scholarly journals The memory tesseract: Mathematical equivalence between composite and separate storage memory models

2019 ◽  
Author(s):  
Matthew A Kelly ◽  
Douglas Mewhort ◽  
Robert West
Keyword(s):  
Fourth Order ◽  
Human Memory ◽  
Memory Models ◽  
Long Term Memory ◽  
Order Tensor ◽  
Competing Models ◽  
Computational Memory ◽  
Theoretical Unification ◽  
Fourth Order Tensor

Computational memory models can explain the behaviour of human memory in diverse experimental paradigms. But research has produced a profusion of competing models, and, as different models focus on different phenomena, there is no best model. However, by examining commonalities among models, we can move towards theoretical unification. Computational memory models can be grouped into composite and separate storage models. We prove that MINERVA 2, a separate storage model of long-term memory, is mathematically equivalent to composite storage memory implemented as a fourth order tensor, and approximately equivalent to a fourth-order tensor compressed into a holographic vector. Building of these demonstrations, we show that MINERVA 2 and related separate storage models can be implemented in neurons. Our work clarifies the relationship between composite and separate storage models of memory, and thereby moves memory models a step closer to theoretical unification.

scholarly journals Integrity basis for a second-order and a fourth-order tensor

1982 ◽  
Vol 5 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Josef Betten
Keyword(s):  
Fourth Order ◽  
Second Order ◽  
Tensor Function ◽  
Order Tensor ◽  
Isotropic Tensor ◽  
Anisotropic Properties ◽  
Isotropic Tensor Function ◽  
Fourth Order Tensor

In this paper a scalar-valued isotropic tensor function is considered, the variables of which are constitutive tensors of orders two and four, for instance, characterizing the anisotropic properties of a material. Therefore, the system of irreducible invariants of a fourth-order tensor is constructed. Furthermore, the joint or simultaneous invariants of a second-order and a fourth-order tensor are found. In a similar way one can construct an integrity basis for a tensor of order greater than four, as shown in the paper, for instance, for a tensor of order six.

scholarly journals Metabolic Impairment in Human Amnesia: A PET Study of Memory Networks

1992 ◽  
Vol 12 (3) ◽  
pp. 353-358 ◽  
Author(s):  
Ferruccio Fazio ◽  
Daniela Perani ◽  
Maria Carla Gilardi ◽  
Fabio Colombo ◽  
Stefano F. Cappa ◽  
...  
Keyword(s):  
Hippocampal Formation ◽  
Cerebral Metabolism ◽  
Human Memory ◽  
Clinical Syndrome ◽  
Long Term Memory ◽  
Positron Emission ◽  
New Information ◽  
Magnetic Resonance Imaging Mri

Human amnesia is a clinical syndrome exhibiting the failure to recall past events and to learn new information. Its “pure” form, characterized by a selective impairment of long-term memory without any disorder of general intelligence or other cognitive functions, has been associated with lesions localized within Papez's circuit and some connected areas. Thus, amnesia could be due to a functional disconnection between components of this or other neural structures involved in long-term learning and retention. To test this hypothesis, we measured regional cerebral metabolism with 2-[18F]fluoro-2-deoxy-d-glucose ([18F]FDG) and positron emission tomography (PET) in 11 patients with “pure” amnesia. A significant bilateral reduction in metabolism in a number of interconnected cerebral regions (hippocampal formation, thalamus, cingulate gyrus, and frontal basal cortex) was found in the amnesic patients in comparison with normal controls. The metabolic impairment did not correspond to alterations in structural anatomy as assessed by magnetic resonance imaging (MRI). These results are the first in vivo evidence for the role of a functional network as a basis of human memory.

scholarly journals Context triggers the retrieval of long-term memories into working memory to guide attention

2018 ◽  
Author(s):  
Sirawaj Itthipuripat ◽  
Geoffrey F Woodman
Keyword(s):  
Working Memory ◽  
Human Subjects ◽  
Brain Activity ◽  
Human Memory ◽  
Long Term Memory ◽  
Behavioral Performance ◽  
Electrical Fields ◽  
Subject Variability ◽  
Transfer Of Information

SummaryHow do we know what we are looking for in familiar scenes and surroundings? Here we tested a novel hypothesis derived from theories of human memory that working memory (WM) buffers mnemonic contents retrieved from long-term memory (LTM) to control attention. To test this hypothesis, we measured the electrical fields recorded noninvasively from human subjects’ as they searched for specific sets of objects in learned contexts. We found that the subjects’ WM-indexing brain activity tracked the number of real-world objects people learned to search for in each context. Moreover, the level of this WM activity predicted the inter-subject variability in behavioral performance. Together, our results demonstrate that familiar contexts can trigger the transfer of information from LTM to WM to provide top-down attentional control.

scholarly journals A Unified Fourth-Order Tensor-Based Smart Community System

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 5990
Author(s):  
Chang Liu ◽  
Huaiyu Wu ◽  
Junyuan Wang ◽  
Mingkai Wang
Keyword(s):  
Human Activity ◽  
Fourth Order ◽  
Intelligent Systems ◽  
High Energy ◽  
Tensor Model ◽  
Order Tensor ◽  
Community System ◽  
Smart Community ◽  
Smart Communities ◽  
Fourth Order Tensor

Empowered by the ubiquitous sensing capabilities of Internet of Things (IoT) technologies, smart communities could benefit our daily life in many aspects. Various smart community studies and practices have been conducted, especially in China thanks to the government’s support. However, most intelligent systems are designed and built individually by different manufacturers in diverging platforms with different functionalities. Therefore, multiple individual systems must be deployed in a smart community to have a set of functions, which could lead to hardware waste, high energy consumption and high deployment cost. More importantly, current smart community systems mainly focus on the technologies involved, while the effects of human activity are neglected. In this paper, a fourth-order tensor model representing object, time, location and human activity is proposed for human-centered smart communities, based on which a unified smart community system is designed. Thanks to the powerful data management abilities of a high-order tensor, multiple functions can be integrated into our system. In addition, since the tensor model embeds human activity information, complex functions could be implemented by exploring the effects of human activity. Two exemplary applications are presented to demonstrate the flexibility of the proposed unified fourth-order tensor-based smart community system.

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