While MRI continues to advance toward ever higher resolution of fine details of brain structure, electrophysiological techniques are still superior in their higher-temporal resolution. We make use of two such techniques with both Electroencephalography (EEG) and Event-Related Potential Studies (ERP) analyses.
The electroencephalogram (EEG) is a record of oscillating voltages between locations on the cerebral cortex that are obtained noninvasively at the scalp. We use a stretch cap to painlessly collect signals from up to 64 scalp sites at a time. From the ongoing mix of ongoing brainwave activity, we can identify and analyze specific potentials. These EEG components are coordinated brain responses to visual, auditory, or somatosensory trigger events that we can analyze to reveal cognitive and emotional brain responses using signal averaging techniques.
Event-related potentials (ERPs) and event-related oscillations (EROs) are components of the scalp-recorded EEG that are time-locked to selected tasks/stimuli. Fluctuations in the ERP waveforms reflect the brain activation that is consistently coordinated in response to triggering events in experimental tasks. Analyses of EROs are commonly divided into five bands: delta (less than 4 Hz), theta (4 - 8 Hz), alpha (8 - 13 Hz), beta (13 - 30 Hz), and gamma (greater than 30 Hz). Each of these oscillations is thought to have a functional significance associated with distinct brain states. For example, the alpha frequency band has been associated with a state of relaxation, while theta activity is observed during some sleep states and during quiet focusing.
While technologies such as MRI offer highly detailed imaging resolution, ERP/ERO responses provide exquisitely high-temporal resolution (~1 ms) that can reveal rapid changes in sensory and cognitive brain responses to selected tasks, as well as subtle differences across subject groups. These electrophysiological analyses provide an exciting complement to the excellent spatial resolution of brain activities provided by MRI. Thus, we are developing neuropsychological paradigms applicable to both EEG and fMRI environments, with the goal of acquiring EEG activities simultaneous with fMRI recordings.
Using ERP techniques, NARC examined salience of monetary reward magnitude (high, low, none) in healthy individuals using a response-inhibition paradigm. This study showed sensitivity of the P300 (an ERP component) to the sustained and graded monetary reward in young, healthy adults (Goldstein et al., 2006), which was absent in age-matched, cocaine addicted individuals (Goldstein et al., 2008). More recently, with the same task, we found that this deficit in reward sensitivity is associated with recency of cocaine use, such that cocaine-addicted individuals with less frequent recent cocaine use (i.e., more protracted withdrawal) show decreased P300 sensitivity as compared to those with more frequent recent cocaine use, whose P300 sensitivity did not differ from that of healthy controls (Parvaz et al., 2016).
Using a reinforcement learning/gambling paradigm we have shown that cocaine-addicted individuals also show deficits in both positive (better than expected) and negative (worse than expected) reward prediction errors. Interestingly, this deficit was also modulated by the recency of cocaine use, such that positive prediction error deficit in addicted individuals may have been temporarily alleviated by recent cocaine use (Parvaz et al., 2015). With this task, we also showed that Reward Positivity component of the ERP can be used to specifically track anhedonia (i.e., the decreased capacity to experience pleasure) in cocaine-addicted individuals (Parvaz et al., 2016c).
In this project, we looked at emotion processing in drug addiction by examining the late positive potential (LPP) component of ERP recorded while subjects passively viewed pleasant, unpleasant, neutral, and cocaine-related pictures. We conducted this project in collaboration with Greg Hajcak, PhD. Results showed that cocaine pictures initially elicited increased electrocortical measures of motivated attention (i.e., LPP amplitude) in ways similar to the affectively pleasant and unpleasant pictures, an effect that was no longer discernible during the late LPP window for current users. This group also exhibited deficient processing of the other emotional stimuli. Results supported a relatively early attention bias to cocaine stimuli in cocaine-addicted individuals, further suggesting that recent cocaine use is characterized by deficient processing of emotional stimuli (Dunning et al., 2011).
In another related project, also in collaboration with Greg Hajcak, PhD, we explored if the explicit instruction to regulate emotion can result in emotion regulation and if it can be quantified using EEG and ERP biomarkers. Our results showed that anterior alpha ERO was sensitive to the activation of top-down prefrontal regulatory mechanisms involved in emotion regulation and the centro-parietal LPP amplitude was sensitive to the bottom-up processes of emotional valuation (Parvaz et al., 2012). These results show that ERP and ERO markers can be used to study emotion regulation in cocaine-addicted individuals.
Finally, we have used affective response as measured with EEG to predict subsequent behavior. For example, we found that LPPs elicited by drug cues predicted subsequent drug-related decision making (Moeller et al., 2012).
Multimodal ERP-MRI Studies
In these studies, we used ERPs in conjunction with structural MRI to establish associations between the high-temporal resolution functional biomarker of reward sensitivity (P300 amplitude) and inhibitory control (N200 amplitude) and the integrity of underlying brain structures (e.g., gray matter volume). In the first project, we showed that reward-modulated P300 amplitude was positively correlated with gray-matter volume of orbitofrontal, dorso- and ventrolateral prefrontal cortex in healthy control subjects. In contrast, cocaine-addicted individuals demonstrated reduced structural integrity of these prefrontal brain regions and reduced P300 responses to reward. They also failed to show the association between reward-modulated P300 amplitude and gray-matter volumes of these brain regions (Parvaz, Konova et al., 2012). In a subsequent project, we showed that N200 amplitude (a marker of inhibitory control) was correlated with the gray matter volume of the mid-cingulate cortex in healthy control subjects, and this association was also absent in cocaine-addicted individuals (Parvaz et al., 2014).
EEG-Based Brain Computer Interface (BCI)
The main goal of this project is to develop and evaluate a BCI-investigative tool that directly uses measurements of neural processing in real time to decrease craving in drug addiction and anger in individuals with intermittent explosive disorder. Over the past few years, a number of BCI and neurofeedback techniques have been developed to translate deliberate neural responses into machine control; however, researchers have not yet fully explored their application to psychopathologies of decreased self-control.