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| Open AccessSynergizing habits and goals with variational Bayes
Intelligent agents can perform two types of behavior, habitual and goal-directed. The authors propose a deep learning framework using a variational Bayes approach, which computationally explains many aspects of the interaction between the two types of behaviors in sensorimotor tasks.
- Dongqi Han
- , Kenji Doya
- & Jun Tani
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Article
| Open AccessLipidome atlas of the adult human brain
While our brain is primarily composed of lipids, their functions have largely remained unexplored. Here, authors show that specific lipids can be linked to the structural organization and functional hierarchy of the human and macaque brain.
- Maria Osetrova
- , Anna Tkachev
- & Philipp Khaitovich
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Article
| Open AccessDuality between predictability and reconstructability in complex systems
Reconstructing the structure of a complex networked system and predicting its time evolution to understand its functions are usually two subjects that are treated separately. The authors propose a theoretical framework based on information theory, that uncovers the relation between reconstructability and predictability in networked systems.
- Charles Murphy
- , Vincent Thibeault
- & Patrick Desrosiers
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| Open AccessNeuronal activation sequences in lateral prefrontal cortex encode visuospatial working memory during virtual navigation
The neural codes underlying working memory are not fully understood. Here the authors recorded neurons in the lateral prefrontal cortex of male macaque monkeys, during a working memory task, and identify activation sequences that encode target locations in the task.
- Alexandra Busch
- , Megan Roussy
- & Julio C. Martinez-Trujillo
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| Open AccessHeterogeneity in strategy use during arbitration between experiential and observational learning
People learn by observing others and from personal experience, but which strategy they favor varies. Here, the authors show that while some people dynamically arbitrate and switch to the strategy that is most reliable, others preferentially use one or a fixed mixture of strategies.
- Caroline J. Charpentier
- , Qianying Wu
- & John P. O’Doherty
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| Open AccessLocalized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex
The extent to which brains employ Bayesian principles remains unclear. Here, the authors provide evidence suggesting that neurons in the medial prefrontal cortex represent the modulation of reward expectation (i.e., prior values) with incoming sensory inputs to compute confidence values.
- Kotaro Ishizu
- , Shosuke Nishimoto
- & Akihiro Funamizu
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Article
| Open AccessHippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans
Whether and how sharp-wave ripples (SWRs) accompany mental states that are less closely linked to events in the immediate environment are not fully understood. Here authors recorded SWRs from hippocampus of 10 epilepsy patients for up to 15 days with experience sampling. SWR rates showed circadian fluctuation and were associated with self-generated thoughts such as mind wandering.
- Takamitsu Iwata
- , Takufumi Yanagisawa
- & Haruhiko Kishima
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| Open AccessSelf-organization of modular activity in immature cortical networks
How the cortex forms spatially structured modules during development is poorly understood. Here, the authors show that activity in early developing cortex is self-organized though local-excitation and lateral inhibition.
- Haleigh N. Mulholland
- , Matthias Kaschube
- & Gordon B. Smith
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| Open AccessDe novo motor learning creates structure in neural activity that shapes adaptation
Using recurrent neural networks, here the authors show that learning the same task through different experiences can lead to important differences in how neural activity is structured. These differences can play a crucial role for subsequent adaptation, with networks that are equally good at the initial task showing opposing trends in adaptation.
- Joanna C. Chang
- , Matthew G. Perich
- & Claudia Clopath
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Article
| Open AccessSpontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity
Cortico-entorhinal interactions remain poorly understood. Here, the authors demonstrate that a model of interacting networks predicts spontaneous persistent activity and inactivity in the medial, but not lateral, entorhinal cortex in vivo.
- Krishna Choudhary
- , Sven Berberich
- & Mayank R. Mehta
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| Open AccessHuman connectome topology directs cortical traveling waves and shapes frequency gradients
The factors that determine the direction of traveling waves in the brain are not well understood. Here, the authors show that the sum of incoming structural connection strengths shape both traveling wave direction and frequency gradients.
- Dominik P. Koller
- , Michael Schirner
- & Petra Ritter
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Article
| Open AccessCross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections
Omics data’s diversity and high-dimensionality challenge integration across technologies and with imaging. Here, authors introduce mapping method xIV-LDDMM that estimates geometric and feature transformations to integrate tissue-scale atlases with molecular and cellular-scale data.
- Kaitlin M. Stouffer
- , Alain Trouvé
- & Michael I. Miller
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| Open AccessDiverse and asymmetric patterns of single-neuron projectome in regulating interhemispheric connectivity
How interhemispheric connections are organized and how interhemispheric communication are regulated are not fully understood. Here authors delineate the diverse single-neuron projection patterns of interhemispheric connections in mice and uncover their influence on functional dynamics, highlighting the importance of heterotopic projections in interhemispheric communication.
- Yao Fei
- , Qihang Wu
- & Cirong Liu
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| Open AccessPrediction error processing and sharpening of expected information across the face-processing hierarchy
Perception and neural processing of sensory information are influenced by prior expectations. Here the authors show investigate how prior expectations contribute to face processing in the brain.
- Annika Garlichs
- & Helen Blank
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Article
| Open AccessRobust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework
Costa et al. designed a modular spiking neural network in a neuromorphic device with heterogeneous silicon neurons that remotely detects epileptiform discharges and High Frequency Oscillations in intra-operative EEG during epilepsy surgery in real-time.
- Filippo Costa
- , Eline V. Schaft
- & Johannes Sarnthein
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| Open AccessConjunctive encoding of exploratory intentions and spatial information in the hippocampus
The hippocampus maps space, but its role in encoding investigatory intentions is unclear. Here the authors show that certain CA1 neurons encode both spatial information and animals’ intention to explore, depending on input from lateral entorhinal cortex.
- Yi-Fan Zeng
- , Ke-Xin Yang
- & Ning Zhou
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| Open AccessNeurocomputational mechanisms involved in adaptation to fluctuating intentions of others
Humans often interact without knowing the cooperative or competitive intentions of others. Here, the authors determined the neurocomputational mechanisms engaged in adapting to fluctuating intentions of others over repeated social interactions.
- Rémi Philippe
- , Rémi Janet
- & Jean-Claude Dreher
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Article
| Open AccessStimulus encoding by specific inactivation of cortical neurons
How neural ensembles encode information remains poorly understood. Here, the authors identify “offsembles”—neurons that are specifically inactivated by sensory stimuli—which, when combined with “onsemble” neurons that are turned on by the stimulus, provide enhanced encoding power to the cortex.
- Jesús Pérez-Ortega
- , Alejandro Akrouh
- & Rafael Yuste
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| Open AccessMultiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex
Understanding the link between multiple movement elements and sequence-related responses in the motor cortex remains elusive. This study reveals a multiplicative joint coding mechanism during motor preparation which transfers to additive during execution, potentially explaining the linear readout of elemental movements.
- Tianwei Wang
- , Yun Chen
- & He Cui
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Article
| Open AccessViability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains
A bio-inspired control architecture for learning agile quadruped locomotion on challenging terrain suggests Viability (i.e., avoiding falls) as the main criterion for quadrupedal gait transitions and energy efficiency is the secondary objective.
- Milad Shafiee
- , Guillaume Bellegarda
- & Auke Ijspeert
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| Open AccessTiming along the cardiac cycle modulates neural signals of reward-based learning
Previous work has shown that natural cardiac rhythms modulate the perception and reaction to sensory cues through changes in associated neural signals. Here, the authors show that sensitivity to prediction errors during reward learning is related to the phase of the cardiac cycle.
- Elsa F. Fouragnan
- , Billy Hosking
- & Alejandra Sel
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| Open AccessAlignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Here, using neural activity patterns in the inferior frontal gyrus and large language modeling embeddings, the authors provide evidence for a common neural code for language processing.
- Ariel Goldstein
- , Avigail Grinstein-Dabush
- & Uri Hasson
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| Open AccessLocal orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain
The brain’s role in supporting consciousness is unclear. Here, authors show that global markers of consciousness in macaque cortex are suppressed by many anaesthetics, and restored by local stimulation of a thalamic nucleus that also induces awakening.
- Andrea I. Luppi
- , Lynn Uhrig
- & Rodrigo Cofre
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| Open AccessA multi-demand operating system underlying diverse cognitive tasks
A consistent set of brain areas is engaged across diverse cognitive tasks. Here, the authors reveal a unifying latent brain state that predicts performance across seven tasks, linking a core control network to cognitive flexibility and adaptive behaviors.
- Weidong Cai
- , Jalil Taghia
- & Vinod Menon
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| Open AccessTemporally organized representations of reward and risk in the human brain
It is unclear how reward and risk are temporally organized in the human brain. Here, the authors demonstrate both sequential and parallel encoding of decision variables, and the role of anterior insula in reward- and risk-prediction error.
- Vincent Man
- , Jeffrey Cockburn
- & John P. O’Doherty
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| Open AccessWalking modulates visual detection performance according to stride cycle phase
“Visual performance might vary during natural behaviour such as walking. Here, the authors use wireless virtual reality to show that oscillations in performance on a visual detection task were systematically linked to the phase of the stride cycle.”
- Matthew J. Davidson
- , Frans A. J. Verstraten
- & David Alais
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| Open AccessImproved modeling of human vision by incorporating robustness to blur in convolutional neural networks
The phenomenon of blurry or degraded visual input in humans has been overlooked in the training of convolutional neural networks (CNNs). Here, the authors show that blur-trained CNNs outperform standard CNNs in predicting neural responses to objects and show improved correspondence with human perception.
- Hojin Jang
- & Frank Tong
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| Open AccessComparative connectomics of dauer reveals developmental plasticity
How the dauer, an alternative developmental stage in nematodes, exhibits distinct behavioral traits remains unclear. Here, the authors reveal the neural circuitry underlying these distinctions by reconstructing the dauer connectome and comparing it with other stages.
- Hyunsoo Yim
- , Daniel T. Choe
- & Junho Lee
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| Open AccessDirect contribution of the sensory cortex to the judgment of stimulus duration
The neural substrates of time perception are still unclear. Here, the authors show that as rats judged tactile stimuli, optogenetic manipulation of somatosensory cortex systematically altered perception of stimulus intensity and of duration, unveiling a multiplexed code.
- Sebastian Reinartz
- , Arash Fassihi
- & Mathew E. Diamond
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| Open AccessA neurophysiological basis for aperiodic EEG and the background spectral trend
The neural mechanisms that give rise to aperiodic EEG signals remains unclear. Here the authors characterize EEG signals generated by neural processes other than brain rhythms, demonstrating that certain drugs alter EEG signals in ways that confound traditional interpretation.
- Niklas Brake
- , Flavie Duc
- & Gilles Plourde
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Article
| Open AccessNeonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment
Neonatal brain dynamics are not well understood. Here, the authors characterise brain transient states in neonates, and show that preterm infants display altered whole brain dynamics and an atypical repertoire of regional transient states, which are associated with behavioural outcomes at 18 months of age.
- Lucas G. S. França
- , Judit Ciarrusta
- & Dafnis Batalle
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| Open AccessEmergence of syntax and word prediction in an artificial neural circuit of the cerebellum
The role of the cerebellum in language processing remains unclear. Here, the authors use a biologically-constrained artificial cerebellar neural network to reveal a dual role of single circuit computation in syntax and word prediction.
- Keiko Ohmae
- & Shogo Ohmae
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| Open AccessAn actor-model framework for visual sensory encoding
Encoding and downsampling images is key for visual prostheses. Here, the authors show that an actor-model framework using the inherent computation of the retinal network yields better performance in downsampling images compared to learning-free methods.
- Franklin Leong
- , Babak Rahmani
- & Diego Ghezzi
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| Open AccessStructural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence
Cortical morphology shows maturation during childhood and adolescence. Here the authors show this is structurally constrained by a diffusion network model and that this constraint is linked to gene expression profiles of microstructural development.
- Xinyuan Liang
- , Lianglong Sun
- & Yong He
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Article
| Open AccessA developmental increase of inhibition promotes the emergence of hippocampal ripples
The developmental trajectory of hippocampal ripples, the electrical signature of long term memory storage, is poorly understood. Here, the authors show that their delayed appearance is mechanistically linked to the maturation of inhibition.
- Irina Pochinok
- , Tristan M. Stöber
- & Ileana L. Hanganu-Opatz
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| Open AccessLatent representations in hippocampal network model co-evolve with behavioral exploration of task structure
How mechanisms of single-cell plasticity lead to task-dependent cognitive maps remains unclear. Here, the authors show that this model of hippocampus shows that cooperation between local plasticity and reinforcement learning of behavior can lead to task-specific latent representations.
- Ian Cone
- & Claudia Clopath
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Article
| Open AccessAcoustic and language-specific sources for phonemic abstraction from speech
How speech sounds come to be understood as language remains unclear. Here, the authors find that brain responses to speech in part reflect abstraction of phonological units specific to the language being spoken, mediated through relationships between acoustic features.
- Anna Mai
- , Stephanie Riès
- & Timothy Q. Gentner
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| Open AccessConnectome-based reservoir computing with the
conn2res toolboxBrain connectivity patterns shape computational capacity of biological neural networks, however mapping empirically measured connectivity to artificial networks remains challenging. The authors present a toolbox for implementing biological neural networks as artificial reservoir networks. The toolbox allows for a variety of empirical/measured connectomes and is equipped with various dynamical systems, and cognitive tasks.
- Laura E. Suárez
- , Agoston Mihalik
- & Bratislav Misic
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| Open AccessDistinguishing examples while building concepts in hippocampal and artificial networks
While the hippocampus is well-known to store specific memories, it can also learn common features that are shared across individual memories. Here, the authors show how this ability arises from dual input pathways and how it can inspire better machine learning methods.
- Louis Kang
- & Taro Toyoizumi
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| Open AccessRamping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior
The authors show that neuronal populations in the human prefrontal-motor network interact via two discernible communication modes – ramping dynamics and neural oscillations. These modes operate in concert to facilitate rule-guided behavior.
- Jan Weber
- , Anne-Kristin Solbakk
- & Randolph F. Helfrich
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| Open AccessRadiomic tractometry reveals tract-specific imaging biomarkers in white matter
Diffusion MRI is used for tract-specific microstructural analysis of the white matter. Here, the authors introduce radiomic tractometry (RadTract), enhancing tractometry with radiomics-based imaging biomarkers for improved predictive modelling.
- Peter Neher
- , Dusan Hirjak
- & Klaus Maier-Hein
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| Open AccessMultimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization
The relationship between fMRI-BOLD and neural activity in the brain is not well understood. Here, the authors combine calcium imaging and fMRI in the mouse brain to compare network organization derived from these imaging modalities.
- Hadi Vafaii
- , Francesca Mandino
- & Luiz Pessoa
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Article
| Open AccessPrefrontal signals precede striatal signals for biased credit assignment in motivational learning biases
People are more likely to take action when they expect a reward but hold back when expecting punishment. Here, the authors show that such motivational biases may stem from biased action outcome learning in cortico-striatal circuits.
- Johannes Algermissen
- , Jennifer C. Swart
- & Hanneke E. M. den Ouden
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Article
| Open AccessSpontaneous emergence of rudimentary music detectors in deep neural networks
Music is processed by dedicated circuits in the brain. Here, the authors show that these circuits can spontaneously emerge in neural networks by learning natural sound processing, even without explicit training with music.
- Gwangsu Kim
- , Dong-Kyum Kim
- & Hawoong Jeong
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Article
| Open AccessA power law describes the magnitude of adaptation in neural populations of primary visual cortex
How cortical populations adapt to the statistics of sensory input is not fully understood. Here the authors show that a power law captures how the magnitude of population responses change across different sensory environments.
- Elaine Tring
- , Mario Dipoppa
- & Dario L. Ringach
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| Open AccessEvidence for increased parallel information transmission in human brain networks compared to macaques and male mice
Differences in information transmission in the brain network between humans and other species are not well understood. Here, the authors apply an information theory approach to structural connectomes and functional MRI and report that human brain networks display more evidence of parallel information transmission compared to macaques and mice.
- Alessandra Griffa
- , Mathieu Mach
- & Enrico Amico
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Article
| Open AccessTargeted V1 comodulation supports task-adaptive sensory decisions
Animals respond rapidly and precisely to a variety of sensory stimuli, but the neural mechanisms supporting this flexibility are not fully understood. Here the authors describe a model of adaptive sensory processing based on functionally-targeted stochastic modulation, and find evidence for this co-variability in macaque V1 and middle temporal area.
- Caroline Haimerl
- , Douglas A. Ruff
- & Eero P. Simoncelli
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Article
| Open AccessAugmenting interpretable models with large language models during training
Prediction and interpretation tasks may be challenging in high-stakes applications, such as medical decision-making, or systems with compute-limited hardware. The authors introduce an augmented framework for leveraging the knowledge learned by Large Language Models to build interpretable models which are both accurate and efficient.
- Chandan Singh
- , Armin Askari
- & Jianfeng Gao
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| Open AccessInternal states as a source of subject-dependent movement variability are represented by large-scale brain networks
How internal states such as confidence and motivation influence motor performance remains unclear. Here, the authors explore brain networks associated with these internal states, finding that the Dorsal Attention Network encodes error states and the Default Network reflects perceived uncertainty.
- Macauley Smith Breault
- , Pierre Sacré
- & Sridevi V. Sarma