Top 10 Biorxiv Papers Today in Neuroscience


2.609 Mikeys
#1. Complex spikes encode reward expectation signals during visuomotor association learning
Naveen Sendhilnathan, Anna E Ipata, Michael E Goldberg
Climbing fiber input to Purkinje cells has been thought to instruct learning related changes in simple spikes and cause behavioral changes through an error-based learning mechanism. Although, this framework explains simple motor learning, it cannot be extended to learning higher-order skills. Recently the cerebellum has been implicated in a variety of cognitive tasks and reward-based learning. Here we show that when a monkey learns a new visuomotor association, complex spikes predict the time of the beginning of the trial in a learning independent manner as well as encode a learning contingent reward expectation signal after the stimulus onset and reward delivery. These complex spike signals are unrelated to and were unlikely to instruct the reward based signal found in the simple spikes. Our results provide a more general role of complex spikes in learning and higher-order processing while gathering evidence for their participation in reward based learning.
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biorxiv_neursci: Complex spikes encode reward expectation signals during visuomotor association learning https://t.co/9c2qFFBrLs #biorxiv_neursci
biorxivpreprint: Complex spikes encode reward expectation signals during visuomotor association learning https://t.co/rp3truOLKs #bioRxiv
NeuroLuyckx: RT @biorxiv_neursci: Complex spikes encode reward expectation signals during visuomotor association learning https://t.co/9c2qFFBrLs #bior…
geewhiz_ephys: RT @biorxiv_neursci: Complex spikes encode reward expectation signals during visuomotor association learning https://t.co/9c2qFFBrLs #bior…
yasuyotanaka: RT @biorxiv_neursci: Complex spikes encode reward expectation signals during visuomotor association learning https://t.co/9c2qFFBrLs #bior…
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2.268 Mikeys
#2. Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance
Cody Baker, Vicky Zhu, Robert Rosenbaum
Balanced excitation and inhibition is widely observed in cortical recordings. How does this balance shape neural computations and stimulus representations? This problem is often studied using computational models of neuronal networks in a dynamically balanced state. However, these balanced network models predict a linear relationship between stimuli and population responses, in contrast to the nonlinearity of cortical computations. We show that every balanced network architecture admits some stimuli that break the balanced state and these breaks in balance push the network into a ''semi-balanced state'' characterized by excess inhibition to some neurons, but an absence of excess excitation. The semi-balanced state is unavoidable in networks driven by multiple stimuli, is more consistent with experimental data, has a direct mathematical relationship to artificial neural networks, and permits nonlinear stimulus representations and nonlinear computations.
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biorxiv_neursci: Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance https://t.co/s5t2Y3aeqy #biorxiv_neursci
biorxivpreprint: Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance https://t.co/ZuTHtQUkob #bioRxiv
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2.268 Mikeys
#3. Disruption of relapse to alcohol seeking by aversive counterconditioning following memory retrieval
Koral Goltseker, Hen Handrus, Segev Barak
Relapse to alcohol abuse is often caused by exposure to potent alcohol-associated cues. Therefore, disruption of the cue-alcohol memory can prevent relapse. It is believed that memories destabilize and become prone for updating upon their reactivation through retrieval, and then re-stabilize within 6 h during a reconsolidation process. We recently showed that relapse to cocaine seeking could be prevented by counterconditioning the cocaine-cues with aversive outcomes following cocaine-memory retrieval, in a place conditioning paradigm. However, to better model addiction-related behaviors, self-administration models are necessary. Here, we demonstrate that relapse to alcohol seeking can be prevented by aversive counterconditioning conducted during alcohol-memory reconsolidation, in conditioned place preference (CPP) and operant self-administration paradigms, in mice and rats, respectively. We found that the reinstatement of alcohol-CPP was abolished only when aversive counterconditioning with water-flooding was given shortly after...
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biorxiv_neursci: Disruption of relapse to alcohol seeking by aversive counterconditioning following memory retrieval https://t.co/7aUsdzDGDY #biorxiv_neursci
biorxivpreprint: Disruption of relapse to alcohol seeking by aversive counterconditioning following memory retrieval https://t.co/PVhlq7PKUZ #bioRxiv
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2.151 Mikeys
#4. Combining multiple functional connectivity methods to improve causal inferences
Ruben Sanchez-Romero, Michael W. Cole
Cognition and behavior emerge from brain network interactions, suggesting that causal interactions should be central to the study of brain function. Yet approaches that characterize relationships among neural time series−functional connectivity (FC) methods−are dominated by methods that assess bivariate statistical associations rather than causal interactions. Such bivariate approaches result in substantial false positives since they do not account for confounders (common causes) among neural populations. A major reason for the dominance of methods such as bivariate Pearson correlation (with functional MRI) and coherence (with electrophysiological methods) may be their simplicity. Thus, we sought to identify an FC method that was both simple and improved causal inferences relative to the most popular methods. We started with partial correlation, showing with neural network simulations that this substantially improves causal inferences relative to bivariate correlation. However, the presence of colliders (common effects) in a...
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matteo_brainnet: RT @biorxiv_neursci: Combining multiple functional connectivity methods to improve causal inferences https://t.co/Fe9vbtolAG #biorxiv_neur…
ayumu_tomaru: RT @biorxiv_neursci: Combining multiple functional connectivity methods to improve causal inferences https://t.co/Fe9vbtolAG #biorxiv_neur…
zhaowenliu_kaka: RT @biorxiv_neursci: Combining multiple functional connectivity methods to improve causal inferences https://t.co/Fe9vbtolAG #biorxiv_neur…
TanguaySabourin: RT @biorxiv_neursci: Combining multiple functional connectivity methods to improve causal inferences https://t.co/Fe9vbtolAG #biorxiv_neur…
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2.081 Mikeys
#5. Hippocampal ensembles represent sequential relationships among discrete nonspatial events
Babak Shahbaba, Lingge LI, Forest Agostinelli, Mansi Saraf, Gabriel A Elias, Pierre F Baldi, Norbert J Fortin
The hippocampus is critical to the temporal organization of our experiences, including the ability to remember past event sequences and predict future ones. Although this fundamental capacity is conserved across modalities and species, its underlying neuronal mechanisms remain poorly understood. Here we recorded hippocampal ensemble activity as rats remembered a sequence of nonspatial events (5 odor presentations unfolding over several seconds), using a task with established parallels in humans. Using novel statistical methods and deep learning techniques, we then identified new forms of sequential organization in hippocampal activity linked with task performance. We discovered that sequential firing fields ("time cells") provided temporal information within and across events in the sequence, and that distinct types of task-critical information (stimulus identity, temporal order, and trial outcome) were also sequentially differentiated within event presentations. Finally, as previously only observed with spatial information, we...
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GarrettJBlair: Hippocampal ensembles represent sequential relationships among discrete nonspatial events - Shahbaba et al. https://t.co/duqe6dBG86
doellerlab: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
d_soto_b: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
NickBDiamond: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
sinclair_allie: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
EliSennesh: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
NeuroSyntheSys: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
Tsusumu2: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
mockpate: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
KeilandWCooper: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
vy_psy: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
cimoore444: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
QasimEtal: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
lajnd: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
nikasamborska: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
NeuroHoke: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
TMR_et_al: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
KafkasAlex: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
NcogEunHyePark: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
HarpRho: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
BilPeshev: RT @biorxiv_neursci: Hippocampal ensembles represent sequential relationships among discrete nonspatial events https://t.co/aQpIG9rd3y #bi…
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2.057 Mikeys
#6. Motor circuit function is stabilized during postembryonic growth by anterograde trans-synaptic Jelly Belly - Anaplastic Lymphoma Kinase signaling
Phil-Alan Ricardo Gaertig, Aaron Daniel Ostrovsky, Linda Joel Manhart, Carlo Natale Giuseppe Giachello, Tatjana Kovacevic, Heidi Lustig, Barbara Chwalla, Sebastian Cachero, Richard A Baines, Matthias Landgraf, Jan Felix Evers
The brain adapts to a changing environment or growing body size by structural growth and synaptic plasticity. Mechanisms studied to date promote synaptic growth between partner neurons, while negative counterparts that inhibit such interactions have so far remained elusive. Here, we investigate the role of Jeb-Alk signaling in coordinating motor circuit growth during larval stages of Drosophila. We quantify neuronal growth dynamics by intra-vital imaging, and synaptogenesis at nanometer resolution using endogenously labeled synaptic proteins, conditionally tagged with a fluorophore, and link changes in circuit anatomy with altered synaptic physiology and behavior. We find that loss of Jeb-Alk signaling leads to increased strengthening of synaptic excitation by developmental addition of additional postsynaptic but not pre-synaptic specializations. These changes ultimately lead to an epilepsy-like seizure behavior. We thus demonstrate that trans-synaptic anterograde Jeb-Alk signaling acts to stabilize developmental plasticity and...
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biorxiv_neursci: Motor circuit function is stabilized during postembryonic growth by anterograde trans-synaptic Jelly Belly - Anaplastic Lymphoma ... https://t.co/VpL0ggwAhz #biorxiv_neursci
biorxivpreprint: Motor circuit function is stabilized during postembryonic growth by anterograde trans-synaptic Jelly Belly - Anaplastic Lymphoma Kinase signaling https://t.co/DpXHoBfAtU #bioRxiv
PAgaertig: Check out this paper on bioRxiv. It has my name on it. ❤️🙃 And those of some great people. 😉 Many thanks to everybody involved 😀 #drosophila #neuroscience @janfevi @Landgraf10006 @COSHeidelberg @UniHeidelberg https://t.co/UdiWdn0NwM
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2.031 Mikeys
#7. Scaling laws in spoken language associated with cognitive functions
Masato S. Abe, Mihoko Otake-Matsuura
A decline in cognitive functions due to aging has led to critical problems in modern society, and it is imperative to develop a method to predict the decline or related diseases, including dementia. Although it has been expected that language could be a sign of the cognitive decline, it remains less understood, especially in natural conditions. In this study, we recorded the large-scale data of one million words from group conversations among healthy elderly people and analysed the relationship between spoken language and cognitive functions based on scaling laws, namely, Zipf's law and Heaps' law. We found that word patterns followed these scaling laws irrespective of cognitive function, but the variations in scaling laws were associated with cognitive functions. Moreover, using generative models, we uncovered the relationship between the variations and cognitive functions. These results indicate that scaling laws in language can be a biomarker for the cognitive decline.
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biorxiv_neursci: Scaling laws in spoken language associated with cognitive functions https://t.co/IMrLFTadPH #biorxiv_neursci
biorxivpreprint: Scaling laws in spoken language associated with cognitive functions https://t.co/lLb2p8Pk8e #bioRxiv
NeuroSyntheSys: RT @biorxiv_neursci: Scaling laws in spoken language associated with cognitive functions https://t.co/IMrLFTadPH #biorxiv_neursci
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Total Words: 7638
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2.025 Mikeys
#8. Altered updating of bodily and spatial representations following tool-use in Complex Regional Pain Syndrome
Axel Davies Vitterso, Gavin Buckingham, Monika Halicka, Michael J Proulx, Janet H Bultitude
Distorted representations of the body and peripersonal space are common in Complex Regional Pain Syndrome (CRPS), and might modulate its symptoms (e.g. asymmetric limb temperature). In pain-free people, such representations are malleable, and update when we interact with objects in our environment (e.g. during tool-use). Distortions are also common after immobilisation, but quickly normalise once movement is regained. We tested the hypothesis that people with CRPS have problems updating bodily and spatial representations, which contributes to the maintenance of their distorted representations by preventing normalization. We also explored spatially defined modulations of hand temperature asymmetries, and any influence of updating bodily and spatial representations on this effect. Thirty-six people with unilateral CRPS (18 upper limb, 18 lower limb) and 36 pain-free controls completed tool-use tasks considered to alter body and peripersonal space representations (measured using tactile distance judgements and a visuotactile...
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biorxiv_neursci: Altered updating of bodily and spatial representations following tool-use in Complex Regional Pain Syndrome https://t.co/YrQ6MzPh0m #biorxiv_neursci
biorxivpreprint: Altered updating of bodily and spatial representations following tool-use in Complex Regional Pain Syndrome https://t.co/0vTXtAv8mr #bioRxiv
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Total Words: 17778
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2.015 Mikeys
#9. The Degree Distribution of Human Brain Functional Connectivity is Generalized Pareto: A Multi-Scale Analysis
Riccardo Zucca, Xerxes D. Arsiwalla, Hoang Le, Mikail Rubinov, Antoni Gurgui, Paul Verschure
Are degree distributions of human brain functional connectivity networks heavy-tailed? Initial claims based on least-square fitting suggested that brain functional connectivity networks obey power law scaling in their degree distributions. This interpretation has been challenged on methodological grounds. Subsequently, estimators based on maximum-likelihood and non-parametric tests involving surrogate data have been proposed. No clear consensus has emerged as results especially depended on data resolution. To identify the underlying topological distribution of brain functional connectivity calls for a closer examination of the relationship between resolution and statistics of model fitting. In this study, we analyze high-resolution functional magnetic resonance imaging (fMRI) data from the Human Connectome Project to assess its degree distribution across resolutions. We consider resolutions from one thousand to eighty thousand regions of interest (ROIs) and test whether they follow a heavy or short-tailed distribution. We analyze...
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biorxiv_neursci: The Degree Distribution of Human Brain Functional Connectivity is Generalized Pareto: A Multi-Scale Analysis https://t.co/P28NjmEMXP #biorxiv_neursci
biorxivpreprint: The Degree Distribution of Human Brain Functional Connectivity is Generalized Pareto: A Multi-Scale Analysis https://t.co/lvhnP7yTRm #bioRxiv
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2.015 Mikeys
#10. Synaptogenic activity of the axon guidance molecule Robo2 is critical for hippocampal circuit function
Heike Blockus, Sebastian Rolotti, Miklos Szoboszlay, Tiffany Ming, Anna Schroeder, Kristel M Vennekens, Phinikoula Katsamba, Fabiana Bahna, Seetha Mannepalli, Goran Ahlsen, Barry Honig, Lawrence Shapiro, Joris de Wit, Attila Losonczy, Franck Polleux
The developmental transition between axon guidance and synapse formation is critical for circuit assembly but still poorly understood at the molecular level. We hypothesized that this key transition could be regulated by axon guidance cues switching their function to regulate synaptogenesis with subcellular specificity. Here, we report evidence for such a functional switch, describing a novel role for the axon guidance molecule Robo2 in excitatory synapse formation onto dendrites of CA1 pyramidal neurons (PNs) in the mouse hippocampus. Cell-autonomous deletion of Robo2 from CA1 PNs leads to a drastic reduction of the number of excitatory synapses specifically in proximal dendritic compartments. At the molecular level, we show that this novel postsynaptic function of Robo2 depends on both its canonical ligand Slit and a novel interaction with presynaptic Neurexins. Biophysical analysis reveals that Robo2 binds directly to Neurexins via its Ig4-5 domains. In vivo 2-photon Ca2+ imaging of CA1 PNs during spatial navigation in mice...
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biorxiv_neursci: Synaptogenic activity of the axon guidance molecule Robo2 is critical for hippocampal circuit function https://t.co/uMzX6IVQob #biorxiv_neursci
biorxivpreprint: Synaptogenic activity of the axon guidance molecule Robo2 is critical for hippocampal circuit function https://t.co/CRNDY5B8kw #bioRxiv
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Authors: 15
Total Words: 12193
Unqiue Words: 3816

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