Electrochemical Dynamic Underlying Human Short-term Memory-Learning: Concurrent Functional MRS-EEG
Poster No:
2112
Submission Type:
Abstract Submission
Authors:
Hossein Mohammadi1, Nasim Dadashi Serej*1,2, Nader Riyahi Alam*3,4, Shahriyar Jamshidi1, Hassan Khajehpour5, Iman Adibi6, Abbas Abbas Rahimiforoushani7, Shaghayegh Karimi8
Institutions:
1Department of Bioimaging, Isfahan University of Medical Sciences (IUMS), Isfahan, Iran, Islamic Republic of, 2School of Computing and Engineering, University of West London, London , United Kingdom, 3Concordia University, PERFORM Center, School of Health, Montreal, Quebec, Canada, 4Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran , Iran, Islamic Republic of, 5Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Quebec, Canada, 6Department of Neurology, School of Medicine, Isfahan University of Medical Sciences (IUMS),, Isfahan, Iran, Islamic Republic of, 7Department of Epidemiology & Biostatistics, School of Public Health, TUMS, Tehran, Iran, Islamic Republic of, 8Department of Medical Physics & Biomedical Engineering, School of Medicine, TUMS, Tehran, Iran, Islamic Republic of
First Author:
Hossein Mohammadi
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)
Isfahan, Iran, Islamic Republic of
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)
Isfahan, Iran, Islamic Republic of
Co-Author(s):
Nasim Dadashi Serej*
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)|School of Computing and Engineering, University of West London
Isfahan, Iran, Islamic Republic of|London , United Kingdom
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)|School of Computing and Engineering, University of West London
Isfahan, Iran, Islamic Republic of|London , United Kingdom
Nader Riyahi Alam*
Concordia University, PERFORM Center, School of Health|Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS)
Montreal, Quebec, Canada|Tehran , Iran, Islamic Republic of
Concordia University, PERFORM Center, School of Health|Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS)
Montreal, Quebec, Canada|Tehran , Iran, Islamic Republic of
Shahriyar Jamshidi
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)
Isfahan, Iran, Islamic Republic of
Department of Bioimaging, Isfahan University of Medical Sciences (IUMS)
Isfahan, Iran, Islamic Republic of
Hassan Khajehpour
Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University
Montreal, Quebec, Canada
Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University
Montreal, Quebec, Canada
Iman Adibi
Department of Neurology, School of Medicine, Isfahan University of Medical Sciences (IUMS),
Isfahan, Iran, Islamic Republic of
Department of Neurology, School of Medicine, Isfahan University of Medical Sciences (IUMS),
Isfahan, Iran, Islamic Republic of
Abbas Abbas Rahimiforoushani
Department of Epidemiology & Biostatistics, School of Public Health, TUMS
Tehran, Iran, Islamic Republic of
Department of Epidemiology & Biostatistics, School of Public Health, TUMS
Tehran, Iran, Islamic Republic of
Shaghayegh Karimi
Department of Medical Physics & Biomedical Engineering, School of Medicine, TUMS
Tehran, Iran, Islamic Republic of
Department of Medical Physics & Biomedical Engineering, School of Medicine, TUMS
Tehran, Iran, Islamic Republic of
Introduction:
Understanding the complex interactions between electrical and metabolic processes in the brain is essential for elucidating the mechanisms underlying short-term memory (STM). These electrochemical, or electro-metabolic, interactions are fundamental to cognitive functions, reflecting the dynamic interplay where electrical activity influences metabolic processes and vice versa. This interplay ensures neurons receive the energy required for sustained activity during memory tasks.
Working memory relies on STM and the temporary storage of sensory information. The glutamate-gated NMDA receptor is essential in memory and learning processes by controlling synaptic plasticity. It operates within a feedback loop where metabolic activity regulates electrical processes and metabolic energy is utilized to synthesize neurotransmitters. Previous fMRI and EEG studies have implicated the frontal and parieto-occipital cortices in STM; however, the dynamic electrochemical interactions, particularly in the right hemisphere, remain inadequately explored.
This groundbreaking study focuses on glutamate levels and glutamate-regulated electrical activity, simultaneously investigating metabolic and electrophysiological changes during rapid memory loads. Utilizing a unique combination of functional Magnetic Resonance Spectroscopy (fMRS) and EEG, this research aims to provide novel insights into the right hemisphere's involvement in STM processes.
Working memory relies on STM and the temporary storage of sensory information. The glutamate-gated NMDA receptor is essential in memory and learning processes by controlling synaptic plasticity. It operates within a feedback loop where metabolic activity regulates electrical processes and metabolic energy is utilized to synthesize neurotransmitters. Previous fMRI and EEG studies have implicated the frontal and parieto-occipital cortices in STM; however, the dynamic electrochemical interactions, particularly in the right hemisphere, remain inadequately explored.
This groundbreaking study focuses on glutamate levels and glutamate-regulated electrical activity, simultaneously investigating metabolic and electrophysiological changes during rapid memory loads. Utilizing a unique combination of functional Magnetic Resonance Spectroscopy (fMRS) and EEG, this research aims to provide novel insights into the right hemisphere's involvement in STM processes.
Methods:
Fourteen healthy right-handed participants (mean age = 30.64 ± 4.49, including five females) conducted simultaneous fMRS-EEG acquisitions during a modified Sternberg verbal working memory task, using memory loads of two, four, and six-letter sets. MR compatible 64 channel EEG electrodes and a trigger box inside a 3 Tesla Siemens MR scanner were used to perform simultaneous MRS-EEG acquisitions concurrently with the task display (Fig.1). In the right dorsolateral prefrontal cortex (DLPFC) and parieto-occipital regions, the glutamate/total-creatine (Glu/tCr) ratio was measured using single voxel MRS utilizing PRESS sequence with TR of 2000 and TE of 40 milliseconds to reduce overlapping signals of glutamate and glutamine. The MRS spectrums were analyzed by LCModel applying a simulated basis set and accounting for tissue and relaxation time correction. ICA extracted the brain activity components of EEG signals, and then the oscillatory activity was calculated in the corresponding surface source areas by applying the Fitting Oscillations and One-Over-F (FOOOF) code to compute the oscillatory power (Fig. 2).
Results:
Increased Glu/tCr modulation was observed with memory load intensification in the DLPFC (19.9%, p = 0.018) and parieto-occipital regions (33%, p = 0.046). Gamma oscillatory activity displayed a similar trend of increase in both regions (DLPFC: F(3,39) = 5.93, p = 0.005; parieto-occipital: F(3,39) = 9.23, p < 0.001). In contrast, alpha activity was suppressed in the parieto-occipital region (F(3,39) = 6.22, p = 0.022). Theta oscillations exhibited a positive correlation with Glu/tCr in the DLPFC (r = 0.317, p = 0.017) and a negative correlation in the parieto-occipital region (r = -0.576, p < 0.001).
Conclusions:
This study offers novel perspectives on how glutamate metabolism and neural oscillations interact during STM. Increased gamma activity in the right DLPFC and parieto-occipital areas was closely linked to elevated Glu/tCr levels. Furthermore, various neuronal mechanisms engaged in different phases of memory processing are suggested by the inverse association between theta oscillations and Glu/tCr levels in the target regions. These results extend the traditional left-hemisphere-centric hypothesis of verbal STM by demonstrating the complementary role of the right hemisphere in STM.
Learning and Memory:
Learning and Memory Other 2
Novel Imaging Acquisition Methods:
EEG
Physiology, Metabolism and Neurotransmission:
Cerebral Metabolism and Hemodynamics
Neurophysiology of Imaging Signals 1
Physiology, Metabolism and Neurotransmission Other
Keywords:
Learning
Magnetic Resonance Spectroscopy (MRS)
Memory
Neurotransmitter
Plasticity
Vision
Other - EEG, Electrophysiology, Metabolism, hemodynamics
1|2Indicates the priority used for review
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Provide references using APA citation style.
Bliss, T.V. and T. Lømo, Long‐lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. The Journal of physiology, 1973. 232(2): p. 331-356.
Castner, S. A., & Williams, G. V. (2007). Tuning the engine of cognition: a focus on NMDA/D1 receptor interactions in prefrontal cortex. Brain and cognition, 63(2), 94-122.
Ezzatdoost, K., Relating the circadian dynamics of cortical glutamate to human motor plasticity: a trimodal MRS-EEG-fMRI imaging study. 2023, Concordia University.
Barr, M. S., Farzan, F., Rusjan, P. M., Chen, R., Fitzgerald, P. B., & Daskalakis, Z. J. (2009). Potentiation of gamma oscillatory activity through repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex. Neuropsychopharmacology, 34(11), 2359-2367.
Emch, M., Von Bastian, C. C., & Koch, K. (2019). Neural correlates of verbal working memory: An fMRI meta-analysis. Frontiers in human neuroscience, 13, 180.
Hancu, I. (2009). Optimized glutamate detection at 3T. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 30(5), 1155-1162.
Mohammadi, H., Jamshidi, S., Khajehpour, H., Adibi, I., Rahimiforoushani, A., Karimi, S., Dadashiserej, N., & Riyahi Alam, N. (2024). Unveiling Glutamate Dynamics: Cognitive Demands in Human Short-Term Memory Learning Across Frontal and Parieto-Occipital Cortex: A Functional MRS Study. Journal of Biomedical Physics and Engineering.
Reiner, A., & Levitz, J. (2018). Glutamatergic signaling in the central nervous system: ionotropic and metabotropic receptors in concert. Neuron, 98(6), 1080-1098.