Biology subjects

Cross, Z.

Publications and source records attributed to Cross, Z..

3 recordsLinked to original sources

bioRxiv2026

From flexible to anticipatory processing: alpha and beta oscillatory signatures of feedback-guided strategy adaptation and memory updating

When humans learn under conditions of uncertainty, they dynamically adjust how they prepare for and respond to feedback. In navigating uncertain environments, the brain minimizes error by continuously refining internal models via memory updating (MU). Feedback is critical for MU, and anticipatory neural mechanisms shape how feedback is processed, likely reflecting learned environmental certainty. However, the literature has largely focused on post-feedback activity, leaving pre-feedback certainty-related mechanisms less understood. The present study aims to address this gap by examining how certainty modulates anticipatory states, preceding feedback and subsequent MU. We examined oscillatory activity prior to performance feedback in a reanalysis of EEG data previously published by Hassall and colleagues (2023). Twenty-one participants (16 female, Mage = 25.81 years) predicted the strength of cartoon characters with varying predictability levels which were learned through exposure. Feedback on prediction accuracy was presented via an animated rising bar. Results revealed that theta power is modulated by accumulative feedback. Linear mixed-effects models revealed an interaction between predictability-related certainty and learning stage: in late learning, higher performance was associated with increased pre-feedback alpha and beta power for low-certainty trials, whereas in early learning, higher performance was associated with decreased beta power. These learning-related modulations in alpha and beta power suggest that initial learning is marked by adaptable exploratory processing. Subsequent learning exhibited increased alpha-mediated inhibition and beta-related anticipatory activity for lower certainty trials, indicative of dynamic strategy refinement and selective engagement of task-relevant information. These results demonstrate that certainty shapes preparatory oscillatory activity associated with MU.

neuroscience↗

bioRxiv2023

Expecting the unexpected: A reanalysis of a multi-laboratory study provides evidence for prediction in language

The extent to which the brain predicts upcoming information during language processing remains controversial. To shed light on this debate, the present study reanalysed Nieuwland and colleagues (2018) replication of DeLong et al. (2005). Participants (N = 356) viewed sentences containing articles and nouns of varying predictability, while their electroencephalogram was recorded. We measured event-related potentials (ERPs) preceding the critical words (namely the semantic prediction potential; SPP), in conjunction with post-word N400 patterns and individual neural metrics. ERP activity was compared with two measures of word predictability: cloze probability and lexical surprisal. In contrast to prior literature, SPP amplitudes did not increase as cloze probability increased, suggesting that the component may not reflect prediction during natural language processing. Initial N400 results at the article provided evidence against phonological prediction in language, in line with Nieuwland and colleagues findings. Strikingly however, when the surprisal of the prior words in the sentence was included in the analysis, increases in article surprisal were associated with increased N400 amplitudes, consistent with prediction accounts. This relationship between surprisal and N400 amplitude was not observed when the surprisal of the two prior words was low, suggesting that expectation violations at the article may be overlooked under highly predictable conditions. Individual alpha frequency (IAF) also modulated the relationship between article surprisal and the N400, emphasising the importance of individual neural factors for prediction. The present study extends upon existing neurocognitive models of language and prediction more generally, by illuminating the flexible and subject-specific nature of predictive processing.

neuroscience↗

bioRxiv2019

Type II Alexander disease caused by splicing errors and aberrant overexpression of an uncharacterized GFAP isoform.

Alexander disease results from gain of function mutations in the gene encoding glial fibrillary acidic protein (GFAP), an intermediate filament protein expressed in astrocytes. At least eight GFAP isoforms have been described, however, the predominant alpha isoform accounts for approximately 90% of GFAP protein in the central nervous system. Here we describe exonic variants identified in three unrelated families with Type II Alexander disease that alter the splicing of GFAP pre-mRNA and result in upregulation of a previously uncharacterized GFAP lambda isoform (NM 001363846.1). Affected members of Family 1 and Family 2 shared the same missense variant, NM 001363846.1:c.1289G>A;p.(Arg430His) while in Family 3 we identified a synonymous variant in the adjacent nucleotide, NM 001363846.1:c.1290C>A;p.(Arg430Arg). Using RNA and protein analysis of brain autopsy samples, and a mini-gene splicing reporter assay, we demonstrate both variants result in upregulation of the lambda isoform. We assessed other GFAP variants in the ClinVar database for predicted aberrant splicing and using the same assay demonstrated significant changes to splicing for two selected variants. Our approach demonstrates the importance of characterizing the effect of GFAP variants on mRNA splicing in order to inform future pathophysiologic and therapeutic study for Alexander disease.

genetics↗