Vasiliki Bougou

Hierarchical and context-dependent encoding of actions in human posterior parietal and motor cortex.

Vasiliki Bougou, Jorge Gámez, Emily R. Rosario, Charles Liu et autres

Action understanding requires internal models that link visual input to motor goals. In monkeys, mirror neurons have been proposed to support this process through motor resonance during observation, yet single-unit evidence in humans remains scarce. We recorded neural activity from the motor …

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Hierarchical and context-dependent encoding of actions in human posterior parietal and motor cortex

Vasiliki Bougou, Jorge Gámez, Emily R. Rosario, Charles Y. Liu et autres

Action understanding requires internal models that link vision to motor goals. In monkeys, mirror neurons demonstrate motor resonance during observation, but single-unit evidence in humans is limited, leaving open whether such representations rely solely on motor resonance. We recorded neural activity from …

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Mesoscale insights in Epileptic Networks: A Multimodal Intracranial Dataset

Vasiliki Bougou, Michaël Vanhoyland, Evy Cleeren, Peter Janssen et autres

Understanding the intricate dynamics of epileptic networks at the mesoscale is crucial for advancing our knowledge of epilepsy pathophysiology and developing targeted interventions. In this data descriptor, we present a comprehensive dataset encompassing intracranial electroencephalography (iEEG) recordings, Local Field Potentials (LFP), and …

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Direct visualization of microwires in hybrid depth electrodes using high‐resolution photon‐counting CT

Steven Smeijers, Walter Coudyzer, Elina Keirse, Vasiliki Bougou et autres

Hybrid depth electrodes are increasingly being used for epilepsy monitoring and human neurophysiology research. Microwires extending from the tip of the Behnke-Fried (BF) electrode into (sub)cortical areas allow to isolate single neurons and perform microstimulation. Conventional CT or MRI visualize the entire …

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Neuronal tuning and population representations of shape and category in human visual cortex

Vasiliki Bougou, Michaël Vanhoyland, Alexander Bertrand, Wim Van Paesschen et autres

Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed large-scale recordings of spiking …

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Active and Passive Cycling Decrease Subthalamic β Oscillations in Parkinson's Disease

Vasiliki Bougou, Michaël Vanhoyland, Thomas Decramer, Anaïs Van Hoylandt et autres

BACKGROUND: Preserved cycling capabilities in patients with Parkinson's disease, especially in those with freezing of gait are still poorly understood. Previous research with invasive local field potential recordings in the subthalamic nucleus has shown that cycling causes a stronger suppression of β …

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Neuronal tuning and population representations of shape and category in human visual cortex.

Peter Janssen, Vasiliki Bougou, Michaël Vanhoyland, Alexander Bertrand et autres

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Neuronal tuning and population representations of shape and category in human visual cortex

Vasiliki Bougou, Michaël Vanhoyland, Alexander Bertrand, Wim Van Paesschen et autres

ABSTRACT Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed the first large-scale …

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Microscale Dynamics of Epileptic Networks: Insights from Multiunit Activity analysis in neurosurgical patients with refractory epilepsy

Vasiliki Bougou, Michaël Vanhoyland, Evy Cleeren, Thomas Decramer et autres

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Evaluation of EEG Connectivity Network Measures based Features in Schizophrenia Classification

Vasiliki Bougou, Iosif Mporas, Pascal A. Schirmer, Todor Ganchev

In this paper an architecture for the classification of Schizophrenia using EEG-based brain connectivity is proposed. Functional and effective networks were constructed from the EEG using a variety of connectivity measures and with graph theory metrics complex network features were extracted. Several …

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