Generating parallel representations of position and identity in the olfactory system.

In Drosophila, a dedicated olfactory channel senses a male pheromone, cis-vaccenyl acetate (cVA), promoting female courtship while repelling males. Here, we show that separate cVA-processing streams extract qualitative and positional information. cVA sensory neurons respond to concentration differences in a 5-mm range around a male. Second-order projection neurons encode the angular position of a male by detecting inter-antennal differences in cVA concentration, which are amplified through contralateral inhibition. At the third circuit layer, we identify 47 cell types with diverse input-output connectivity. One population responds tonically to male flies, a second is tuned to olfactory looming, while a third integrates cVA and taste to coincidentally promote female mating. The separation of olfactory features resembles the mammalian what and where visual streams; together with multisensory integration, this enables behavioral responses appropriate to specific ethological contexts.

Early Binaural Hearing: The Comparison of Temporal Differences at the Two Ears.

Many mammals, including humans, are exquisitely sensitive to tiny time differences between sounds at the two ears. These interaural time differences are an important source of information for sound detection, for sound localization in space, and for environmental awareness. Two brainstem circuits are involved in the initial temporal comparisons between the ears, centered on the medial and lateral superior olive. Cells in these nuclei, as well as their afferents, display a large number of striking physiological and anatomical specializations to enable submillisecond sensitivity. As such, they provide an important model system to study temporal processing in the central nervous system. We review the progress that has been made in characterizing these primary binaural circuits as well as the variety of mechanisms that have been proposed to underlie their function.

Benchmarking mapping algorithms for cell-type annotating in mouse brain by integrating single-nucleus RNA-seq and Stereo-seq data.

Limited gene capture efficiency and spot size of spatial transcriptome (ST) data pose significant challenges in cell-type characterization. The heterogeneity and complexity of cell composition in the mammalian brain make it more challenging to accurately annotate ST data from brain. Many algorithms attempt to characterize subtypes of neuron by integrating ST data with single-nucleus RNA sequencing (snRNA-seq) or single-cell RNA sequencing. However, assessing the accuracy of these algorithms on Stereo-seq ST data remains unresolved. Here, we benchmarked 9 mapping algorithms using 10 ST datasets from four mouse brain regions in two different resolutions and 24 pseudo-ST datasets from snRNA-seq. Both actual ST data and pseudo-ST data were mapped using snRNA-seq datasets from the corresponding brain regions as reference data. After comparing the performance across different areas and resolutions of the mouse brain, we have reached the conclusion that both robust cell-type decomposition and SpatialDWLS demonstrated superior robustness and accuracy in cell-type annotation. Testing with publicly available snRNA-seq data from another sequencing platform in the cortex region further validated our conclusions. Altogether, we developed a workflow for assessing suitability of mapping algorithm that fits for ST datasets, which can improve the efficiency and accuracy of spatial data annotation.

The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy.

Successful surgical treatment of drug-resistant epilepsy traditionally relies on the identification of seizure onset zones (SOZs). Connectome-based analyses of electrographic data from stereo electroencephalography (SEEG) may empower improved detection of SOZs. Specifically, connectome-based analyses based on the Interictal Suppression Hypothesis (ISH) posit that when the patient is not having a seizure, SOZs are inhibited by non-SOZs through high inward connectivity and low outward connectivity. However, it is not clear whether there are other motifs that can better identify potential SOZs. Thus, we sought to use unsupervised machine learning to identify network motifs that elucidate SOZs and investigate if there is another motif that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8-12Hz). Principal component analysis (PCA) was performed on each patient's connectivity matrix. Each patient's components were analyzed qualitatively to identify common patterns across patients. A quantitative definition was then used to identify the component that most closely matched the observed pattern in each patient. A motif characteristic of the Interictal Suppression Hypothesis (high-inward and low-outward connectivity) was present in all individuals and found to be the most robust motif for identification of SOZs in 64/81 (79%) patients. This principal component demonstrated significant differences in SOZs compared to non-SOZs. While other motifs for identifying SOZs were present in other patients, they differed for each patient, suggesting that seizure networks are patient specific, but the ISH is present in nearly all networks. We discovered that a potentially suppressive motif based on the Interictal Suppression Hypothesis was present in all patients, and it was the most robust motif for SOZs in 79% of patients. Each patient had additional motifs that further characterized SOZs, but these motifs were not common across all patients. This work has the potential to augment clinical identification of SOZs to improve epilepsy treatment.

Anatomo-functional basis of emotional and motor resonance elicited by facial expressions.

Simulation theories predict that the observation of other's expressions modulates neural activity in the same centers controlling their production. This hypothesis has been developed by two models, postulating that the visual input is directly projected either to the motor system for action recognition (motor resonance) or to emotional/interoceptive regions for emotional contagion and social synchronization (emotional resonance). Here we investigated the role of frontal/insular regions in the processing of observed emotional expressions by combining intracranial recording, electrical stimulation and effective connectivity. First, we intracranially recorded from prefrontal, premotor or anterior insular regions of 44 patients during the passive observation of emotional expressions, finding widespread modulations in prefrontal/insular regions (anterior cingulate cortex, anterior insula, orbitofrontal cortex and inferior frontal gyrus) and motor territories (rolandic operculum and inferior frontal junction). Subsequently, we electrically stimulated the activated sites, finding that (a) in the anterior cingulate cortex and anterior insula, the stimulation elicited emotional/interoceptive responses, as predicted by the 'emotional resonance model', (b) in the rolandic operculum it evoked face/mouth sensorimotor responses, in line with the 'motor resonance' model, and (c) all other regions were unresponsive or revealed functions unrelated to the processing of facial expressions. Finally, we traced the effective connectivity to sketch a network-level description of these regions, finding that the anterior cingulate cortex and the anterior insula are reciprocally interconnected while the rolandic operculum is part of the parieto-frontal circuits and poorly connected with the formers. These results support the hypothesis that the pathways hypothesized by the 'emotional resonance' and the 'motor resonance' models work in parallel, differing in terms of spatio-temporal fingerprints, reactivity to electrical stimulation and connectivity patterns.

Chiral Acetal-Based Stereo-Controlled Degradable Polymer Synthesis.

The precise synthesis of chiral polymers remains a significant challenge in polymer chemistry, particularly for applications in advanced biomedical and electronic materials. The development of degradable polymers is important for eco-friendly and advanced materials. Here, we introduce a stereo-controlled degradable polymer via cascade enyne metathesis polymerization and enantioselective acetal synthesis through Pd-catalyzed asymmetric hydroamination. This approach allows for the creation of chiral acetal-based polymers with controlled stereochemistry and degradability, highlighting their potential for use in drug delivery and electronic applications. This concept article reviews the background, development, and potential applications of these stereo-controlled degradable polymers.

Merging Photocatalytic Doubly-Decarboxylative Csp 2 -Csp 2 Cross-Coupling for Stereo-Selective (E)-α,ß-Unsaturated Ketones Synthesis.

A photocatalytic domain of doubly decarboxylative Csp 2 -Csp 2 cross coupling reaction is disclosed. Merging iridium and palladium photocatalysis manifested carbon-carbon bonds in a tandem dual-radical pathway. Present catalytic platform efficiently cross-coupled α, ß-unsaturated acids and α-keto acids to afford a variety of α, ß-unsaturated ketones with excellent (E)-selectivity and functional group tolerance. Mechanistically, photocatalyst implicated through reductive quenching cycle whereas cross coupling proceeded over one electron oxidative pallado-cycle.

Stereo-Active Lone Pairs Induced Second Harmonic Generation Responses and Electrocatalytic Activity in Hybrid Material.

The lone pair electrons in the electronic structure of molecules have been a prominent research focus in chemistry for more than a century. Stable s2lone pair electrons significantly influence material properties, including thermoelectric properties, nonlinear optical properties, ferroelectricity, and electro(photo)catalysis.While major advances have been achieved in understanding the influence of lone pair electrons on material characteristics, research on this effect in organic-inorganic hybrid materials is in its initial stage. In this work, we successfully obtained a novel organic-inorganic hybrid material incorporating Ge with 4s2 lone pair electrons, (MeHDabco)2[GeBr3]4-H2O (MeHDabco = N-methyl-1,4-diazabicyclo[2.2.2]octane) (1). Driven by the stereochemically active lone pair electrons on the Ge2+, 1 crystallizes in the noncentrosymmetric space group P21 at room temperature and exhibits good second harmonic generation (SHG) responses. Interestingly, 1 also shows electrocatalytic activity for the hydrogen evolution reaction due to the existence of lone pair electrons on Ge2+ cations. The electrochemical experiment combined with the DFT calculations revealed the lone pair electrons act as both an active site for proton adsorption and facilitate the ionization of water. This work not only emphasizes the important role of lone pair electrons in material properties and functions but also provides new insight for designing novel Ge-based hybrid materials.

Multisite thalamic recordings to characterize seizure propagation in the human brain.

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in a subset of patients with refractory focal epilepsy. One important uncertainty is to what extent thalamic subregions other than the ANT could be recruited more prominently in the propagation of focal onset seizures. We designed the current study to simultaneously monitor the engagement of the ANT, mediodorsal (MD) and pulvinar (PUL) nuclei during seizures in patients who could be candidates for thalamic neuromodulation. We studied 11 patients with clinical manifestations of presumed temporal lobe epilepsy (TLE) undergoing invasive stereo-encephalography (sEEG) monitoring to confirm the source of their seizures. We extended cortical electrodes to reach the ANT, MD and PUL nuclei of the thalamus. More than one thalamic subdivision was simultaneously interrogated in nine patients. We recorded seizures with implanted electrodes across various regions of the brain and documented seizure onset zones (SOZ) in each recorded seizure. We visually identified the first thalamic subregion to be involved in seizure propagation. Additionally, in eight patients, we applied repeated single pulse electrical stimulation in each SOZ and recorded the time and prominence of evoked responses across the implanted thalamic regions. Our approach for multisite thalamic sampling was safe and caused no adverse events. Intracranial EEG recordings confirmed SOZ in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites, highlighting the importance of invasive monitoring for accurate localization of SOZs. In all patients, seizures with the same propagation network and originating from the same SOZ involved the same thalamic subregion, with a stereotyped thalamic EEG signature. Qualitative visual reviews of ictal EEGs were largely consistent with the quantitative analysis of the corticothalamic evoked potentials, and both documented that thalamic nuclei other than ANT could have the earliest participation in seizure propagation. Specifically, pulvinar nuclei were involved earlier and more prominently than ANT in more than half of the patients. However, which specific thalamic subregion first demonstrated ictal activity could not be reliably predicted based on clinical semiology or lobar localization of SOZs. Our findings document the feasibility and safety of bilateral multisite sampling from the human thalamus. This may allow more personalized thalamic targets to be identified for neuromodulation. Future studies are needed to determine if a personalized thalamic neuromodulation leads to greater improvements in clinical outcome.

Characterization of anti-seizure medication reduction and discontinuation rates following epilepsy surgery.

OBJECTIVE: Many patients pursue epilepsy surgery with the hope of reducing or stopping anti-seizure medications (ASMs), in addition to reducing their seizure frequency and severity. While ASM decrease is primarily driven by surgical outcomes and patient preferences, preoperative estimates of meaningful ASM reduction or discontinuation are uncertain, especially when accounting for the various forking paths possible following intracranial EEG (iEEG), including resection, neuromodulation, or even the absence of further surgery. Here, we characterize in detail the ASM reduction in a large cohort of patients who underwent iEEG, facilitating proactive, early counseling for a complicated cohort considering surgical treatment. METHODS: We identified a multi-institutional cohort of patients who underwent iEEG between 2001 and 2022, with a minimum of two years follow-up. The total number of ASMs prescribed immediately prior to surgery, choice of investigation modality, and subsequent surgical treatment were extracted for each patient. Primary endpoints included decreases in ASM counts from preoperative baseline to various follow-up intervals. RESULTS: A total of 284 patients were followed for a median of 6.0 (range 2,22) years after iEEG surgery. Patients undergoing resection saw an average reduction of âˆ¼ 0.5 ASMs. Patients undergoing neuromodulation saw no decrease and trended towards requiring increased ASM usage during long-term follow-up. Only patients undergoing resection were likely to completely discontinue all ASMs, with an increasing probability over time approaching âˆ¼ 10 %. Up to half of resection patients saw ASM decreases, which was largely stable during long-term follow-up, whereas only a quarter of neuromodulation patients saw a reduction, though their ASM reduction decreased over time. CONCLUSIONS: With the increasing use of stereotactic EEG and non-curative neuromodulation procedures, realistic estimates of ASM reduction and discontinuation should be considered preoperatively. Almost half of patients undergoing resective surgery can expect to reduce their ASMs, though only a tenth can expect to discontinue ASMs completely. If reduction is not seen early, it likely does not occur later during long-term follow-up. Less than a third of patients undergoing neuromodulation can expect ASM reduction, and instead most may require increased usage during long-term follow-up.

Periventricular nodular heterotopia is coupled with the neocortex during resting and task states.

Periventricular nodular heterotopia (PVNH) is a well-defined developmental disorder characterized by failed neuronal migration, which forms ectopic neuronal nodules along the ventricular walls. Previous studies mainly focus on clinical symptoms caused by the PVNH tissue, such as seizures. However, little is known about whether and how neurons in the PVNH tissue functionally communicate with neurons in the neocortex. To probe this, we applied magnetoencephalography (MEG) and stereo-electroencephalography (sEEG) recordings to patients with PVNH during resting and task states. By estimating frequency-resolved phase coupling strength of the source-reconstructed neural activities, we found that the PVNH tissue was spontaneously coupled with the neocortex in the α-ß frequency range, which was consistent with the synchronization pattern within the neocortical network. Furthermore, the coupling strength between PVNH and sensory areas effectively modulated the local neural activity in sensory areas. In both MEG and sEEG visual experiments, the PVNH tissue exhibited visual-evoked responses, with a similar pattern and latency as the ipsilateral visual cortex. These findings demonstrate that PVNH is functionally integrated into cognition-related cortical circuits, suggesting a co-development perspective of ectopic neurons after their migration failure.

Two stages of speech envelope tracking in human auditory cortex modulated by speech intelligibility.

The envelope is essential for speech perception. Recent studies have shown that cortical activity can track the acoustic envelope. However, whether the tracking strength reflects the extent of speech intelligibility processing remains controversial. Here, using stereo-electroencephalogram technology, we directly recorded the activity in human auditory cortex while subjects listened to either natural or noise-vocoded speech. These 2 stimuli have approximately identical envelopes, but the noise-vocoded speech does not have speech intelligibility. According to the tracking lags, we revealed 2 stages of envelope tracking: an early high-γ (60-140 Hz) power stage that preferred the noise-vocoded speech and a late θ (4-8 Hz) phase stage that preferred the natural speech. Furthermore, the decoding performance of high-γ power was better in primary auditory cortex than in nonprimary auditory cortex, consistent with its short tracking delay, while θ phase showed better decoding performance in right auditory cortex. In addition, high-γ responses with sustained temporal profiles in nonprimary auditory cortex were dominant in both envelope tracking and decoding. In sum, we suggested a functional dissociation between high-γ power and θ phase: the former reflects fast and automatic processing of brief acoustic features, while the latter correlates to slow build-up processing facilitated by speech intelligibility.

Impact of surrounding tissue-type and peri-electrode gap in stereoelectroencephalography guided (SEEG) radiofrequency thermocoagulation (RF-TC): a computational study.

PURPOSE: To use computational modeling to provide a complete and logical description of the electrical and thermal behavior during stereoelectroencephalography-guided (SEEG) radiofrequency thermo-coagulation (RF-TC). METHODS: A coupled electrical-thermal model was used to obtain the temperature distributions in the tissue during RF-TC. The computer model was first validated by an ex vivo model based on liver fragments and later used to study the impact of three different factors on the coagulation zone size: 1) the difference in the tissue surrounding the electrode (gray/white matter), 2) the presence of a peri-electrode gap occupied by cerebrospinal fluid (CSF), and 3) the energy setting used (power-duration). RESULTS: The model built for the experimental validation was able to predict both the evolution of impedance and the short diameter of the coagulation zone (error < 0.01 mm) reasonably well but overestimated the long diameter by 2 - 3 mm. After adapting the model to clinical conditions, the simulation showed that: 1) Impedance roll-off limited the coagulation size but involved overheating (around 100 °C); 2) The type of tissue around the contacts (gray vs. white matter) had a moderate impact on the coagulation size (maximum difference 0.84 mm), and 3) the peri-electrode gap considerably altered the temperature distributions, avoided overheating, although the diameter of the coagulation zone was not very different from the no-gap case (<0.2 mm). CONCLUSIONS: This study showed that computer modeling, especially subject- and scenario-specific modeling, can be used to estimate in advance the electrical and thermal performance of the RF-TC in brain tissue.

Advancement in chiral heterocycles for the antidiabetic activity.

For the synthesis and development of pharmaceuticals, chirality is an important structural component. Chiral heterocyclic compounds have annoyed the interest of synthetic chemists who are working to create useful and efficient techniques for these molecules. As indicated by the expanding number of chiral drugs created in the last two decades, the link between chirality and pharmacological activity has become more important in the pharmaceutical and biopharmaceutical industries. Approximately 65% of currently used drugs are chiral, and many of them are promoted as racemates in many circumstances. There are a growing number of new chiral heterocyclic compounds with important biological properties and intriguing uses in medical chemistry and drug discovery. In this study, we review current breakthroughs in chiral heterocycles and their different physiological activities that have been published in the last year (from 2010 to early 2023). This study focuses on the current trends in the use of chiral heterocycles in drug design and the creation of several powerful and competent candidates for diabetic illnesses.

Separation and simultaneous estimation of enantiomers and Diastereomers of muscarinic receptor antagonist Solifenacin using stability-indicating Normal-phase HPLC technique with chiral stationary phase amylose tris-(3,5-dimethylphenylcarbamate).

The R,S-enantiomer impurity and diastereomer impurities (S,S-isomer and R,R-isomer) of the solifenacin (S,R-enantiomer) were effectively separated and quantified simultaneously utilizing normal-phase high-performance liquid chromatography with a chiral stationary phase consisting of amylose tris (3,5-dimethylphenylcarbamate) coated on silica-gel (Chiralpak, AD-H). The enantiomeric and stereo-selective separation was achieved within a run time of 35 minutes using a mobile phase of 'n-hexane, ethanol, and diethylamine' in an isocratic elution mode with a detection wavelength of 220 nm. The validation attributes assessed were accuracy (which showed excellent recoveries between 97.5% and 100.4%) and linearity (which was proven in the range of 0.081-1.275 µg.mL-1 , with a linear regression of 0.999). The stress testing experiments proved that the developed methodology by the HPLC technique has stability-indicating characteristics, as all closely eluting peak pairs were separated well with a resolution of 2.3 and without any interference. The proposed methodology was highly efficient in separating and simultaneously determining the chiral impurities (enantiomers and diastereomers) of the solifenacin in the release and stability sample analyses of drug substances and tablets in pharmaceutical formulations.

Frame-based versus robot-assisted stereo-electro-encephalography for drug-resistant epilepsy.

BACKGROUND: Stereoelectroencephalography (SEEG) is an effective presurgical invasive evaluation for drug-resistant epilepsies. The introduction of robotic devices provides a simplified, accurate, and safe alternative to the conventional SEEG technique. We report our institutional experience with robot-assisted SEEG and compare its in vivo accuracy, operation efficiency, and safety with the more traditional SEEG workflow. METHODS: All patients with medically refractory focal epilepsy who underwent SEEG depth electrode implantation between 2014 and 2022 were included in this study. Technical advancements of the robot-assisted technique are described. Analyses of patient demographics, electrode implantation accuracy, operation time, and procedure-related complications were performed. RESULTS: One hundred and sixty-six patients underwent 167 SEEG procedures. The first 141 procedures were performed using a conventional approach involving a Leksell stereotactic system, and the last 26 procedures were robot-assisted. Among the 1726 depth electrodes that were inserted, the median entry point localization error was as follows: conventional (1.0 mm; range, 0.1-33.5 mm) and robot-assisted (1.1 mm; range, 0-4.8 mm) (P = 0.17). The median target point localization error was as follows: conventional (2.8 mm; range, 0.1-49 mm) and robot-assisted (1.8 mm; range, 0-30.3 mm) (P < 0.001). The median operation time was significantly reduced with the robot-assisted workflow (90 min vs. 77.5 min; P < 0.01). Total complication rates were as follows: conventional (17.7%) and robot-assisted (11.5%) (P = 0.57). Major complication rates were 3.5% and 7.7% (P = 0.77), respectively. CONCLUSIONS: SEEG is a safe and highly accurate method that provides essential guidance for epilepsy surgery. Implementing SEEG in conjunction with multimodal planning systems and robotic devices can further increase safety margin, surgical efficiency, and accuracy.

OptiGait: Gait Monitoring Using An Ankle-Worn Stereo Camera System.

We developed an ankle-worn gait monitoring system for tracking gait parameters, including length, width, and height. The system utilizes ankle bracelets equipped with wide-angle infrared (IR) stereo cameras tasked with monitoring a marker on the opposing ankle. A computer vision algorithm we have also developed processes the imaged marker positions to estimate the length, width, and height of the person's gait. Through testing on multiple participants, the prototype of the proposed gait monitoring system exhibited notable performance, achieving an average accuracy of 96.52%, 94.46%, and 95.29% for gait length, width, and height measurements, respectively, despite distorted wide-angle images. The OptiGait system offers a cost-effective and user-friendly alternative compared to existing gait parameter sensing systems, delivering comparable accuracy in measuring gait length and width. Notably, the system demonstrates a novel capability in measuring gait height, a feature not previously reported in the literature.

Spatial transcriptomics: Technologies, applications and experimental considerations.

The diverse cell types of an organ have a highly structured organization to enable their efficient and correct function. To fully appreciate gene functions in a given cell type, one needs to understand how much, when and where the gene is expressed. Classic bulk RNA sequencing and popular single cell sequencing destroy cell structural organization and fail to provide spatial information. However, the spatial location of gene expression or of the cell in a complex tissue provides key clues to comprehend how the neighboring genes or cells cross talk, transduce signals and work together as a team to complete the job. The functional requirement for the spatial content has been a driving force for rapid development of the spatial transcriptomics technologies in the past few years. Here, we present an overview of current spatial technologies with a special focus on the commercially available or currently being commercialized technologies, highlight their applications by category and discuss experimental considerations for a first spatial experiment.

Multimodal Mobile Robotic Dataset for a Typical Mediterranean Greenhouse: The GREENBOT Dataset.

This paper presents an innovative dataset designed explicitly for challenging agricultural environments, such as greenhouses, where precise location is crucial, but GNNS accuracy may be compromised by construction elements and the crop. The dataset was collected using a mobile platform equipped with a set of sensors typically used in mobile robots as it was moved through all the corridors of a typical Mediterranean greenhouse featuring tomato crops. This dataset presents a unique opportunity for constructing detailed 3D models of plants in such indoor-like spaces, with potential applications such as robotized spraying. For the first time, to the authors' knowledge, a dataset suitable to test simultaneous localization and mapping (SLAM) methods is presented in a greenhouse environment, which poses unique challenges. The suitability of the dataset for this purpose is assessed by presenting SLAM results with state-of-the-art algorithms. The dataset is available online.

UAV-Borne Mapping Algorithms for Low-Altitude and High-Speed Drone Applications.

This article presents an analysis of current state-of-the-art sensors and how these sensors work with several mapping algorithms for UAV (Unmanned Aerial Vehicle) applications, focusing on low-altitude and high-speed scenarios. A new experimental construct is created using highly realistic environments made possible by integrating the AirSim simulator with Google 3D maps models using the Cesium Tiles plugin. Experiments are conducted in this high-realism simulated environment to evaluate the performance of three distinct mapping algorithms: (1) Direct Sparse Odometry (DSO), (2) Stereo DSO (SDSO), and (3) DSO Lite (DSOL). Experimental results evaluate algorithms based on their measured geometric accuracy and computational speed. The results provide valuable insights into the strengths and limitations of each algorithm. Findings quantify compromises in UAV algorithm selection, allowing researchers to find the mapping solution best suited to their application, which often requires a compromise between computational performance and the density and accuracy of geometric map estimates. Results indicate that for UAVs with restrictive computing resources, DSOL is the best option. For systems with payload capacity and modest compute resources, SDSO is the best option. If only one camera is available, DSO is the option to choose for applications that require dense mapping results.