Dr. Ariel Tankus
Our research focuses on the development of novel neuroprostheses, also known as brain-machine interfaces (BMI) or brain-computer interfaces (BCI), for restoration of speech faculties which are devices aimed to artificially speak for a person based solely on his or her brain activity.
Participants in our research are neurosurgical patients undergoing implantation of depth electrodes for clinical reasons, for example due to Parkinson’s disease or epilepsy. With epilepsy patients we also investigate the neuronal basis of ictogenesis.Our goal is to let completely paralyzed people speak again using these devices. For this, we study the neuronal encoding of speech features at the single neuron level as well as artificial intelligence (AI) methods, for example deep learning (DL), to decode the neuronal information and infer speech contents.
Behavioral Neuroscience
Clinical Neuroscience
Brain Disorders Research
- A. Tankus, E. Stern, G. Klein, N. Kaptzon, L. Nash, T. Marziano, O. Shamia, G. Gurevitch, L. Bergman, L. Goldstein, F. Fahoum, I. Strauss. A speech neuroprosthesis in the frontal lobe and hippocampus: decoding high frequency activity into phonemes. Neurosurgery, 96(2):356-364, 2025.
- A. Tankus, N. Rosenberg, O. Ben-Hamo, E. Stern, I. Strauss. Machine Learning Decoding of Single Neurons in the Thalamus for Speech Brain-Machine Interfaces. Journal of Neural Engineering, 21(3):036009, 2024.
- A. Tankus, L. Solomon, Y. Aharony, A. Faust-Socher, I. Strauss. Machine Learning Algorithm for Decoding Multiple Subthalamic Spike Trains for Speech Brain-Machine Interfaces. Journal of Neural Engineering, 18:066021, 2021.
- A. Tankus, Y. Lustig, G. Gurevitch, A. Faust-Socher, I. Strauss. Neuronal Encoding of Speech Features in the Human Thalamus in Parkinson’s Disease and Essential Tremor Patients. Neurosurgery, 94(2):307-316, 2024.
- A. Tankus, I. Fried, S. Shoham. Structured neuronal encoding and decoding of human speech features. Nature Communications, 3:1015, 2012.
