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Record W6990917073

The emergence of visual responses in the developing retinotectal system in vivo

2013· dissertation· en· W6990917073 on OpenAlexaff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2013
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsTrinity College
Fundersnot available
KeywordsGlutamatergicXenopusTectumNeuronPopulationReceptive fieldSensory systemPremovement neuronal activity
DOInot available

Abstract

fetched live from OpenAlex

<p>Patterned neuronal activity driven by the sensory environment plays a key role in the development of precise synaptic connectivity in the brain. It is well established that the action potentials (‘spikes’) generated by individual neurons are crucial to this developmental process. A neuron’s spiking activity is jointly determined by its synaptic inputs and its intrinsic excitability. It is therefore important to ask how a neuron develops these attributes, and whether the emergence of spiking might itself be governed by activity-dependent processes. In this thesis, I address these questions in the retinotectal system of Xenopus laevis.</p> <p>First, I investigate the extent to which visuospatial information is available to the developing retinotectal system. I show that the eyes of developing Xenopus larvae are hyperopic at the onset of vision, but rapidly grow towards correct vision. Despite its imperfect optics, the Xenopus eye is able to generate spatially restricted activity on the retina, which is evident in the spatial structure of the receptive fields (RFs) of tectal neurons. Using a novel method to map the visually driven spiking output and synaptic inputs of the same tectal neuron in vivo, I show that neuronal spiking activity closely follows the spatiotemporal profile of glutamatergic inputs.</p> <p>Next, I characterise a population of neurons in the developing optic tectum that does not fire action potentials, despite receiving visually evoked glutamatergic and γ-aminobutyric acid (GABA)ergic synaptic inputs. A comparison of visually spiking and visually non-spiking neurons reveals that the principal reason these neurons are ‘silent’ is that they lack sufficient glutamatergic synaptic excitation.</p> <p>In the final section of the thesis, I investigate whether visually driven activity can play a role in the ‘unsilencing’ of these silent neurons. I show that non-spiking tectal neurons can be rapidly converted into spiking neurons through a visual conditioning protocol. This conversion is associated with a selective increase in glutamatergic input and implicates a novel, spike-independent form of synaptic potentiation. I provide evidence that this novel plasticity process is mediated by GABAergic inputs that are depolarising during early development, and can act in synergy with N-methyl-D-aspartate receptors (NMDARs) to strengthen immature glutamatergic synapses. Consistent with this, preventing the depolarising effects of GABA or blocking NMDARs abolished the activity-dependent unsilencing of tectal neurons.</p> <p>These results therefore support a model in which GABAergic and glutamatergic transmitter systems function synergistically to enable a neuron to recruit the synaptic excitation it needs to develop sensory-driven spiking activity. This represents a transition with important consequences for both the functional output and the activity-dependent development of a neuron.</p>

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

Explore more

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