New papers on Computational neuroscience
59 new papers on computational neuroscience in the last 7 days, within Brain & mind. These are the 50 Pipette rates most worth reading, with the main result in the authors' own words.
The best of the week
Lifespan EEG Reference Charts Reveal Aperiodic Confounds in Beta-Band Biomarkers Across Neurological and Neuropsychiatric Disorders
In this paper, we establish the first comprehensive lifespan reference charts for beta oscillations (N = 22,094, ages: 1-100 years) using complementary analytic approaches that isolate periodic oscillations from aperiodic background activity.
PreprintClaims a big stepAVMoments-EEG: A Large-Scale EEG Dataset of Naturalistic Audiovisual Event Perception
Here, we introduce AVMoments-EEG, the first large-scale, high-temporal-resolution human EEG dataset designed to characterize neural responses to naturalistic audiovisual events.
PreprintAI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets
These findings provide a falsifiable upstream method for designing and behaviorally testing candidate representational targets for future neuromodulation in psychiatry, while marking the limits of the present static approximation.
PreprintHow sparse can a fly-brain model be? Connection strength, wiring placement, network state and task jointly determine function-preserving compression of the Drosophila connectome
These results provide a first benchmark for connectome sparsification and show that what must be kept depends on task and network state.
PreprintConnectivity allometry is a robust organizing principle of the human functional connectome
We found that human functional networks were organized according to a robust and spatially heterogeneous connectivity allometry, whereby regional functional connectivity scales nonlinearly with whole-brain connectivity strength.
PreprintAI agents at the brain-computer interface: separating inference from control
No direct agent arm improved on the resolvers risk-coverage frontier, but a hybrid architecture in which models proposed semantic corrections and an external gate retained admission authority extended coverage beyond the resolver in five of ten models without observed unfaithful executions.
PreprintReal-world useAn fMRI dysmaturity signature in preterm neonates: Responsiveness of brain areas and its relation to newborn brain development
These findings reveal that intrinsic responsiveness captures a previously underappreciated dynamical dimension of neonatal brain organization and provides sensitive markers of neurodevelopmental maturity.
PreprintZero-shot evaluations expose structured generalization limits in predictive models of the brain
Together, the zero-shot evaluation framework provides a scalable and unified approach for evaluating brain models across prediction and cognitive neuroscience tests, which can help us better understand what current models capture and what still remains to be explained.
PreprintMultidimensional semantic representations emerge from multi-frequency representational similarity learning
We found significant decoding of graded, multidimensional semantic information from a wide range of frequencies (4 - 200 Hz), but not from individual frequency bands, providing clear evidence that multidimensional semantic information is coded in a transfrequency fashion.
PreprintA theory of plasticity: capacity for change as inverse configurational constraint
Here I propose that plasticity, understood as a prospective property, is inverse configurational constraint: a system is plastic to the extent that its present configuration weakly constrains displacement toward alternatives within a declared representation.
PreprintWhat Transfers Across Brains Is Not What Stays Within Individuals: Evidence from Bilingual Language States
Our findings reveal two levels of organization: a common component that supports transfer between brains and an individual component that remains reliably stable within a person across sessions.
PreprintDynamic belief representation and updating through learned attractor-like dynamics in the frontal cortex
Our findings indicate that the brain approximates belief-state inference through learned, task-specific attractor-like dynamics.
PreprintDeep Learning in Infant Functional Neuroimaging: Challenges, Advances, and Future Directions
Here, we review recent advances in deep learning for infant functional neuroimaging, synthesizing progress across input representation formatting, population and individualized brain mapping, longitudinal trajectory forecasting, robust and explainable model evaluation, and biological translation.
PreprintReal-world useOpening the black box toward a modular approach to spike sorting
To address this issue, we developed a modular and common framework to develop, benchmark, and assemble the key computational steps that are used in state-of-the-art spike sorting algorithms.
Peer-reviewed journalBold claims, read criticallyReal-world usePredictive coding networks capture human neural representations missing in supervised DNNs
We show that brain representations after statistical learning are better modeled by a predictive local target than a supervised or contrastive target, and that during learning, the brain attenuates category-specific representations while retaining predictive ones.
PreprintComputing the geometry of phase-amplitude coupling: A new moment-based framework
We propose formalising PAC as a hierarchy of representations, introducing a circular-moment decomposition that preserves richer geometric information.
PreprintPlasticity degeneracy underlies flexible formation and reconfiguration of spatial representations in hippocampal granule cells
Our findings reveal extensive plasticity degeneracy in hippocampal spatial coding and suggest that flexible neural representations emerge not from unique plasticity rules involving one single component, but from a repertoire of alternative plasticity routes that are capable of implementing the same computation.
PreprintThe balance of local and distributed excitation shapes brain stability and reflects aging- and Alzheimer's disease-related alterations
Together, these findings establish the R-ratio as a biologically interpretable marker of whole-brain excitation balance and demonstrate its utility for linking biophysical mechanisms with large-scale brain dynamics, aging, and neurodegeneration.
PreprintDale's law, stability and nonlinearity are sufficient constraints to ignite transient and self-sustained neural dynamics
Here, we show that three simple ingredients: Dalean connectivity, stability, and nonlinear neural responses, suffice to reverse-engineer networks that produce transient, steady-state, and self-sustained periodic activity.
PreprintBold claims, read criticallyLearning to play with spikes: characterizing, predicting, and engineering unsupervised plasticity rules for spiking reservoir computing
Together, these results offer competitive performance against classical reservoir computing while providing a transparent, interpretable account of what makes a plasticity rule useful for neuromorphic hardware and biological computing.
PreprintObservation-related activity in the human motor cortex increases with effector anthropomorphicity
We found a relationship between neural modulation and effector anthropomorphicity (i.e., human-likeness) that existed on an ensemble-wide and individual-neuron level, suggesting that human motor cortex activity incrementally increases in response to the visually observed agent's human-likeness.
Peer-reviewed journalReal-world useRapid estimation of receptive fields across stages of the early visual system
Our approach enables rapid and interpretable functional characterization of large populations of visual neurons, enabling to simultaneously recover receptive fields and feature tuning, whenever a low-dimensional feature space can be specified beforehand.
PreprintPopulation coding under the scale invariance of high-dimensional noise
Contrary to previous reports, we find that leading noise components that scale linearly with population size, and thus can limit information, are not sufficiently aligned with the signal to impose a bound.
Peer-reviewed journalMedial temporal default mode network selectively encodes autobiographical visual imagery
Representational similarity analysis revealed that the MT-DMN encoded the participant-specific representational structure of image representations, even when controlling for semantic features derived from a large language model.
Peer-reviewed journalNeuralRNN: a unified framework for recurrent neural network methods in cognitive neuroscience
Here we introduce NeuralRNN, an open-source Python framework that unifies these paradigms and model variants in a general-purpose pipeline.
PreprintState-Transition Dynamics in the HR--Deceleration Capacity Feature Space: Passive Assessment of Autonomic Dysfunction from 24-Hour Heart Rate
In a clinical subset (N = 26) with concurrent active reflex testing, Relaxation metrics predicted Valsalva Ratio (R2 = 0.58) and Excitation metrics predicted Tilt SBP drop (R2 = 0.62), indicating that the framework can serve as a passive surrogate for standard autonomic reflex tests.
PreprintBold claims, read criticallyReal-world useIdentifying Neural State Changes due to Gain versus Off-Manifold Displacement
Here, I introduce a geometric decomposition that separates changes attributable to gain modulation of a nearby manifold state from movement within the manifold and genuine off-manifold displacement.
PreprintA transformer-based model reveals sparse, stimulus-dependent orientation readout from macaque V1 population activity
The model reconstructed stimulus orientation with high precision and revealed, through its self-attention maps, a sparse and stimulus-dependent readout structure.
PreprintField-Based Characterization of Temporal Interference Stimulation: Beyond the Target-Centric Perspective
Applied to TI simulations using individualized tetrahedral head models, the framework demonstrates that the few largest connected components above an elevated intensity threshold collectively provide a more accurate representation of the stimulation targets.
PreprintReal-world useReal-time closed-loop feedback system for mouse mesoscale cortical signal and movement control
We present the implementation and efficacy of an open-source closed-loop neurofeedback (CLNF) and closed-loop movement feedback (CLMF) system.
Peer-reviewed journalHow Similar Are Two Brains? A Comprehensive Benchmark of Brain Network Similarity Measures
For this reason, we conclude that DeltaCon is the best general-purpose similarity measure.
PreprintBold claims, read criticallyHead-level lesion-symptom mapping of picture naming in vision-language models
These results show that ablating the head whose removal disrupts naming does not establish that the head computes the behavior, that the result generalizes across models, or that the behavior localizes to a head at all.
PreprintBiophysical modeling reveals how recording geometry shapes representations of cortical activity
Together, these results show that extracellular measurements represent an interaction between biological source organization and recording geometry.
PreprintSpike-history gating of plateau potentials enables closed-loop rewriting of CA1 representations
Here we propose that recent somatic spike history provides a cell-specific gate for plateau initiation, making neurons sensitive to rising activity after relative silence while suppressing repeated plasticity during sustained firing.
PreprintA redundant encoding algorithm for artificial sensory information speeds learning and improves multisensory-guided navigation
We found that redundant encoding sped learning of the ICMS signal relative to sparse encoding.
PreprintBold claims, read criticallyReal-world useEnhanced tactile coding in rat neocortex under darkness
We found that the neural representations of tactile stimuli became more distinct in the dark, indicating a reorganization of sensory processing in S1 when visual input was removed.
Peer-reviewed journalRecovery from disorders of consciousness: Lesions and GABAergic modulation in a biologically inspired spiking neural network
Our findings suggest that the paradoxical effect of GABA A receptor PAMs arises from the restoration of excitatory–inhibitory balance when inhibitory networks are moderately disrupted.
Peer-reviewed journalOn the neural origin of hexadirectional fMRI modulations
Here, we propose targeted experiments that can distinguish these mechanisms, for which we assess the expected effect sizes via simulations.
PreprintCombatting nonidentifiability to infer motor cortex inputs yields similar encoding of initial and corrective movements
Inferred inputs were tuned similarly for initial and corrective movements, suggesting shared input encoding across visually-instructed and corrective movements previously obscured by M1 dynamics.
Peer-reviewed journalTE-aware state analysis and evolution in dynamic network connectivity
Here we present a methodological and empirical study of TE-dependent evolution of dynamic connectivity states, with a phenomenological two-component model for interpretation.
PreprintComputational simulation reveals the critical role of spike-timing-dependent plasticity in synchrony
Specifically, we find that STDP and desynchronization form a regulatory loop, in which STDP regulates the level of synchrony, and synchrony regulates subsequent learning strength.
PreprintBold claims, read criticallyEEG Functional Connectivity Reveals Accelerated Brain Aging in Young Adults with Cognitive Deficits and Mental Health Conditions
This work advances the understanding of EEG mechanisms contributing to brain age and could provide an interpretation for physiological or psychological conditions associated with brain age.
PreprintA Comparison of Brain Metabolic Connectivity Methods Topology, Cognition, Age, Structure, and Genetics
Collectively, these results indicate that the optimal connectivity approach depends on the research question. fPET connectivity with dynamic scans offers utility for cognition and ageing studies, tracer distribution for single-scan designs with careful interpretation of age and cognition relationships, kinetic approaches for novel biological insights into glucose kinetics and fMRI for multi-modal integration.
PreprintChaotic Dynamics-Regulated Topological Learning for Patient-Specific Preictal State Identification
The results support offline discrimination of preictal and interictal channel-level nodes within fixed patient-specific networks.
PreprintReal-world useCode availableConcordance between the fast and efficient mixed-effects algorithm (FEMA) and conventional mixed-effects modeling for whole-brain connectivity in longitudinal chronic pain
Despite these differences, the two implementations produced highly concordant results: fixed-effect estimates and test statistics correlated at r [≥] 0.999 (Lin's concordance correlation coefficient [≥] 0.999), and the two approaches reached the same statistical conclusion for 99.98% of edges.
PreprintSubCortexMesh: A Python toolbox for surface-based analysis of subcortical brain regions
We present SubCortexMesh as a user-friendly toolbox which covers automated surface estimation from popular subcortical volume segmentations (FreeSurfer and the Functional Magnetic Resonance Imaging of the Brain Software Library (FSL)), computes shape-related vertex-wise metrics (thickness, surface area and curvature) for whole cohorts and includes statistical analyses.
PreprintDecoding instrumental lever pressing from prefrontal, accumbens, and hippocampal local field potentials: conservation across sex, task, and dopamine depletion
Altogether these results suggest that there are robust distributed patterns of LFP associated with lever-pressing behavior under multiple drug, task, and sex conditions.
PreprintBrain age prediction from structural and functional connectivity across the lifespan using connectome-based predictive modeling
This work demonstrates the utility of CPM for characterizing distributed structural and functional connectivity patterns associated with chronological age across the lifespan and provides a foundation for future studies of individual variability in brain maturation and aging.
PreprintExploring Healthy Neurocognitive Ageing with Deep Learning Interpretability Methods
Together, these findings suggest that healthy ageing involves a redistribution of functional organisation that extends beyond a single DMN-FPN axis towards a broader DMN-CON-SMN-FPN configuration.
PreprintA Test for Confounding in Coupling of Multimodal Neuroimaging Data
We propose a formal U-statistic-based test for such covariate effects, enabling both diagnostic evaluation of assumption violations and scientific discovery.
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