scholarly journals The Generalized Quantum Episodic Memory Model

2016 ◽  
Vol 41 (8) ◽  
pp. 2089-2125 ◽  
Author(s):  
Jennifer S. Trueblood ◽  
Pernille Hemmer
Keyword(s):  
Episodic Memory ◽  
Memory Model

scholarly journals Evaluative conditioning as memory-based judgment

2018 ◽  
Author(s):  
Christoph Stahl ◽  
Frederik Aust
Keyword(s):  
Episodic Memory ◽  
Future Development ◽  
Formal Model ◽  
Evaluative Conditioning ◽  
Present Approach ◽  
Process Models ◽  
Dual Process ◽  
Memory Model ◽  
Challenges And Opportunities ◽  
Attitude Learning

The article proposes a view of evaluative conditioning (EC) as resulting from judgments based on learning instances stored in memory. It is based on the formal episodic memory model MINERVA 2. Additional assumptions specify how the information retrieved from memory is used to inform specific evaluative dependent measures. The present approach goes beyond previous accounts in that it uses a well-specified formal model of episodic memory; it is however more limited in scope as it aims at explaining EC phenomena that do not involve reasoning processes. The article illustrates how the memory-based-judgment view accounts for several empirical findings in the EC literature that are often discussed as evidence for dual-process models of attitude learning. It sketches novel predictions, discusses limitations of the present approach, and identifies challenges and opportunities for its future development.

scholarly journals HOW A PEAK CAN BE SEARCHED FOR IN AN ALMOST EVERYWHERE FLATLAND OF ALTITUDE ZERO? — TINY FLAT ISLAND IN HUGE LAKE

2014 ◽  
pp. 32-37
Author(s):  
Akira Imada
Keyword(s):  
Neural Network ◽  
Associative Memory ◽  
Configuration Space ◽  
Fitness Landscape ◽  
Spiking Neurons ◽  
The Other ◽  
Memory Model ◽  
Almost Everywhere

We are exploring a weight configuration space searching for solutions to make our neural network with spiking neurons do some tasks. For the task of simulating an associative memory model, we have already known one such solution — a weight configuration learned a set of patterns using Hebb’s rule, and we guess we have many others which we have not known so far. In searching for such solutions, we observed that the so-called fitness landscape was almost everywhere completely flatland of altitude zero in which the Hebbian weight configuration is the only unique peak, and in addition, the sidewall of the peak is not gradient at all. In such circumstances how could we search for the other peaks? This paper is a call for challenges to the problem.

scholarly journals Spatio-Temporal Sequential Memory Model With Mini-Column Neural Network

2021 ◽  
Vol 15 ◽  
Author(s):  
Yawen Lan ◽  
Xiaobin Wang ◽  
Yuchen Wang
Keyword(s):  
Spike Timing ◽  
Spiking Neurons ◽  
Inhibitory Neurons ◽  
Human Cognition ◽  
Memory Model ◽  
Central Component ◽  
Incorrect Prediction ◽  
Proposed Model ◽  
Sequential Memory ◽  
Spatio Temporal

Memory is an intricate process involving various faculties of the brain and is a central component in human cognition. However, the exact mechanism that brings about memory in our brain remains elusive and the performance of the existing memory models is not satisfactory. To overcome these problems, this paper puts forward a brain-inspired spatio-temporal sequential memory model based on spiking neural networks (SNNs). Inspired by the structure of the neocortex, the proposed model is structured by many mini-columns composed of biological spiking neurons. Each mini-column represents one memory item, and the firing of different spiking neurons in the mini-column depends on the context of the previous inputs. The Spike-Timing-Dependant Plasticity (STDP) is used to update the connections between excitatory neurons and formulates association between two memory items. In addition, the inhibitory neurons are employed to prevent incorrect prediction, which contributes to improving the retrieval accuracy. Experimental results demonstrate that the proposed model can effectively store a huge number of data and accurately retrieve them when sufficient context is provided. This work not only provides a new memory model but also suggests how memory could be formulated with excitatory/inhibitory neurons, spike-based encoding, and mini-column structure.

scholarly journals Evaluative Conditioning as Memory-Based Judgment

2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Christoph Stahl ◽  
Frederik Aust
Keyword(s):  
Episodic Memory ◽  
Future Development ◽  
Formal Model ◽  
Evaluative Conditioning ◽  
Present Approach ◽  
Process Models ◽  
Dual Process ◽  
Memory Model ◽  
Challenges And Opportunities ◽  
Attitude Learning

The article proposes a view of evaluative conditioning (EC) as resulting from judgments based on learning instances stored in memory. It is based on the formal episodic memory model MINERVA 2. Additional assumptions specify how the information retrieved from memory is used to inform specific evaluative dependent measures. The present approach goes beyond previous accounts in that it uses a well-specified formal model of episodic memory; it is however more limited in scope as it aims to explain EC phenomena that do not involve reasoning processes. The article illustrates how the memory-based-judgment view accounts for several empirical findings in the EC literature that are often discussed as evidence for dual-process models of attitude learning. It sketches novel predictions, discusses limitations of the present approach, and identifies challenges and opportunities for its future development.

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