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A team from the Grainger College of Engineering at the University of Illinois at Urbana-Champaign determined that the decision-making process operates under a different dynamic than cognitive hierarchical models. The study, published in the journal Proceedings of the National Academy of Sciences (PNAS) and led by Professor Yurii Vlasov, demonstrates that initial sensory regions actively participate in cognitive choices.
The study of cognitive hierarchical models
Historically, neuroscience and computer science conceived brain architecture as a sequential system where data travels from the senses to the frontal cortex. However, experiments conducted with mice in virtual reality environments revealed that the primary somatosensory cortex registers patterns directly linked to analytical processing.
Consequently, higher brain areas send descending signals to early regions through reciprocal communication circuits. This continuous mechanism of processing and response transforms the current understanding of how living beings function. Likewise, these discoveries challenge the theoretical foundations employed for decades in the creation of computational algorithms.
Currently, the computational infrastructure oriented toward deep learning requires substantial energy consumption to execute highly complex tasks. The emulation of biological efficiency, perfected by evolution over millions of years, offers an ideal alternative to optimize software and hardware architecture.
In this way, the integration of feedback loops in synthetic neural networks would enable data processing in both directions simultaneously. Engineers seek to apply this structural flexibility with the objective of reducing energy expenditure in computing centers and improving the problem-solving capacity of automated systems.
In view of this, the research team plans to deepen the measurement of the temporal dynamics of brain signals. The development of more precise technologies will facilitate the identification of specific circuits that coordinate cognitive processing, laying the foundations for designing digital architectures with superior performance.
Source and photo: ScienceDaily
