Fred W Sabb

University of Oregon, Eugene, Oregon, United States

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Publications (53)274.21 Total impact

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    ABSTRACT: Stimulant use disorders are associated with deficits in striatal dopamine receptor availability, abnormalities in mesocorticolimbic resting-state functional connectivity (RSFC) and impulsivity. In methamphetamine-dependent research participants, impulsivity is correlated negatively with striatal D2-type receptor availability, and mesocorticolimbic RSFC is stronger than that in controls. The extent to which these features of methamphetamine dependence are interrelated, however, is unknown. This question was addressed in two studies. In Study 1, 19 methamphetamine-dependent and 26 healthy control subjects underwent [(18)F]fallypride positron emission tomography to measure ventral striatal dopamine D2-type receptor availability, indexed by binding potential (BPND), and functional magnetic resonance imaging (fMRI) to assess mesocorticolimbic RSFC, using a midbrain seed. In Study 2, an independent sample of 20 methamphetamine-dependent and 18 control subjects completed the Barratt Impulsiveness Scale in addition to fMRI. Study 1 showed a significant group by ventral striatal BPND interaction effect on RSFC, reflecting a negative relationship between ventral striatal BPND and RSFC between the midbrain and striatum, orbitofrontal cortex and insula in methamphetamine-dependent participants, but a positive relationship in the control group. In Study 2, an interaction of the group with RSFC on impulsivity was observed. Methamphetamine-dependent users exhibited a positive relationship of midbrain RSFC to the left ventral striatum with cognitive impulsivity, whereas a negative relationship was observed in healthy controls. The results indicate that ventral striatal D2-type receptor signaling may affect the system-level activity within the mesocorticolimbic system, providing a functional link that may help explain high impulsivity in methamphetamine-dependent individuals.Molecular Psychiatry advance online publication, 2 February 2016; doi:10.1038/mp.2015.223.
    No preview · Article · Feb 2016 · Molecular Psychiatry
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    ABSTRACT: Schizophrenia patients exhibit impaired working and episodic memory, but this may represent generalized impairment across memory modalities or performance deficits restricted to particular memory systems in subgroups of patients. Furthermore, it is unclear whether deficits are unique from those associated with other disorders. Healthy controls (n=1101) and patients with schizophrenia (n=58), bipolar disorder (n=49) and attention-deficit-hyperactivity-disorder (n=46) performed 18 tasks addressing primarily verbal and spatial episodic and working memory. Effect sizes for group contrasts were compared across tasks and the consistency of subjects' distributional positions across memory domains was measured. Schizophrenia patients performed poorly relative to the other groups on every test. While low to moderate correlation was found between memory domains (r=.320), supporting modularity of these systems, there was limited agreement between measures regarding each individual's task performance (ICC=.292) and in identifying those individuals falling into the lowest quintile (kappa=0.259). A general ability factor accounted for nearly all of the group differences in performance and agreement across measures in classifying low performers. Pathophysiological processes involved in schizophrenia appear to act primarily on general abilities required in all tasks rather than on specific abilities within different memory domains and modalities. These effects represent a general shift in the overall distribution of general ability (i.e., each case functioning at a lower level than they would have if not for the illness), rather than presence of a generally low-performing subgroup of patients. There is little evidence that memory impairments in schizophrenia are shared with bipolar disorder and ADHD. Copyright © 2015 Elsevier B.V. All rights reserved.
    Full-text · Article · Aug 2015 · Schizophrenia Research
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    ABSTRACT: Motor response inhibition is mediated by neural circuits involving dopaminergic transmission; however, the relative contributions of dopaminergic signaling via D1- and D2-type receptors are unclear. Although evidence supports dissociable contributions of D1- and D2-type receptors to response inhibition in rats and associations of D2-type receptors to response inhibition in humans, the relationship between D1-type receptors and response inhibition has not been evaluated in humans. Here, we tested whether individual differences in striatal D1- and D2-type receptors are related to response inhibition in human subjects, possibly in opposing ways. Thirty-one volunteers participated. Response inhibition was indexed by stop-signal reaction time on the stop-signal task and commission errors on the continuous performance task, and tested for association with striatal D1- and D2-type receptor availability [binding potential referred to nondisplaceable uptake (BPND)], measured using positron emission tomography with [(11)C]NNC-112 and [(18)F]fallypride, respectively. Stop-signal reaction time was negatively correlated with D1- and D2-type BPND in whole striatum, with significant relationships involving the dorsal striatum, but not the ventral striatum, and no significant correlations involving the continuous performance task. The results indicate that dopamine D1- and D2-type receptors are associated with response inhibition, and identify the dorsal striatum as an important locus of dopaminergic control in stopping. Moreover, the similar contribution of both receptor subtypes suggests the importance of a relative balance between phasic and tonic dopaminergic activity subserved by D1- and D2-type receptors, respectively, in support of response inhibition. The results also suggest that the stop-signal task and the continuous performance task use different neurochemical mechanisms subserving motor response inhibition. Copyright © 2015 the authors 0270-6474/15/355990-08$15.00/0.
    Full-text · Article · Apr 2015 · The Journal of Neuroscience : The Official Journal of the Society for Neuroscience
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    ABSTRACT: Transdisciplinary research is a rapidly expanding part of science and engineering, demanding new methods for connecting results across fields. In biomedicine for example, modeling complex biological systems requires linking knowledge across multiple levels of science, from genes to disease. The move to multilevel research requires new strategies; in this paper we present path knowledge discovery, a novel methodology for linking published research findings. Path knowledge discovery consists of two integral tasks: 1) association path mining among concepts in a multipart lexicon that crosses disciplines, and 2) fine-granularity knowledge-based content retrieval along the path(s) to permit deeper analysis. Implementing this methodology has required development of innovative measures of association strength for pairwise associations, as well as the strength for sequences of associations, in addition to powerful lexicon-based association expansion to increase the scope of matching. In our discussions, we describe the validation of the methodology using a published heritability study from cognition research, and we obtain comparable results. We show how path knowledge discovery can greatly reduce a domain expert's time (by several orders of magnitude) when searching and gathering knowledge from the published literature, and can facilitate derivation of interpretable results.
    No preview · Article · Jan 2015

  • No preview · Chapter · Dec 2014
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    ABSTRACT: Background / Purpose: Schizophrenia patients exhibit impaired working and episodic memory that relates to functioning and prognosis. However, the relationship of deficits in schizophrenia to the distribution of performance across memory subsystems in controls and other psychiatric disorders is unclear. Main conclusion: There are consistent, moderate to large impairments across memory measures in schizophrenia. While there is some consistency across measures as to individual levels of performance, this is primarily accounted for by a single generalized cognitive factor (PC1). This same generalized cognitive factor accounts for nearly all of the group differences on performance across tasks.
    Full-text · Conference Paper · Jun 2014
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    ABSTRACT: Sexual dimorphism in the brain and cognition is a topic of widespread interest. Many studies of sex differences have focused on visuospatial and verbal abilities, but few studies have investigated sex differences in executive functions. We examined two key components of executive function - response inhibition and response monitoring - in healthy men (n = 285) and women (n = 346) performing the Stop-signal task. In this task, participants are required to make a key press to a stimulus, unless a tone is presented at some delay following the initial stimulus presentation; on these infrequent trials, participants are instructed to inhibit their planned response. Response inhibition was assessed with an estimate of the latency needed to inhibit a response (stop-signal reaction time), and response monitoring was measured by calculating the degree to which participants adjusted their reaction times based on the immediately preceding trial (e.g., speeding following correct trials and slowing following errors). There were no sex differences in overall accuracy or response inhibition, but women showed greater sensitivity to trial history. Women sped up more than men following correct 'Go' trials, and slowed down more than men following errors. These small but statistically significant effects (Cohen's d = 0.25-0.3) suggest more flexible adjustments in speed-accuracy trade-offs in women and greater cognitive flexibility associated with the responsive control of action.
    Full-text · Article · May 2014 · British Journal of Psychology
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    ABSTRACT: Studies of adults with attention-deficit/hyperactivity disorder (ADHD) have suggested that they have deficient response inhibition, but findings concerning the neural correlates of inhibition in this patient population are inconsistent. We used the Stop-Signal task and functional magnetic resonance imaging (fMRI) to compare neural activation associated with response inhibition between adults with ADHD (N=35) and healthy comparison subjects (N=62), and in follow-up tests to examine the effect of current medication use and symptom severity. There were no differences in Stop-Signal task performance or neural activation between ADHD and control participants. Among the ADHD participants, however, significant differences were associated with current medication, with individuals taking psychostimulants (N=25) showing less stopping-related activation than those not currently receiving psychostimulant medication (N=10). Follow-up analyses suggested that this difference in activation was independent of symptom severity. These results provide evidence that deficits in inhibition-related neural activation persist in a subset of adult ADHD individuals, namely those individuals currently taking psychostimulants. These findings help to explain some of the disparities in the literature, and advance our understanding of why deficits in response inhibition are more variable in adult, as compared with child and adolescent, ADHD patients.
    Full-text · Article · Apr 2014 · Psychiatry Research: Neuroimaging
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    ABSTRACT: Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights.
    Full-text · Article · Feb 2014 · Proceedings of the National Academy of Sciences
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    ABSTRACT: The stop-signal task, in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision making, a drift-diffusion model of simple decisions was fitted to stop-signal task data from go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the go stimulus correlated with greater activation in the right frontal pole for both go and stop trials. On stop trials, stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and BG. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology.
    Full-text · Article · Jan 2014 · Journal of Cognitive Neuroscience

  • No preview · Chapter · Jan 2014
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    ABSTRACT: Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART), which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analog Risk Taking (BART) task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity (DI) and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.
    Full-text · Article · Sep 2013 · Frontiers in Neuroscience
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    ABSTRACT: Understanding the relationship between brain and complex latent behavioral constructs like cognitive control will require an inordinate amount of data. Internet-based methods can rapidly and efficiently refine behavioral measures in very large samples that are needed for genetics and behavioral research. Cognitive control is a multifactorial latent construct that is considered to be an endophenotype in numerous neuropsychiatric disorders, including attention deficit/hyperactivity disorder (ADHD). While previous studies have demonstrated high correlations between Web- and lab-based scores, skepticism remains for its broad implementation. Here, we promote a different approach by characterizing a completely Web-recruited and tested community family sample on measures of cognitive control. We examine the prevalence of attention deficit symptoms in an online community sample of adolescents, demonstrate familial correlations in cognitive control measures, and use construct validation techniques to validate our high-throughput assessment approach. A total of 1214 participants performed Web-based tests of cognitive control with over 200 parent–child pairs analyzed as part of the primary study aims. The data show a wide range of “subclinical” symptomatology in a web community sample of adolescents that supports a dimensional view of attention and also provide preliminary narrow-sense heritability estimates for commonly used working memory and response inhibition tests. Finally, we show strong face and construct validity for these measures of cognitive control that generally exceeds the evidence required of new lab-based measures. We discuss these results and how broad implementation of this platform may allow us to uncover important brain–behavior relationships quickly and efficiently.
    Full-text · Article · Sep 2013 · Brain and Behavior
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    Robert M Bilder · Andrew G Howe · Fred W Sabb
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    ABSTRACT: Reports an error in "Multilevel Models From Biology to Psychology: Mission Impossible" by Robert M. Bilder, Andrew S. Howe and Fred w. Sabb (Journal of Abnormal Psychology, Advanced Online Publication, May 6, 2013, np). The name of author Andrew G. Howe was misspelled as Andrew S. Howe. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2013-15712-001.) Systematic efforts are underway to address major flaws in the current diagnostic taxonomy of mental disorders, fostering hope that a new nosology might be based on brain biology. The National Institute of Mental Health Research Domains Criteria (RDoC) initiative aims to redefine mental illness leveraging information that spans molecular to behavioral levels of analysis. Major effort is still needed to forge multilevel conceptual and measurement models capable of representing knowledge within and across these levels. The development of such models may help refine and share complex hypotheses, and reduce the risk of replacing the current taxonomy with dimensions and/or categories that manifest little incremental biological validity. To create useful models we need to define concepts, relations among concepts, and links to supporting evidence. Some methods already enable representation of concepts and measures at the levels of behavioral and basic biological processes, but a major gap at the level of neural circuitry must be bridged to link basic biological and behavioral levels. We provide a schematic framework, using as an example the representation of selected "working memory" concepts and evidence across multiple levels of analysis as these have been described in the RDoC Workshops. This example illustrates multiple challenges and some possible solutions that may help clarify the aims of individual research projects and enable integration of diverse efforts on RDoC and related initiatives. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
    Full-text · Article · Aug 2013 · Journal of Abnormal Psychology
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    Robert M Bilder · Andrew S Howe · Fred W Sabb
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    ABSTRACT: Systematic efforts are underway to address major flaws in the current diagnostic taxonomy of mental disorders, fostering hope that a new nosology might be based on brain biology. The National Institute of Mental Health Research Domains Criteria (RDoC) initiative aims to redefine mental illness leveraging information that spans molecular to behavioral levels of analysis. Major effort is still needed to forge multilevel conceptual and measurement models capable of representing knowledge within and across these levels. The development of such models may help refine and share complex hypotheses, and reduce the risk of replacing the current taxonomy with dimensions and/or categories that manifest little incremental biological validity. To create useful models we need to define concepts, relations among concepts, and links to supporting evidence. Some methods already enable representation of concepts and measures at the levels of behavioral and basic biological processes, but a major gap at the level of neural circuitry must be bridged to link basic biological and behavioral levels. We provide a schematic framework, using as an example the representation of selected "working memory" concepts and evidence across multiple levels of analysis as these have been described in the RDoC Workshops. This example illustrates multiple challenges and some possible solutions that may help clarify the aims of individual research projects and enable integration of diverse efforts on RDoC and related initiatives. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
    Full-text · Article · May 2013 · Journal of Abnormal Psychology
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    ABSTRACT: The Barratt Impulsiveness Scale (Version 11; BIS-11; Patton, Stanford, & Barratt, 1995) is a gold-standard measure that has been influential in shaping current theories of impulse control, and has played a key role in studies of impulsivity and its biological, psychological, and behavioral correlates. Psychometric research on the structure of the BIS-11, however, has been scant. We therefore applied exploratory and confirmatory factor analyses to data collected using the BIS-11 in a community sample (N = 691). Our goal was to test 4 theories of the BIS-11 structure: (a) a unidimensional model, (b) a 6 correlated first-order factor model, (c) a 3 second-order factor model, and (d) a bifactor model. Among the problems identified were (a) low or near-zero correlations of some items with others; (b) highly redundant content of numerous item pairs; (c) items with salient cross-loadings in multidimensional solutions; and, ultimately, (d) poor fit to confirmatory models. We conclude that use of the BIS-11 total score as reflecting individual differences on a common dimension of impulsivity presents challenges in interpretation. Also, the theory that the BIS-11 measures 3 subdomains of impulsivity (attention, motor, and nonplanning) was not empirically supported. A 2-factor model is offered as an alternative multidimensional structural representation. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
    Full-text · Article · Apr 2013 · Psychological Assessment

  • No preview · Conference Paper · Aug 2012
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    ABSTRACT: Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what "mental processes" exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.
    Full-text · Article · Sep 2011 · Frontiers in Neuroinformatics
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    ABSTRACT: Cognitive impairments are central to schizophrenia and could mark underlying biological dysfunction but efforts to detect genetic associations for schizophrenia or cognitive phenotypes have been disappointing. Phenomics strategies emphasizing simultaneous study of multiple phenotypes across biological scales might help, particularly if the high heritabilities of schizophrenia and cognitive impairments are due to large numbers of genetic variants with small effect. Convergent evidence is reviewed, and a new collaborative knowledgebase - CogGene - is introduced to share data about genetic associations with cognitive phenotypes, and enable users to meta-analyze results interactively. CogGene data demonstrate the need for larger studies with broader representation of cognitive phenotypes. Given that meta-analyses will probably be necessary to detect the small association signals linking the genome and cognitive phenotypes, CogGene or similar applications will be needed to enable collaborative knowledge aggregation and specify true effects.
    Full-text · Article · Aug 2011 · Trends in Cognitive Sciences
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    ABSTRACT: The application of statistical machine learning techniques to neuroimaging data has allowed researchers to decode the cognitive and disease states of participants. The majority of studies using these techniques have focused on pattern classification to decode the type of object a participant is viewing, the type of cognitive task a participant is completing, or the disease state of a participant's brain. However, an emerging body of literature is extending these classification studies to the decoding of values of continuous variables (such as age, cognitive characteristics, or neuropsychological state) using high-dimensional regression methods. This review details the methods used in such analyses and describes recent results. We provide specific examples of studies which have used this approach to answer novel questions about age and cognitive and disease states. We conclude that while there is still much to learn about these methods, they provide useful information about the relationship between neural activity and age, cognitive state, and disease state, which could not have been obtained using traditional univariate analytical methods.
    Full-text · Article · Jun 2011 · Frontiers in Neuroscience

Publication Stats

3k Citations
274.21 Total Impact Points

Institutions

  • 2015
    • University of Oregon
      Eugene, Oregon, United States
  • 2001-2014
    • University of California, Los Angeles
      • • Department of Psychiatry and Biobehavioural Sciences
      • • Institute for Neuroscience and Human Behavior
      • • Division of Adult Psychiatry
      Los Ángeles, California, United States
    • University of Pittsburgh
      • Department of Psychiatry
      Pittsburgh, Pennsylvania, United States
  • 2002
    • Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
      • Department of Medicine
      Torrance, California, United States
  • 2000
    • Princeton University
      • Department of Psychology
      Princeton, New Jersey, United States