Neural evidence for Bayesian trial-by-trial adaptation on the N400 during semantic priming.

When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) - a direct neural measure of semantic processing. N400 modulation is observed even when the context is a single semantically related "prime" word. This so-called "N400 semantic priming effect" is sensitive to the probability of encountering a related prime-target pair within an experimental block, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using a Bayesian learning model that estimates and updates the probability of encountering a related versus an unrelated prime-target pair on each successive trial. We found that our model's trial-by-trial estimates of target word probability accounted for significant variance in trial-by-trial N400 amplitude. These findings suggest that Bayesian principles contribute to how comprehenders adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing

Comprehenders Rationally Adapt Semantic Predictions to the Statistics of the Local Environment: a Bayesian Model of Trial-by-Trial N400 Amplitudes

When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) – a direct neural measure of semantic processing. This N400 modulation is observed even when the context is just a single semantically related “prime” word. This so-called “N400 semantic priming effect” is sensitive to the probability of seeing a related prime-target pair within experimental blocks, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using an optimal Bayesian learner, and link this model to N400 amplitudes using an information-theoretic measure, surprisal. We found that this model could account for the N400 amplitudes evoked by words (whether related or unrelated) as adaptation unfolds across individual trials. These findings suggest that comprehenders may rationally adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing

Neural evidence for Bayesian trial-by-trial adaptation on the N400 during semantic priming.

When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) - a direct neural measure of semantic processing. N400 modulation is observed even when the context is a single semantically related "prime" word. This so-called "N400 semantic priming effect" is sensitive to the probability of encountering a related prime-target pair within an experimental block, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using a Bayesian learning model that estimates and updates the probability of encountering a related versus an unrelated prime-target pair on each successive trial. We found that our model's trial-by-trial estimates of target word probability accounted for significant variance in trial-by-trial N400 amplitude. These findings suggest that Bayesian principles contribute to how comprehenders adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing

Priming production: Neural evidence for enhanced automatic semantic activity preceding language production in schizophrenia

Introduction: Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs). Methods: 19 people with schizophrenia and 16 demographically-matched healthy controls named target pictures that were very quickly preceded by masked prime words. To probe automatic semantic activity prior to production, we measured the N400 ERP component evoked by these targets. To determine the origin of any automatic semantic abnormalities, we manipulated the type of relationship between prime and target such that they overlapped in (a) their semantic features (semantically related, e.g. “cake” preceding a , (b) their initial phonemes (phonemically related, e.g. “stomach” preceding a ), or (c) both their semantic features and their orthographic/phonological word form (identity related, e.g. “socks” preceding a ). For each of these three types of relationship, the same targets were paired with unrelated prime words (counterbalanced across lists). We contrasted ERPs and naming times to each type of related target with its corresponding unrelated target. Results: People with schizophrenia showed abnormal N400 modulation prior to naming identity related (versus unrelated) targets: whereas healthy control participants produced a smaller amplitude N400 to identity related than unrelated targets, patients showed the opposite pattern, producing a larger N400 to identity related than unrelated targets. This abnormality was specific to the identity related targets. Just like healthy control participants, people with schizophrenia produced a smaller N400 to semantically related than to unrelated targets, and showed no difference in the N400 evoked by phonemically related and unrelated targets. There were no differences between the two groups in the pattern of naming times across conditions. Conclusion: People with schizophrenia can show abnormal neural activity associated with automatic semantic processing prior to language production. The specificity of this abnormality to the identity related targets suggests that that, rather than arising from abnormalities of either semantic features or lexical form alone, it may stem from disruptions of mappings (connections) between the meaning of words and their form

Developing antisense oligonucleotides for a TECPR2 mutation-induced, ultra-rare neurological disorder using patient-derived cellular models

Mutations in the TECPR2 gene are the cause of an ultra-rare neurological disorder characterized by intellectual disability, impaired speech, motor delay, and hypotonia evolving to spasticity, central sleep apnea, and premature death (SPG49 or HSAN9;OMIM: 615031). Little is known about the biological function of TECPR2, and there are currently no available disease-modifying therapies for this disease. Here we describe implementation of an antisense oligonucleotide (ASO) exon-skipping strategy targeting TECPR2 c.1319delT (p.Leu440Argfs*19), a pathogenic variant that results in a premature stop codon within TECPR2 exon 8. We used patient-derived fibroblasts and induced pluripotent stem cell (iPSC)-derived neurons homozygous for the p.Leu440Argfs*19 mutation to model the disease in vitro. Both patient-derived fibroblasts and neurons showed lack of TECPR2 protein expression. We designed and screened ASOs targeting sequences across the TECPR2 exon 8 region to identify molecules that induce exon 8 skipping and thereby remove the premature stop signal. TECPR2 exon 8 skipping restored in-frame expression of a TECPR2 protein variant (TECPR2 Delta Ex8) containing 1,300 of 1,411 amino acids. Optimization of ASO sequences generated a lead candidate (ASO-005-02) with similar to 27 nM potency in patientderived fibroblasts. To examine potential functional rescue induced by ASO-005-02, we used iPSC-derived neurons to analyze the neuronal localization of TECPR2 Delta Ex8 and showed that this form of TECPR2 retains the distinct, punctate neuronal expression pattern of full-length TECPR2. Finally, ASO-005-02 had an acceptable tolerability profile in vivo following a single 20-mg intrathecal dose in cynomolgus monkeys, showing some transient non-adverse behavioral effects with no correlating histopathology. Broad distribution of ASO-005-02 and induction of TECPR2 exon 8 skipping was detected in multiple central nervous system (CNS) tissues, supporting the potential utility of this therapeutic strategy for a subset of patients suffering from this rare disease