research

 Our research on phenomenology has focused on determining: 1) whether  negative symptoms are best conceptualized as a categorical, dimensional,  or hybrid construct; 2) how many domains are part of the negative  symptom construct. Our findings indicate that negative symptoms are a  hybrid dimensional-categorical construct, such that people with  schizophrenia differ in kind above a certain symptom threshold that is  predictive of individual differences in the severity of several external  correlates. Early work that we and others conducted on the factor  structure of negative symptoms supported a two dimensional  conceptualization. However, most recently, we have found that the  construct is best considered in relation to 5 domains (anhedonia,  avolition, asociality, blunted affect, alogia); this finding has been  replicated using multiple mathematical techniques (e.g., CFA and network analysis), using multiple scales (BNSS, CAINS, SANS), across multiple cultures, both sexes, and all phases of illness (prodromal, first episode, chronic) suggesting that the 5 domain conceptualization  is robust. Recently, we have been examining whether these 5 domains have  distinct pathophysiological mechanisms and clinical correlates to  determine whether a change is needed for DSM-5 negative symptom  diagnostic criteria and whether the 5 domains reflect distinct treatment  targets. 

 The development of next-generation negative symptom  assessments has been another key focus of research in the CAN Lab. In  2005, NIMH held a consensus development conference on negative symptoms.  A key conclusion of this meeting was that new rating scales were needed  to increase chances of observing treatment effects. Two second generation negative symptom rating scales resulted  from this initiative. Dr. Strauss was co-developer of one of these  scales, the Brief Negative Symptom Scale (BNSS), and served as PI on  multiple studies validating the scale. Dr Strauss has also led efforts  in translating the BNSS into over a dozen languages  and facilitating  its primary intended use as an outcome measure in industry sponsored  clinical trials.  He has also begun developing and validating novel digital phenotyping measures of negative  symptoms that likely reflect the third generation of negative symptom  assessment (e.g., geolocation, accelerometry, ambient sound, measures of facial and vocal affect recorded from ambulatory videos).  We are pioneering big data analytic approaches for evaluating digital phenotyping data.

 The primary focus of our research is on identifying  mechanisms underlying negative symptoms. Our initial studies examined  the most straightforward explanation for avolitional symptoms in  schizophrenia- that individuals fail to engage in activities because they  do not find them rewarding; however, this hypothesis was not supported  because subjective and neurophysiological response to rewarding stimuli  is intact in schizophrenia. This finding lead us to explore why  apparently normal hedonic responses do not translate into goal-directed  behavior in schizophrenia. We have demonstrated that abnormalities in  several aspects of reward processing (e.g., reinforcement learning,  effort-cost computation, value representation, uncertainty-driven  exploration) that are driven by aberrant cortico-striatal interactions  may prevent intact hedonic responses from influencing decision-making  processes that are needed to initiate motivated behavior. We have also  demonstrated that avolition is associated with dysfunctional  cognition-emotion interactions (e.g., memory, attention), emotion  regulation abnormalities, social cognition impairments, a reduction in  the positivity offset, and anhedonic beliefs. Most recently, we are exploring a novel "bioecosystem" theory of negative symptoms that proposes interactions between person-level biological and psychological factors with environmental systems (microsystem, mesosystem, exosystem, and macrosystem) that cause or maintain negative symptoms.

 In collaboration with colleagues in psychiatry, Dr. Strauss has conducted clinical trials examining the  efficacy of pharmacological treatments for negative symptoms. Based on  our studies showing a role for endogenous oxytocin in social cognition  deficits and negative symptoms, we examined the efficacy of oxytocin as a  treatment for asociality. In two trials, oxytocin was not more  effective than placebo, and we recently extended this work by  demonstrating that combining oxytocin with psychosocial treatment has no  added benefit over psychosocial treatment alone. In collaboration with the pharmaceutical industry, we have examined the symptom network structure that predicts successful treatment of negative symptoms. In a phase 2B study of Roluperidone, we found that avolition was the most central symptom for the treatment of negative symptoms- when motivational deficits were successfully targeted, a casscadidng effect was seen in terms of improvement in the other 4 domains: asociality, anhedonia, blunted affect, alogia. This was replicated in the Phase 3 roluperidone trial.  We have also explored the efficacy of a cognitive behavioral mHealth intervention for negative symptoms using a novel app-based therapy. 

In the past few years, we have  expanded our work on the phenomenology, etiology, assessment, and treatment  of negative symptoms into the psychosis prodrome. In the Georgia and Illinois Negative Symptom Study (GAINS) R01, we developed and validated a new scale for those at clinical high-risk for psychosis, the  Negative Symptom Inventory- Psychosis Risk. Individuals at clinical high-risk for psychosis are best fit by a 5 factor and hierarchical model, suggesting similar underlying factor structure to schizophrenia. In our studies examining negative symptom mechanisms,  we have found that reward processing deficits  predict the severity of negative symptoms in youth at clinical high-risk for psychosis. However, due  to the greater propensity for depression in this phase of illness,  hedonic deficits play a greater role in negative symptoms in the  prodrome than in schizophrenia, propagating forward and creating  deficits in other aspects of reward processing that also occur in  schizophrenia. We are currently conducting longitudinal studies to  determine which reward processing mechanisms associated with negative  symptoms predict the emergence of psychotic disorders versus other  conditions (e.g., depression) in youth at clinical high-risk for  psychosis in the CAPR R01. This study also seeks to develop a symptom sensitive online cognitive task screening battery that can index level of psychosis risk.

Our research on emotion regulation aims to delineate the nature of emotion regulation abnormalities at various stages (identification, selection, implementation, monitoring dynamics) across phases of psychosis. We find a similar profile in prodromal and chronic illness phases, characterized by a low threshold for identifying the need to regulate, difficulty selecting contextually appropriate strategies, less effective implementation, and greater rates of switching and stopping regulatory attempts. Using EMA, EEG, fMRI, and eye tracking, we find evidence for moderators of these stage-specific abnormalities, such as effort allocation, prefrontal-amygdala coupling, dysfunctional patterns of attention, and emotional awareness.In an R61 grant from NIMH, we recently showed that an emotion regulation intervention delivered over an app can augment some of these underlying mechanisms, increasing attentional control and prefrontal activation. In the R33 phase of the grant, we are examining whether mechanism engagement can be replicated in a subsequent study and whether prefrontal activation enhancement predicts subsequent improvement in symptoms. 

We use EEG to examine the time-course of neural activity in relation to various emotional and cognitive processes. EEG involves recording electrical activity along the scalp. EEG measures voltage fluctuations resulting from ionic current flows within neurons. In our studies, we have primarily been interested in Event Related Potentials (ERPs), which are averaged EEG responses that are time-locked to stimuli in an experiment. For example, we have examined time-locked response to pleasant, unpleasant, and neutral images to explore the time-course of affective response in people with schizophrenia compared to controls. Our EEG studies are conducted within our laboratory in the Psychology Department. We have three 64-channel Brain Vision ActiChamp Systems. We have been using EEG/ERPs since 2010.

We use eye-tracking to measure the role of visual attention in various cognitive and emotional processes. We do this by measuring point of gaze or motion of the eyes relative to the head and a stimulus presented on the computer screen using an eye-tracker. The eye-tracker monitors the position of the pupil, pupil size, and corneal reflection as a participant views images on the screen. We have used eye-tracking to explore individual components of attention and how they interact with emotional vs. neutral stimuli in people with schizophrenia and controls. We are also interested in how pupil dilation is impacted by various manipulations of emotion and cognitive load. Our lab has two SR Research Eyelink 1000 systems that are used to measure attentional allocation and pupil dilation. This desktop mounted system allows for a remote and headfree evaluation of eye-movements at a very high sampling rate. We also interface EEG/ERPs and eye-tracking in the lab and fMRI and eye tracking at the BIRC.  We have been using eye tracking since 2004.

Our fMRI studies are conducted at UGA's Biomedical Imaging Research Center (BIRC): https://birc.uga.edu/. The BIRC houses a state-of-the-art, General Electric 32-channel fixed-site Signa HDx 3.0 Tesla Magnetic Resonance Imaging (MRI) magnet. The magnet makes available multiple magnetic resonance imaging techniques including magnetic resonance imaging for structural tissue imaging (MRI), functional neuroimaging (fMRI) for studies of brain activation in real time, magnetic resonance spectroscopy (MRS) for the study of chemical changes in the brain, and magnetic resonance angiography (MRA) for the study of vascular changes throughout the system. Multinuclear spectroscopy (MNS) is available for enhanced spectroscopic studies and includes phosphorous-31.  We have been using fMRI since 2019.

We use the wireless Bionomadix recording system from Biopac to examine facial electromyography, respiration, heart rate, and skin conductance. These psychophysiological measures allow us to explore the timecourse of psychophysiological response in relation to emotional reactivity and emotion regulation tasks, as well as the coherence between subjective, neural, and peripheral psychophysiological response when used in conjunction with our other measures. We use the wireless bionomadix system in our studies involving social interaction, as well as more traditional computerized laboratory paradigms examining emotion.  We have been using peripheral psychophysiology since 2013.

We use digital phenotyping to explore symptoms and their mechanisms as they occur in everyday life. Participants are asked to carry a smart phone and wear a digital band that collects psychophysiology for several days in the context of everyday life. Participants report their current activities, as well as their emotional experience during those activities at several points throughout the day. The internal sensors of the phone also passively collect objective data related to behavior via measurements of accelerometry, geolocation, and ambient sound. Participants also record brief videos on the cell phone that are later submitted to automated algorithms for processing facial and vocal affect. We are using these digital phenotyping methods to explore hypotheses related to negative symptoms, as well as the reliability and validity of active and passive data collection methods as third-generation negative symptom measures. We have been using digital phenotyping since 2015.

We obtain salivary and blood samples to test hypotheses related to neuroendocrine (e.g., cortisol) and immune (cytokines) function in relation to task performance. Salivary samples are obtained and stored in a -40 freezer located in our lab in the Psychology building. Blood samples are obtained and stored at the Clinical Translational Research Unit on the UGA Medical School campus. We have been gathering saliva/blood draws since 2010.  

The BNSS is a 13-item psychiatric rating scale designed to assess the negative symptoms of schizophrenia. The scale is rated after completing a 15-minute interview. The BNSS includes a brief but comprehensive 9 page manual, a workbook to be used when conducting the clinical interview, and a scoresheet. In multiple psychometric studies, the BNSS has demonstrated excellent inter-rater agreement, internal-consistency, test-retest reliability, convergent validity, and discriminant validity. It produces a 5 factor solution for the domains of anhedonia, avolition, asocality, restricted affect, alogia. The BNSS has been, or is currently in the process of being translated into several languages, including: Spanish, Italian, German, Cantonese, French, Korean, and Turkish. Individuals interested in obtaining BNSS materials and publications can visit our Resources page. Commercial entities wishing to use the BNSS in clinical trials can contact Prophase, which offers professional BNSS training that was developed in consultation with the test developers. Drs. Strauss and Kirkpatrick receive royalties and consultation fees from Prophase LLC in connection with commercial use of the BNSS and other professional activities. Individual researchers/research groups may use the BNSS free of charge and obtain training materials by contacting Dr. Strauss gstrauss@uga.edu or Dr. Kirkpatrick bkirkpatrick@unr.edu 

 The NSI-PR is a new measure that was developed via a multi-site collaborative R01 from NIMH as part of the Georgia and Illinois Negative Symptom Study (GAINS). The study is conducted in the laboratories of Dr. Gregory Strauss at UGA, Dr. Vijay Mittal at Northwestern, and Dr. Elaine Walker at Emory University.  The final measure was developed as part of an iterative data-driven process based on multiple studies. It is currently being validated as part of the GAINS R01 and will be used in the multi-site ProNet U01.  It is an 11 item clinical rating scale designed to assess negative symptoms in the prodromal phase of illness specifically. The scale is rated after a 15 minute interview. Materials include a manual, interview guide, scoresheet, and frequently asked questions sheet. A powerpoint introductory training lecture and instructional training videos  are also available upon request. To obtain the latest version please email Dr. Strauss gstrauss@uga.edu or Dr. Mittal: vijay.mittal@northwestern.edu. 

We are developing and validating a number of novel digital phenotyping methods for assessing psychiatric symptoms. These involve active methods (e.g., daily surveys, cognitive tests, videos) completed by the participant on the phone, as well as passive methods that involve unobtrusively recording objective measures of symptoms via the internal sensors of the phone (e.g., geolocation, accelerometry, ambient sound). Contact Dr. Strauss at gstrauss@uga.edu for details.