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Predictive coding theories propose that the brain constantly updates internal models to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link prediction error encoding and optimization of sensory representations remain unclear. Here, we provide evidence how predictive learning shapes the representational geometry of the human brain. We recorded magnetoencephalography (MEG) in humans listening to acoustic sequences with different levels of regularity. We found that the brain aligns its representational geometry to match the statistical structure of the sensory inputs, by clustering temporally contiguous and predictable stimuli. Crucially, the magnitude of this representational shift correlates with the synergistic encoding of prediction errors in a network of high-level and sensory areas. Our findings suggest that, in response to the statistical regularities of the environment, large-scale neural interactions engaged in predictive processing modulate the representational content of sensory areas to enhance sensory processing. This study shows that the human brain aligns its neural representations to the statistical structure of sensory inputs, and that the magnitude of this representational shift correlates with the synergistic encoding of prediction errors.

•Consciousness may emerge after thalamocortical networks form at 26 weeks gestation.•A “local-global” approach suggests consciousness in newborns and 35 week fetuses.•Default mode network activity has been observed in fetuses from 37 weeks.•We propose that sensory perturbations may be used to infer perinatal consciousness.•This could be done using prediction errors to perturb perinatal brain networks. When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory (“beep-and-zip”), visual (“flash-and-zip”), or even olfactory (“sniff-and-zip”) cortical perturbations in place of electromagnetic perturbations (“zap-and-zip”) might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.

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. [Display omitted]

Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate. Automatic state detection through algorithms relies on different parameters and thresholds derived from both the heart rate variability (HRV) and the actogram, which are highly dependent on the specific datasets and are prone to artefacts. Furthermore, the development of the fetal states is dynamic over the gestational period and the evaluation usually only separated into early and late gestation (before and after 32 weeks). In the current work, fBS detection was consistent between the classification algorithm and visual inspection in 87 fetal magnetocardiographic data segments between 27 and 39 weeks of gestational age. To identify how automated fBS detection could be improved, we first identified commonly used parameters for fBS classification in both the HRV and the actogram, and investigated their distribution across the different fBS. Then, we calculated a receiver operating characteristics (ROC) curve to determine the performance of each parameter in the fBS classification. Finally, we investigated the development of parameters over gestation through linear regression. As a result, the parameters derived from the HRV have a higher classification accuracy compared to those derived from the body movement as defined by the actogram. However, the overlapping distributions of several parameters across states limit a clear separation of states based on these parameters. The changes over gestation of the HRV parameters reflect the maturation of the fetal autonomic nervous system. Given the higher classification accuracy of the HRV in comparison to the actogram, we suggest to focus further research on the HRV. Furthermore, we propose to develop probabilistic fBS classification approaches to improve classification in less prototypical datasets.

In calf fattening, housing climate conditions are essential for optimal performance and welfare. Validated methods to measure the long-term housing climate are lacking. The present study investigated climate parameters for 14 weeks in Swiss calf fattening housing with two different ammonia (NH3) sensors: six stationary sensors (Dräger Polytron 8100) were installed at animal level and four mobile sensors (Dräger x-AM 5100) were attached to the calves’ heads. Temperature, relative humidity, and carbon dioxide (CO2) concentrations were recorded by two stationary data loggers (testo 160 IAQ). Data were analyzed descriptively, and 4 h mean values of maximum NH3 concentrations of mobile and stationary sensors were compared using the Wilcoxon test for paired data. The 4 h mean values of temperature, relative humidity, and CO2 concentrations and the 4 h mean values of maximum NH3 concentrations of stationary and mobile sensors were analyzed by ANOVA in two linear models. The overall 4 h mean of maximum NH3 concentrations ranged between 5.9–9.4 ppm for measurements of stationary sensors and between 11.3–14.7 ppm for measurements of mobile sensors. The NH3 concentrations measured by mobile sensors showed significantly higher peak values and more fluctuations. Additionally, an interaction effect was observed between the NH3 concentrations measured by either sensor and CO2 concentrations (p < 0.01 (mobile sensors); p < 0.0001 (stationary sensors), temperature values (p < 0.0001 (both sensors)), and relative humidity (p < 0.0001 (both sensors)). The measurements of the implemented method showed that corresponding housing climate parameters fluctuated strongly, and NH3 reached high peak values. Validated measurement methods might allow for a detailed assessment of the housing climate in practice, and for further research on suitable management methods for housing climate optimization in the future.

Electrogram-based identification of the regions maintaining persistent Atrial Fibrillation (AF) is a subject of ongoing debate. Here, we explore the concept of local electrical dyssynchrony to identify AF drivers. Local electrical dyssynchrony was calculated using mean phase coherence. High-density epicardial mapping along with mathematical model were used to explore the link between local dyssynchrony and properties of wave conduction. High-density mapping showed a positive correlation between the dyssynchrony and number of fibrillatory waves (R2 = 0.68, p<0.001). In the mathematical model, virtual ablation at high dyssynchrony regions resulted in conduction regularization. The clinical study consisted of eighteen patients undergoing catheter ablation of persistent AF. High-density maps of left atrial (LA) were constructed using a circular mapping catheter. After pulmonary vein isolation, regions with the top 10% of the highest dyssynchrony in LA were targeted during ablation and followed with ablation of complex atrial electrograms. Catheter ablation resulted in termination during ablation at high dyssynchrony regions in 7 (41%) patients. In another 4 (24%) patients, transient organization was observed. In 6 (35%) there was no clear effect. Long-term follow-up showed 65% AF freedom at 1 year and 22% at 2 years. Local electrical dyssynchrony provides a reasonable estimator of regional AF complexity defined as the number of fibrillatory waves. Additionally, it points to regions of dynamical instability related with action potential alternans. However, despite those characteristics, its utility in guiding catheter ablation of AF is limited suggesting other factors are responsible for AF persistence.

Mast cells (MC) are bone marrow derived haematopoetic cells playing a crucial role not only in immune response but also in the tumor microenvironment with protumorigenic and antitumorigenic functions. The role of MC in primary cutaneous T-cell lymphomas (CTCL), a heterogeneous group of non-Hodgkin lymphomas with initial presentation in the skin, is largely unknown. To gain more accurate information about presence, number, distribution and state of activation (degranulated vs. non-degranulated) of MC in CTCL variants and clinical stages. We established a novel computer-aided tissue analysis method on digitized skin sections. Immunohistochemistry with an anti-MC tryptase antibody was performed on 34 biopsies of different CTCL subtypes and on control skin samples. An algorithm for the automatic detection of the epidermis and of cell density based CTCL areas was developed. Cells were stratified as being within the CTCL infiltrate, in P1 (a surrounding area 0-30 μm away from CTCL), or in P2 (30-60 μm away from CTCL) area. We found high MC counts within CTCL infiltrates and P1 and a decreased MC number in the surrounding dermis P2. Higher MC numbers were found in MF compared to all other CTCL subgroups. Regarding different stages of MF, we found significantly higher mast cell counts in stages IA and IB than in stages IIA and IIB. Regarding MC densities, we found a higher density of MC in MF compared to all other CTCL subgroups. More MC were non-degranulated than degranulated. Here for the first time an automated method for MC analysis on tissue sections and its use in CTCL is described. Eliminating error from investigator bias, the method allows for precise cell identification and counting. Our results provide new insights on MC distribution in CTCL reappraising their role in the pathophysiology of CTCL.

Ultra-high-density (UHD) mapping can improve scar area detection and fast activation mapping in patients undergoing catheter ablation of ventricular tachycardia (VT). The aim of the present study was to compare the outcome after VT ablation guided by UHD and conventional point-by-point 3D-mapping. The acute and long-term ablation outcome of 61 consecutive patients with UHD mapping (64-electrode mini-basket catheter) was compared to 61 consecutive patients with conventional point-by-point 3D-mapping using a 3.5 mm tip catheter. Patients, whose ablation was guided by UHD mapping had an improved 24-months outcome in comparison to patients with conventional mapping (cumulative incidence estimate of the combination of recurrence or disease-related death of 52.4% (95% confidence interval (CI) [36.9–65.7]; recurrence: n = 25; disease-related death: n = 4) versus 69.6% (95% CI [55.9–79.8]); recurrence: n = 31; disease-related death n = 11). In a cause-specific Cox proportional hazards model, UHD mapping (hazard ratio (HR) 0.623; 95% CI [0.390–0.995]; P  = 0.048) and left ventricular ejection fraction > 30% (HR 0.485; 95% CI [0.290–0.813]; P  = 0.006) were independently associated with lower rates of recurrence or disease-related death. Other procedural parameters were similar in both groups. In conclusion, UHD mapping during VT ablation was associated with fewer VT recurrences or disease-related deaths during long-term follow-up in comparison to conventional point-by-point mapping. Complication rates and other procedural parameters were similar in both groups.

Yeast cells can be killed upon expression of pro-apoptotic mammalian proteins. We have established a functional yeast survival screen that was used to isolate novel human anti-apoptotic genes overexpressed in treatment-resistant tumors. The screening of three different cDNA libraries prepared from metastatic melanoma, glioblastomas and leukemic blasts allowed for the identification of many yeast cell death-repressing cDNAs, including 28% of genes that are already known to inhibit apoptosis, 35% of genes upregulated in at least one tumor entity and 16% of genes described as both anti-apoptotic in function and upregulated in tumors. These results confirm the great potential of this screening tool to identify novel anti-apoptotic and tumor-relevant molecules. Three of the isolated candidate genes were further analyzed regarding their anti-apoptotic function in cell culture and their potential as a therapeutic target for molecular therapy. PAICS, an enzyme required for de novo purine biosynthesis, the long non-coding RNA MALAT1 and the MAST2 kinase are overexpressed in certain tumor entities and capable of suppressing apoptosis in human cells. Using a subcutaneous xenograft mouse model, we also demonstrated that glioblastoma tumor growth requires MAST2 expression. An additional advantage of the yeast survival screen is its universal applicability. By using various inducible pro-apoptotic killer proteins and screening the appropriate cDNA library prepared from normal or pathologic tissue of interest, the survival screen can be used to identify apoptosis inhibitors in many different systems.

PurposePulsed-field ablation (PFA) is a new energy source to achieve pulmonary vein isolation (PVI) by targeted electroporation of cardiomyocytes. Experimental and controlled clinical trial data suggest good efficacy of PFA-based PVI. We aimed to assess efficacy, safety and follow-up of PFA-based PVI in an early adopter routine care setting.MethodsConsecutive patients with symptomatic paroxysmal or persistent atrial fibrillation (AF) underwent PVI using the Farawave® PFA ablation catheter in conjunction with three-dimensional mapping at two German high-volume ablation centers. PVI was achieved by applying 8 PFA applications in each PV.ResultsA total of 138 patients undergoing a first PVI (67 ± 12 years, 66% male, 62% persistent AF) were treated. PVI was achieved in all patients by deploying 4563 applications in 546 PVs (8.4 ± 1.0/PV). Disappearance of PV signals after the first application was demonstrated in 544/546 PVs (99.6%). More than eight PFA applications were performed in 29/546 PVs (6%) following adapted catheter positioning or due to reconnection as assessed during remapping. Mean procedure time was 78 ± 22 min including pre- and post PVI high-density voltage mapping. PFA catheter LA dwell-time was 23 ± 9 min. Total fluoroscopy time and dose area product were 16 ± 7 min and 505 [275;747] cGy*cm2. One pericardial tamponade (0.7%), one transient ST-elevation (0.7%) and three groin complications (2.2%) occurred. 1-year follow-up showed freedom of arrhythmia in 90% in patients with paroxysmal AF (n = 47) and 60% in patients with persistent AF (n = 82, p = 0.015).ConclusionsPFA-based PVI is acutely highly effective and associated with a beneficial safety and low recurrence rate.