Neural networks implicated in autobiographical memory training
| Autor: | Dragoş Cȋrneci, Mihaela Onu, Claudiu C. Papasteri, Dana Georgescu, Catalina Poalelungi, Alexandra Sofonea, Nicoleta Puşcaşu, Dumitru Tanase, Teofila Rădeanu, Maria-Yaelle Toader, Andreea L. Dogaru, Ioana R. Podină, Alexandru I. Berceanu, Ioana Carcea |
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| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Recall Autobiographical memory General Neuroscience Memory Episodic Cognition General Medicine Memory training Memory improvement Mental Recall Humans Neural Networks Computer Effects of sleep deprivation on cognitive performance Cues Psychology Neuroscience Default mode network |
| Popis: | Training of autobiographical memory has been proposed as an intervention to improve cognitive function. The neural substrates for such improvements are poorly understood. Several brain areas have been previously linked to autobiographical recollection, including structures in the default mode network (DMN) and the sensorimotor network. Here, we tested the hypothesis that changes in connectivity within different neural networks support distinct aspects of memory improvement in response to training on a group of 59 human subjects. We found that memory training using olfactory cues increases resting-state intranetwork DMN connectivity, and this associates with improved recollection of cue-specific memories. On the contrary, training decreased resting-state connectivity within the sensorimotor network, a decrease that correlated with improved ability for voluntary recall. Moreover, preliminary data indicate that only the decrease in sensorimotor connectivity associated with the training-induced decrease in the tumor necrosis factor α (TNFα) factor, an immune modulation previously linked to improved cognitive performance. We identified functional and biochemical factors that associate with distinct memory processes improved by autobiographical training. Pathways which connect autobiographical memory with both high-level cognition and somatic physiology are discussed. |
| Databáze: | OpenAIRE |
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