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Record W3193058493 · doi:10.1177/1087054720923061

Neurobiological Basis of Reinforcement-Based Decision-Making in Adults With ADHD Treated With Lisdexamfetamine Dimesylate

2021· article· en· W3193058493 on OpenAlexaff
Iliyan Ivanov, Jeffrey H. Newcorn, Beth Krone, X. Li, Stéphanie Duhoux, Stuart F. White, Kurt P. Schulz, Anne‐Claude Bedard, Juan D. Pedraza, Lenard A. Adler, James Blair

Bibliographic record

VenueJournal of Attention Disorders · 2021
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyOrbitofrontal cortexFunctional magnetic resonance imagingAttention deficit hyperactivity disorderPutamenVoxelRating scaleVentral striatumPrefrontal cortexAudiologyClinical psychologyDevelopmental psychologyPsychiatryNeuroscienceStriatumMedicineDopamineCognition

Abstract

fetched live from OpenAlex

Background: The objective of this study was to examine changes in the activation of the brain reward system following treatment with lisdexamfetamine (LDX) vs. placebo (PL) as a function of clinical improvement in attention deficit/hyperactivity disorder (ADHD) symptoms. Methods: Twenty adults with ADHD were included in a randomized cross-over study. Participants underwent two functional magnetic resonance imaging (fMRI) scans, after receiving 3 to 5 weeks of treatment with both LDX and PL. During scanning, participants performed the passive-avoidance learning task to assess reward-related learning using computational variables (e.g., estimated value and prediction error). Pre-treatment to post-treatment symptom change was assessed via the ADHD Rating Scale (ADHD-RS). The imaging contrasts were Object Choose or Object Refuse during the object choice component of the task, modulated by expected value (reward vs. nonreward cue), and Reward vs. Punishment during feedback, modulated by prediction error (expected vs. actual outcome). To address the primary objective, we performed group-level mass univariate analyses between pre-treatment to post-treatment percent change of the ADHD-RS total scores and the four contrast images under the choice and feedback conditions, with significance set at a whole-brain voxel-wise threshold of p < .05 with family-wise error (FWE) correction and an extent (cluster) threshold of 50 contiguous voxels. Results: Improvement in ADHD symptoms was accompanied by significant increases of brain activation during the Object Refuse, Reward and Punishment contrasts in a widespread network including left caudate and putamen, and right orbitofrontal cortex (i.e., reward-related signaling) and left middle frontal, superior frontal, and precentral gyri (i.e., executive control). Conclusions: These findings are the first to show that the increase in responsiveness of systems engaged in reward processing with LDX treatment is positively related to symptom improvement. Results support the hypothesis that LDX treatment may restore balance to dysfunction (e.g., hypoactivation) within the brain reward circuitry in adults with ADHD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.285
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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