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Record W7161975422 · doi:10.82308/35475

Dynamics of information processing and spontaneous activity during sleep

2025· dissertation· en· W7161975422 on OpenAlexaboutno aff
Dhruv Mehrotra

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsHippocampal formationPopulationOscillation (cell signaling)Sensory systemSleep (system call)Dynamics (music)Nerve netInformation processingCognitionNeural activity

Abstract

fetched live from OpenAlex

Brain oscillations are critical for inter-regional communication and the orchestration of higher order cognitive processes such as attention and memory consolidation. Oscillations underlying these phenomena are typically mediated via underlying neural population activity, but the exact mechanisms that determine how the oscillations are generated remain open questions in the field. In this work, I examined two classes of oscillations that are crucial for memory consolidation: the cortical slow wave and hippocampal sharp wave-ripples, in pursuit of elucidating the contributions of single neurons to these processes. Critically, these oscillations occur during sleep, which also enables us to understand the intrinsic mechanisms underlying their spontaneous initiation, devoid of sensory inputs. I used the spatial navigation system as a model to study memory consolidation, as spatially tuned activity is a relatively simple readout compared to other brain systems. Specifically, I examined the organization of sequences in the cortical head-direction system and uncovered a dorsoventral activation pattern. Using the head-direction cell activity as a readout, I was able to elucidate the content of these sequences and showed that population activity rapidly converges towards a stable orientation, and this direction is chosen at random during each oscillatory period. Finally, using a combination of computational modeling, and ex vivo patch clamp experiments I, in collaboration with colleagues from the University of Edinburgh, uncovered a hitherto ignored key player in the dynamics of the slow oscillation in the cortex – hyperpolarization-activated currents. I showed that these currents might play brain-wide roles in the organization of cortical sequences. This finding has important implications for the organization of activity along the dorsoventral axis, a common feature observed throughout the navigation system, and the organization of sequences in the cortex, more generally. I then turned to a downstream structure, the hippocampus, to examine the other key oscillation in memory consolidation – sharp wave-ripples. In collaboration with colleagues from the department of Pharmacology and Therapeutics at McGill University, I worked on a mouse model of Christianson Syndrome, a recently discovered neurodevelopmental and neurodegenerative disorder, and led the first investigation, to our knowledge, into understanding the mechanisms underlying the cognitive deficits in this disorder, focusing on oscillatory activity in the hippocampus. We tested these animals on a hippocampal-dependent spatial memory task and found deficits in their performance. To further investigate the neural mechanisms underlying these cognitive deficits, we examined their hippocampal place cell activity. Interestingly, these animals had intact place fields. Instead, I found differences in the frequency composition of sharp wave-ripples in the disease model, suggesting that alterations in the composition of these oscillations might be crucial for deficits in cognitive processes. Broadly, by characterizing hippocampal activity in these animals, I provide insights into how a single gene mutation can affect network activity in the hippocampus, which leads to debilitating cognitive deficits. Taken together, my findings reveal novel aspects of single neuron activity that shape oscillations during sleep. These findings have important implications for gaining mechanistic insights into the organization of spontaneous activity patterns during sleep, but also into their functional roles within the spatial navigation system. Critically, my work lies at the interface of health and disease, laying the foundation for further discovery and characterization of neural biomarkers in preclinical models of Christianson Syndrome to inform future clinical studies and precision medicine therapies

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.014
GPT teacher head0.286
Teacher spread0.272 · 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 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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