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Electrophysiology

Electrophysiology. Neurons are Electrical. Remember that Neurons have electrically charged membranes they also rapidly discharge and recharge those membranes (graded potentials and action potentials) Review relevant textbook sections if this isn’t familiar to you. Neurons are Electrical.

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Electrophysiology

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  1. Electrophysiology

  2. Neurons are Electrical • Remember that Neurons have electrically charged membranes • they also rapidly discharge and recharge those membranes (graded potentials and action potentials) • Review relevant textbook sections if this isn’t familiar to you

  3. Neurons are Electrical • Importantly, we think the electrical signals are fundamental to brain function, so it makes sense that we should try to directly measure these signals • but how?

  4. Subdural Grid • Intracranial electrodes typically cannot be used in human studies

  5. Subdural Grid • Intracranial electrodes typically cannot be used in human studies • It is possible to record from the cortical surface Subdural grid on surface of Human cortex

  6. Electroencephalography and the Event-Related Potential • Could you measure these electric fields without inserting electrodes through the skull?

  7. Electroencephalography and the Event-Related Potential • 1929 – first measurement of brain electrical activity from scalp electrodes (Berger, 1929)

  8. Electroencephalography and the Event-Related Potential Voltage Time • Place an electrode on the scalp and another one somewhere else on the body • Amplify the signal to record the voltage difference across these electrodes • Keep a running measurement of how that voltage changes over time • This is the human EEG

  9. Electroencephalography and the Event-Related Potential • 1929 – first measurement of brain electrical activity from scalp electrodes (Berger, 1929) • Initially believed to be artifactual and/or of no significance

  10. Electroencephalography • pyramidal cells span layers of cortex and have parallel cell bodies • their combined extracellular field is small but measurable at the scalp!

  11. Electroencephalography • The field generated by a patch of cortex can be modeled as a single equivalent dipolar current source with some orientation (assumed to be perpendicular to cortical surface) Duracell

  12. Electroencephalography • Electrical potential is usually measured at many sites on the head surface • More is sometimes better

  13. Magnetoencephalography • For any electric current, there is an associated magnetic field Electric Current Magnetic Field

  14. Magnetoencephalography • For any electric current, there is an associated magnetic field • magnetic sensors called “SQuID”s can measure very small fields associated with current flowing through extracellular space Electric Current Magnetic Field SQuID Amplifier

  15. Magnetoencephalography • MEG systems use many sensors to accomplish source analysis • MEG and EEG are complementary because they are sensitive to orthogonal current flows • MEG is very expensive

  16. EEG/MEG • EEG changes with various states and in response to stimuli

  17. EEG/MEG • Any complex waveform can be decomposed into component frequencies • E.g. • White light decomposes into the visible spectrum • Musical chords decompose into individual notes

  18. EEG/MEG • EEG is characterized by various patterns of oscillations • These oscillations superpose in the raw data 4 Hz 4 Hz + 8 Hz + 15 Hz + 21 Hz = 8 Hz 15 Hz 21 Hz

  19. How can we visualize these oscillations? • The amount of energy at any frequency is expressed as % power change relative to pre-stimulus baseline • Power can change over time 48 Hz % change From Pre-stimulus 24 Hz 16 Hz Frequency 8 Hz 4 Hz +200 +400 +600 0 (onset) Time

  20. Where in the brain are these oscillations coming from? • We can select and collapse any time/frequency window and plot relative power across all sensors Win Lose

  21. Where in the brain are these oscillations coming from? • Can we do better than 2D plots on a flattened head? • we (often) want to know what cortical structures might have generated the signal of interest • One approach to finding those signal sources is Beamformer

  22. Beamforming • Beamforming is a signal processing technique used in a variety of applications: • Sonar • Radar • Radio telescopes • Cellular transmision

  23. Beamformer • Applying the Beamformer approach yields EEG or MEG data with fMRI-like imaging R L

  24. The Event-Related Potential (ERP) • Embedded in the EEG signal is the small electrical response due to specific events such as stimulus or task onsets, motor actions, etc.

  25. The Event-Related Potential (ERP) • Embedded in the EEG signal is the small electrical response due to specific events such as stimulus or task onsets, motor actions, etc. • Averaging all such events together isolates this event-related potential

  26. The Event-Related Potential (ERP) • We have an ERP waveform for every electrode

  27. The Event-Related Potential (ERP) • We have an ERP waveform for every electrode • Sometimes that isn’t very useful

  28. The Event-Related Potential (ERP) • We have an ERP waveform for every electrode • Sometimes that isn’t very useful • Sometimes we want to know the overall pattern of potentials across the head surface • isopotential map

  29. The Event-Related Potential (ERP) • We have an ERP waveform for every electrode • Sometimes that isn’t very useful • Sometimes we want to know the overall pattern of potentials across the head surface • isopotential map Sometimes that isn’t very useful - we want to know the generator source in 3D

  30. Brain Electrical Source Analysis • Given this pattern on the scalp, can you guess where the current generator was?

  31. Brain Electrical Source Analysis • Given this pattern on the scalp, can you guess where the current generator was? Duracell

  32. Brain Electrical Source Analysis • Source Analysis models neural activity as one or more equivalent current dipoles inside a head-shaped volume with some set of electrical characteristics

  33. Brain Electrical Source Analysis Project “Forward Solution” This is most likely location of dipole Compare to actual data

  34. Brain Electrical Source Analysis • EEG data can now be coregistered with high-resolution MRI image

  35. Intracranial and “single” Unit • Single or multiple electrodes are inserted into the brain • “chronic” implant may be left in place for long periods

  36. Intracranial and “single” Unit • Single electrodes may pick up action potentials from a single cell • An electrode may pick up thecombined activity from several nearby cells • spike-sorting attempts to isolate individual cells

  37. Intracranial and “single” Unit • Simultaneous recording from many electrodes allows recording of multiple cells

  38. Intracranial and “single” Unit • Output of unit recordings is often depicted as a “spike train” and measured in spikes/second Stimulus on Spikes

  39. Intracranial and “single” Unit • Output of unit recordings is often depicted as a “spike train” and measured in spikes/second • Spike rate is almost never zero, even without sensory input • in visual cortex this gives rise to “cortical grey” Stimulus on Spikes

  40. Intracranial and “single” Unit • By carefully associating changes in spike rate with sensory stimuli or cognitive task, one can map the functional circuitry of one or more brain regions

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