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Record W4413920645 · doi:10.22215/cujs.v5i1.5286

Therapeutic Effects of Psychedelics and their Non-Hallucinogenic Analogs on Depressive-Like Behaviour

2025· article· en· W4413920645 on OpenAlexaff
Kaylee Reid, Argel Aguilar‐Valles

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHallucinogenPsilocybinPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Major depressive disorder (MDD) is a complex and debilitating condition affecting approximately 280 million people worldwide. Its heterogeneous nature makes it difficult to establish clinical treatment guidelines that address individual differences in treatment response. As a result, many individuals experience treatment-resistant depression (TRD) failing to respond to first-line antidepressants. This increases the burden on healthcare systems and highlights the need for new, fast-acting therapies. Psychedelics have emerged as promising candidates due to their rapid and sustained antidepressant effects, with compounds such as psilocybin demonstrating the ability to enhance neuroplasticity through 5-HT2A receptor activation. However, their hallucinogenic properties limit clinical accessibility, necessitating intensive therapeutic supervision. Non-hallucinogenic analogs, like 2-bromo-lysergic acid diethylamide (2-Br-LSD), offer a potentially safer alternative by promoting neuroplasticity without causing hallucinations. Indeed, it still remains unclear whether hallucinatory activity is required for therapeutic benefit. This thesis examines the antidepressant effects of psilocybin and 2-Br-LSD in rodent models of depression following chronic stress. It is hypothesized that both compounds will reduce depression-like behaviours in mice by modulating neural circuits involved in mood regulation. By investigating whether the therapeutic benefits can occur without hallucinations, this work aims to assess the potential of 2-Br-LSD as a more accessible treatment option for TRD.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.317
Teacher spread0.303 · 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
Published2025
Admission routes1
Has abstractyes

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