31 Disorganization of language and working memory networks in frontal versus temporal lobe epilepsy
Bibliographic record
Abstract
Objectives/Aims Cognitive impairment is a common comorbidity of epilepsy, and can be more burdensome than seizures themselves. Temporal and frontal lobe epilepsy (TLE, FLE) are accompanied by multi-domain cognitive impairment. While the underlying neural substrates have been extensively investigated in TLE, functional imaging studies in FLE are scarce. Here, we aimed to: (i) investigate systems-level neural processes accounting for cognitive dysfunction in FLE; (ii) directly compare FLE and TLE patients, establishing commonalities and differences; and (iii) decode the potential influence of clinical characteristics on cognitive network architecture. Methods We capitalized on a large, single-centre sample of 172 adult participants (56 with FLE, 64 with TLE, 52 with controls) who were investigated via: (i) an extensive neuropsychological test battery that included attention, psychomotor speed, language, working memory, executive function, and episodic memory tests; and (ii) four functional MRI tasks probing expressive language (verbal fluency, verb generation) and working memory (verbal and visuo-spatial). Patient groups were comparable in age of epilepsy onset, disease duration, and antiseizure medication load. We mapped task-related brain activation and deactivation using a novel multiscale approach, and tracked reorganization in FLE and TLE. We complemented voxel-based maps with profiling of task effects across established motifs of functional brain organization: (i) canonical resting-state functional networks, and (ii) the principal functional connectivity gradient, that encodes a continuous transition from lower-level (sensory) to higher-order (transmodal) brain areas. Results We find that cognitive impairment in FLE is accompanied by broadly reduced activation across frontoparietal attentional and executive networks, and reduced default-mode network deactivation, indicating large-scale disorganization of task-related recruitment, particularly during working memory. Patterns of dysfunction in FLE and TLE are broadly similar, but some traits are syndrome-specific: impaired task-related deactivation of the default-mode network is more prominent in FLE, while impaired recruitment of posterior language areas is more marked in TLE. More severe epilepsy, as tracked by age at onset, epilepsy duration, seizure frequency, time since last seizure, and propensity for focal-to-bilateral tonic-clonic seizures, relates to more marked cognitive network disorganization both in FLE and TLE. Conclusions Our study elucidates neural processes underlying cognitive impairment in the most common focal epilepsies, identifies frontoparietal executive alterations as a shared biological signature, irrespective of seizure focus localization, and shows that temporal lobe language alterations are TLE-specific. The highlighted systems-level behaviour may be amenable to future remediation strategies, including neurostimulation.
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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) | 0.002 | 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".