed, and is implemented using reconfigurable hardware. Compared to a more conventional functional language implementation targeting a standard RISC processor running on the same reconfigurable hardware, the Reduceron offers a significant improvement in run-time performance.


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