Imroatul Nasiyah
Researchers at Skoltech have pioneered a groundbreaking mathematical model that delves into the intricate workings of memory, yielding astonishing insights that could revolutionize fields ranging from robotics and artificial intelligence to our fundamental understanding of the human mind. Their meticulous analysis of this model has revealed a compelling suggestion: there might exist an optimal number of senses for efficient information processing, and intriguingly, this ideal number appears to be seven, potentially surpassing the commonly accepted five. This discovery, detailed in the prestigious journal Scientific Reports, challenges our conventional perception of sensory input and opens up exciting new avenues for scientific exploration.
The study, spearheaded by Professor Nikolay Brilliantov and his team at Skoltech AI, builds upon a rich tradition of memory research dating back to the early 20th century. Their focus was on modeling the fundamental building blocks of memory, known as "engrams." An engram, in this context, can be visualized as a distributed network of neurons across various brain regions that synchronize their firing patterns. Each engram serves as a representation of a specific concept, characterized by a unique set of features. For humans, these features are directly linked to our sensory experiences. For instance, the concept of a banana is not just its visual appearance but also its distinct aroma, taste, texture, and potentially other sensory qualities. Within this theoretical framework, a concept like a banana is effectively transformed into a multi-dimensional object within a vast mental landscape that encapsulates all our stored memories.
The dynamic nature of engrams is a crucial aspect of the model. These neural clusters are not static; they evolve over time. Their sharpness or diffuseness, representing the clarity and accessibility of a memory, is influenced by the frequency with which they are activated by external sensory stimuli. This continuous interplay between sensory input and neural activation forms the basis of our learning processes and, conversely, our forgetting. As we navigate and interact with our environment, our engrams are constantly being refined, strengthened, or allowed to fade.
Professor Brilliantov elaborated on the mathematical underpinnings of their findings: "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." This steady state represents a stable configuration of memories. The truly remarkable aspect of their research emerged when they analyzed the ultimate capacity of these conceptual spaces. "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." This suggests that a seven-dimensional conceptual space, analogous to having seven distinct senses, can accommodate a significantly larger number of unique concepts compared to spaces with fewer dimensions.
To further clarify this pivotal conclusion, the researchers explained it in simpler terms: Imagine that the objects and phenomena in the external world can be described by a finite set of characteristics, which correspond to the dimensions of a conceptual space. The goal is to maximize the number of distinct concepts that can be associated with these objects, thereby increasing the brain’s capacity to store and differentiate information. A greater capacity implies a more nuanced and comprehensive understanding of the world. Their mathematical analysis revealed that this maximum capacity is achieved precisely when the dimension of this conceptual space is seven. This leads directly to their hypothesis that seven might be the optimal number of senses for maximal memory storage and retrieval.
A significant aspect of their findings is the robustness of this "seven senses" conclusion. The researchers emphasized that this number appears to be independent of the specific details of their model, such as the inherent properties of the conceptual space itself or the nature of the stimuli that provide sensory impressions. The number seven emerges as a fundamental and persistent characteristic of memory engrams themselves. However, they also noted a crucial caveat: the model treats multiple engrams of varying sizes that are clustered around a common central point as representing similar concepts. In their calculations of memory capacity, these closely related engrams are considered as a single, unified concept. This simplification is essential for assessing the distinctiveness of stored information.
The profound implications of this research extend beyond theoretical curiosity. Memory in humans and other living organisms is an inherently enigmatic phenomenon, deeply intertwined with consciousness and our subjective experience of reality. Advancing our theoretical models of memory is therefore not merely an academic pursuit; it is a vital step towards unlocking deeper insights into the very nature of the human mind. Furthermore, this work holds immense promise for the development of artificial intelligence. By understanding the optimal sensory dimensionality for memory, we can strive to create AI agents that possess more sophisticated, humanlike memory capabilities, enabling them to learn, reason, and interact with the world in more intelligent and adaptive ways.
The potential applications for robotics are equally compelling. Robots equipped with enhanced sensory processing capabilities, potentially informed by the "seven senses" principle, could navigate complex environments with greater precision, make more informed decisions, and perform tasks that require a deeper understanding of their surroundings. This could lead to advancements in areas such as autonomous navigation, advanced manufacturing, and even sophisticated human-robot interaction.
While the immediate application to human evolution is acknowledged as speculative, the study’s authors are open to the possibility of future evolutionary adaptations. Professor Brilliantov mused, "It could be that humans of the future would evolve a sense of radiation or magnetic field." Such novel senses, if they were to emerge, would naturally increase the dimensionality of our conceptual space, potentially aligning with the seven-dimensional optimum predicted by their model. Regardless of future evolutionary trajectories, the immediate practical importance for robotics and the theory of artificial intelligence is undeniable. The mathematical framework developed by the Skoltech team provides a concrete, data-driven foundation for designing more efficient and capable artificial cognitive systems. This research represents a significant leap forward in our quest to understand, and ultimately replicate, the remarkable capabilities of biological memory.
