Event-Related Potentials (ERPs)

2.7.1. Background of ERPs

The electroencephalogram (EEG) is a recording of neural electrical activity obtained by amplifying the signal from electrodes placed in contact with the scalp. EEG was reported for the first time in a set of experiments by Hans Berger in 1929 (Berger 1929). Over the ensuing decades, it has been used in a variety of clinical and scientific contexts. The main drawback of raw EEG is that it represents a conglomeration of simultaneously occurring neural activities making the isolation of individual phenomena of interest problematic. Responses to sensory stimuli can however be extracted from the background EEG activity by simple averaging of data following the onset of each stimulus. This method is based on the idea that spontaneous EEG activity has no fixed temporal relationship with the time point in which the stimulus is delivered; in contrast neural responses to sensory stimuli are time-locked to their onset. Averaging the data immediately following uniform events therefore leads to augmentation of the sensory response and reduces the contribution of unrelated neural activity. These responses are called event-related potentials (ERPs), highlighting the fact that they represent electrical responses to controlled events.

2.7.2. Neural basis of ERPs

Two main types of electrical activity are generated by neurons and could thus be the neural basis of ERPs: action potentials and postsynaptic potentials. The former are voltage spikes that travel from the beginning of the axon to its terminals. At the

Page | 45 terminal they cause release of neurotransmitters into the synaptic cleft resulting in excitation of the post-synaptic neuron. The latter are voltages that arise when neurotransmitters bind to post-synaptic receptors. Action potentials have negligible contribution to the generation of the ERP signal, as they last only about a millisecond, occur at slightly different times even in neurons that fire in a coordinated fashion and are not fixed but rather travel rapidly down axons. In contrast, post-synaptic potentials last up to hundreds of milliseconds and occur instantaneously at fixed locations (cell body) which allows their summation. The simultaneous occurrence of postsynaptic activity in millions of spatially aligned neurons produces a signal which may be measurable at the scalp. These requirements are most likely to be met by pyramidal cells lying perpendicular to the scalp. It is thus assumed that the ERP peaks are produced almost exclusively by the post-synaptic signal of coherently activated pyramidal neurons (Luck 2005).

2.7.3. Advantages and disadvantages of the ERP technique

The graded waxing and waning of postsynaptic potentials is volume conducted to the scalp where it is picked up by the EEG electrodes. With this type of conduction the delay between the brain activity and its reflection in EEG signal is below the millisecond level. This renders the ERP technique superior to other neuroimaging methods in terms of its temporal resolution: it allows tracking of activity on millisecond basis. It is however poorer than other methods in regards to its spatial resolution (the ability to indicate where activities originate from). This is due mostly to the substantial blurring of signal resulting from the weak conductive capacity of the scalp (Luck 2005).

2.7.4. ERP analysis

Event-related potential data are analyzed by determining the latency and amplitude of peaks of interest in a single electrode or a group of electrodes and using these values in statistical comparisons. Latencies can be measured by visually identifying the peak of interest and determining the latency of its highest point. This method however may introduce a subjective element, especially given that peaks often reach their maximum

Page | 46 at different electrodes in different participants. A more robust approach is to

determine the ERP latency of maximum activity using Global Field Potentials (GFP). This is a method that plots the overall ERP scalp activity which reduces the impact of individual topographical differences.

The main outcome measure of most ERP studies is the amplitude of ERP components. The most common approach in measuring peak amplitude is to determine a time window for each component of interest and to determine the maximum amplitude in this window. This method is called peak amplitude measure. Another method is to define the mean amplitude for the time window of interest (mean amplitude measure) (Luck 2005). The latter is the preferred approach due to several reasons. Firstly, searching for peaks in large time windows often detects the rising or falling edge of an irrelevant overlapping component. Using shorter time windows and using a non- automated approach to peak identification can help reduce the impact of this but introduces subjectivity of the data analysis, as each peak has to be individually selected by the researcher. Secondly, peak amplitude is susceptible to distortion by high-frequency noise. This is due to the possibility of noise deflection being registered as an ERP component, leading to artificially higher peak amplitudes in noisy recordings. Lastly, when there is substantial inter-trial variability in the peak latency, the peak amplitude of the averaged component will be lower than the

individual ERPs. In contrast to peak amplitude, mean amplitude measurement allows shorter windows of interest and does not become biased by noise levels or latency jitter.

2.7.5. Visual Evoked Potentials (VEPs)

The current thesis dealt with the electrophysiology of early visual information processing in schizophrenia and consequently focused on several well characterized visual ERPs. Three major visual evoked potentials (VEPs) peak within the first 200 ms post stimulus: the so-called C1, P1 and N1 (Figure 2.6). C1 is the first VEP peaking at approximately 80-100 ms and is largest at the midline occipital electrodes. Source analysis studies have suggested that it originates from the primary visual cortex (V1). C1 is positive in response to images presented in the lower visual field

Page | 47 and negative for stimuli appearing in the upper visual field (Di Russo et al. 2003). C1 has traditionally been attributed to bottom-up processes, but recent data suggest that it is more sensitive to internal states than previously thought (Kelly et al. 2008; Rauss et al. 2009). C1 is followed by P1, which has a typical bilateral occipital distribution (Figure 2.7). It peaks around 100-130 ms but its latency varies significantly depending on the contrast of the stimulus. Its cortical generators have been suggested to be the middle occipital gyrus (dorsal visual stream) and the fusiform gyrus (ventral visual stream) (Di Russo et al. 2002). P1 is the earliest visual component that is under top- down influence, as its amplitude is sensitive to the direction of spatial attention (Di Russo et al. 2003; Lalor et al. 2007). A cornerstone human lesion study showed that prefrontal cortex plays a key part in this top-down modulation (Barcelo et al. 2000). P1 is followed by N1, a negative potential peaking typically between 150 and 200 ms (Figure 2.6). It also has a bilateral occipital distribution and has been linked to activity primarily in the ventral visual stream (parietal cortex and lateral occipital cortex) (Di Russo et al. 2002). N1 amplitude is also modulated by spatial attention (Heinze et al. 1990). Functionally, C1 is thought to represent activation of the primary visual cortex; P1 reflects early pattern detection processes; N1 represents discriminative processing (Luck 2005).

This thesis focused on the characteristics of P1 and N1 potentials in schizophrenia spectrum disorders, as their amplitude and latency are a sensitive measure of the quality of early information processing. In addition, the fact that both of them are subject to top-down modulation renders them useful in testing the efficiency of long- range connectivity in schizophrenia.

Page | 48 Figure 2.6. An example of occipitally recorded VEP. Arrows show all major visual peaks except for C1. Large vertical tick at stimulus onset, vertical ticks at every 200 ms thereafter.

Figure 2.7. Topographical distribution of the P1 potential. Data presented for pairs of frontal (F3, F4), central (C3, C4) and occipital (O1, O2) electrodes.

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