bioRxiv Subject Collection: Neuroscience's Journal
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Sunday, May 4th, 2025
| Time |
Event |
| 5:01a |
Inter-brain similarity and connectivity based on EEG hyperscanning during patient-acupuncturist interactions
The study of patient-clinician relationships is a vital branch of interpersonal interaction research. Acupuncture attaches great importance to positive patient-clinician interactions; thus, it serves as a typical example of patient-clinician interaction research. Based on electroencephalography (EEG) hyperscanning, this study explored inter-brain similarity based on spatial correlations between two brains as well as inter-brain connectivity of different regions through different frequency bands. Regarding inter-brain similarity, both acupuncture and sham acupuncture significantly decreased spatial correlation during certain sessions during acupuncture. Regarding inter-brain connectivity, acupuncture enhanced not only the connectivity of the beta frequency band in the right temporoparietal regions but also the connectivity of the fast-ripple frequency band in the right and left temporoparietal regions. These results suggest that inter-brain similarity should be emphasized in patient-clinician relationship research. Moreover, high-frequency oscillations (HFOs) potentially play an important role in inter-brain connectivity in addition to the classical EEG low-frequency bands. | | 5:01a |
Automatic Individual Cortical Parcellation for the Human Connectome Project
The original Human Connectome Project multimodal cortical parcellation (HCP_MMP1.0) used MRI-derived local features and long-distance functional connectivity measures to define a multimodal parcellation at the group level, accompanied by an automated areal classifier, to create subject-specific mappings of the human cerebral cortex. These mappings, referred to as individual (cortex) parcellations, aim to capture individual variability in areal organization by learning from both structural and functional data. However, a strict supervised learning approach using the group parcellation as labels would have no incentive to learn individual differences that registration is unable to reconcile (e.g., atypical 55b topologies). Furthermore, there are many types of resting state network (RSN) feature maps, and it is unclear which type would most accurately or effectively classify areas, or even what should be the primary criteria for evaluating classification performance. Here, we introduce an Areal Recognition Ensemble with Nested Approach (ARENA) classifier that learns from uncertain labels, using a novel application of weakly supervised learning to this type of problem. Additionally, in comparing multiple candidate RSN decompositions, temporal ICA and PROFUMO maps outperformed the original spatial ICA-based approach based on objective criteria. With these refinements, the ensemble classifier achieved a reliable individual variability score of 8380, an average areal detection rate of 97.8%, and test-retest reproducibility of 73.3%, outperforming a retrained version of the original Multi-layer Perceptron (MLP) model (whose reliable individual variability score was 3128, average areal detection rate was 97.2%, and test-retest reproducibility was 71.6% on the same dataset). Furthermore, the ARENA classifier demonstrated stronger generalization for all three measures when applied to task fMRI data that were not part of the training dataset. Using the refined classifier and leveraging all 1071 HCP-Young Adult subjects, we identified new types of atypical organization of language-related area 55b. Here we provide the fully data-driven HCP_MMP1.0_1071_MPM (Maximum Probability Map) group parcellation and a summary of area 55b organization in both hemispheres. Our automated individual parcellation pipeline powered by the novel ARENA classifier is now integrated into the HCP pipelines, offering a user-friendly tool for the neuroimaging community. | | 5:01a |
Isolation of Neural Stem Cells Using Platelet Derived Growth Factor C
Here, we show that Platelet-Derived Growth Factor C (PDGFC) supports the isolation of neural stem cells (NSCs) from the murine subventricular zone (SVZ) and maintains them in quiescent and slowly proliferating states. We also show that NSCs isolated using PDGFC can be induced to proliferate rapidly when switched to media supplemented with Epidermal Growth Factor and Fibroblast Growth Factor (EGF/FGF), the gold standard growth condition for NSCs. Although patterns of gene expression in NSCs isolated in PDGFC or in EGF/FGF are similar, a comparative analysis of quiescence genes reveals that NSCs in PDGFC are more like SVZ tissue than are NSCs maintained in EGF/FGF. In addition, NSCs isolated using PDGFC transition to oligodendrocyte progenitor cells (OPCs) when FGF is added to PDGFC and have an expression profile indistinguishable from OPCs that are isolated traditionally using PDGFA/FGF. | | 5:41a |
Electrophysiological recordings reveal photoreceptor coupling in the dorsal rim areas of honeybee and bumblebee eyes
Many insects rely on skylight polarization patterns to navigate their habitats. To perform this vital task, most insect species have evolved specialized ommatidia in the dorsal rim area (DRA) of their compound eyes that are adapted to detect linearly polarized light in large patches of sky. In this study, we conducted electrophysiological recordings of honeybee (Apis mellifera) and bumblebee (Bombus terrestris) photoreceptors in the DRA and other regions of the compound eye to map their receptive fields. For both species, we report novel evidence for photoreceptor coupling, i.e., spatial summation, present in the retinal layer of the DRA. We explore spatial summation as a possible, eye-region-specific mechanism to increase the effective size of DRA ommatidia receptive fields; a crucial functional feature of the polarization compass. | | 5:41a |
Integrating simulated and experimental data to identify mitochondrial bioenergetic defects in Parkinson's Disease models
Mitochondrial bioenergetics are vital for ATP production and are associated with several diseases, including Parkinsons Disease. Here, we simulated a computational model of mitochondrial ATP production to interrogate mitochondrial bioenergetics under physiological and pathophysiological conditions, and provide a data resource that can be used to interpret mitochondrial bioenergetics experiments. We first characterised the impact of several common respiratory chain impairments on experimentally-observable bioenergetic parameters. We then established an analysis pipeline to integrate simulations with experimental data and predict the molecular defects underlying experimental bioenergetic phenotypes. We applied the pipeline to data from Parkinsons Disease models. We verified that the impaired bioenergetic profile previously measured in Parkin knockout neurons can be explained by increased mitochondrial uncoupling. We then generated primary cortical neurons from a Pink1 KO mouse model of Parkinsons, and measured reduced OCR capacity and increased resistance to Complex III inhibition. Here, our pipeline predicted that multiple respiratory chain impairments are required to explain this bioenergetic phenotype. Finally, we provide all simulated data as a user-friendly resource that can be used to interpret mitochondrial bioenergetics experiments, predict underlying molecular defects, and inform experimental design. | | 7:32a |
Combined Angiographic, Structural and Perfusion Radial Imaging using Arterial Spin Labeling
Purpose: To develop a non-contrast MRI method for the simultaneous acquisition of time-resolved 3D angiographic, perfusion and multi-contrast T1-weighted structural brain images in a single six-minute acquisition. Methods: The proposed Combined Angiographic, Structural and Perfusion Radial Imaging using Arterial Spin Labeling (CASPRIA) pulse sequence uses pseudocontinuous arterial spin labeling (PCASL) to label inflowing blood, an inversion pulse to provide background suppression and T1-weighted contrast, and a continuous 3D golden ratio spoiled gradient echo readout. Label-control subtraction isolates the blood signal and can be flexibly reconstructed at high/low spatiotemporal resolution for angiography/perfusion imaging. The mean signal retains the static tissue, allowing T1-weighted structural images to be reconstructed at different effective inversion times. CASPRIA was compared with conventional time-of-flight (TOF) angiography, 3D-gradient and spin echo (3D-GRASE) PCASL perfusion imaging and magnetization-prepared rapid gradient echo (MP-RAGE) structural imaging (10 minutes total) in healthy volunteers. Results: CASPRIA gave improved distal vessel visibility and fewer artefacts than TOF angiography, whilst also providing dynamic information, with blood transit time and dispersion maps. CASPRIA perfusion images were comparable to 3D-GRASE data, but without through-slice blurring or artefacts in inferior brain regions. Comparable quantitative cerebral blood flow maps were produced, with CASPRIA being significantly more repeatable. Structural CASPRIA images were comparable to MP-RAGE, but also yielded a range of T1-weighted contrasts and allowed quantitative T1 maps to be estimated. Conclusion: CASPRIA is an efficient single acquisition to provide intrinsically co-registered quantitative information about brain blood flow and structure that has considerable advantages over conventional methods. | | 7:32a |
Effects of stimulus modality and response type on oddball stimulus discrimination using polarity-considered EEG microstate labeling
Objective: Brain-computer interfaces (BCIs) require effective feature extraction and dimensionality reduction from multidimensional brain signals. Electroencephalogram (EEG) microstate analysis offers a fast and noise-resistant approach by classifying the states of brain signals into spatial distribution patterns (templates). Each EEG segment was assigned the template with the highest spatial correlation, reducing the information to a one-dimensional representation. However, prior BCI studies have often ignored the polarity of spatial distributions in these templates. Incorporating polarity during labeling may enhance classification performance. This study investigated the effectiveness of polarity-considered microstate labeling for classifying infrequent stimuli in an auditory-visual oddball task with implications for BCI applications. Method: EEG recordings were analyzed using polarity-considered microstate labeling to classify infrequent stimuli. This study examined the effects of stimulus modality (auditory or visual), modality conditions (unimodal: stimulus and response in the same modality; cross-modal: stimulus and response in different modalities), and response type (key-press task vs. mental counting task) on classification accuracy. Machine learning models were used for classification, including support vector machine, random forest, logistic regression, XGBoost, CatBoost and K-means methods. Results: Polarity-considered labeling outperformed the non-polarity approach, especially in decision-tree-based models (20.1% improvement in the key-press task and 22.2% improvement in the mental counting task). A significant interaction was observed between stimulus modality and response type, with the highest accuracy achieved when the infrequent stimuli in the key-press task involved cross-modal visual information. Conclusion: The findings suggest that polarity-considered microstate labeling enhances EEG-based classification. This approach has potential applications in BCI, such as in P300 spellers using cross-modal auditory-visual stimuli. | | 10:17a |
Adaptations in common synaptic inputs to spinal motor neurons during grasping versus a less functional hand task
Previous evidence suggests that shared synaptic inputs across spinal motor neurons play a key role in coordinating multiple muscles during hand movements, reducing control complexity. In this study, we investigated how the nervous system modulates these common synaptic inputs during a functionally relevant grip (grasping) compared to less functionally relevant hand tasks. Seventeen participants performed three different tasks: simultaneous four-finger flexion without thumb involvement (four-finger flexion), thumb flexion, and simultaneous flexion of both fingers and thumb (grasping). For each task, subjects sustained isometric contractions at 5% and 15% of maximal voluntary contraction, while high-density surface electromyograms (HDsEMG) were recorded from the superficial extrinsic flexor muscles of the hand. Motor unit spike trains were decomposed from HDsEMG and tracked across tasks, and their mean discharge rate was calculated. Coherence between motor units was quantified within the delta, alpha, and beta bands to estimate common synaptic oscillations. At both force levels, the mean discharge rate decreased during grasping compared to four-finger flexion but increased during grasping compared to thumb flexion. Additionally, the area under the curve of coherence within the alpha band decreased by ~20% during grasping compared to the four-finger flexion task, with no significant delta or beta bands changes. These reductions in alpha band coherence were reflected in force oscillations, showing decreased force-neural drive coupling within the alpha band and increased force steadiness during grasping compared to four-finger flexion. Our findings suggest that a functionally relevant and frequently used grip involves distinct neural control mechanisms that ultimately enhance force control. | | 4:49p |
Isomerized Aβ in the brain can distinguish the status of amyloidosis in the Alzheimer's Disease spectrum
Extracellular amyloid plaques, the pathognomonic hallmark of Alzheimer's Disease (AD), are also observed in cognitively unimpaired subjects in the preclinical stages. Progressive accumulation of fibrillar amyloid-{beta} (A{beta}) as plaques and perivascular deposits occur two decades prior to clinical onset, making A{beta} a long-lived peptide. To characterize the amyloid plaques biochemically, both the A{beta} load as well the post-translational modifications (PTMs) could serve as markers for distinguishing the pre-clinical stage compared to later prodromal and clinical stages of AD. Recently, we described the presence of extensive isomerization of the A{beta} N-terminus in AD post-mortem brains that are significantly increased compared to the age-matched non-AD control brains with A{beta} aggregates in the frontal cortex. In this report, we used targeted mass spectrometry to conduct a quantitative analysis of the most common PTMs associated with A{beta} pyroglutamation, citrullination, N-terminal truncation (A{beta}4-x), C-terminal truncation (A{beta}42 and A{beta}40), and isomerization of aspartic acid residues (Asp-1 and Asp-7) in postmortem human brain tissue from pathologically negative (no A{beta} plaques) controls, controls with A{beta} plaques, Parkinson's disease (PD) with and without A{beta} accumulation/plaques and symptomatic AD. The AD cases contained statistically significant amounts of Asp-1and Asp-7 isomerized A{beta}1-15 (~ 90 %) compared to controls (preclinical AD) and PD brains with fibrillar A{beta} aggregates/deposits. We find that ratio of isomerized N-terminus A{beta} (A{beta}1-15) species in the brain detergent soluble pool differentiates older fibrillar A{beta} deposits in symptomatic AD brain compared to A{beta} deposits detected in preclinical AD and PD. Citrullinated A{beta}3pglu-15 was increased only in symptomatic AD, highlighting this A{beta} PTM is a unique feature of parenchymal plaques in advanced AD. Our results have implications for early therapeutic targeting of these modified species as well potential for better biofluid biomarker development for drug efficacy monitoring. |
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