Research
Phenomenology of Negative Symptoms
Phenomenology of Negative Symptoms
Phenomenology of Negative Symptoms
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.
Assessment of Negative Symptoms
Phenomenology of Negative Symptoms
Phenomenology of Negative Symptoms
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. Most recently, he co-developed and validated a new scale for those at high-risk, the Negative Symptom Inventory- Psychosis Risk, which is being examined in an R01 from NIMH. 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.
Etiology of Negative Symptoms
Treatment of Negative Symptoms
Treatment of Negative Symptoms
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. In the past few years, we have expanded our work on the etiology of negative symptoms into the psychosis prodrome, where we have found that reward processing deficits predict the severity of negative symptoms in at-risk youth. 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. 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.
Treatment of Negative Symptoms
Treatment of Negative Symptoms
Treatment of 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. Most recently, we are exploring the efficacy of a novel app-based cognitive training intervention for improving emotion regulation abnormalities via a direct mechanistic effect on the prefrontal cortex. We are examining whether increased prefrontal activation leads to better emotion regulation, and whether this translates into reductions in negative symptoms, positive symptoms, and improved functional outcome Dr. Lauren Luther is also exploring the efficacy of a cognitive behavioral mHealth intervention for negative symptoms using a novel app-based therapy.
Our Methods
Electroencephalography (EEG)
Functional Magnetic Ressonance Imaging (fMRI)
Electroencephalography (EEG)
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.
Eye Tracking
Functional Magnetic Ressonance Imaging (fMRI)
Electroencephalography (EEG)
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.
Functional Magnetic Ressonance Imaging (fMRI)
Functional Magnetic Ressonance Imaging (fMRI)
Functional Magnetic Ressonance Imaging (fMRI)
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.
Psychophysiology
Digital Phenotyping
Functional Magnetic Ressonance Imaging (fMRI)
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.
Digital Phenotyping
Digital Phenotyping
Digital Phenotyping
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.
Blood Draw/Saliva
Digital Phenotyping
Digital Phenotyping
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.
Grant Funding
National Institute of Mental Health
Brain & Behavior Research Foundation
National Institute of Mental Health
National Science Foundation
Brain & Behavior Research Foundation
National Institute of Mental Health
Brain & Behavior Research Foundation
Brain & Behavior Research Foundation
Brain & Behavior Research Foundation
American Psychological Foundation
American Psychological Foundation
Brain & Behavior Research Foundation
VA MIRECC
American Psychological Foundation
UGA Internal
UGA Internal
American Psychological Foundation
UGA Internal
Measures
Brief Negative Symptom Scale (BNSS)
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
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
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
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 10-15 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.
Digital Phenotyping
Negative Symptom Inventory-Psychosis Risk (NSI-PR)
Digital Phenotyping
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.