Biology subjects

Shigihara, Y.

Publications and source records attributed to Shigihara, Y..

4 recordsLinked to original sources

bioRxiv2025

OddSNP: a predictive framework for optimizing multiplexed single-cell RNA-seq experiments

Donor multiplexing is a powerful strategy to increase scale, lower the costs, and reduce batch effects in single-cell RNA sequencing (scRNAseq), but clear guidelines for experimental design are lacking, forcing researchers to risk costly demultiplexing failures. To address this, we introduce SNP-Information Content (SNP-IC), a quantitative metric computable from simple unpooled pilot data that accurately predicts the success of genotype-based demultiplexing. Across multiple large-scale datasets using stem cell and organoid models, we establish a robust SNP-IC threshold of approximately 50, above which cells can be reliably assigned to their donor of origin. For more challenging genotype-free approaches, we define a pairwise metric, cpSNP-IC, and demonstrate a much higher requirement of approximately 3,000. Our open-source framework, oddSNP, implements this predictive model, allowing researchers to perform in silico titrations of sequencing depth and donor complexity to optimize experimental design before committing to large-scale studies. oddSNP provides a practical framework, enabling researchers to strategically optimize sequencing depth and donor numbers to maximize experimental success while managing costs and minimizing the risk of catastrophic data loss.

bioinformatics↗

bioRxiv2023

Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses

The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study, we introduce a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network. The resting-state neural activity of 195 cognitively healthy subjects from three different databases (MEG: 123 subjects; EEG1: 27 subjects; EEG2: 45 subjects) was analysed. In a first step, MEG and EEG signals were filtered with a narrow-band filter bank (1 Hz bandwidth) from 1 to 70 Hz with a 0.5 Hz step. Next, the connectivity in each of these filtered signals was estimated using the orthogonalized version of the amplitude envelope correlation to obtain the frequency-dependent functional neural network. Finally, a community detection algorithm was used to identify communities in the frequency domain showing a similar network topology. We have called this approach the "Connectivity-based Meta-Bands" (CMB) algorithm. Additionally, two types of synthetic signals were used to configure the hyper-parameters of the CMB algorithm. We observed that the classical approaches to band segmentation reflect the underlying network topologies at group level for the MEG signals, but they fail to adapt to the individual differentiating patterns revealed by our methodology. On the other hand, the sensitivity of EEG signals to reflect this underlying frequency-dependent network structure is limited. To the best of our knowledge, this is the first study that proposes an unsupervised band segmentation method based on the topological similarity of functional neural network across frequencies. This methodology fully accounts for subject-specific patterns, providing more robust and personalized analyses, and paving the way for new studies focused on exploring the frequency-dependent structure of brain connectivity.

bioinformatics↗

bioRxiv2020

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Traditional magnetoencephalographic (MEG) brain imaging scanners consist of a rigid sensor array surrounding the head; this means that they are maximally sensitive to superficial brain structures. New technology based on optical pumping means that we can now consider more flexible and creative sensor placement. Here we explored the magnetic fields generated by a model of the human hippocampus not only across scalp but also at the roof of the mouth. We found that simulated hippocampal sources gave rise to dipolar field patterns with one scalp surface field extremum at the temporal lobe and a corresponding maximum or minimum at the roof of the mouth. We then constructed a fitted dental mould to accommodate an Optically Pumped Magnetometer (OPM). We collected data using a previously validated hippocampal-dependent task to test the empirical utility of a mouth-based sensor, with an accompanying array of left and right temporal lobe OPMs. We found that the mouth sensor showed the greatest task-related theta power change. We also found that, as predicted by the simulations, the mouth sensor was anti-correlated with those on over the temporal lobes. We found that this sensor had a mild effect on the reconstructed power in the hippocampus (~10% change) but that coherence images between the mouth sensor and reconstructed source images showed a global maximum in the right hippocampus. We conclude that augmenting a scalp-based MEG array with sensors in the mouth shows unique promise for both basic scientists and clinicians interested in interrogating the hippocampus.

neuroscience↗

bioRxiv2017

Very Early Responses to Colour Stimuli Detected in Prestriate Visual Cortex by Magnetoencephalography (MEG)

Previous studies with the visual motion and form systems show that visual stimuli belonging to these categories trigger much earlier latency responses from the visual cortex than previously supposed and that the source of the earliest signals can be located in either the prestriate cortex or in both the striate (V1) and prestriate cortex. This is consistent with the known anatomical connections since, in addition to the classical retino-geniculo-striate cortex input, there are direct anatomical inputs from both the lateral geniculate nucleus and the pulvinar that reach the prestriate visual cortex without passing through V1. In pursuing our studies, we thought it especially interesting to study another cardinal visual attribute, namely colour, to learn whether colour stimuli also provoke very early responses, at less than 50 ms, from visual cortex. To address the question, we asked participants to view stimuli that changed in colour and used magneto-encephalography to detect very early responses (< 50 ms) in the occipital visual cortex. Our results show that coloured stimuli also provoke an early cortical response (M30), with an average peak time at 30.8 ms, thus bringing the colour system into line with the visual motion and form systems. We conclude that colour signals reach visual cortex, including prestriate visual cortex, earlier than previously supposed.\n\nKey points summaryO_LIWe measured visual evoked responses to colour stimuli using magnetoencephalography.\nC_LIO_LIAn early response was identified, at around 30 ms after stimulation.\nC_LIO_LIThe sources of the response were estimated to be in prestriate cortex.\nC_LIO_LIColour signals thus appear to evoke very early cortical responses, just like form and motion signals.\nC_LI\n\nAbbreviations list

neuroscience↗