Iliana is a postdoctoral researcher with the Brain Interfacing Laboratory. She graduated from Stanford with her Ph.D. in Electrical Engineering in 2023.
She has been awarded the Stanford Gerald J. Lieberman Fellowship (2022), the American Heart Association Predoctoral Fellowship (2021), the Cadence Women in Technology Scholarship (2021), and the NSF Graduate Research Fellowship (2017). She received her BS in Electrical Engineering with honors from Stanford in 2017 and was awarded the Firestone Medal for Excellence in Undergraduate Research for her honors thesis.
Iliana's long-term research interests involve combining electrical engineering and neuroscience to further our understanding of motor control and one day incorporate this new knowledge into improved brain-computer interfaces or enhanced rehabilitation for clinical populations with compromised mobility.
Honors & Awards
Gerald J. Lieberman Fellowship, Stanford University (2022)
Predoctoral Fellowship, American Heart Association (2021)
Women in Technology Scholarship, Cadence (2021)
Justice, Equity, Diversity & Inclusion (JEDI) Travel Award, Stanford School of Engineering (2021)
Graduate Research Fellowship, National Science Foundation (2017)
Firestone Medal for Excellence in Undergraduate Research, Stanford University (June 2017)
Education & Certifications
Ph.D., Stanford University, Electrical Engineering (2023)
B.S., Stanford University, Electrical Engineering (2017)
Neuroelectrophysiology-Compatible Electrolytic Lesioning
View details for DOI 10.7554/eLife.84385.1
Frequency shifts and depth dependence of premotor beta band activity during perceptual decision-making.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural activity in the premotor and motor cortices shows prominent structure in the beta frequency range (13-30 Hz). Currently, the behavioral relevance of this beta band activity (BBA) is debated. The underlying source of motor BBA and how it changes as a function of cortical depth is also not completely understood. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex (PMd) of two male rhesus macaques performing a visual reaction time (RT) reach discrimination task. We observed robust BBA before and after the onset of the visual stimulus but not during the arm movement. While post-stimulus BBA was positively correlated with RT throughout the beta frequency range, pre-stimulus correlation varied by frequency. Low beta frequencies (12 to 20 Hz) were positively correlated with RT and high beta frequencies (22 to 30 Hz) were negatively correlated with RT. Analysis and simulations suggested that these frequency-dependent correlations could emerge due to a shift in the component frequencies of the pre-stimulus BBA as a function of RT, such that faster RTs are accompanied by greater power in high beta frequencies. We also observed a laminar dependence of BBA, with deeper electrodes demonstrating stronger power in low beta frequencies both pre- and post-stimulus. The heterogeneous nature of BBA and the changing relationship between BBA and RT in different task epochs may be a sign of the differential network dynamics involved in cue expectation, decision-making, motor preparation, and movement execution.SIGNIFICANCE STATEMENTBeta band activity (BBA) has been implicated in motor tasks, in disease states, and as a potential signal for brain-machine interfaces. However, the behavioral relevance of BBA and its laminar organization in premotor cortex have not been completely elucidated. Here we addressed these unresolved issues using simultaneous recordings from multiple cortical layers of the premotor cortex of monkeys performing a decision-making task. Our key finding is that BBA is not a monolithic signal. Instead, BBA consists of at least two frequency bands. The relationship between BBA and eventual behavior, such as reaction time, also dynamically changes depending on task epoch. We also provide further evidence that BBA is laminarly organized, with greater power in deeper electrodes for low beta frequencies.
View details for PubMedID 30606756
- Exploration of available feature detection and identification systems and their performance on radiographs SPIE-INT SOC OPTICAL ENGINEERING. 2016
- Hybrid object detection system for X-ray radiographs SPIE-INT SOC OPTICAL ENGINEERING. 2016
- Exploring the feasibility of traditional image querying tasks for industrial radiographs SPIE-INT SOC OPTICAL ENGINEERING. 2015