Top 10 Biorxiv Papers Today in Neuroscience


2.036 Mikeys
#1. A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals
Poomipat Boonyakitanont, Apiwat Lek-uthai, Krisnachai Chomtho, Jitkomut Songsiri
This paper aims to apply machine learning techniques to an automated epileptic seizure detection using EEG signals to help neurologists in a time-consuming diagnostic process. We employ two approaches based on convolution neural networks (CNNs) and artificial neural networks (ANNs) to provide a probability of seizure occurrence in a windowed EEG recording of 18 channels. In order to extract relevant features based on time, frequency, and time-frequency domains for these networks, we consider an improvement of the Bayesian error rate from a baseline. Features of which the improvement rates are higher than the significant level are considered. These dominant features extracted from all EEG channels are concatenated as the input for ANN with 7 hidden layers, while the input of CNN is taken as raw multi-channel EEG signals. Using multi-concept of deep CNN in image processing, we exploit 2D-filter decomposition to handle the signal in spatial and temporal domains. Our experiments based on CHB-MIT Scalp EEG Database showed that both ANN...
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biorxiv_neursci: A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals https://t.co/3dvanEeJam #biorxiv_neursci
biorxivpreprint: A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals https://t.co/t2yaYBvOl4 #bioRxiv
matteo_brainnet: RT @biorxiv_neursci: A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals https://t.co/3dvanEeJam #biorxiv_neursci
zuxfoucault: RT @biorxiv_neursci: A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals https://t.co/3dvanEeJam #biorxiv_neursci
poppingjun: RT @biorxiv_neursci: A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals https://t.co/3dvanEeJam #biorxiv_neursci
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Authors: 4
Total Words: 4740
Unqiue Words: 1746

2.035 Mikeys
#2. Egocentric boundary vector tuning of the retrosplenial cortex
Andrew Alexander, Lucas Carstensen, James Hinman, Florian Raudies, G. William Chapman, Michael Hasselmo
The retrosplenial cortex is reciprocally connected with a majority of structures implicated in spatial cognition and damage to the region itself produces numerous spatial impairments. However, in many ways the retrosplenial cortex remains understudied. Here, we sought to characterize spatial correlates of neurons within the region during free exploration in two-dimensional environments. We report that a large percentage of retrosplenial cortex neurons have spatial receptive fields that are active when environmental boundaries are positioned at a specific orientation and distance relative to the animal itself. We demonstrate that this vector-based location signal is encoded in egocentric coordinates, localized to the dysgranular retrosplenial sub-region, independent of self-motion, and context invariant. Further, we identify a sub-population of neurons with this response property that are synchronized with the hippocampal theta oscillation. Accordingly, the current work identifies a robust egocentric spatial code in retrosplenial...
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biorxiv_neursci: Egocentric boundary vector tuning of the retrosplenial cortex https://t.co/sjJr7gEflw #biorxiv_neursci
biorxivpreprint: Egocentric boundary vector tuning of the retrosplenial cortex https://t.co/m7LayMNI6o #bioRxiv
tom_hartley: RT @biorxiv_neursci: Egocentric boundary vector tuning of the retrosplenial cortex https://t.co/sjJr7gEflw #biorxiv_neursci
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Authors: 6
Total Words: 0
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2.033 Mikeys
#3. Collaborative Cross Mouse Populations as a Resource for the Study of Epilepsy
Bin Gu, John R Shorter, Lucy H Williams, Timothy A Bell, Pablo Hock, Katherine A Dalton, YIYUN PAN, Darla R Miller, Ginger D Shaw, Brian C Cooley, Ben D Philpot, Fernando Pardo Manuel de Villena
Epilepsy is a neurological disorder with complex etiologies and genetic architecture. Animal models have a critical role in understanding the pathophysiology of epilepsy. Here we studied epilepsy utilizing a genetic reference population of Collaborative Cross (CC) mice with publicly available whole genome sequences. We measured multiple epilepsy traits in 35 CC strains, and we identified novel animal models that exhibit extreme outcomes in seizure susceptibility, seizure propagation, epileptogenesis, and sudden unexpected death in epilepsy. We performed QTL mapping in an F2 population and identified seven novel and one previously identified loci associated with seizure sensitivity. We combined whole genome sequence and hippocampal gene expression to pinpoint biologically plausible candidate genes and candidate variants associated with seizure sensitivity. These resources provide a powerful toolbox for studying complex features of seizures and for identifying genes associated with particular seizure outcomes, and hence will...
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biorxiv_neursci: Collaborative Cross Mouse Populations as a Resource for the Study of Epilepsy https://t.co/6tWXQsocgp #biorxiv_neursci
biorxivpreprint: Collaborative Cross Mouse Populations as a Resource for the Study of Epilepsy https://t.co/VIHgHxlvNo #bioRxiv
LalDennis: RT @biorxivpreprint: Collaborative Cross Mouse Populations as a Resource for the Study of Epilepsy https://t.co/VIHgHxlvNo #bioRxiv
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Authors: 12
Total Words: 0
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2.027 Mikeys
#4. Adult-born hippocampal neurons undergo extended development and are morphologically distinct from neonatally-born neurons
John Darby Cole, Delane Espinueva, Desiree R Seib, Matthew B Cooke, Shaina P Cahill, Timothy O'Leary, Sharon S Kwan, Jason S Snyder
During immature stages, adult-born neurons pass through critical periods for survival and plasticity. It is generally assumed that by 2 months of age adult-born neurons are mature and equivalent to the broader neuronal population, raising questions of how they might contribute to hippocampal function in old age when neurogenesis has declined. However, few have examined older adult-born neurons, or directly compared them to neurons born in infancy. Here, we used a retrovirus to visualize functionally-relevant morphological features of 2- to 24-week-old adult-born neurons in the rat. Two-week-old neurons had a high proportion of dendritic filopodia, small presynaptic terminals and an overproduction of distal dendritic branches that were later pruned, collectively indicating immaturity. From 2-7 weeks neurons grew and attained a relatively mature phenotype. However, several features of 7-week-old neurons suggested a later wave of growth: these neurons had larger nuclei, thicker dendrites and more dendritic filopodia than all other...
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biorxiv_neursci: Adult-born hippocampal neurons undergo extended development and are morphologically distinct from neonatally-born neurons https://t.co/xGyelE6l3S #biorxiv_neursci
biorxivpreprint: Adult-born hippocampal neurons undergo extended development and are morphologically distinct from neonatally-born neurons https://t.co/YrHDU2MelK #bioRxiv
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Authors: 8
Total Words: 16091
Unqiue Words: 3760

2.027 Mikeys
#5. Frontoparietal network dynamics impairments in juvenile myoclonic epilepsy revealed by MEG energy landscape
Dominik Krzeminski, Naoki Masuda, Khalid Hamandi, Krish D Singh, Bethany Routley, Jiaxiang Zhang
Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy affecting brain activity. It is unclear to what extent JME leads to abnormal network dynamics across functional networks. Here, we proposed a method to characterise network dynamics in MEG resting-state data, combining a pairwise maximum entropy model (pMEM) and the associated energy landscape analysis. Fifty-two JME patients and healthy controls underwent a resting-state MEG recording session. We fitted the pMEM to the oscillatory power envelopes in theta (4-7 Hz), alpha (8-13 Hz), beta (15-25 Hz) and gamma (30-60 Hz) bands in three source-localised resting-state networks: the frontoparietal network (FPN), the default mode network (DMN), and the sensorimotor network (SMN). The pMEM provided an accurate fit to the MEG oscillatory activity in both patient and control groups, and allowed estimation of the occurrence probability of each network state, with its regional activity and pairwise regional co-activation constrained by empirical data. We used...
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biorxiv_neursci: Frontoparietal network dynamics impairments in juvenile myoclonic epilepsy revealed by MEG energy landscape https://t.co/i477oclZ4C #biorxiv_neursci
biorxivpreprint: Frontoparietal network dynamics impairments in juvenile myoclonic epilepsy revealed by MEG energy landscape https://t.co/MdoJbcFbv9 #bioRxiv
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Authors: 6
Total Words: 0
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2.018 Mikeys
#6. A computational knowledge engine for human neuroscience
Elizabeth Beam, Christopher Potts, Russell A. Poldrack, Amit Etkin
Functional neuroimaging has been a mainstay of human neuroscience for the past 25 years. The goal for this research has largely been to understand how activity across brain structures relates to mental constructs and computations. However, interpretation of fMRI data has often occurred within knowledge frameworks crafted by experts, which have the potential to reify historical trends and amplify the subjective biases that limit the replicability of findings. In other words, we lack a comprehensive data-driven ontology for structure-function mapping in the human brain, through which we can also test the explanatory value of current dominant conceptual frameworks. Ontologies in other fields are popular tools for automated data synthesis, yet relatively few attempts have been made to engineer ontologies in a data-driven manner. Here, we employ a computational approach to derive a data-driven ontology for neurobiological domains that synthesizes the texts and data of nearly 20,000 human neuroimaging articles. The data-driven ontology...
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MarinaP63: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
woodforbrains: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
IM_Inman: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
NeuroSyntheSys: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
zuxfoucault: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
JoshuaHendrikse: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
Coka_Hoo: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
poppingjun: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
yuuyuuyuuyuu10: RT @biorxiv_neursci: A computational knowledge engine for human neuroscience https://t.co/idewBSPLv8 #biorxiv_neursci
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Sample Sizes : [1816]
Authors: 4
Total Words: 9299
Unqiue Words: 2195

2.012 Mikeys
#7. Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent outcomes in a rat model of early life adversity
Jennifer A Honeycutt, Camila Demaestri, Shayna Peterzell, Marisa M Silveri, Xuezhu Cai, Praveen Kulkarni, Miles G Cunningham, Craig F Ferris, Heather C Brenhouse
Background: Adverse early experiences significantly alter behavioral and neural trajectories via aberrant brain maturation. Children with a history of early life stress (ELS) exhibit maladaptive behaviors and increased risk of mental illness later in life. Evidence in ELS-exposed humans identifies a role of atypical corticolimbic development; specifically, within amygdala-prefrontal cortex (PFC) circuits, and show precocially mature corticolimbic functional connectivity (FC). However, the neurobiological substrates of such ELS-driven developmental changes remain unknown. Here, we identify putative neurobiological changes to determine the timeline of developmental perturbations following ELS in rats. Methods: Anterograde axonal tracing from basolateral amygdala (BLA) to pre- and infralimbic (PL, IL) PFC was quantified at postnatal days (PD)28, 38, and 48, along with anxiety-like behavior, in maternally separated (ELS) or control reared (CON) male and female rats. Resting state (rs)FC was assessed at PD28 and PD48 in a separate...
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biorxiv_neursci: Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent ... https://t.co/lacyJ1iqIM #biorxiv_neursci
biorxivpreprint: Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent outcomes in a rat model of early life adversity https://t.co/rr1pfTuFLr #bioRxiv
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2.012 Mikeys
#8. Effects of hM4Di activation in CamKII basolateral amygdala neurons and CNO treatment on Sensory-Specific vs. General-PIT; refining PIT circuits and considerations for using CNO.
Rifka C Derman, Caroline E Bass, Carrie Ferrario
Pavlovian stimuli can influence instrumental behaviors, a phenomenon known as Pavlovian-to-instrumental transfer (PIT). PIT arises via psychologically and neurobiologically independent processes as Sensory-Specific-PIT (SS-PIT) and General-PIT. SS-, but not General-PIT, relies on the basolateral amygdala (BLA), however the specific BLA neuronal populations involved are unknown. Therefore, here we determined the contribution of glutamatergic BLA neurons to SS-PIT. The BLA was transduced with virus containing either GFP or hM4Di, driven by the CamKII promoter. Rats were then tested for SS- and General-PIT following Vehicle or Clozapine-n-oxide (CNO, the hM4Di-activating ligand) injection. CNO had no effect on SS-PIT in the GFP control group, but selectively blocked its expression in the hM4Di-expressing group. Furthermore, CNO did not alter the expression of Pavlovian outcome devaluation effects in GFP or hM4Di expressing groups, indicating that the hM4Di-mediated loss of SS-PIT did not result from an inability to recall the...
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biorxiv_neursci: Effects of hM4Di activation in CamKII basolateral amygdala neurons and CNO treatment on Sensory-Specific vs. General-PIT; refining ... https://t.co/URZd1mN8TP #biorxiv_neursci
biorxivpreprint: Effects of hM4Di activation in CamKII basolateral amygdala neurons and CNO treatment on Sensory-Specific vs. General-PIT; refining PIT circuits and considerations for using CNO. https://t.co/PnivR4Kp9g #bioRxiv
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2.012 Mikeys
#9. Maternal antioxidant treatment prevents behavioural and neural changes in offspring exposed to prenatal social stress
Hannah Scott, Thomas J Phillips, Ying Sze, Alessio Alfieri, Mark F Rogers, Charles Patrick Case, Paula J Brunton
Maternal exposure to social stress during pregnancy is associated with an increased risk of psychiatric disorders in the offspring in later life. However, the mechanism through which the effects of maternal stress are transmitted to the foetus is unclear. Using a rat model, we explored the mechanisms by which maternal social stress is conveyed to the foetus and the potential for targeted treatment to prevent disease in the offspring. Maternal stress increased circulating corticosterone in the mother, but not the foetuses. Maternal stress also induced oxidative stress in the placenta, but not in the foetal brain, and this was prevented by administration of a nanoparticle-bound antioxidant. Moreover, antioxidant treatment prevented prenatal stress-induced anxiety-like behaviour in the adult male offspring, along with several stress-induced neuroanatomical, neurochemical and gene expression changes in the offspring brain. Importantly, many of these neural effects were mimicked in neuronal cultures by application of...
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biorxiv_neursci: Maternal antioxidant treatment prevents behavioural and neural changes in offspring exposed to prenatal social stress https://t.co/4Dji5n5Gwn #biorxiv_neursci
biorxivpreprint: Maternal antioxidant treatment prevents behavioural and neural changes in offspring exposed to prenatal social stress https://t.co/oGdJr6zNXd #bioRxiv
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Authors: 7
Total Words: 13924
Unqiue Words: 3623

2.012 Mikeys
#10. Optimized visual stimuli for BCI with hessenberg decomposition based extreme learning machine
Apdullah Yayık, Yakup Kutlu, Gokhan Altan
Background and Objectives: Brain-computer interfaces (BCIs) aim to provide neuroscientific communication platform for human-beings, in particular locked-in patients. In most cases event-related potentials (ERPs), averaged voltage responses to a specific target stimuli over time, have key roles in designing BCIs. With this reason, for the last several decades BCI researchers heavily have focused on signal processing methods to improve quality of ERPs. However, designing visual stimulus with considering their physical properties with regard to rapid and also reliable machine learning algorithms for BCIs remain relatively unexplored. Addressing the issues explained above, in summary the main contributions of this study are as follows: (1) optimizing visual stimulus in terms of size, color and background and, (2) to enhance learning capacity of conventional extreme learning machine (ELM) using advanced linear algebra techniques. Methods: Two different sized (small and big), three different colored (blue, red and colorful) images with...
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biorxiv_neursci: Optimized visual stimuli for BCI with hessenberg decomposition based extreme learning machine https://t.co/HzZDhcL3Az #biorxiv_neursci
biorxivpreprint: Optimized visual stimuli for BCI with hessenberg decomposition based extreme learning machine https://t.co/g3jxCzvNG2 #bioRxiv
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