ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

For citation:

Chholak P., Tabari F., Pisarchik A. N. Revealing the neural network underlying covert picture-naming paradigm using magnetoencephalography. Izvestiya VUZ. Applied Nonlinear Dynamics, 2022, vol. 30, iss. 1, pp. 76-95. DOI: 10.18500/0869-6632-2022-30-1-76-95

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Language: 
English
Heading: 
Nonlinear Dynamics and Neuroscience
Article type: 
Article
UDC: 
530.182, 612.821.1
DOI: 
10.18500/0869-6632-2022-30-1-76-95

Revealing the neural network underlying covert picture-naming paradigm using magnetoencephalography

Autors: 
Chholak Parth, Universidad Politécnica de Madrid, Centre for Biomedical Technology
Tabari Fatemeh, Universidad Autónoma de Madrid
Pisarchik Alexander Nikolaevich, Universidad Politécnica de Madrid, Centre for Biomedical Technology
Abstract: 

The ability to name trivial everyday objects is a key cognitive function that is tested after head injuries or brain surgeries. Although quite a lot of long-standing knowledge on this topic has accumulated over the past few decades and many theoretical models have been created, the underlying neural substrate and brain functioning are still not fully aligned. As far as we know, there have been no studies on this topic using magnetoencephalography (MEG), which allows recording electrophysiological activity with a high temporal resolution. Therefore, to study the underlying spatio-temporal brain activations during the sensory and semantic processing of object naming, we conducted MEG experiments with 15 subjects grouped into three equal-sized groups with different types of language training and skills. Using boundary element methods for modelling cortical surfaces and dynamic statistical parametric mapping to solve the inverse problem, we reconstructed the cortical source activity from the recorded MEG data. The reconstructed cortical maps showed a homogeneous brain response in all three groups at the sensory processing stage, while the responses between the three groups at the semantic processing stage were different. In addition, average time courses were constructed for key brain regions such as the lateral occipital cortex (LO), fusiform gyrus (FG), Broca’s area (BA), and Wernicke’s area (WA). The obtained results assume unimodal forms for LO and WA time series, and bimodal forms for FG and BA. The only LO curve peak and the first FG peak resided in the time interval for the sensory processing stage, whereas, the only WA peak, the second FG peak and the second BA peak resided in the semantic processing stage. The first BA peak was located at the boundary separating the two stages. In addition to segregating regions involved in sensory and semantic processing, this study confirmed the involvement of FG in object naming (for the first time using MEG) that is at risk of resection during mesial temporal lobe epilepsy interventions. However, the results from this work are preliminary due to the limited sample size, and future research with a larger cohort of subjects are needed to verify/strengthen the findings of this study.

Key words: 
magnetoencephalography
picture naming
object recognition
cognitive neuroscience
visual perception
Acknowledgments: 
This study was supported by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Science, Technology and Higher Education (UID/PSI/01662/2019), through the national funds (PIDDAC). The data analysis was supported by the Russian Science Foundation, grant No. 19-12-00050. The authors acknowledge Dr. Adriana Sampaio and Elena Garayzabal Heinze for their role in administering the experiments, fruitful suggestions, and financial support. We would also like to thank Eduardo Lopez-Caneda and Alberto J. Gonzalez-Villar for their help and support in data collection. Lastly, we thank the participating children and their parents along with the King’s College La Moraleja, Hastings School Madrid and C.E.I.P. Principe de Asturias who helped with the data collection and their invaluable input and support.
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Received: 
10.07.2021
Accepted: 
01.08.2021
Published: 
31.01.2022
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