A Cognitive Architecture for Visual Memory Identification

A Cognitive Architecture for Visual Memory Identification

Karina Jaime (Department of Computer Science, CINVESTAV Unidad Guadalajara, Guadalajara, México), Gustavo Torres (Computer Science, Autonomous University of Guadalajara, Zapopan, México), Félix Ramos (Department of Computer Science, CINVESTAV Unidad Guadalajara, Guadalajara, México) and Gregorio Garcia-Aguilar (Faculty of Psychology, Benemerita Universidad Autonoma de Puebla, México)
DOI: 10.4018/ijssci.2014040104
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Memory is an important process of human behavior. In particular visual memory encode, store, and retrieve acquired knowledge about the environment. The visual memory system involves different kinds of processes, such as sensory input and short-term visual memory. The model presents a first approach for visual memory recognition that supports the three stages mentioned above. The model design is based on neuroscience results. The model consists of nodes. Each node represents a brain area that is involved in the visual memory system. The nodes run in a distributed system and send messages with visual memory information. This document presents only the memory system specifications that support a cognitive architecture for visual object identification. The authors validated the model with two case studies: known and unknown stimulus.
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A Proposed Model For Visual Memory Identification

Memory is an important process of human behavior because it enables the brain to encode, store and retrieve acquired knowledge about the environment (Kandel & Kupfermann, 2000). Memory (together with other cognitive functions) creates predictive scenarios, and generates thoughts, decisions, and responses. Visual memory is involved in object identification by discriminating new data from stored data.

Neuropsychologists have split memory into two systems: short-term memory and long-term memory. When past information has not been stored, it has been retained in short-term memory. Retained past events are stored in long-term memory (Atkinson & Shiffrin, 1968).

The long-term memory system holds two kinds of information: declarative or explicit data and non-declarative or implicit data (Kandel & Kufermann, 2000). Declarative memory does the effort of recalling events and facts. Non-declarative memory retains information regarding well-structured and effortless processes: habits, reflexes, motor and emotional responses (Milner, Squire, & Kandel, 1998). The short-term memory and long-term memory systems can be found in different brain processes: sensory, cognitive and metacognitive brain operations.

Due to their importance, memory-related brain processes have been studied separately. In this paper, we model a section of the long-term memory system, namely, visual memory. This involves different kinds of processes: sensory input, short and long-term visual memory, among others.

Current knowledge of visual sensory memory states that sensory input is supported by the primary visual cortex (Wutz & Kandel, 2000). The role of visual sensory memory in complex cognitive functioning is probably null because this form of memory is not persistent over time.

Short-term visual memory is an important form of visual memory in complex cognition, because it works to maintain the representation of just a few objects in the visual field for a short time, preventing disruptions due to the eyes' movements, and allowing the eye to follow a target in a fast-changing situation. Hence, its role is associated with the allocation of visual-attention resources. The firing of neurons from the lateral occipital cortex supports the functioning of short-term visual memory. Long-term visual memory is a form of memory that is highly important in cognitive functioning because it deals with general and specific information about an object in the visual scene as well as identifying and categorizing it (Atkinson & Shiffrin, 1968; Hollingworth & Luck, 2008). Current knowledge in neuroscience states that the parahippocampal and hippocampal cortices serve to recollect and retrieve contextual information. This has been disregarded when researchers model visual memory processes in cognitive architectures. Instead, specific forms of long-term memory systems have been developed, such as semantic and procedural memories.

Widrow and Aragon (2010) propose a general model of “cognitive memory”. This model stores visual information, and the rest of the sensory information received from the scene, in an empty storage called “folder”. All the information stored in each folder is associated with each other. An associative neural network performs the retrieving process. The neural network used as a “prompt signal” the any type of information (visual, auditory, tactile, among others).

Endowing virtual agents with visual memory will improve their supporting cognitive architecture. Even though artificial cognitive architectures (ACA's) usually rely on different forms of memory systems, none have developed visual memory. This is an important point, because delineating this system assumes the dynamic participation of several modules of the cognitive architecture. Stressing communication between these modules is as important as module construction to deal with all forms of visual information.

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