Background
Neural events are characteristics, transient, coordinated, neural activities that we can identify in aggregated signals (e.g., local field potentials or LFPs). It has been shown some neural events have signatures across several scales (neurons, neural populations, and large-scale networks). Moreover, they are also closely connected to behavior; for instance, Sharp-Wave Ripples is one of the most studied neural events and, over two decades, it has been shown they are broadly involved in cognitive functions (from memory consolidation to offline and online planning).
Project theme
We will different methods for identifying neural events on electrophysiology data recorded from rodents, or/and mice, or/and primates. We will compare the results from different methods, a pick a subset to use for the next step. Then we will investigate the behavior in the vicinity of these events. If time allows, we will also investigate how between different brain regions interact during these events.
Skill we might need (N=necessary, D=desired, P=plus)
- (N) Have background (bachelor) in (computational) neuroscience, neuroscience, physics, mathematics, statistics, machine learning, psychology, and other related fields.
- (N) Familiarity with Python or/and MATLAB.
- (P) Being comfortable with programming (best would be, Python, or Matlab).
- (P) Have experience in the analysis of neurophysiology data.
- (P) Familiarity with machine learning techniques or/and sufficient mathematical background.
Learning targets
- Learn analysis of electrophysiology data
- Learn neural data analysis techniques
- Learn topics in systems and computational neuroscience
Relevant literature
- [1] Transient oscillations as computations for cognition: Analysis, modeling and function
- [2] The hippocampal sharp wave–ripple in memory retrieval for immediate use and consolidation
Interested?
If you are interested please fill this form, and select the corresponding project code. ] If you need further information please get in touch with the contact person noted below.
