An optimized acetylcholine sensor for monitoring in vivo cholinergic activity, bioRxiv, 2019-12-03
The ability to directly measure acetylcholine (ACh) release is an essential first step towards understanding its physiological function. Here we optimized the GRABACh (GPCR-Activation–Based-ACh) sensor with significantly improved sensitivity and minimal downstream coupling. Using this sensor, we measured in-vivo cholinergic activity in both Drosophila and mice, revealing compartmental ACh signals in fly olfactory center and single-trial ACh dynamics in multiple regions of the mice brain under a variety of different behaviors
biorxiv neuroscience 100-200-users 2019Spontaneous generation of face recognition in untrained deep neural networks, bioRxiv, 2019-12-02
AbstractFace-selective neurons are observed in the primate visual pathway and are considered the basis of facial recognition in the brain. However, it is debated whether this neuronal selectivity can arise spontaneously, or requires training from visual experience. Here, we show that face-selective neurons arise spontaneously in random feedforward networks in the absence of learning. Using biologically inspired deep neural networks, we found that face-selective neurons arise under three different network conditions one trained using non-face natural images, one randomized after being trained, and one never trained. We confirmed that spontaneously emerged face-selective neurons show the biological view-point-invariant characteristics observed in monkeys. Such neurons suddenly vanished when feedforward weight variation declined to a certain level. Our results suggest that innate face-selectivity originates from statistical variation of the feedforward projections in hierarchical neural networks.
biorxiv neuroscience 0-100-users 2019The frequency gradient of human resting-state brain oscillations follows cortical hierarchies, bioRxiv, 2019-11-28
AbstractThe human cortex is characterized by local morphological features such as cortical thickness, myelin content and gene expression that change along the posterior-anterior axis. We investigated if these structural gradients are associated with a similar gradient in a prominent feature of brain activity – namely the frequency of brain oscillations. In resting-state MEG recordings from healthy participants (N=187), we found that the strongest peak frequency in a brain area decreases significantly, gradually and robustly along the posterior-anterior axis following the global hierarchy from early sensory to higher-order areas. This spatial gradient of peak frequency was significantly anticorrelated with the cortical thickness of corresponding areas representing a proxy of the cortical hierarchical level. This result indicates that the intrinsic ‘resonance’ frequency decreases systematically from early sensory to higher-order areas and establishes a new structure-function relationship pertaining to brain oscillations as a core organizational principle that may underlie hierarchical specialization in the brain.
biorxiv neuroscience 100-200-users 2019Variability in the analysis of a single neuroimaging dataset by many teams, bioRxiv, 2019-11-16
SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.
biorxiv neuroscience 500+-users 2019Natural image reconstruction from brain waves a novel visual BCI system with native feedback, bioRxiv, 2019-10-02
AbstractHere we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naïve subjects because of the user-friendly and intuitive way the visual patterns are employed to modify the brain states.
biorxiv neuroscience 200-500-users 2019Molecular Atlas of the Adult Mouse Brain, bioRxiv, 2019-09-28
AbstractBrain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain organization based on unbiased extraction of spatially-defining features. Applying whole-brain spatial transcriptomics, we captured the gene expression signatures to define the spatial organization of molecularly discrete subregions. We found that the molecular code contained sufficiently detailed information to directly deduce the complex spatial organization of the brain. This unsupervised molecular classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and a new division of striatum. The whole-brain molecular atlas further supports the identification of the spatial origin of single neurons using their gene expression profile, and forms the foundation to define a minimal gene set - a brain palette – that is sufficient to spatially annotate the adult brain. In summary, we have established a new molecular atlas to formally define the identity of brain regions, and a molecular code for mapping and targeting of discrete neuroanatomical domains.
biorxiv neuroscience 200-500-users 2019