Neural mechanisms of associative cortical plasticity in cognitive domain: Magnetoencephalographic studies
- Авторлар: Chernyshev B.V.1,2, Pultsina K.I.1, Tretyakova V.D.1, Razorenova A.M.1, Pavlova A.A.1, Stroganova T.A.1
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Мекемелер:
- Moscow State University of Psychology and Education
- Lomonosov Moscow State University
- Шығарылым: Том 18, № 4 (2023)
- Беттер: 602-605
- Бөлім: Conference proceedings
- ##submission.dateSubmitted##: 14.11.2023
- ##submission.dateAccepted##: 16.11.2023
- ##submission.datePublished##: 15.12.2023
- URL: https://genescells.ru/2313-1829/article/view/623326
- DOI: https://doi.org/10.17816/gc623326
- ID: 623326
Дәйексөз келтіру
Аннотация
Acquisition of language semantics is widely believed to be facilitated by biological mechanisms of associative learning [1]. However, current understanding of brain mechanisms underlying learning and memory is primarily based on simple models, including animal models, with mechanisms of learning in the cognitive realm largely unknown. Semantic language learning serves as a compelling example of these cognitive processes, whose brain mechanisms pose a challenge to explanation at the level of basic neural networks. Particularly, many processes underlying such learning still lack clear understanding, including the mechanisms that enable correlational coincidence of neuronal representation required for Hebbian plasticity, the reverberatory replay of the to-be associated representations in working memory, and the involvement of consolidation, among others.
We conducted a series of studies modeling the acquisition of semantic knowledge of action-related vocabulary to investigate these questions. We implemented a unique trial-and-error-based procedure for semantic acquisition, in which participants obtained associations between newly introduced pseudowords and actions through active learning. The experimental procedure comprised the delivery of acoustically equivalent pseudowords that were previously unknown to the subjects. Participants were instructed to execute movements of their hands and feet in response to specific pseudowords. Following each trial, participants received either positive or negative feedback depending on their performance. During the learning phase, MEG was recorded, as well as during passive presentations of the same pseudowords before and after learning to control for attention and motor preparation effects. Our analysis involved event-related fields and beta oscillations.
Our experiments showed that cortical plasticity related to word learning could be detected immediately after learning, without the need for prolonged consolidation time [2].
We observed two effects during learning that could contribute to Hebbian plasticity by linking auditory speech representations of pseudowords with associated movements.
First, we observed the reactivation of auditory speech representations during the initialization of movement. This mechanism apparently creates the conditions for temporal coincidence of activations in two representations, specifically an auditory speech representation and a representation of a motor program.
During the learning process, we observed a considerable rise in beta oscillations that occurred during and after action execution. This effect comprised a typical beta-rebound in the sensorimotor regions and a significant surge in beta activity in various associative cortical regions. We postulate that these beta oscillations constitute a reverberation mechanism that reinforces the associative connection and guards it against potential interference [3].
In further experiments, we administered the learning process over two consecutive days with an overnight interval between recordings. We evaluated beta power dynamics during the acquisition of novel pseudowords on day 1 and during task rehearsal following overnight sleep on day 2. Beta event-related synchronization in the frontal regions emerged upon the attainment of the pseudoword learning rules on day 1, and remained unchanged after sleep and subsequent rehearsal on day 2. The prefrontal beta rhythm’s dynamics mirrored the corresponding behavioral changes: subjects executed the task with minimal errors on day 2 upon meeting the learning criterion on day 1. Beta event-related synchronization augmented continuously in the posterior temporal and parietal cortices on day 2 and potentially contributed towards the assimilation of newly-acquired associations in long-term memory.
In summary, our research offers fresh perspectives on the intricate neural mechanisms underlying plasticity in the human brain within the cognitive domain.
Толық мәтін
Acquisition of language semantics is widely believed to be facilitated by biological mechanisms of associative learning [1]. However, current understanding of brain mechanisms underlying learning and memory is primarily based on simple models, including animal models, with mechanisms of learning in the cognitive realm largely unknown. Semantic language learning serves as a compelling example of these cognitive processes, whose brain mechanisms pose a challenge to explanation at the level of basic neural networks. Particularly, many processes underlying such learning still lack clear understanding, including the mechanisms that enable correlational coincidence of neuronal representation required for Hebbian plasticity, the reverberatory replay of the to-be associated representations in working memory, and the involvement of consolidation, among others.
We conducted a series of studies modeling the acquisition of semantic knowledge of action-related vocabulary to investigate these questions. We implemented a unique trial-and-error-based procedure for semantic acquisition, in which participants obtained associations between newly introduced pseudowords and actions through active learning. The experimental procedure comprised the delivery of acoustically equivalent pseudowords that were previously unknown to the subjects. Participants were instructed to execute movements of their hands and feet in response to specific pseudowords. Following each trial, participants received either positive or negative feedback depending on their performance. During the learning phase, MEG was recorded, as well as during passive presentations of the same pseudowords before and after learning to control for attention and motor preparation effects. Our analysis involved event-related fields and beta oscillations.
Our experiments showed that cortical plasticity related to word learning could be detected immediately after learning, without the need for prolonged consolidation time [2].
We observed two effects during learning that could contribute to Hebbian plasticity by linking auditory speech representations of pseudowords with associated movements.
First, we observed the reactivation of auditory speech representations during the initialization of movement. This mechanism apparently creates the conditions for temporal coincidence of activations in two representations, specifically an auditory speech representation and a representation of a motor program.
During the learning process, we observed a considerable rise in beta oscillations that occurred during and after action execution. This effect comprised a typical beta-rebound in the sensorimotor regions and a significant surge in beta activity in various associative cortical regions. We postulate that these beta oscillations constitute a reverberation mechanism that reinforces the associative connection and guards it against potential interference [3].
In further experiments, we administered the learning process over two consecutive days with an overnight interval between recordings. We evaluated beta power dynamics during the acquisition of novel pseudowords on day 1 and during task rehearsal following overnight sleep on day 2. Beta event-related synchronization in the frontal regions emerged upon the attainment of the pseudoword learning rules on day 1, and remained unchanged after sleep and subsequent rehearsal on day 2. The prefrontal beta rhythm’s dynamics mirrored the corresponding behavioral changes: subjects executed the task with minimal errors on day 2 upon meeting the learning criterion on day 1. Beta event-related synchronization augmented continuously in the posterior temporal and parietal cortices on day 2 and potentially contributed towards the assimilation of newly-acquired associations in long-term memory.
In summary, our research offers fresh perspectives on the intricate neural mechanisms underlying plasticity in the human brain within the cognitive domain.
ADDITIONAL INFORMATION
Funding sources. Our study was conducted as part of the state assignment of the Ministry of Education of the Russian Federation (No. 073-00038-23-02 of 13.02.2023, entitled “Investigation of the neural mechanisms underlying semantic learning using magnetoencephalography”).
Авторлар туралы
B. Chernyshev
Moscow State University of Psychology and Education; Lomonosov Moscow State University
Хат алмасуға жауапты Автор.
Email: b_chernysh@mail.ru
Ресей, Moscow; Moscow
K. Pultsina
Moscow State University of Psychology and Education
Email: b_chernysh@mail.ru
Ресей, Moscow
V. Tretyakova
Moscow State University of Psychology and Education
Email: b_chernysh@mail.ru
Ресей, Moscow
A. Razorenova
Moscow State University of Psychology and Education
Email: b_chernysh@mail.ru
Ресей, Moscow
A. Pavlova
Moscow State University of Psychology and Education
Email: b_chernysh@mail.ru
Ресей, Moscow
T. Stroganova
Moscow State University of Psychology and Education
Email: b_chernysh@mail.ru
Ресей, Moscow
Әдебиет тізімі
- Pulvermuller F. Neural reuse of action perception circuits for language, concepts and communication. Progress in Neurobiology. 2018;160:1–44. doi: 10.1016/j.pneurobio.2017.07.001
- Razorenova AM, Chernyshev BV, Nikolaeva AY, et al. Rapid Cortical Plasticity Induced by Active Associative Learning of Novel Words in Human Adults. Frontiers in Neuroscience. 2020;14:895. doi: 10.3389/fnins.2020.00895
- Pavlova A, Tyulenev N, Tretyakova V, et al. Learning of new associations invokes a major change in modulations of cortical beta oscillations in human adults. Psychophysiology. 2023;60(8):e14284. doi: 10.1111/psyp.14284
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