David Bruce Grayden

This study shows that tagging frequency affects neural responses and cognitive performance in attention tasks using SSVEPs and ERPs.

This paper presents a simulation framework to evaluate EEG source localisation methods by generating biologically plausible seizure dynamics and EEG signals with known ground truth.

This paper uses structural eigenmodes of the brain to improve EEG source localization in epilepsy, finding geometric eigenmodes slightly outperform connectome eigenmodes.

This study uses a neural mass model to predict seizure duration from neural connectivity patterns in a rat epilepsy model, finding that preictal connectivity parameters can forecast seizure length with high accuracy.

This study identifies dynamic multiday seizure cycles in a Tetanus Toxin rat model, showing evolving rhythms that may inform seizure prediction and treatment.

This study identifies cyclical patterns in seizure duration in the Tetanus Toxin rat model, showing predictable rhythms linked to EEG power, which could improve epilepsy management.

This study uses a neural mass model to analyze iEEG data from a Tetanus Toxin rat epilepsy model, finding correlations between connectivity weights and seizure frequency, and showing longer recovery times before seizures.

This paper demonstrates that micro intravascular electrodes can record high-quality ivEEG signals from cortical and deep veins, enabling better spatial resolution and functional mapping compared to traditional methods.

This study uses a neural mass model to show reduced synaptic heterogeneity in a Tetanus Toxin rat epilepsy model, linked to increased network synchrony.

This paper introduces a predictive coding model to study motion detection, showing how prior knowledge and sensory data balance in schizophrenia, with longer convergence times in higher noise.

This paper introduces adaptive delayed feedback control (aDFC) to disrupt neuronal oscillations and shows it outperforms standard DFC in reducing network synchrony.

This paper investigates how epilepsy patients respond to photic stimulation, finding differences in EEG biomarkers that suggest cortical excitability changes associated with seizure states.

The paper develops a neural mass model of a cortical column to study inhibitory stabilization across layers, finding that layers 4 and 5 exhibit ISN behavior with paradoxical responses, while layer 2/3 does not.

This paper proposes a biologically plausible model for learning complex cells in V1 using BCM rule-based plasticity, showing it can replicate experimental diversity in receptive field properties.

This study analyzes long-term intracranial EEG recordings to examine variability and circadian patterns of high-frequency activity and epileptiform spikes in patients with drug-resistant epilepsy.

The paper was withdrawn due to a duplicate posting and directs readers to the current version on bioRxiv.

This study shows that GABA-mediated tonic inhibition differentially modulates gain in cortical interneurons based on their electrophysiological properties.

This study identifies critical slowing as a biomarker for seizure susceptibility using long-term iEEG recordings from epilepsy patients.