Biology subjects

Schleger, F.

Publications and source records attributed to Schleger, F..

4 recordsLinked to original sources

bioRxiv2020

Magnetoencephalographic Signatures of Conscious Processing Before Birth

The concept of fetal consciousness is a widely discussed topic. In this study, we applied a hierarchical rule learning paradigm to investigate the possibility of fetal conscious processing during the last trimester of pregnancy. We used fetal magnetoencephalography, to assess fetal brain activity in 56 healthy fetuses between gestational week 25 and 40, during an auditory oddball paradigm containing first- and second-order regularities. The comparison of fetal brain responses towards standard and deviant tones revealed that the investigated fetuses show signs of hierarchical rule learning, and thus the formation of a memory trace for the second-order regularity. This ability develops over the course of the last trimester of gestation, in accordance with processes in physiological brain development and was only reliably present in fetuses older than week 35 of gestation. Analysis of fetal autonomic nervous system activity replicates findings in newborns, showing importance of activity state for cognitive processes. On the whole, our results support the assumption that fetuses in the last weeks of gestation are capable of consciously processing stimuli that reach them from outside the womb.

neuroscience↗

bioRxiv2020

Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

Humans are highly attuned to patterns in the environment. This ability to detect environmental patterns, referred to as statistical learning, plays a key role in many diverse aspects of cognition. However, the spatiotemporal neural mechanisms underlying implicit statistical learning, and how these mechanisms may relate or give rise to explicit learning, remain poorly understood. In the present study, we investigated these different aspects of statistical learning by using an auditory nonlinguistic statistical learning paradigm combined with magnetoencephalography. Twenty-four healthy volunteers were exposed to structured and random tone sequences, and statistical learning was quantified by neural entrainment. Already early during exposure, participants showed strong entrainment to the embedded tone patterns. A significant increase in entrainment over exposure was detected only in the structured condition, reflecting the trajectory of learning. While source reconstruction revealed a wide range of brain areas involved in this process, entrainment in areas around the left pre-central gyrus as well as right temporo-frontal areas significantly predicted behavioral performance. Sensor level results confirmed this relationship between neural entrainment and subsequent explicit knowledge. These results give insights into the dynamic relation between neural entrainment and explicit learning of triplet structures, suggesting that these two aspects are systematically related yet dissociable. Neural entrainment reflects robust, implicit learning of underlying patterns, whereas the emergence of explicit knowledge, likely built on the implicit encoding of structure, varies across individuals and may depend on factors such as sufficient exposure time and attention.

neuroscience↗

bioRxiv2020

Magnetoencephalographic Signatures of Hierarchical Rule Learning in Newborns

Estimating the extent to which newborn humans process input from their environment, especially regarding the depth of processing, is a challenging question. To approach this problem, we measured brain responses in 20 newborns with magnetoencephalography (MEG) in a "local-global" auditory oddball paradigm in which two-levels of hierarchical regularities are presented. Results suggest that infants in the first weeks of life are able to learn hierarchical rules, yet a certain level of vigilance seems to be necessary. Newborns detected violations of the first-order regularity and displayed a mismatch response between 200-400ms. Violations of the second-order regularity only evoked a late response in newborns in an active state, which was expressed by a high heart rate variability. These findings are in line with those obtained in human adults and older infants suggesting a continuity in the functional architecture from term- birth on, despite the important immaturity of the human brain at this age.

neuroscience↗

bioRxiv2019

Evaluating Complexity of Fetal MEG Signals: A Comparison of Different Metrics and Their Applicability

In this work, we aim to investigate whether information based metrics of neural activity are a useful tool for the search for consciousness before and shortly after birth. Neural activity is measured using fetal magnetoencephalography (fMEG) in human fetuses and neonates. Based on recent theories on consciousness, information-based metrics are established to measure brain complexity and to assess different levels of consciousness. Different metrics (measures of entropy, compressibility and fractality) are, thus, explored in a reference population and their usability is evaluated. For comparative analysis, two fMEG channels were selected: one where brain activity was previously detected and one at least 15cm away, that represented a control channel. The usability of each metric was evaluated and results from the brain and control channel were compared. Concerning the ease of use with fMEG data, Lempel-Ziv-Welch (LZW) compression was evaluated as best, as it is unequivocal and needs low computational effort. The fractality measures have a high parameter space and therefore forfeit comparability, while entropy measures require a higher computational effort and more parameters to adjust compared to LZW. Comparison of a channel with brain activity and a control channel in neonatal recordings showed significant differences in most complexity metrics. This clear difference can be seen as proof of concept for the usability of complexity metrics in fMEG. For fetal data, this comparison produced less clear results which can be related to leftover maternal signals included in the control channel. Further work is necessary to conclusively interpret results from the analysis of fetal recordings. Yet this study shows that complexity metrics can be used for fMEG data on early consciousness and the evaluation gives a guidance for future work. The inconsistency of results from different metrics highlights the challenges of working with complexity metrics as neural correlates of consciousness, as well as the caution one should apply to interpret them.

neuroscience↗