James Ashe, MD
Professor, Department of Neuroscience
Professor, Department of Neuroscience
The primary interest of my laboratory is in motor learning in the most general sense. We are concerned with how we learn regularities in our immediate environment and how this learning is reflected in our actions and behavior. To address these issues, we use psychophysical studies, functional imaging in humans, and direct neural recording from areas in frontal cortex in non-human primates.
- Motor learning of new dynamic environments. We have been examining the neural control of adaptation and learning in specific physical environments, usually in the form of state dependent force fields. The work focuses on the learning, storage, and consolidation of and interference with internal models of motor behavior.
- Neural basis and mechanisms of motor learning in probabilistic environments. We examine how subjects use probabilistic information and predictability in their immediate environment to shape their actions and behavior. The learning behaviors we study range from complex probabilistic patterns to deterministic sequences.
- Neural control and learning of serial order. The concept of serial order is fundamental to much of our behavior from basic motor function to language production. We have examined the neural basis of serial order and sequence production in well practiced motor behaviors and also during the learning of these behaviors through trial and error.
- The modulation of action through reward. Much of our behavior is shaped by rewards (both external and internal); we have recently begun to examine how reward (and punishment) influences motor learning. Disruption of the reward-action system may be a fundamental problem in some disease conditions such as Parkinsons disease.
- Neural control of goals versus actions. In everyday life, we typically decide on goals and then perform the actions to achieve them. We are now studying the system in prefrontal cortex that deals with goals and actions in an effort to understand how these interrelated factors are controlled.
Tadipatri, VA, Tewfik, AH, Pellizzer, G & Ashe, J 2017, ‘Overcoming Long-Term Variability in Local Field Potentials Using an Adaptive Decoder’ IEEE Trans Biomed Eng, vol. 64, no. 2, pp. 319-328. https://doi.org/10.1109/TBME.2016.2557070
Lungu, OV, Bares, M, Liu, T, Gomez, CM, Cechova, I & Ashe, J 2016, ‘Trial-to-trial Adaptation: Parsing out the Roles of Cerebellum and BG in Predictive Motor Timing’ J Cogn Neurosci, vol. 28, no. 7, pp. 920-34. https://doi.org/10.1162/jocn_a_00943
Lu, X & Ashe, J 2015, ‘Dynamic reorganization of neural activity in motor cortex during new sequence production’ Eur J Neurosci, vol. 42, no. 5, pp. 2172-8. https://doi.org/10.1111/ejn.12979
Tadipatri, VA, Tewfik, AH & Ashe, J 2014, ‘Long-term decoding of arm movement using Spatial Distribution of Neural Patterns’ Conf Proc IEEE Eng Med Biol Soc, vol. 2014, pp. 1642-5. https://doi.org/10.1109/EMBC.2014.6943920
Ashe, J & Bushara, K 2014, ‘The olivo-cerebellar system as a neural clock’ Adv Exp Med Biol, vol. 829, pp. 155-65. https://doi.org/10.1007/978-1-4939-1782-2_9
Bareš, M, Apps, R, Kikinis, Z, Timmann, D, Oz, G, Ashe, JJ, Loft, M, Koutsikou, S, Cerminara, N, Bushara, KO & Kašpárek, T 2015, ‘Proceedings of the workshop on Cerebellum, Basal Ganglia and Cortical Connections Unmasked in Health and Disorder held in Brno, Czech Republic, October 17th, 2013’ Cerebellum, vol. 14, no. 2, pp. 142-50. https://doi.org/10.1007/s12311-014-0595-y
Tadipatri, VA, Tewfik, AH, Ashe, J & Pellizzer, G 2013, ‘Source localization techniques for direction decoding from local field potentials’ Conf Proc IEEE Eng Med Biol Soc, vol. 2013, pp. 838-41. https://doi.org/10.1109/EMBC.2013.6609631
Tadipatri, VA, Tewfik, AH, Ashe, J & Pellizzer, G 2012, ‘Robust movement direction decoders from local field potentials using spatio-temporal qualitative patterns’ Conf Proc IEEE Eng Med Biol Soc, vol. 2012, pp. 4623-6. https://doi.org/10.1109/EMBC.2012.6346997
Wu, X, Ashe, J & Bushara, KO 2011, ‘Role of olivocerebellar system in timing without awareness’ Proc Natl Acad Sci U S A, vol. 108, no. 33, pp. 13818-22. https://doi.org/10.1073/pnas.1104096108
Gowreesunker, BV, Tewfik, AH, Tadipatri, VA, Ashe, J, Pellize, G & Gupta, R 2011, ‘A subspace approach to learning recurrent features from brain activity’ IEEE Trans Neural Syst Rehabil Eng, vol. 19, no. 3, pp. 240-8. https://doi.org/10.1109/TNSRE.2011.2106802