Biology subjects

Warnke, L.

Publications and source records attributed to Warnke, L..

4 recordsLinked to original sources

bioRxiv2021

Dynamic predictive coding across the left fronto-temporal language hierarchy: Evidence from MEG, EEG and fMRI

We used MEG and ERPs to track the time-course and localization of evoked activity produced by expected, unexpected plausible and implausible words during incremental language comprehension. We interpret the full pattern of evoked responses and functional connectivity within a hierarchical predictive coding framework in which evoked activity reflects residual information (error) that is passed up and down the cortical hierarchy. Between 300-500ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), while implausible inputs produced a selectively enhanced response within left inferior frontal cortex (event-level prediction error). Between 600-1000ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that induced top-down shifts of event-level and lexico-semantic representations), while highly implausible inputs activated posterior fusiform and medial temporal cortices, supporting orthographic reanalysis and new learning. Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.

neuroscience↗

bioRxiv2019

Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis

It has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used Magnetoencephalography (MEG) and Electroencephalography (EEG), in combination with Representational Similarity Analysis (RSA), to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate constraining verbs was greater than following inanimate constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words. Significance statementLanguage inputs unfold very quickly during real-time communication. By predicting ahead we can give our brains a "head-start", so that language comprehension is faster and more efficient. While most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context, "they cautioned the...", we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

neuroscience↗

bioRxiv2019

Interaction between DNA damage response, translation and apoptosome determines cancer susceptibility to TOP2 poisons

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We show that glioblastoma (GBM), the most malignant of all primary brain tumors in adults is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 impaired the induction of pro-apoptotic gene APAF1 following etoposide treatment, and led to resistance to this drug and doxorubicin. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from multiple cancers.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/614024v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (14K):\norg.highwire.dtl.DTLVardef@310f7org.highwire.dtl.DTLVardef@14ed578org.highwire.dtl.DTLVardef@a0d9c0org.highwire.dtl.DTLVardef@37f59a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2018

Activation of dopamine receptor 2 (DRD2) prompts transcriptomic and metabolic plasticity in glioblastoma

Glioblastoma (GBM) is one of the most aggressive and lethal tumor types. Evidence continues to accrue indicating that the complex relationship between GBM and the brain microenvironment contributes to this malignant phenotype. However, the interaction between GBM and neurotransmitters, signaling molecules involved in neuronal communication, remains incompletely understood. Here we examined, in both sexes of humans and mice, how the monoamine dopamine influences GBM cells. We demonstrate that GBM cells express DRD2, with elevated expression in the glioma-initiating cell (GIC) population. Stimulation of DRD2 caused neuron-like depolarization exclusively in GICs. In addition, long-term activation of DRD2 heightened the sphere-forming capacity of GBM cells as well as tumor engraftment efficiency. Mechanistic investigation revealed that DRD2 signaling activates the hypoxia response and functionally alters metabolism. Finally, we found that GBM cells synthesize and secrete dopamine themselves, suggesting a potential autocrine mechanism. These results identify dopamine signaling as a potential therapeutic target in GBM and further highlight neurotransmitters as a key feature of the pro-tumor microenvironment.\n\nSignificance StatementThis work offers critical insight into the role of the neurotransmitter dopamine in the progression of GBM. We show that dopamine induces specific changes in the state of tumor cells, augmenting their growth and shifting them to a more stem-cell like state. Further, we show that dopamine can alter the metabolic behavior of GBM cells, increasing glycolysis. Finally, we show that GBM cells, including tumor samples from patients, can synthesize and secrete dopamine, suggesting an autocrine signaling process underlying these results. These results describe a novel connection between neurotransmitters and brain cancer, further highlighting the critical influence of the brain milieu on GBM.

cancer biology↗