By collecting the neural signals from the rat brain, Indian scientists have devised the first-of-its-kind instrument for understanding the process of long-term memory consolidation in the brain. Learning and memory are two of the brain’s most fundamental functions, and they’re also one of the most researched topics in neuroscience.
The acquisition of new information and memory are linked to learning. Long-term memory (LTM) is formed when acquired data is retained. The new technology, which employs a behavioural tagging paradigm, is a first-of-its-kind tool for studying LTM consolidation via behavioural analysis. In a similar vein, bio-impulses are currently being utilised to investigate the latent characteristics of memory consolidation using a technique known as In Vivo Electrophysiology, which involves recording neural signals from mouse brains under controlled conditions.
Prof. Suhel Parvez and his team invented the Behavioural Tagging model for understanding the process of LTM consolidation in the brain at the Department of Toxicology, School of Chemical and Life Sciences, Jamia Hamdard (Deemed to be University), New Delhi. The findings were published in the journals ‘Theranostics’ and ‘Ageing Research Reviews’ recently.
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For capturing bio-signals and developing the behavioural tagging model, the researchers used the In Vivo Electrophysiology Facility established at the Department of Toxicology with support from the Department of Science and Technology (DST) under the “Promotion of University Research and Scientific Excellence (PURSE)” programme.
“The institution has many neurobehavioral apparatuses for rodents to assess parameters that are assessed using Any-MAZE software.” In addition, research on neurodegenerative disorders that cause memory impairment, such as dementia, Alzheimer’s disease, Parkinson’s disease, and others, could benefit from the findings of this study in order to establish a direct link between the memory consolidation pathway and memory impairment mechanisms in such diseased states,” Prof. Suhel said.
