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Electrophysiology. Neurons are Electrical Remember that Neurons have electrically charged membranes they also rapidly discharge and recharge those membranes.

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Presentation on theme: "Electrophysiology. Neurons are Electrical Remember that Neurons have electrically charged membranes they also rapidly discharge and recharge those membranes."— Presentation transcript:

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 Time Voltage -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)

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 Magnetic Field Electric Current

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 Magnetic Field Electric Current 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 8 Hz 15 Hz 21 Hz 4 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 Frequency Time 0 (onset) +200+400 4 Hz 8 Hz 16 Hz 24 Hz 48 Hz % change From Pre-stimulus +600

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 WinLose

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 L R

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?

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 This is most likely location of dipole Project “Forward Solution” 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 the combined 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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