ELECTROPHYSIOLOGY

Question 1

How is the world out there perceived, comprehended and acted by neurons in the brain?

*Neuroscience

Answer 1

Neural representation
The way in which objects and properties of the outside world manifest themselves in the neural signal (e.g. different spiking rates for different stimuli)

Question 2

How is the world out there perceived, comprehended and acted by neurons in the brain?

**Cognitive psychology

Answer 2

Mental representations
The way in which objects and properties of the outside world manifest themselves in the mind, Example: the image of a person (grandmother).

Question 3

Neuronal recording

Answer 3

(single and multi unit recording)

Question 4

Electroencephalography

Answer 4

(changes in electrical potential on the scalp)

Question 5

HOW DOES IT WORK? Single Cell and Multi-Unit Recordings

Answer 5

Invasive: it requires implanting a microelectrode in the brain tissue (normally conducted in animals).

Question 6

intercellular vs extracellular and measurment of action potential

Answer 6

When neurons fire an action potential, the change in voltage is recorded by the electrode.
We can then relate neuronal activity to experimental events (stimuli/responses). By studying the relationship between neuronal responses and experimental events, we can investigate what cognitive processes the brain area we’re recording from is involved.

Question 7

fine neuroanatomy - What can we measure?

Answer 7

Activity of a single neuron (single-unit recording)

Activity of multiple neurons (multi-unit recording)

Question 8

Activity of a single neuron (single-unit recording)

Answer 8

We can look at firing rate: count of action potentials (“spikes”) per sec

Question 9

Activity of multiple neurons (multi-unit recording)

Answer 9

We can look at the pattern of activity across neurons (e.g. synchronous firing)

Question 10

What coding schemes does the brain use (Rolls & Deco, 2002)?

Answer 10

1 - Local representation
2- Sparse distributed
3- Fully distributed representation

Question 11

Local representation

What coding schemes does the brain use

Answer 11

All the information about a stimulus is carried by one neuron (grandmother cell).

Question 12

Sparse Distributed representation

What coding schemes does the brain use

Answer 12

All the information is carried by a few neurons in a population.

Question 13

Fully distributed representation

What coding schemes does the brain use

Answer 13

All the information is carried by all the neurons in a population.

Question 14

Grandmother cells

Answer 14

Single-cell recording in an epileptic patient during surgery. This neuron fires when the
patient sees a picture of a specific person (Halle Berry) but not pictures of other persons.

Question 15

Electroencephalography (EEG)

Answer 15

Continuous recording of electrical activity in the brain

Event-related potentials (ERPs)

Non-invasive: main electrophysiological technique in humans
Electrodes placed on the scalp
Measures summed electrical potentials
from millions of neurons

Note: electrical signals from a single neuron are too small to record non-invasively and can’t be distinguished from signals from other neurons.

Question 16

Event-related potentials (ERPs)

Answer 16

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Question 17

How/Why can we detect electrical

Answer 17

activity of neurons on the scalp?

Synchronously active populations of neurons generate a large enough electrical field

Not measuring action potentials; instead postsynaptic potentials in dendrites

Question 18

the signal from a single neuron is too small to detect at the scalp
So how do we detect signals at all?

Answer 18

Synchronously active neurons: spiking at the same time

Physiological origin of EEG signal is the postsynaptic potentials in dendrites of cortical neurons (not action potentials)

Question 19

Electroencephalography (EEG)

EEG electrode arrangement

Answer 19

The 10–20 system of electrodes used in a typical EEG/ERP experiment.

Question 20

Predictable EEG for different behavioral states

Answer 20

Important in clinical investigations as an indicator of:
Alertness
Brain Health (e.g. epilepsy)

*NOT widely used in cognitive neuroscience.

Question 21

USING EEG TO STUDY COGNITION

Answer 21

In a continuous EEG recording, can’t tell what part of the signal has to do with the cognitive process of interest

What we can do is have the participant perform a task and look at the portions of the signal at critical periods (during stimuli or responses)

Say we’re interested in the brain’s response to hearing tones
What might we do if we’re interested in the brain’s response to the tones?
Kind of obvious: just look at the portions of the signal when person is hearing ones

Question 22

Using EEG to study cognition: Event-related potentials (ERPs)

Answer 22

Activity from several trials is averaged together to extract signal (e.g. electrical activity associated with stimulus onset) from noise (e.g. background electrical activity)

Question 23

Data for any one trial consists of response to stimulus + random noise

What happens when you average?

increase signal-to-noise ratio

Answer 23

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Question 24

Signal to noise ratio: like in math, a fraction
Here when noise decreases, SNR goes up.
How else could we make SNR go up?

Answer 24

Why does averaging increase SNR?

Assumptions
Noise is random, therefore, when averaged across trials
it should cancel out

Signal is not random and it
is similar across trials, so it
should not cancel out.

Noise is random: sometimes positive, sometimes negative
One moment you may be thinking about the weather, another thinking about what you had for dinner last night.
Average of zero
Like if I got you guys to all pick a random number between plus 10 and minus 10, the average would be zero

But signal is not zero – similar every time
So by averaging we’re reducing the noise, just like on the last slide, which increases the signal to noise ratio.

Question 25

ERP COMPONENTS

Answer 25

Electrodes record a series of positive (P) and negative (N) peaks

Peaks referred to consecutively (P1, P2) or based on timing (e.g. P300 is positive peak around 300ms)

Question 26

Features of interest in ERP

Answer 26

Amplitude: size of electrical change (microvolts, mV)
Number of neurons working together

Latency: time from onset of stimulus
How quickly neurons react

Question 27

EXAMPLE OF FEATURES OF INFERENCE

Answer 27

NoGo N2: successful no-go trials
Neural activity associated with inhibiting habitual responses
N2 latency decreases and amplitude increases with age
Neurons associated with inhibition become more efficient with age

Question 28

Advantages and Disadvantages of ERP

Answer 28

ERP signal is directly related to neural activity
I.e. it is a direct measure of neural activity

Electrical activity is conducted instantaneously to the scalp
ERP has an excellent temporal resolution

Can’t tell where the ERP signal is coming from
ERP has poor spatial resolution

Question 29

Spatial Resolution of ERPs

Answer 29

Two problems:
Electrical signal from a particular source is distorted
When it hits the skull, tends to spread underneath the scull

Question 30

Spatial Resolution of ERPs

The inverse problem

Answer 30

Given an electrical signal recorded at the scalp, can’t know where it’s coming from
Where in the cortex are the signals coming from? How many sources are there?

Question 31

DIPOLES

Answer 31

Getting around the inverse problem (badly)
Some researchers use dipole modeling: this makes assumptions about the number of dipoles (regions of electrical activity aka brain areas)

Better still, if interested in spatial resolution, use another technique (e.g. fMRI or Magnetoencelography)

Question 32

How are ERP components related to cognitive processes?

Answer 32

Recording electrical signal at the scalp, (but really interested in cognitive processes (e.g. perception, attention, memory). ) - (()) ESBER
How are ERP components related to cognitive processes?

In ERP, different peaks may approximately reflect the functioning of different cognitive stages

Not a simple relationship between ERP peak and cognition, because each peak is a sum of different electrical activities

Imagine a simple cognitive task like the go no-go task. Might require 3 cognitive processes:
Perceive the stimulus, make a decision, execute a motor response.
We get people to do this task, observe an ERP wave like this.
What’s your guess about how these ERP components are relate to those cognitive processes?
So that would mean that the timing of this component is related to the timing of that cognitive process.

You’d be wrong!
It’s not the case that this wave that we measure definitely represents some particular cognitive process
We can’t say that Peak 1 represents perceiving the stimulus

Imagine 3 cognitive processes located in 3 different parts of the brain, say one for perceiving the stimulus, one for making a decision, one for making a motor response
When each one of those is active, going to produce electrical changes
If their activity overlaps, what we measure at the scalp is the sum of the electrical activity of all components that are active at the same time
Positive ones will make the signal go higher, negative ones will tend to make the signal lower

Question 33

ERP Summary

Answer 33

Based on EEG (electroencephalography) recordings
synchronized to some aspect of the event (e.g. onset of a stimulus)

EEG signal is averaged over many events
reduce effects of random neural firing

Electrodes record a series of positive and negative peaks

Timing (latency) and amplitude of the peaks may be related to different aspects of the stimulus and the task

Question 34

Single and multi-unit recordings

Answer 34

Invasive; excellent spatial and temporal resolution

Measure action potentials from individual neurons

Question 35

ERP

Answer 35

ERP - Overall summary -
Non-invasive; excellent temporal resolution, lower spatial resolution than single unit
Measure summed postsynaptic potentials from millions of neurons