scholarly journals Olfactory memory capacity of the cricket Gryllus bimaculatus

2006 ◽  
Vol 2 (4) ◽  
pp. 608-610 ◽  
Author(s):  
Yukihisa Matsumoto ◽  
Makoto Mizunami
Keyword(s):  
Learning And Memory ◽  
Storage Capacity ◽  
Memory Capacity ◽  
Neural Mechanisms ◽  
Olfactory Learning ◽  
Memory Storage ◽  
Gryllus Bimaculatus ◽  
Water Reward ◽  
Olfactory Memory ◽  
Stimulus Arrangement

Olfactory learning in insects is a useful model for studying neural mechanisms underlying learning and memory, but memory storage capacity for olfactory learning in insects has not been studied. We investigate whether crickets are capable of simultaneously memorizing seven odour pairs. Fourteen odours were grouped into seven A/B pairs, and crickets in one group were trained to associate A odours with water reward and B odours with saline punishment for all the seven pairs. Crickets in another group were trained with the opposite stimulus arrangement. Crickets in all the groups exhibited significantly greater preference for the odours associated with water reward for all the seven odour pairs. We conclude that crickets are capable of memorizing seven odour pairs at the same time.

The visual arrays task…visual storage capacity or attention control?

2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  
Keyword(s):  
Working Memory ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Data Sets ◽  
Independent Data ◽  
Visual Storage ◽  
Design Selection ◽  
The Relationship

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.

Effective Neuronal Learning with Ineffective Hebbian Learning Rules

2001 ◽  
Vol 13 (4) ◽  
pp. 817-840 ◽  
Author(s):  
Gal Chechik ◽  
Isaac Meilijson ◽  
Eytan Ruppin
Keyword(s):  
Hebbian Learning ◽  
Memory Capacity ◽  
Network Size ◽  
Memory Storage ◽  
Effective Learning ◽  
Regulatory Processes ◽  
Level Information ◽  
Zero Sum ◽  
Synaptic Learning ◽  
Weight Correction

In this article we revisit the classical neuroscience paradigm of Hebbian learning. We find that it is difficult to achieve effective associative memory storage by Hebbian synaptic learning, since it requires network-level information at the synaptic level or sparse coding level. Effective learning can yet be achieved even with nonsparse patterns by a neuronal process that maintains a zero sum of the incoming synaptic efficacies. This weight correction improves the memory capacity of associative networks from an essentially bounded one to a memory capacity that scales linearly with network size. It also enables the effective storage of patterns with multiple levels of activity within a single network. Such neuronal weight correction can be successfully carried out by activity-dependent homeostasis of the neuron's synaptic efficacies, which was recently observed in cortical tissue. Thus, our findings suggest that associative learning by Hebbian synaptic learning should be accompanied by continuous remodeling of neuronally driven regulatory processes in the brain.

scholarly journals Neural mechanisms of interference control in working memory capacity

2017 ◽  
Vol 39 (2) ◽  
pp. 772-782 ◽  
Author(s):  
Jessica Bomyea ◽  
Charles T. Taylor ◽  
Andrea D. Spadoni ◽  
Alan N. Simmons
Keyword(s):  
Working Memory ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Neural Mechanisms ◽  
Interference Control

Distributed Plasticity for Olfactory Learning and Memory in the Honey Bee Brain

2011 ◽  
pp. 393-408 ◽  
Author(s):  
Brian H. Smith ◽  
Ramón Huerta ◽  
Maxim Bazhenov ◽  
Irina Sinakevitch
Keyword(s):  
Learning And Memory ◽  
Honey Bee ◽  
Olfactory Learning

scholarly journals Neural mechanisms of AVPR1A RS3-RS1 haplotypes that impact verbal learning and memory

NeuroImage ◽  
2020 ◽  
Vol 222 ◽  
pp. 117283
Author(s):  
Yan Zhang ◽  
Dan Zhu ◽  
Peng Zhang ◽  
Wei Li ◽  
Wen Qin ◽  
...  
Keyword(s):  
Learning And Memory ◽  
Verbal Learning ◽  
Neural Mechanisms

scholarly journals Conditional Rescue of Olfactory Learning and Memory Defects in Mutants of the 14-3-3ζ Geneleonardo

2001 ◽  
Vol 21 (21) ◽  
pp. 8417-8425 ◽  
Author(s):  
Nisha Philip ◽  
Summer F. Acevedo ◽  
Efthimios M. C. Skoulakis
Keyword(s):  
Learning And Memory ◽  
Olfactory Learning
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