Comparison of state-dependent activity patterns in the thalamocortical, hippocampal and amygdalocortical systems
Bibliographic record
Abstract
The significance of neuronal oscillations in the amygdala and related cortices Even when deprived of sensory stimulation, neurons hum continuously. That is, their membrane potential fluctuates constantly and the depolarizing phase of these oscillations sometimes gives rise to action potentials. Interestingly, this spontaneous activity is not random. Correlated neuronal events, occurring in a pulsatile or oscillatory manner, can be measured in the extracellular space as currents. These events result from non-linear interactions between the intrinsic membrane properties of neurons and the particular properties of the synaptic network of which they are a part (Llinás, 1988). Oscillations in various frequency ranges are observed in different brain regions; these rhythms vary depending on the behavioural state (Buzsáki et al. , 1983; Steriade, 1997a). The relevance of oscillations to brain function stems from the fact that neuronal events underlying cognition are embedded in these endogenous rhythms. Stated otherwise, one cannot disentangle oscillations from coding in large neuronal ensembles. Moreover, during sleep, when the brain is largely disconnected from the outside world, neurons generate a variety of oscillations and synchronized population bursts that are thought to play a critical role in memory consolidation (see Section 6.3). Finally, because related parts of the brain tend to display similar oscillations, the analysis of spontaneous oscillatory activity can reveal functional kinship among brain structures. This chapter compares the neuronal oscillations displayed by the amygdala and related cortices.
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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 | 0.000 |
| 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".