Discovering Pathophysiologic Networks of Temporal Lobe Epilepsy Using the BrainMap Community Portal through the Texas Advanced Computing Center

Temporal lobe epilepsy (TLE) seizures cause regional damage, detectable on imaging of brain structure (VBM) and function (VBM). Damage is mediated by aberrant neuronal activity propagating along existing network architecture. TLE networks remain ill-defined and are of great interest to diagnostic and therapeutic development. Independent component analysis (ICA) can detect neural-networks by computing multi-variate co-occurrence patterns across a volume and is validated for coordinate-based meta-analysis (CBMA/Meta-ICA). Meta-ICA is methodologically distinct from mass-univariate meta-analytics (ALE) that simply detect robust regions/hubs of pathology. Although meta-ICA is typically used to extract canonical/healthy networks, we applied meta-ICA to VBM/VBP reports of TLE-pathology, to infer TLE-specific network anomalies. To identify TLE-networks, BrainMap Community Portal applications were used to access coordinate-results (Sleuth) of 74 experiments (n=1599), model coordinates as spatial probability distributions (weighted by sample-size) and apply ICA (Meta-ICA) at dimensions:d=1&2 (per sample-size restrictions), computing coordinate co-occurrence within and across experiments. TLE pathology-hubs were computed (GingerALE) separately as spatial convergence across studies (ALE), agnostic to within-study co-occurrence. Two anatomically distinct TLE-networks were identified (i.e. no overlap, excepting ALE hubs). Network-IC1 included brain-regions involved in language processing (speech-execution:Z=6.95; speech-cognition:Z=4.10) at d=2, with similar results (spatial-correlation:R=0.89) at d=1. Network-IC2 included brain-regions involved in emotion (reward:Z=4.76) and cognition (attention:Z=4.02; memory:Z=3.80). Meta-ICA implicated a superset of hub regions from GingerALE (IC1-tonsil; IC2-pulvinar, caudate, superior-temporal; Both-hippocampus, MDN-thalamus), uniquely identifying anterior nucleus, insula, supramarginal, and pre/paracentral gyri. Neither network matched canonical networks. VBM/VBP distribution to ICs was homogenous (χ2:p=0.07). Meta-ICA networks align with TLE symptom profiles. IC1 (verbal/visual) disruption can impair communication and cause visual hallucinosis. IC2 (limbic) aligns with social-emotional deficits; dyscognitive seizures disrupt cognition (attention/memory), impair awareness, and induce postictal amnesia. These findings reveal two novel TLE-networks, debut the first low-d meta-ICA detection of disease-networks, and highlight a BrainMap Community Portal use-case with implications in biomarker development within/beyond epilepsy pathologies.