Steady State Responses: Electrophysiological Assessment of Sensory Function in Schizophrenia
Bibliographic record
Abstract
Persons with schizophrenia experience subjective sensory anomalies and objective deficits on assessment of sensory function. Such deficits could be produced by abnormal signaling in the sensory pathways and sensory cortex or later stage disturbances in cognitive processing of such inputs. Steady state responses (SSRs) provide a noninvasive method to test the integrity of sensory pathways and oscillatory responses in schizophrenia with minimal task demands. SSRs are electrophysiological responses entrained to the frequency and phase of a periodic stimulus. Patients with schizophrenia exhibit pronounced auditory SSR deficits within the gamma frequency range (35-50 Hz) in response to click trains and amplitude-modulated tones. Visual SSR deficits are also observed, most prominently in the alpha and beta frequency ranges (7-30 Hz) in response to high-contrast, high-luminance stimuli. Visual SSR studies that have used the psychophysical properties of a stimulus to target specific visual pathways predominantly report magnocellular-based deficits in those with schizophrenia. Disruption of both auditory and visual SSRs in schizophrenia are consistent with neuropathological and magnetic resonance imaging evidence of anatomic abnormalities affecting the auditory and visual cortices. Computational models suggest that auditory SSR abnormalities at gamma frequencies could be secondary to gamma-aminobutyric acid-mediated or N-methyl-D-aspartic acid dysregulation. The pathophysiological process in schizophrenia encompasses sensory processing that probably contributes to alterations in subsequent encoding and cognitive processing. The developmental evolution of these abnormalities remains to be characterized.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".