Mathematical Model Suggests Seven Senses Optimal for Memory, Implications for AI and Robotics

Mathematical model of memory suggests seven senses are optimal

Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, and for better understanding of human memory. Published in Scientific Reports, the study suggests there may be an optimal number of senses -- if so, those of us with five senses could use a couple more. "Our conclusion is, of course, highly speculative in application to human senses, although you never know: It could be that humans of the future would evolve a sense of radiation or magnetic field. But in any case, our findings may be of practical importance for robotics and the theory of artificial intelligence," said study co-author Professor Nikolay Brilliantov of Skoltech AI. "It appears that when each concept retained in memory is characterized in terms of seven features -- as opposed to, say, five or eight -- the number of distinct objects held in memory is maximized." In line with a well-established approach, which originated in the early 20th century, the team models the fundamental building blocks of memory: the memory "engrams." An engram can be viewed as a sparse ensemble of neurons across multiple regions in the brain that fire together. The conceptual content of an engram is an ideal abstract object characterized with regard to multiple features. In the context of human memory, the features correspond to sensory inputs, so that the notion of a banana would match up with a visual image, a smell, the taste of a banana, and so on. This results in a five-dimensional object that exists and evolves in a five-dimensional space populated by all the other concepts retained in memory. The evolution of engrams refers to concepts becoming more focused or blurred with time, depending on how often the engrams get activated by a stimulus acting from the outer world via the senses, triggering the memory of the respective object. This models learning and forgetting as a result of interaction with the environment. "We have mathematically demonstrated that the engrams in the conceptual space tend to evolve toward a steady state, which means that after some transient period, a 'mature' distribution of engrams emerges, which then persists in time," Brilliantov commented. "As we consider the ultimate capacity of a conceptual space of a given number of dimensions, we somewhat surprisingly find that the number of distinct engrams stored in memory in the steady state is the greatest for a concept space of seven dimensions. Hence the seven senses claim." In other words, let the objects that exist out there in the world be described by a finite number of features corresponding to the dimensions of some conceptual space. Suppose that we want to maximize the capacity of the conceptual space expressed as the number of distinct concepts associated with these objects. The greater the capacity of the conceptual space, the deeper the overall understanding of the world. It turns out that the maximum is attained when the dimension of the conceptual space is seven. From this, the researchers conclude that seven is the optimal number of senses. According to the researchers, this number does not depend on the details of the model -- the properties of the conceptual space and the stimuli providing the sense impressions. The number seven appears to be a robust and persistent feature of memory engrams as such. One caveat is that multiple engrams of differing sizes existing around a common center are deemed to represent similar concepts and are therefore treated as one when calculating memory capacity. The memory of humans and other living beings is an enigmatic phenomenon tied to the property of consciousness, among other things. Advancing the theoretical models of memory will be instrumental to gaining new insights into the human mind and recreating humanlike memory in AI agents.

Mathematical Model Of Memory Suggests 7 Senses Are Optimal

Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, and for better understanding of human memory. Published in Scientific Reports, the study suggests there may be an optimal number of senses -- if so, those of us with five senses could use a couple more! "Our conclusion is of course highly speculative in application to human senses, although you never know: It could be that humans of the future would evolve a sense of radiation or magnetic field. But in any case, our findings may be of practical importance for robotics and the theory of artificial intelligence," said study co-author Professor Nikolay Brilliantov of Skoltech AI. "It appears that when each concept retained in memory is characterized in terms of seven features -- as opposed to, say, five or eight -- the number of distinct objects held in memory is maximized." In line with a well-established approach, which originated in the early 20th century, the team models the fundamental building blocks of memory: the memory "engrams." An engram can be viewed as a sparse ensemble of neurons across multiple regions in the brain that fire together. The conceptual content of an engram is an ideal abstract object characterized with regard to multiple features. In the context of human memory, the features correspond to sensory inputs, so that the notion of a banana would match up with a visual image, a smell, the taste of a banana, and so on. This results in a five-dimensional object that exists and evolves in a five-dimensional space populated by all the other concepts retained in memory. The evolution of engrams refers to concepts becoming more focused or blurred with time, depending on how often the engrams get activated by a stimulus acting from the outer world via the senses, triggering the memory of the respective object. This models learning and forgetting as a result of interaction with the environment. "We have mathematically demonstrated that the engrams in the conceptual space tend to evolve toward a steady state, which means that after some transient period, a 'mature' distribution of engrams emerges, which then persists in time," Brilliantov commented. "As we consider the ultimate capacity of a conceptual space of a given number of dimensions, we somewhat surprisingly find that the number of distinct engrams stored in memory in the steady state is the greatest for a concept space of seven dimensions. Hence the seven senses claim." In other words, let the objects that exist out there in the world be described by a finite number of features corresponding to the dimensions of some conceptual space. Suppose that we want to maximize the capacity of the conceptual space expressed as the number of distinct concepts associated with these objects. The greater the capacity of the conceptual space, the deeper the overall understanding of the world. It turns out that the maximum is attained when the dimension of the conceptual space is seven. From this the researchers conclude that seven is the optimal number of senses. According to the researchers, this number does not depend on the details of the model -- the properties of the conceptual space and the stimuli providing the sense impressions. The number seven appears to be a robust and persistent feature of memory engrams as such. One caveat is that multiple engrams of differing sizes existing around a common center are deemed to represent similar concepts and are therefore treated as one when calculating memory capacity. The memory of humans and other living beings is an enigmatic phenomenon tied to the property of consciousness, among other things. Advancing the theoretical models of memory will be instrumental to gaining new insights into the human mind and recreating humanlike memory in AI agents.