Biology subjects

Ghaderi, A.

Publications and source records attributed to Ghaderi, A..

4 recordsLinked to original sources

bioRxiv2025

High-Frequency Spinal Cord Stimulation Reorganizes Cortical Cross-Frequency Coupling in a Region- and Time-Dependent Manner

Pain management strategies have progressed beyond traditional pharmacologic and physical interventions, integrating advanced neuromodulation techniques such as deep brain stimulation, peripheral nerve stimulation, and high-frequency spinal cord stimulation (hSCS). Despite its clinical efficacy, the supraspinal mechanisms underlying hSCS remain poorly understood. Prior work in sheep demonstrated that hSCS modulates gamma ({gamma}) band (70-150 Hz) activity in the primary somatosensory and association cortices, implicating cortical involvement in pain modulation. Given, the interaction between low and high oscillations, we hypothesized that hSCS modulates {gamma} activity in a region- and time-dependent manner through specific coupling with theta ({square}) rhythms (4-8 Hz). Using 96-channel subdural electrocorticography (ECoG), we computed {square}-{gamma} phase-amplitude coupling (PAC) and the corresponding modulation index (MI) to quantify the effects of hSCS. While the preferred {square}phase of {gamma} activity remained consistent across conditions and regions, MI increased significantly post-stimulation--most prominently in the association cortex, where robust -{gamma} phase locking was observed. In contrast, the somatosensory cortex exhibited weaker and more variable locking. Temporally, both cortices demonstrated an early, rapid increase in MI post-hSCS, accompanied by a shift (association) and attenuation (somatosensory) of the secondary peak. These findings reveal distinct regional and temporal dynamics in PAC following hSCS and suggest complementary roles of somatosensory and association cortices in processing neuromodulatory input. hSCS appears to reorganize cortical cross-frequency interactions, supporting its role in reorganizing functional network dynamics relevant to sensory processing and the subjective pain experience.

neuroscience↗

bioRxiv2025

Spatial task instructions and global activation trends influence functional modularity in the cortical reach network

Humans can be instructed to ignore visual cues or use them as landmarks for aiming movements (Musa et al. 2024), but it is not known how such allocentric cues interact with egocentric target codes and general planning activity to influence cortical network properties. To answer these questions, we applied graph theory analysis (GTA) to a previously described fMRI dataset (Chen et al. 2014). Participants were instructed to reach toward targets defined in egocentric or landmark-centered (allocentric) coordinates. During Egocentric pointing, cortical nodes clustered into four bilateral modules with correlated BOLD signals: a superior occipital-parietal / somatomotor module, an inferior parietal / lateral frontal module, a superior temporal / inferior frontal module, and an inferior occipital-temporal / prefrontal module. The Allocentric task showed only three modules, in part because inferior occipital nodes were incorporated into the superior occipital-parietal / somatomotor module. Both tasks engaged local (within module) and global (between module) cortical hubs, but the Allocentric task recruited additional hubs associated with allocentric visual codes and ego-allocentric integration. Removing reach-related activation trends reduced global synchrony and increased clustering, specifically diminishing dorsoventral coupling in the allocentric task. Cross-validated decoding confirmed that modularity provided the best predicter of task type and suggest that temporal / parietal modules spanning prefrontal cortex play an important role in task instruction. These results demonstrate that activation trends related to motor plans influence global network integration, whereas task instructions influence intermediate / local network properties, such as the modular integration and hub recruitment observed in our Allocentric task. HighlightsO_LIThe study explores how egocentric and allocentric cues affect cortical networks. C_LIO_LIGraph theory analysis (GTA) was applied to fMRI data from pointing tasks. C_LIO_LIEgocentric pointing formed four cortical modules; allocentric formed three. C_LIO_LIAllocentric tasks recruited additional hubs for dorsal-ventral integration. C_LIO_LIRemoving reach-related activation trends reduced global synchrony in the allocentric task. C_LI

neuroscience↗

bioRxiv2024

Saccades Influence Functional Modularity in the Human Cortical Vision Network

Visual cortex is thought to show both dorsoventral and hemispheric modularity, but it is not known if the same functional modules emerge spontaneously from an unsupervised network analysis, or how they interact when saccades necessitate increased sharing of spatial information. Here, we address these issues by applying graph theory analysis to fMRI data obtained while human participants decided whether an objects shape or orientation changed, with or without an intervening saccade across the object. BOLD activation from 50 vision-related cortical nodes was used to identify local and global network properties. Modularity analysis revealed three sub-networks during fixation: a bilateral parietofrontal network linking areas implicated in visuospatial processing and two lateralized occipitotemporal networks linking areas implicated in object feature processing. When horizontal saccades required visual comparisons between visual hemifields, functional interconnectivity and information transfer increased, and the two lateralized ventral modules became functionally integrated into a single bilateral sub-network. This network included between module connectivity hubs in lateral intraparietal cortex and dorsomedial occipital areas previously implicated in transsaccadic integration. These results provide support for functional modularity in the visual system and show that the hemispheric sub-networks are modified and functionally integrated during saccades.

neuroscience↗

bioRxiv2024

Visual network modularity and communication alterations in ADHD subtypes: evidence from source localized EEG and graph theoretical analysis

The neurobiological basis of ADHD and its subtypes remains unclear, with inconsistent findings from studies using electrophysiology and neuroimaging. Some studies suggest ADHD-I is a distinct disorder, but there is also evidence of similar neural basis in ADHD-I and ADHD-C subtypes. This study investigates the neural basis of ADHD and its subtypes using a subnetwork modularity approach based on graph theoretical analysis of EEG data from 35 children aged 7-11. EEG was recorded in the eyes open condition and preprocessed. After preprocessing, data was analyzed using LORETA algorithm to estimate current densities in 84 regions of interest (ROIs) in the cortex and calculate functional connectivity between these ROIs in different EEG frequency bands. Then, we evaluated modularity of five functional brain networks (default mode, central control, salience, visual, and sensorimotor) using Newman modularity algorithm. Further, we evaluated edge betweenness centrality to assess communications between these functional brain networks. The study found that different brain networks have modularity in certain frequency bands, and ADHD groups showed reduced modularity of the visual network compared to normal groups in the alpha1 band (8-10 Hz). The communication between the visual network and other brain networks, except the salience network, was also reduced in ADHD groups (in the alpha1 band). However, there were no significant differences in the modularity of brain networks and communication among them between two ADHD subtypes. The results suggest a novel mechanism for ADHD involving lower intrinsic modularity in the visual network, disturbed communication between the visual network and other networks, and potential impact on the function of control and sensorimotor networks. Further, our results suggest that there may be a common neural basis for both subtypes, involving a shared disturbance in the modularity and connectivity of the ventral network. This supports the idea that ADHD-I and ADHD-C are subtypes within the same category and contradicts previous studies that suggest they are separate disorders.

neuroscience↗