The formation of memories is one of the most fascinating aspects of the human brain. It is a process that is still largely a mystery, but scientists
Key Highlights :
The research team used a novel method that combines optical and machine-learning-based approaches to detect the neuronal networks involved in the formation of memories. They were able to capture the complex changes that occur during memory formation and uncover the mechanisms by which memories are created.
Animals learn to adapt to changing environments for survival, and associative learning is one of the simplest types of learning. In the last two decades, technical developments in molecular, genetic, and optogenetic methods have made it possible to identify brain regions and populations of neurons that control the formation and retrieval of new memories.
The research team focused on the dorsal part of the medial prefrontal cortex (dmPFC), which is critical for the retrieval of associative fear memory in rodents. They used longitudinal two-photon imaging and various computational neuroscience techniques to determine how neural activity changes in the mouse prefrontal cortex after learning in a fear-conditioning paradigm.
The team developed a new analytical method based on the 'elastic net,' a machine-learning algorithm, to identify which specific neurons encode fear memory. They further analyzed the spatial arrangement and functional connectivity of the neurons using graphical modeling.
The researchers discovered direct evidence that associative memory formation was accompanied by a novel associative connection between originally distinct networks – the conditioned stimulus (CS) network and the unconditioned stimulus (US) network. This connection facilitated information processing by triggering a fear response (CR) to a CS.
The findings of the study support the idea that memories are formed by the enhancement of neural connections, which are strengthened by the repeated activation of groups of neurons. The study also demonstrates how combined methods (optics and machine learning) can be used to visualize the dynamics of neural networks in great detail.
The study provides valuable insight into the physical changes that occur in the brain when a new memory is formed. This knowledge could be used to develop treatments for memory-related disorders and to better understand the neurological changes associated with learning and memory.
The Study Explores How Physical Changes in the Brain Occur When a New Memory is Formed
