Hayriye Cagnan

The paper finds evidence of traveling beta waves in the subthalamic nucleus of Parkinson's patients using local field potential recordings and a spherical wave model.

The paper investigates cerebellar oscillatory activity during motor tasks and finds that cerebellar rhythms adjust their influence based on cue predictability.

This study shows that state-dependent deep brain stimulation in Parkinson's disease increases movement speed more effectively during fast movements, using machine learning to decode brain signals for real-time adjustments.

This study identifies disruptions in rhythmic brain networks in essential tremor patients during naturalistic movement, linking altered network engagement to motor deficits and tremor severity.

The paper identifies multiple spatially discrete beta ensembles in parkinsonian cortico-basal ganglia networks, showing they form functionally connected clusters of neurons.

This study shows that transcranial random noise stimulation improves inhibitory behavior by increasing low-beta power and intermittent beta-burst duration, particularly in impulsive individuals.

The paper investigates how reward, effort, and choice are encoded hierarchically across the cortex and basal ganglia during cost-benefit decisions in rats.

The paper models selective visual attention in macaques using Dynamic Causal Modeling to show that intrinsic V1 modulation explains attention effects in V1-V4 communication through changes in inhibition.

The paper investigates how burst characteristics in beta rhythms of the motor cortex differ across movement states and how they contribute to state classification and cortical processing.

This paper demonstrates how connectivity in the cortico-basal-ganglia circuit influences beta oscillations and shows that phase-locked stimulation can modulate these oscillations based on network state.

This study shows that alternating subthalamic nucleus deep brain stimulation can entrain stepping rhythms in Parkinson's patients, suggesting the STN's role in step timing control.

This paper introduces a framework using Approximate Bayesian Computation to infer large-scale brain networks from empirical data, demonstrating its ability to identify generating models and estimate parameters accurately.

The paper uses a Wilson-Cowan model to analyze phase-dependent effects of deep brain stimulation in essential tremor patients, showing the model can predict tremor responses and fit patient data.

This paper predicts the effects of deep brain stimulation using a reduced coupled oscillator model and proposes a hybrid strategy for closed-loop DBS in essential tremor patients.

This study examines beta burst dynamics in the cortico-basal ganglia network of PD patients and rats, showing phase relationships and rhythmic activity patterns that correlate with motor impairment.

This study investigates the neural mechanisms underlying transitions in cortical beta power in Parkinsonian rats using dynamic causal modeling and identifies key thalamocortical coupling patterns.

This study shows that phase-dependent electrical stimulation can suppress beta oscillations in Parkinson's patients, offering a potential therapeutic strategy.