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Record W7061612649

Psychophysical properties of midbrain dopamine neurons and implications for the antidepressant effect of deep brain stimulation

2023· dissertation· en· W7061612649 on OpenAlexfundno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesCanadian Institutes of Health ResearchConcordia University
KeywordsMidbrainDopamineElectrical brain stimulationStimulationBrain stimulation
DOInot available

Abstract

fetched live from OpenAlex

The discovery that animals engage in intracranial self-stimulation (ICSS) provided a direct way to study the neural networks that direct motivation. In ICSS experiments, animals are implanted with electrodes terminating in reward-implicated substrates. The development of optogenetics advanced the study of the brain reward system by confirming a causal role of midbrain dopamine firing in reward seeking. Since then, the correspondence of optical stimulation parameters to the neural signal of dopamine neurons causing operant behavior has been studied. In parallel, attention was paid to the application of deep brain stimulation on refractory mental illness, including depression. This thesis describes two psychophysical experiments that use optogenetic ICSS of midbrain dopamine neurons. The first experiment shows that, for a substantial range of powers (~12.6 mW - 31.6 mW), the trade-off between power and pulse duration undergoes temporal summation, aligning with Bloch’s Law. Pulse duration can be used to control the volume of activated opsin-expressing dopamine neurons. The second experiment provides a psychophysical measurement of firing fidelity of midbrain dopamine neurons. This study supports that pulse frequencies higher than 40 Hz are ineffective or counter-productive at improving the vigor of operant behavior. Together these experiments highlight the benefit of using measurable outcomes (e.g., operant response) as the basis for making inferences about the effectiveness of optical stimulation. These experiments contribute to the hypothesis that, similarly to electrical ICSS, the variable determining the intensity of reward seeking is the induced aggregate firing rate. Such insights can aid the understanding of how deep brain stimulation functions to alleviate depression. It is suggested here that the antidepressant effects of deep brain stimulation of the medial forebrain bundle (MFB) may involve activation of non-dopaminergic neural pathways. The reward platform hypothesis is presented, which suggests that MFB stimulation may cause antidepressant effects by facilitating reward seeking. This hypothesis is developed in relation to motivation parameters that promote involvement with response-contingent rewarding activities. Ways to test this hypothesis in both pre-clinical and clinical models are proposed. This thesis provides practical guidelines for optogenetic experiment designs, and it outlines original, theory-driven hypotheses about the structural and functional underpinnings of antidepressant deep brain stimulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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