NCOG-15. COMPARATIVE ANALYSIS OF GLIOMA INDUCED IMPAIRMENT MODELS

Abstract

Abstract Speech is produced by the coordination of neural networks involved in language processing and motor control of vocal outputs, both of which can be disrupted by diffuse gliomas. Natural language is the instinctual written or spoken language profile that an individual has developed throughout his or her lifetime. Recent psycholinguistic analyses suggest that patterns of natural language may be an accurate measure for assessing clinical and behavioral conditions. One important feature of natural language is speech onset. Speech delays are common complaints among patients with glioma. Here, we assess the relationship between speech onset and histologic-molecular features of glioma. Speech onset was defined as acoustic measure of the interval of time between the release of the oral constriction in a stop consonant and the onset of subsequent voicing. Audio samples and video analysis of oral kinetics were analyzed from patients with newly diagnosed low- and high-grade glioma. Features were extracted by manual segmentation and aligned for each trial with high-density electrode arrays to record task specific responses from gliomas projecting to the cortical surface. A total of 1,120 stimuli (672 = picture naming (PN) and 448 auditory naming (AN) trials were presented. As expected, patients with glioblastoma had higher picture and auditory naming error rates (p < 0.001, Mann-Whitney U test) compared with diffuse low-grade gliomas. Assuming speech errors produce slower response times, we next measured only correct behavioral responses which demonstrated 7% slower speech initiation responses (p < 0.0001, Mann-Whitney U test) when comparing patients with glioblastoma and diffuse low-grade gliomas. Slowed speech responses did not require glioma infiltration into canonical cortical speech areas of the lateral prefrontal cortex and superior temporal gyrus. Finally, we identified electrophysiological biomarkers of speech errors. These results deepen our understanding of speech processing impairments, which are not based purely on coding errors.