Electoencephalogram (EEG) represents voltage differences (or oscillations) between two locations on the cerebral cortex that are recorded at the scalp. These recordings capture neural activity between the thalamus and the cortex. A set of small gelled electrodes held onto the scalp allow analysis systems to collect and analyze these brainwaves. We use a stretch cap to painlessly collect signals from up to 64 sites at a time. From this mix of ongoing EEG, brainwave potentials are collected. These coordinated brain responses to visual, auditory, or somatosensory trigger events that can be analyzed using signal averaging techniques.
Event-related potentials (ERPs)are components of the scalp-recorded EEG. This non-invasive technology records the brain's electrical signals that are time-locked to selected tasks/stimuli. ERPs (e.g. the N1, P2, N2 and P3 peaks) are the averaged responses time-locked to the experimental trigger event. These ERP components reflect the brain activation that is consistently coordinated in response to the triggering events in experimental tasks.
Event-related oscillations (EROs) are components of the EEG studied in the frequency, rather than time, domain. The frequency range of background EEG oscillations is 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 and has been associated with specific brain states. For example, alpha frequency band has been associated with a state of relaxation, while theta activity is observed during some sleep states, and during quiet focusing.
These ERP/ERO responses have high temporal resolution and can reveal minute changes in sensory and cognitive brain responses to selected tasks as well as subtle differences between subject groups. These analyses provide an exciting complement to the excellent spatial resolution of brain activities provided by fMRI . Thus, we are developing neuropsychological paradigms that can be used in both EEG and fMRI environments, with the goal of acquiring EEG simultaneously with fMRI recordings (in collaboration with Giorgio Bonmassar, Ph.D.) .
Using Event-Related EEG in the Study of Drug Addiction
We examined the effect of monetary reward salience on ERP components and behavior using a response inhibition paradigm in 16 healthy participants. The ERPs were recorded from 64 channels while subjects performed a warned reaction time Go/No-Go task; monetary reward conditions (high, low, none) varied across blocks of trials. This study showed sensitivity of the P3 (but not CNV) to this sustained and graded monetary reward in young healthy adults (Goldstein et al., 2006). Validating our fMRI results (Goldstein et al., 2007b), ERP results suggested a compromised P3 sensitivity to the same monetary reward in age-matched cocaine addicted individuals (Goldstein et al., 2008).
In this project we looked at emotion processing in drug addiction by examining the late positive potential (LPP) component of ERP while subjects passively view pleasant, unpleasant, neutral, and cocaine-related pictures. This project was carried out in collaboration with Greg Hajcak, Ph.D. Results showed that Cocaine pictures elicited increased electrocortical measures of motivated attention in ways similar to affectively pleasant and unpleasant pictures in all cocaine addicted individuals, 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 (early LPP window â€“ pleasant pictures; late LPP window â€“ pleasant and unpleasant pictures). Results were unique to the LPP and not EPN. Taken together, results support a relatively early attention bias to cocaine stimuli in cocaine addicted individuals, further suggesting that recent cocaine use decreases such attention bias during later stages of processing but at the expense of deficient processing of other emotional stimuli (Dunning et al., 2011).
In this project, subjects are asked to make decisions on a forced choice gambling task. Our goal here is to assess how behavior and psychophysiological response on the task is impacted by cocaine use. This project is carried out in collaboration with Greg Hajcak, Ph.D.
Brain Computer Interface (BCI).
The main goal of this project is to develop and evaluate a BCI-based investigative and assessment tool that directly utilizes measurements of neural processing in real-time to decrease craving in drug addiction. Over the past few years, a number of BCI and neurofeedback techniques have been developed to translate deliberate neural responses into machine control; however, application to psychopathologies of decreased self-control is yet to be explored. This project is carried out in collaboration with Dennis McFarland, Ph.D.