Top 10 Biorxiv Papers Today in Neuroscience


2.074 Mikeys
#1. BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain
Deniz Kumral, Firat Sansal, Elena Cesnaite, Keyvan Mahjoory, Esra Al, Michael Gaebler, Vadim V Nikulin, Arno Villringer
Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability − identified with either hemodynamic or electrophysiological methods − reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25±3 years, N=135) and older (67±4 years, N=54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1−12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode...
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biorxivpreprint: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/hkQieiMbXf #bioRxiv
biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorxiv_neursci
woodforbrains: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
danieltomasz: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
DVSneuro: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
Sc1naps: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
dixy0: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
karimjerbineuro: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
BrainHealthNW: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
ivanoras: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
CuriousMZD: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
Pascual_Marqui: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
johnmvore: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
izzetborakis: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
Aykut__Eken: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
LKhenissi: RT @biorxiv_neursci: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/1NmXa6ZFVy #biorx…
sbotlite: RT @biorxivpreprint: BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain https://t.co/hkQieiMbXf #bioRx…
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Authors: 8
Total Words: 0
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2.025 Mikeys
#2. Biological Aging in Childhood and Adolescence Following Experiences of Threat and Deprivation: A Systematic Review and Meta-Analysis
Natalie L Colich, Maya L Rosen, Eileen S Williams, Katie A McLaughlin
Life history theory argues that exposure to early-life adversity (ELA) accelerates development, although existing evidence for this varies. We present a meta-analysis and systematic review testing the hypothesis that ELA involving threat (e.g., violence exposure) will be associated with accelerated biological aging across multiple metrics, whereas exposure to deprivation (e.g., neglect, institutional rearing) and low-socioeconomic status (SES) will not. We meta-analyze 46 studies (n=64,925) examining associations of ELA with pubertal timing and cellular aging (telomere length and DNA methylation age), systematically review 19 studies (n=2276) examining ELA and neural markers of accelerated development (cortical thickness and amygdala-prefrontal cortex functional connectivity) and evaluate whether associations of ELA with biological aging vary according to the nature of adversity experienced. ELA overall was associated with accelerated pubertal timing (d=-0.12) and cellular aging (d=-0.32). Moderator analysis revealed that ELA...
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biorxivpreprint: Biological Aging in Childhood and Adolescence Following Experiences of Threat and Deprivation: A Systematic Review and Meta-Analysis https://t.co/pfGyttWDV6 #bioRxiv
biorxiv_neursci: Biological Aging in Childhood and Adolescence Following Experiences of Threat and Deprivation: A Systematic Review and Meta-Analysis https://t.co/MAqcisIXRx #biorxiv_neursci
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Authors: 4
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2.02 Mikeys
#3. Loss of the Alzheimer's-linked bridging integrator 1 (BIN1) protein affects synaptic structure and disrupts tau localisation and release
Elizabeth B Glennon, Dawn H-W Lau, Rebecca M.C. Gabriele, Matthew F Taylor, Claire Troakes, Christina Elliott, Richard Killick, Diane P Hanger, Beatriz G Perez-Nievas, Wendy Noble
Background: Post-translational modifications of tau modify its interaction with binding partners and cause tau mislocalisation and altered tau function in Alzheimer's disease (AD). The AD risk gene BIN1, is a binding partner for tau, however the mechanism by which BIN1 influences tau function is not fully understood. We hypothesised that BIN1 modulates AD risk by causing damaging tau mis-sorting to the synapse. Methods: Tau and BIN1 levels, distribution and interactions were assessed in post-mortem control and AD brain and in primary neurons. In primary neurons, tau was further examined using structured illumination microscopy and immunoblotting following BIN1 knockdown, BIN1-tau interactions were examined using proximity ligation assays and tau release from neurons was measured by sensitive sandwich ELISA. Results: Proline 216 in tau was identified as critical for tau interaction with the BIN1-SH3 domain, and tau phosphorylation at serine/threonine residues disrupted this interaction. Subcellular fractionation showed that BIN1 is...
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biorxivpreprint: Loss of the Alzheimer's-linked bridging integrator 1 (BIN1) protein affects synaptic structure and disrupts tau localisation and release https://t.co/cf3Z2i2AQ5 #bioRxiv
biorxiv_neursci: Loss of the Alzheimer's-linked bridging integrator 1 (BIN1) protein affects synaptic structure and disrupts tau localisation and release https://t.co/GaOY2UHiAG #biorxiv_neursci
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Authors: 10
Total Words: 10385
Unqiue Words: 2932

2.018 Mikeys
#4. Separability and Geometry of Object Manifolds in Deep Neural Networks
Uri Cohen, SueYeon Chung, Daniel D Lee, Haim Sompolinsky
Stimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural population responses called an 'object manifold.' Changes in the object representation along a hierarchical sensory system are associated with changes in the geometry of those manifolds, and recent theoretical progress connects this geometry with 'classification capacity,' a quantitative measure of the ability to support object classification. Deep neural networks trained on object classification tasks are a natural testbed for the applicability of this relation. We show how classification capacity improves along the hierarchies of deep neural networks with different architectures. We demonstrate that changes in the geometry of the associated object manifolds underlie this improved capacity, and shed light on the functional roles different levels in the hierarchy play to achieve it, through orchestrated reduction of manifolds' radius, dimensionality...
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biorxivpreprint: Separability and Geometry of Object Manifolds in Deep Neural Networks https://t.co/CHD3UjC31t #bioRxiv
biorxiv_neursci: Separability and Geometry of Object Manifolds in Deep Neural Networks https://t.co/vzQEutfmMT #biorxiv_neursci
SiaAhmadi1: RT @biorxiv_neursci: Separability and Geometry of Object Manifolds in Deep Neural Networks https://t.co/vzQEutfmMT #biorxiv_neursci
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Authors: 4
Total Words: 11491
Unqiue Words: 2737

2.018 Mikeys
#5. A freely available, self-calibrating software for automatic measurement of freezing behavior
Felippe E. Amorim, Thiago C. Moulin, Olavo B. Amaral
Freezing behavior is commonly used as a measure of associative fear memory. It can be measured by a trained observer, but this task is time-consuming and subject to variation. Commercially available software packages can also be used to quantify freezing; however, they can be expensive and usually require various parameters to be adjusted by the researcher, leading to additional work and variability in results. With this in mind, we developed Phobos, a freely available, self-calibrating software that measures freezing in a set of videos using a brief manual quantification performed by the user to automatically adjust parameters. To optimize the software, we used four different video sets with different features in order to determine the most relevant parameters, the amount of videos needed for calibration and the minimum criteria to consider it reliable. The results of four different users were compared in order to test intra- and interobserver variability in manual and automated freezing scores. Our results suggest that Phobos...
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poppingjun: RT @biorxiv_neursci: A freely available, self-calibrating software for automatic measurement of freezing behavior https://t.co/1TWQhIEPsv…
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Repository: Phobos
User: Felippe-espinelli
Language: MATLAB
Stargazers: 0
Subscribers: 0
Forks: 0
Open Issues: 0
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Sample Sizes : [122, 25, 35, 13, 15, 14, 12]
Authors: 3
Total Words: 7373
Unqiue Words: 1713

2.015 Mikeys
#6. Expression of c-Fos and Arc in hippocampal region CA1 marks neurons that exhibit learning-related activity changes
David Mahringer, Anders V Petersen, Aris Fiser, Hiroyuki Okuno, Haruhiko Bito, Jean-Francois Perrier, Georg B Keller
Immediate early genes (IEGs) are transcribed in response to neural activity and necessary for many forms of plasticity. However, the dynamics of their expression during learning, as well as their relationship to neural activity, remain unclear. Here we used two-photon imaging in transgenic mice that express a GFP-tagged variant of Arc or c-Fos and a red-shifted calcium indicator to measure learning-related changes in IEG expression levels and neural activity in hippocampal region CA1 as mice learned to perform a two-alternative forced choice task. Neural activity levels correlated positively with IEG expression levels in vivo. In addition, we found that with learning, a subset of neurons in CA1 increased their responses to the reward-predicting cue, and IEG expression levels early in learning were selectively increased in neurons that would exhibit the strongest learning-related changes. Our findings are consistent with an interpretation of IEG expression levels as markers for experience dependent plasticity.
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biorxivpreprint: Expression of c-Fos and Arc in hippocampal region CA1 marks neurons that exhibit learning-related activity changes https://t.co/vqh3KYrMaY #bioRxiv
biorxiv_neursci: Expression of c-Fos and Arc in hippocampal region CA1 marks neurons that exhibit learning-related activity changes https://t.co/cqsHzj5gvR #biorxiv_neursci
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Authors: 7
Total Words: 9514
Unqiue Words: 2974

2.013 Mikeys
#7. Novel Strategies for Glutamate Clearance in the Glia-Deprived Synaptic Hub of C. elegans
Joyce Chan, Kirsten KyungHwa Lee, Jenny Chan Ying Wong, Paola Morocho, Itzhak Mano
Brain function requires the ability to form neuronal circuits that mediate focused and accurate communication. Since the vast majority of brain synapses use Glutamate (Glu) as their neurotransmitter, unintended spillover of Glu between adjacent synapses is a critical challenge. To ensure accurate neurotransmission and avert synaptic mix-up, specialized Glu Transporters (GluTs) clear the synapse of released Glu. While classical views of neuronal morphology and physiology depict isolated spiny synapses enwrapped by GluT-expressing glia, in reality, a considerable portion of synapses are flat, glial coverage in some parts of the brain is rather sparse, and extracellular space is larger than previously estimated. This suggests that diffusion in interstitial fluids might have an important role in Glu clearance in these synapses. To understand basic principles of Glu clearance in flat-, glia-deprived synapses, we study the physiology of neuronal circuits in the C. elegans nerve ring, the nematode's aspiny synaptic hub. We use behavioral...
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biorxivpreprint: Novel Strategies for Glutamate Clearance in the Glia-Deprived Synaptic Hub of C. elegans https://t.co/bppSX3uakH #bioRxiv
biorxiv_neursci: Novel Strategies for Glutamate Clearance in the Glia-Deprived Synaptic Hub of C. elegans https://t.co/l7h6j473i1 #biorxiv_neursci
poppingjun: RT @biorxivpreprint: Novel Strategies for Glutamate Clearance in the Glia-Deprived Synaptic Hub of C. elegans https://t.co/bppSX3uakH #bio…
sbotlite: RT @biorxivpreprint: Novel Strategies for Glutamate Clearance in the Glia-Deprived Synaptic Hub of C. elegans https://t.co/bppSX3uakH #bio…
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Authors: 5
Total Words: 14058
Unqiue Words: 4473

2.013 Mikeys
#8. Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates
Nicole Eichert, Emma C. Robinson, Katherine L. Bryant, Saad Jbabdi, Mark Jenkinson, Longchuan Li, Kristine Krug, Kate E. Watkins, Rogier B. Mars
Evolutionary adaptations can affect different aspects of brain architecture, including areal expansion, relocation, or changes in connectivity profiles. Distinguishing between different types of reorganization is critical for our understanding of brain evolution. We propose to address this using a computational neuroanatomy approach. We investigate the extent to which between-species cortical alignment based on myelin can predict changes in connectivity patterns across macaque, chimpanzee and human brains. We show that expansion and relocation of brain areas as predicted by the myelin-based alignment are sufficient to predict reorganization of several white matter tracts and their terminations in temporal, frontal and parietal cortex. A notable exception is the arcuate fasciculus, in which we found extensive tract expansion into new territories that cannot be explained by cortical expansion. The presented approach can flexibly be extended to include other features of cortical organization and other species, which allows us to...
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biorxivpreprint: Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates https://t.co/eQPHok2cMp #bioRxiv
biorxiv_neursci: Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates https://t.co/or3qd6SXSQ #biorxiv_neursci
PromPreprint: Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates https://t.co/VeUnMlA4rZ
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Sample Sizes : [4421, 1053, 25, 3, 20155, 3, 25155, 3, 25, 3, 1053, 3, 25105, 3, 25105, 3]
Authors: 9
Total Words: 10825
Unqiue Words: 2682

2.012 Mikeys
#9. An oscillator ensemble model of sequence learning
Alexander Maye, Peng Wang, Jonathan Daume, Xiaolin Hu, Andreas K. Engel
Learning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral \`fingerprint' which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this \`fingerprint' by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of...
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biorxivpreprint: An oscillator ensemble model of sequence learning https://t.co/LKXFE7G1Gq #bioRxiv
biorxiv_neursci: An oscillator ensemble model of sequence learning https://t.co/sjd65ylypq #biorxiv_neursci
_AndyAlexander: RT @biorxiv_neursci: An oscillator ensemble model of sequence learning https://t.co/sjd65ylypq #biorxiv_neursci
neuro_ara: RT @biorxiv_neursci: An oscillator ensemble model of sequence learning https://t.co/sjd65ylypq #biorxiv_neursci
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Authors: 5
Total Words: 8919
Unqiue Words: 2553

2.009 Mikeys
#10. Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations
Maxime Van Egroo, Justinas Narbutas, Daphne Chylinski, Pamela Villar González, Pouya Ghaemmaghami, Vincenzo Muto, Christina Schmidt, Giulia Gaggioni, Gabriel Besson, Xavier Pépin, Elif Tezel, Davide Marzoli, Caroline Le Goff, Etienne Cavalier, André Luxen, Eric Salmon, Pierre Maquet, Mohamed A Bahri, Christophe Phillips, Christine Bastin, Fabienne Collette, Gilles Vandewalle
Age-related cognitive decline is rooted in alterations in brain integrity as well as in sleep-wake regulation. Here, we investigated whether preserved sleep-wake regulation of cortical function during wakefulness could represent a positive factor for cognitive fitness in aging, independently of early age-related alterations in brain structure associated with Alzheimer's disease neuropathology. We quantified slow waves generation during sleep and cortical excitability dynamics during prolonged wakefulness as sensitive markers of age-related alteration in sleep-wake regulation in 60 healthy late middle-aged individuals (50-69y; 42 women). We evaluated brain integrity with amyloid-beta-PET and tau-PET, and with MRI. Participants' cognition was extensively assessed. We first confirm that sleep slow waves generation is associated with amyloid-beta burden. Although cortical excitability dynamics during wakefulness is related to sleep slow waves, it is not associated with amyloid-beta nor with tau burden. We further show that individuals...
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biorxivpreprint: Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations https://t.co/DWhwBRFA6X #bioRxiv
biorxiv_neursci: Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations https://t.co/0btZvUrtKJ #biorxiv_neursci
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Authors: 22
Total Words: 10201
Unqiue Words: 2990

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