Memory-based Pattern Completion in Database Semantics

2005 ◽  
Vol 9 (1) ◽  
pp. 69-92 ◽  
Author(s):  
Roland Hausser
eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Kevin A Bolding ◽  
Shivathmihai Nagappan ◽  
Bao-Xia Han ◽  
Fan Wang ◽  
Kevin M Franks

Pattern completion, or the ability to retrieve stable neural activity patterns from noisy or partial cues, is a fundamental feature of memory. Theoretical studies indicate that recurrently connected auto-associative or discrete attractor networks can perform this process. Although pattern completion and attractor dynamics have been observed in various recurrent neural circuits, the role recurrent circuitry plays in implementing these processes remains unclear. In recordings from head-fixed mice, we found that odor responses in olfactory bulb degrade under ketamine/xylazine anesthesia while responses immediately downstream, in piriform cortex, remain robust. Recurrent connections are required to stabilize cortical odor representations across states. Moreover, piriform odor representations exhibit attractor dynamics, both within and across trials, and these are also abolished when recurrent circuitry is eliminated. Here, we present converging evidence that recurrently-connected piriform populations stabilize sensory representations in response to degraded inputs, consistent with an auto-associative function for piriform cortex supported by recurrent circuitry.


2019 ◽  
Author(s):  
Rosemary Cowell ◽  
Morgan Barense ◽  
Patrick Sadil

Thanks to patients Phineas Gage and Henry Molaison, we have long known that behavioral control depends on the frontal lobes, whereas declarative memory depends on the medial temporal lobes. For decades, cognitive functions – behavioral control, declarative memory – have served as labels for characterizing the division of labor in cortex. This approach has made enormous contributions to understanding how the brain enables the mind, providing a systems-level explanation of brain function that constrains lower-level investigations of neural mechanism. Today, the approach has evolved such that functional labels are often applied to brain networks rather than focal brain regions. Furthermore, the labels have diversified to include both broadly-defined cognitive functions (declarative memory, visual perception) and more circumscribed mental processes (recollection, familiarity, priming). We ask whether a process – a high-level mental phenomenon corresponding to an introspectively-identifiable cognitive event – is the most productive label for dissecting memory. For example, the process of recollection conflates a neurocomputational operation (pattern completion-based retrieval) with a class of representational content (associative, high-dimensional, episodic-like memories). Because a full theory of memory must identify operations and representations separately, and specify how they interact, we argue that processes like recollection constitute inadequate labels for characterizing neural mechanisms. Instead, we advocate considering the component operations and representations of mnemonic processes in isolation, when examining their neural underpinnings. For the neuroanatomical organization of memory, the evidence suggests that pattern completion is recapitulated widely across cortex, but the division of labor between cortical sites can be explained by representational content.


2021 ◽  
pp. JN-RM-0051-21
Author(s):  
Luis Carrillo-Reid ◽  
Shuting Han ◽  
Darik A. O’Neil ◽  
Ekaterina Taralova ◽  
Tony Jebara ◽  
...  

Author(s):  
Ricardo André Pereira Freitas ◽  
José Carlos Ramalho

Due to the expansion and growth of information technologies, much of human knowledge is now recorded on digital media. A new problem in the digital universe has arisen: Digital Preservation. This chapter addresses the problems of Digital Preservation and focuses on the conceptual model within a specific class of digital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). The authors address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation “property.” For the representation of this higher layer of abstraction present in databases, they use an ontology-based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that the authors tentatively represent using “Web Ontology Language” (OWL). From the initial prototype, they develop a framework (supported by case studies) and establish a mapping algorithm for the conversion between databases and OWL. The ontology approach is adopted to formalize the knowledge associated to the conceptual model of the database and also a methodology to create an abstract representation of it. The system is based on the functional axes (ingestion, administration, dissemination, and preservation) of the OAIS reference model.


Hippocampus ◽  
2018 ◽  
Vol 29 (4) ◽  
pp. 340-351 ◽  
Author(s):  
Paula Vieweg ◽  
Martin Riemer ◽  
David Berron ◽  
Thomas Wolbers

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