Biology subjects

Born, S.

Publications and source records attributed to Born, S..

3 recordsLinked to original sources

bioRxiv2026

An fMRI dataset of verbalized spontaneous thought with annotated transcripts and self-report trait measures

Spontaneous thought is pervasive in everyday human cognition, yet datasets capturing its neural dynamics under minimally interrupted conditions remain limited. The current dataset was acquired from a think-aloud functional MRI experiment in which 118 participants continuously verbalized their spontaneous thoughts during 10-minute scanning sessions. The raw MRI data and verbal transcripts with sentence-level timestamps were previously released and analyzed in our prior study examining neural activity associated with thought transitions. Building on that release, we additionally provide preprocessed MRI data, speech transcriptions with word-level timestamps aligned to image acquisition, large language model-generated ratings of transcribed thoughts across emotional and sensory dimensions, and self-report survey measures assessing personality, mental health, and cognitive abilities. Validation analyses demonstrated activation in expected cortical regions associated with speech production and sensory content identified from transcript annotations, agreement between language model and human ratings, and adequate internal consistency of survey measures, supporting the datasets overall quality. This dataset enables reuse for investigations of spontaneous thought, speech generation, and individual differences using naturalistic functional MRI data.

neuroscience↗

bioRxiv2024

Neural dynamics of spontaneous memory recall and future thinking in the continuous flow of thoughts

The human brain constantly recalls past experiences and anticipates future events, generating a continuous flow of thoughts. However, the neural mechanisms underlying the natural transitions and trajectories of thoughts during spontaneous memory recall and future thinking remain underexplored. To address this gap, we conducted a functional magnetic resonance imaging study using a think-aloud paradigm, where participants verbalize their uninterrupted stream of thoughts during rest. We found that transitions between thoughts, particularly those involving significant shifts in semantic content, activate the brains default and control networks. These neural responses to internally generated thought boundaries produce activation patterns resembling those triggered by external event boundaries. Moreover, interactions within and between these networks shape the overall semantic structure of thought trajectories: stronger functional connectivity within the medial temporal subsystem of the default network predicts greater variability in thoughts, while stronger connectivity between the control and core default networks is associated with reduced variability. Together, our findings highlight how the default and control networks guide the dynamic transitions and structure of naturally arising memory and future thinking.

neuroscience↗

bioRxiv2023

Modeling of enzyme-mediated glucose release to facilitate continuous feed in miniaturized cultivations

When striving for maximal throughput at minimal volumes while cultivating close to industrial conditions, simple and robust feeding strategies offer important advantages. Enzyme-mediated glucose cleavage from dextrin is an easy way of imitating continuous fed-batch in the small scale, with no complex equipment required. While the release rate - and thus the feed rate - can be controlled by adapting the enzyme concentration, it strongly depends on the concentration of the involved substances and the environmental conditions. Thus, it is a challenge to use the technology for controlling the specific growth rate, as it is commonly done with feed pumps. For solving this problem, we present here a mathematical model that extends simple Michaelis-Menten kinetics by considering different substrate fractions and can be applied to control the glucose release rate even in high throughput experiments. The fitted model was used during automated microbial cultivations to control the growth rate in quasi-continuous fed-batch processes and to realize different exponential growth rates by intermittent additions of enzyme and dextrin by a liquid handling robot system. We thus present an approach for defined biocatalytically controlled glucose supply of small-scale systems, where - if at all - continuous feeding was only possible with low accuracy or high technical efforts until now.

bioengineering↗