Synaptic Interactions Between Thalamic and Cortical Inputs Onto Cortical Neurons In Vivo
Bibliographic record
Abstract
To study the interactions between thalamic and cortical inputs onto neocortical neurons, we used paired-pulse stimulation (PPS) of thalamic and cortical inputs as well as PPS of two cortical or two thalamic inputs that converged, at different time intervals, onto intracellularly recorded cortical and thalamocortical neurons in anesthetized cats. PPS of homosynaptic cortico-cortical pathways produced facilitation, depression, or no significant effects in cortical pathways, whereas cortical responses to thalamocortical inputs were mostly facilitated at both short and long intervals. By contrast, heterosynaptic interactions between either cortical and thalamic, or thalamic and cortical, inputs generally produced decreases in the peak amplitudes and depolarization area of evoked excitatory postsynaptic potentials (EPSPs), with maximal effect at approximately 10 ms and lasting from 60 to 100 ms. All neurons tested with thalamic followed by cortical stimuli showed a decrease in the apparent input resistance (R(in)), the time course of which paralleled that of decreased responses, suggesting that shunting is the factor accounting for EPSP's decrease. Only half of neurons tested with cortical followed by thalamic stimuli displayed changes in R(in). Spike shunting in the thalamus may account for those cases in which decreased synaptic responsiveness of cortical neurons was not associated with decreased R(in) because thalamocortical neurons showed decreased firing probability during cortical stimulation. These results suggest a short-lasting but strong shunting between thalamocortical and cortical inputs onto cortical neurons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".