Unit 2: ERPs and oscillations

 What do event-related potentials (ERPs) help researchers study?

The electrocortical dynamics of information processing—how the brain’s electrical activity changes over time as it processes information.

What does it mean for an ERP to be “time-locked” to an event?

Brain activity is aligned to the timing of a specific event, such as a stimulus or response.

What types of events can researchers use to time-lock ERPs?

Stimuli and responses.

 Why is the same event repeated throughout an ERP task?

To collect multiple trials of brain activity that can be aligned and averaged.

What is an epoch in ERP research?

A segment of EEG activity surrounding a specific event.

Why do researchers average epochs?

To reduce activity that is not time-locked to the event and reveal the event-related activity.

 What happens to activity that is not time-locked as more trials are averaged?

It tends to cancel out and approach zero.

With an infinite number of trials, what would happen to the non-time-locked activity?

Under the averaging assumption, it would average to zero.

How are ERP components typically named?

By their peak timing and polarity (e.g., P100) or the specific event eliciting the response (e.g., ERN, error-related negativity).

What does P100 mean?

A positive ERP component that peaks approximately 100 milliseconds after an event.

How are early and later ERP components broadly categorized?

Early components reflect bottom-up sensory processes; later components reflect top-down cognitive processes.

What are the limitations of the fixed-latency, averaged ERP approach?

• Voltage differences are difficult to compare and interpret.

• The neuroanatomical basis of the signal or effect is uncertain.

• Averaging removes potentially interesting activity that is not phase-locked to event onset.

Why move beyond the time domain when studying EEG?

ERPs reveal only a limited picture of EEG dynamics, leaving out potentially meaningful activity.

When might the ERP averaging approach be impractical?

When collecting a sufficiently large number of trials is not feasible.

Why doesn’t brain function always fit the “ERP format”?

Brain activity is not always time-locked to specific events, and what is treated as “background noise” may be meaningful.

What is an EEG signal composed of?

A mixture of sine waves with different frequencies, amplitudes, and phases

Why are EEG oscillations useful markers of brain function?

They more directly reflect the properties of cells and networks and may be among the richest markers of function available from EEG.

At what scales do brain oscillations occur, and where are they observed?

They occur at multiple spatial and temporal scales and are observed across species.

Can oscillatory analysis investigate single-trial activity?

Yes—it can examine activity in individual trials.

What happens to ERP information when oscillatory analysis is added?

Nothing is lost; ERP analysis is enhanced.

 What features of oscillatory dynamics can researchers examine?

Spectral power density, phase consistency/coherence, evoked versus induced activity, cross-frequency coupling, and functional connectivity.

What are the types of cross-frequency coupling?

Amplitude-amplitude, phase-phase, and amplitude-phase.

 What can spectral dynamics reveal that the ERP approach may miss?

Important EEG features that are obscured or lost through ERP averaging.

What activity do ERPs capture?

Activity that is both time-locked and phase-locked relative to an event.

How do amplitude and phase help measure event-related changes?

They provide distinct but complementary measurements of event-related changes