Coding of changes in motion direction by local field potentials in primate area MT
Bibliographic record
Abstract
In primate area MT, direction-selective neurons convey information about a stimulus’ motion direction, as early as in their initial response. These neurons may also selectively signal transient changes in motion direction by increasing or decreasing their firing rate depending on whether the direction change deviated closer to or further away from their preferred direction. These properties may thus serve to detect and discriminate changes in a stimulus’ feature. Another potential source of neuronal encoding of motion direction relies on the activity of local field potentials (LFPs). Indeed, LFPs in area MT are tuned for motion direction, in a frequency-dependent manner. It is, however, unclear whether LFPs can provide a reliable signal to detect and discriminate changes in a stimulus’ feature. To investigate this issue, we recorded LFPs and spiking activity of direction-selective neurons in area MT of monkeys trained to covertly detect a 30-degree motion direction change in one of two moving RDPs. On each trial, both RDPs moved either in the preferred or antipreferred (AP) direction, and thus the actual motion direction after the change deviated away from either the preferred or the AP direction. Across the neuronal population (n=73), the motion direction change evoked a significant (p<0.05) decrease or increase in firing rates when the change deviated the motion direction away from preferred and AP, respectively. The direction change also induced changes in the LFP power in all frequency bands. However, only the gamma-band power reflected the identity of the change, being significantly larger when the change deviated the motion direction away from AP compared to away from preferred. These results indicate that the detection of transient stimulus changes can be encoded by LFPs in all frequency bands, while the discrimination of the type of change may be encoded by LFPs in the gamma band. Meeting abstract presented at VSS 2013
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".