Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.neuroimage.2023.120364 | DOI Listing |
Angew Chem Int Ed Engl
January 2025
East China Normal University, Dept. of Chemistry, Dongchuan Road 500, 200062, Shanghai, CHINA.
Monitoring dynamic neurochemical signals in the brain of free-moving animals remains great challenging in biocompatibility and direct implantation capability of current electrodes. Here we created a self-supporting polymer-based flexible microelectrode (rGPF) with sufficient bending stiffness for direct brain implantation without extra devices, but demonstrating low Young's modulus with remarkable biocompatibility and minimal position shifts. Meanwhile, screening by density functional theory (DFT) calculation, we designed and synthesized specific ligands targeting Mg2+ and Ca2+, and constructed Mg-E and Ca-E sensors with high selectivity, good reversibility, and fast response time, successfully monitoring Mg2+ and Ca2+ in vivo up to 90 days.
View Article and Find Full Text PDFJ Headache Pain
January 2025
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.
View Article and Find Full Text PDFBrain Topogr
January 2025
Department of Radiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, No 152, Ai Guo Road, Dong Hu District, Nanchang, Jiangxi, 330006, China.
Stroke is a condition characterized by damage to the cerebral vasculature from various causes, resulting in focal or widespread brain tissue damage. Prior neuroimaging research has demonstrated that individuals with stroke present structural and functional brain abnormalities, evident through disruptions in motor, cognitive, and other vital functions. Nevertheless, there is a lack of studies on alterations in static and dynamic functional network connectivity in the brains of stroke patients.
View Article and Find Full Text PDFSci Rep
January 2025
Civil and Transportation College, Beihua University, Jilin, China.
An improved concrete structure health monitoring method based on G-S-G is proposed, which fully combines an optimized Gray-Level Co-occurrence Matrix (GLCM) with an improved Self-Organizing Map (SOM) neural network to achieve accurate and real-time concrete structure health monitoring. First of all, in order to obtain a dynamic image of the crack damage region of interest (ROI) with clear contrast and obvious target, the image acquisition system and image optimization method are used to process the damaged image. Moreover, in order to realize the accurate location of crack damage, crack damage identification research based on GLCM-SOM effectively eliminates the interference of honeycomb and pothole damage on crack damage.
View Article and Find Full Text PDFJ Oral Facial Pain Headache
March 2024
Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, 100081 Beijing, China.
Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysiology and developing effective analgesics. However, pain assessment methods for TN mouse models have not been widely studied, resulting in a critical gap in our understanding of TN. With the rapid advancement of deep learning, numerous pain assessment methods based on deep learning have emerged.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!