The work in our lab is concerned with better understanding the contribution of dynamic neural processes to intra- and inter-individual variability in cognitive functioning. This research primarily involves behavioral and EEG/MEG studies with healthy individuals, which we ultimately plan to extend to neuropsychiatric groups.
Our studies typically combine standardized cognitive assessments (as typically applied in neuropsychological assessment) with experimental tasks and ERP or time-frequency analysis of task-related and spontaneous EEG data. Although much of our work addresses basic questions in cognitive electrophysiology, we believe our focus on neural dynamics and momentary behavioral variation will be increasingly relevant to clinical neuropsychology, particularly as the field moves more toward assessment of subtle dysfunction that is apt characterize mild or sub-clinical conditions (e.g., persons at risk for neurodegenerative disorders, mild TBI sequelae, cognitive effects of chronic illnesses, neuropsychiatric conditions, etc.). A number of related sub-questions emerge out of the basic lab framework. Some examples from current projects include:
- What are the shared features of tasks that elicit cognitive differences, and what are the neural bases of those effects?
- What role do novelty, expectation, and uncertainty play in relation to adaptive behavior and cognitive functioning?
- How do neural oscillatory phenomena relate to cognitive differences, and to the current major biological theories of intelligence such as the Neural Efficiency Hypothesis, and Parieto-Frontal Integration Theory?
- In what ways does the structure of spontaneous neural activity constrain task-related dynamics, and particularly in response to unexpected events?
- How do factors like fatigue and motivation impact neuropsychological test performance, and how can EEG/ERP measures help us better understand those effects?
Ultimately, we hope that this work can shed light on the functional mechanisms of fluid cognitive dysfunction, and help improve approaches to neuropsychological assessment.
OPPORTUNITIES FOR STUDENTS
Graduate: I am unlikely to recruit a new graduate student for the class entering Fall 2020. Students who are apt to have the best fit with the lab are those seeking a career in clinical neuropsychology, and who also have a strong interest in electrophysiology and neural mechanisms of cognition. Prior experience with electrophysiology, neuroimaging, and/or programming is highly valued, as is prior experience in clinical settings or with patient populations.
Students who join the lab will have many opportunities to contribute to the projects described above, and to develop their own novel directions that are consistent with the general laboratory focus.
Postdoctoral Fellowship, Medical College of Wisconsin (Adult Clinical Neuropsychology,
Ph.D., University of New Mexico (Psychology, 2010)
M.S., University of New Mexico (Psychology, 2007)
B.A., New Mexico State University (Psychology & Philosophy, 2003)
McKinney, T.L., Euler, M.J., & Butner, J.E. (2019). It’s about time: The role of temporal variability in improving assessment of executive functioning. The Clinical Neuropsychologist.
McKinney, T.L., & Euler, M.J. (2019). Neural anticipatory mechanisms predict faster reaction times and higher fluid intelligence. Psychophysiology. 2019;00:e13426.
Euler, M.J. (2018). Intelligence and uncertainty: Implications of hierarchical predictive processing for the neuroscience of cognitive ability. Neuroscience and Biobehavioral Reviews, 94, 93-112. Download
Euler, M.J., McKinney, T.L., Schryver, H.M., &, Okabe, H. (2017). ERP Correlates of the Decision Time-IQ Relationship: The Role of Complexity in Task- and Brain-IQ Effects. Intelligence, 65, 1-10. Download
Wiltshire, T.J., Euler, M.J., McKinney, T.L., & Butner, J.E., (2017). Changes in dimensionality and fractal scaling suggest soft-assembled dynamics in human EEG. Frontiers in Physiology, 8:633. Download
Euler, M. J., Weisend, M. P, Jung, R. E., Thoma, R. J., & Yeo, R. A. (2015). Reliable activation to novel stimuli predicts higher fluid intelligence. NeuroImage, doi: 10.1016/j.neuroimage.2015.03.078 Download
Euler, M. J., Niermeyer, M. A., & Suchy, Y. (2016). Neurocognitive and neurophysiological correlates of motor planning during familiar and novel contexts. Neuropsychology, http://dx.doi.org/10.1037/neu0000219 Download
Euler, M. J., Wiltshire, T., Niermeyer, M. A., & Butner, J. E. (2016). Working Memory Performance Inversely Predicts Spontaneous Delta and Theta-band Scaling Relations. Brain Research, 1637, 22-33. http://dx.doi.org/10.1016/j.brainres.2016.02.008 Download
Suchy, Y., Euler, M. J., & Eastvold, A. (2014). Exaggerated reaction to novelty as a subclinical consequence of mild traumatic brain injury. Brain Injury. Advance online publication. doi: 10.3109/02699052.2014.888766 Download
MY CURRENT GRADUATE STUDENTS