Biology subjects

Jansma, B. M.

Publications and source records attributed to Jansma, B. M..

4 recordsLinked to original sources

bioRxiv2025

Harry Potter meets Markov: Neural event representation in the reading network during narrative processing

People segment ongoing information into meaningful mental representations known as events. Recent studies have found a spatio-temporal hierarchy in the event structure during movie watching and story listening. How the human brain segments stories while reading remains unclear. We examined event segmentation while reading Harry Potter using publicly available 3T fMRI data. To identify neural events, we employed a Hidden Markov Model (HMM) within six regions of interest (ROI) in the reading network. The ROIs included the inferior frontal gyrus (IFG), middle frontal gyrus (MFG), angular gyrus (AG), inferior frontal gyrus orbital (IFGorb), anterior temporal lobe (ATL), and posterior temporal lobe (PTL). These regions are also associated with DMN. The results revealed multiple timescales of events, with the IFG and AG representing shorter events, while the IFGorb, ATL, PTL and MFG represent relatively longer events. Boundaries of longer events were partially aligned within short events, suggesting a nested hierarchical event structure. Further comparisons identified associations between neural events and annotations from humans and ChatGPT (automated and less subjective segmentation) in the inferior frontal, temporal and parietal areas. Notably, the AG (a core region of the DMN and memory processing) and the IFG (relevant for language processing) exhibited stronger alignment with both sets of annotations. The findings suggest an important role of AG and IFG in event segmentation in reading. They also confirm the connection between the reading network and the DMN in event segmentation. This connection seems to be linked to the hierarchical processing of context-dependent semantic information during reading.

neuroscience↗

bioRxiv2022

Spatiotemporal patterns of sleep spindle activity in human anterior thalamus and cortex

Sleep spindles (8 - 16 Hz) are transient electrophysiological events during non-rapid eye movement sleep. While sleep spindles are routinely observed in the cortex using scalp electroencephalography (EEG), recordings of their thalamic counterparts have not been widely studied in humans. Based on a few existing studies, it has been hypothesized that spindles occur as largely local phenomena. We investigated intra-thalamic and thalamocortical spindle co-occurrence, which may underlie thalamocortical communication. We obtained scalp EEG and thalamic recordings from 7 patients that received bilateral deep brain stimulation (DBS) electrodes to the anterior thalamus for the treatment of drug resistant focal epilepsy. Spindles were categorized into subtypes based on their main frequency (i.e., slow (10{+/-}2 Hz) or fast (14{+/-}2 Hz)) and their level of thalamic involvement (spanning one channel, or spreading uni- or bilaterally within the thalamus). For the first time, we contrasted observed spindle patterns with permuted data to estimate random spindle co-occurrence. We found that multichannel spindle patterns were systematically coordinated at the thalamic and thalamocortical level. Importantly, distinct topographical patterns of thalamocortical spindle overlap were associated with slow and fast subtypes of spindles. These observations provide further evidence for coordinated spindle activity in thalamocortical networks. HighlightsO_LISleep spindles were measured in human anterior thalamus and on the scalp C_LIO_LIBoth fast and slow spindles occurred in the anterior thalamus C_LIO_LI> 25% of spindles spanned multiple channels in thalamus and cortex C_LIO_LIA novel statistical approach confirmed that spindle co-occurrences were not random C_LIO_LICortical spindle patterns depended on thalamic involvement and spindle frequency C_LI

neuroscience↗

bioRxiv2021

Phonological and temporal regularities lead to differential ERP effects in self- and externally generated speech

Some theories of predictive processing propose reduced sensory and neural responses to anticipated events. Support comes from M/EEG studies, showing reduced auditory N1 and P2 responses to self-compared to externally generated events, or when stimulus properties are more predictable (e.g. prototypical). The current study examined the sensitivity of N1 and P2 responses to statistical regularities of speech. We employed a motor-to-auditory paradigm comparing ERP responses to externally and self-generated pseudowords, varying in phonotactic probability and syllable stress. We expected to see N1 and P2 suppression for self-generated stimuli, with greater suppression effect for more predictable features such as high phonotactic probability and first syllable stress in pseudowords. We observe an interaction between phonotactic probability and condition on the N1 amplitude, with an enhanced effect of phonotactic probability in processing self-generated stimuli. However, the directionality of this effect was reversed compared to what was expected, namely a larger N1 amplitude for high probability items, possibly indicating a perceptual bias toward the more predictable item. We further observed an effect of syllable stress on the P2 amplitude, with greater amplitudes in response to first syllable stress items. The current results suggest that phonotactic probability plays an important role in processing self-generated speech, supporting feedforward models involved in speech production.

neuroscience↗

bioRxiv2019

A novel approach for combining task-dependent gamma with alpha and beta power modulation for enhanced identification of eloquent cortical areas using ECoG in patients with medical-refractory epilepsy

Electrical stimulation mapping (ESM) is the gold standard for identification of \"eloquent\" areas prior to resection of epileptogenic tissue, however, it is time consuming and may cause side effects, especially stimulation-induced seizures and after-discharges. Broadband gamma activity (55 - 200 Hz) recorded with subdural electrocorticography (ECoG) during cognitive tasks has been proposed as an attractive tool for mapping cortical areas with specific function but until now has not proven definitive clinical value. Fewer studies have addressed whether the alpha (8 - 12 Hz) and beta (15 - 25 Hz) band activity could also be used to improve eloquent cortex identification. We compared alpha, beta and broadband gamma activity, and their combination for the identification of eloquent cortical areas defined by ESM. Ten patients participated in a delayed-match-to-sample task, where syllable sounds were matched to visually presented letters and responses given by keyboard. We used a generalized linear model (GLM) approach to find the optimal weighting of low frequency bands and broadband gamma power to predict the ESM categories. Broadband gamma activity increased more in eloquent areas than in non-eloquent areas and this difference had a diagnostic ability (area under (AU) the receiving operating characteristic curve - AUROC) of [~]70%. Both alpha and beta power decreased more in eloquent areas. Alpha power had lower AUROC than broadband gamma while beta had similar AUROC. AUROC was enhanced by the combination of alpha and broadband gamma (3% improvement) and by the combination of beta and broadband gamma (7% improvement) over the use of broadband gamma alone. Further analysis showed that the relative performance of broadband gamma and low frequency bands depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patients attention to the stimulus. However, the combination of beta band and broadband gamma always gave the best performance. We show how ECoG power modulation from cognitive testing periods can be used to map the probability of eloquence by ESM and how this probability can be used as an aid for optimal ESM planning. We conclude that low frequency power during cognitive testing can contribute to the identification of eloquent areas in patients with focal refractory epilepsy improving its precision but does not replace the need of ESM.\n\nHighlightsO_LIGamma, alpha and beta band activity has significant diagnostic ability to identify ESM defined eloquent cortical areas.\nC_LIO_LIWe present a novel method to combine gamma and low frequency activity for enhanced identification.\nC_LIO_LIWe quantify how identification is dependent on analysis time window, cortical function, and patients attentional engagement.\nC_LIO_LIWith further development, this approach may offer an alternative to ESM mapping with reduced burden for patients.\nC_LI

neuroscience↗