1296 Shared Cortical Language Networks With Convergent Hierarchical Network Dynamics for Lexicosemantic Processing in Comprehension and Naming

INTRODUCTION: Theoretical models suggest that spoken and written language engage a shared lexicosemantic processing network in perception and production, yet convergent neural mechanisms are unclear. METHODS: 65 ECoG patients completed auditory (AN) and orthographic (ON) naming. We analyzed gamma activity (70-115Hz) with mixed-effects multilevel analyses to identify the lexicosemantic processing network during comprehension and naming. We mapped network dynamics using autoregressive hidden Markov models (ARHMM). We used direct cortical stimulation (DCS) to attribute causality to critical nodes. RESULTS: At speech onset, activation of superior temporal gyrus (pSTG) was followed by superior temporal sulcus (pSTS) and middle temporal gyrus (pMTG). For each written word, visual cortex activity was followed by activation of lexical (fusiform gyrus, Fus; pSTS; pMTG) and phonological (intraparietal sulcus, IPS; pSTG) reading routes. Both modalities engaged posterolateral temporal cortex (pLTC) for comprehension, and activity was correlated with phrasal composition (p<0.01) implicating it in compositional semantics. The last word activated a shared network (pLTC; Fus; IPS; pars triangularis, pTr) for naming. ARHMM isolated 5 states for AN and 6 for ON with 3 convergent states. The first convergent state occurring at stimulus offset was characterized by outflow from pLTC, Fus, IPS, and pTr, and state duration was correlated with reaction time (p<0.001) implicating it in lexical access. Lastly, during stimulus presentation, DCS of Heschl’s gyrus disrupted listening, while DCS of planum temporale and pLTC disrupted listening and reading. At stimulus offset, DCS of pLTC, Fus, IPS, and pTr disrupted AN and ON. CONCLUSIONS: Juxtaposing network dynamics of multimodal lexicosemantic processing in speech perception and production informs our understanding of specialized and shared language networks providing new insights to facilitate designs of neural prosthetics for language disorders.