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Brain May Work Best With 7 Senses, Not 5, Study Suggests

Brain May Work Best With 7 Senses, Not 5, Study Suggests

A new mathematical model published in Scientific Reports suggests the brain's memory capacity is maximized in a seven-dimensional space, challenging the traditional five-sense framework and offering new insights for AI.

A bright conceptual illustration visualizing a mathematical model over a neural network background in reference to brain functions.

Source:

Tech Xplore

New Model Suggests Seven Senses Optimal for Memory

Scientists at the Skolkovo Institute of Science and Technology (Skoltech) have developed a mathematical model that challenges the long-held concept of five senses. Their research, published in the peer-reviewed journal Scientific Reports, proposes that memory capacity reaches its peak when operating in a seven-dimensional space.

This suggests that seven senses, rather than five, would be the optimal number for maximizing learning and recall.

The team, led by Professor Nikolay Brilliantov, found that when memories are characterized by seven distinct features, the number of objects the brain can hold in memory is maximized. This discovery provides a new mathematical framework for understanding how information is encoded and stored.

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A vivid multi-colored digital rendering of brain regions, highlighting diverse sensory processing areas.

Source:

ScienceDaily

The Role of Memory Engrams

The research builds on the concept of memory engrams—the fundamental units of memory. An engram is understood as a sparse group of neurons that fire together to represent a concept, such as a banana, which is characterized by features like its look, smell, and taste.

Dynamic Memory Evolution

The Skoltech model demonstrates that these engrams are not static. They evolve dynamically based on external stimuli.

  • Learning: Frequent recall of a memory strengthens and refines the engram.

  • Forgetting: Disuse causes the engram to become more diffuse.

Professor Brilliantov explained that engrams evolve toward a stable state. "After some transient period, a 'mature' distribution of engrams emerges," he noted. "We somewhat surprisingly find that the number of distinct engrams stored in memory... is the greatest for a concept space of seven dimensions."

High-quality image of a human brain with glowing neural circuits, representing memory and cognition.

Source:

Asianet Newsable

Implications for AI and Human Evolution

The findings have significant implications for artificial intelligence and robotics. The research suggests that designing AI with seven distinct sensory inputs could optimize its learning and memory capabilities, moving beyond simply mimicking human senses.

Future of Human Senses

While Professor Brilliantov called the application to humans "highly speculative," he raised intriguing possibilities for future evolution.

"It could be that humans of the future would evolve a sense of radiation or magnetic field," he commented.

This research establishes a mathematical link between memory, senses, and intelligence. It challenges the assumption that more senses would always improve memory, instead pointing to an optimal number. This breakthrough could reshape how both neuroscience and artificial intelligence approach the challenge of enhancing information storage and learning efficiency.

Implications for AI and Human Evolution

The findings have significant implications for artificial intelligence and robotics. The research suggests that designing AI with seven distinct sensory inputs could optimize its learning and memory capabilities, moving beyond simply mimicking human senses.

Future of Human Senses

While Professor Brilliantov called the application to humans "highly speculative," he raised intriguing possibilities for future evolution.

"It could be that humans of the future would evolve a sense of radiation or magnetic field," he commented.

This research establishes a mathematical link between memory, senses, and intelligence. It challenges the assumption that more senses would always improve memory, instead pointing to an optimal number. This breakthrough could reshape how both neuroscience and artificial intelligence approach the challenge of enhancing information storage and learning efficiency.

How does the seven-dimensional conceptual space enhance memory capacity?

According to the Skoltech model, a seven-dimensional conceptual space represents a mathematical sweet spot for memory. The research demonstrates that the number of distinct objects, or memory engrams, that can be stored and recalled reaches its absolute maximum when characterized by seven distinct features. Adding more or fewer dimensions diminishes this capacity.

How does the seven-dimensional conceptual space enhance memory capacity?

According to the Skoltech model, a seven-dimensional conceptual space represents a mathematical sweet spot for memory. The research demonstrates that the number of distinct objects, or memory engrams, that can be stored and recalled reaches its absolute maximum when characterized by seven distinct features. Adding more or fewer dimensions diminishes this capacity.

How does the seven-dimensional conceptual space enhance memory capacity?

According to the Skoltech model, a seven-dimensional conceptual space represents a mathematical sweet spot for memory. The research demonstrates that the number of distinct objects, or memory engrams, that can be stored and recalled reaches its absolute maximum when characterized by seven distinct features. Adding more or fewer dimensions diminishes this capacity.

What practical applications could this model have for AI development?

What practical applications could this model have for AI development?

What practical applications could this model have for AI development?

Could this discovery lead to new treatments for memory-related disorders?

Could this discovery lead to new treatments for memory-related disorders?

Could this discovery lead to new treatments for memory-related disorders?

How do the engrams in the brain evolve over time according to this model?

How do the engrams in the brain evolve over time according to this model?

How do the engrams in the brain evolve over time according to this model?

What are the potential implications for future human evolution based on this research?

What are the potential implications for future human evolution based on this research?

What are the potential implications for future human evolution based on this research?

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