What constitutes normal cortical dynamics in healthy human subjects is a major question systems neuroscience. Numerous vitro and vivo animal studies have shown that ongoing or resting are characterized by cascades of activity across many spatial scales, termed neuronal avalanches. In experiment theory, avalanche identified two measures: (1) power law the size distribution with an exponent −3/2 (2) branching parameter critical value 1, reflecting balanced propagation at border premature...

Population rate models provide powerful tools for investigating the principles that underlie cooperative function of large neuronal systems. However, biophysical interpretations these have been ambiguous. Hence, their applicability to real systems and experimental validation severely limited. In this work, we show conductance-based cortical networks can be described by simplified models, provided network state does not possess a high degree synchrony. We first derive precise mapping between...

Sleep encompasses approximately a third of our lifetime, yet its purpose and biological function are not well understood. Without sleep optimal brain functioning such as responsiveness to stimuli, information processing, or learning may be impaired. Such observations suggest that plays crucial role in organizing reorganizing neuronal networks the toward states where processing is optimized. Increasing evidence suggests cortical operate near critical state characterized by balanced activity...

Measuring and assessing the cognitive load associated with different tasks is crucial for many applications, from design of instructional materials to monitoring mental well-being aircraft pilots. The goal this paper utilize EEG infer workload subjects during intelligence tests. We chose well established advanced progressive matrices test, an ideal framework because it presents problems at increasing levels difficulty has been rigorously validated in past experiments. train classic machine...

Abstract Neurons in the brain are wired into adaptive networks that exhibit collective dynamics as diverse scale-specific oscillations and scale-free neuronal avalanches. Although existing models account for avalanches separately, they typically do not explain both phenomena, too complex to analyze analytically or intractable infer from data rigorously. Here we propose a feedback-driven Ising-like class of neural captures simultaneously quantitatively. In simplest yet fully microscopic model...

Recurrent connections play an important role in cortical function, yet their exact contribution to the network computation remains unknown. The principles guiding long-term evolution of these are poorly understood as well. Therefore, gaining insight into computational and mechanism shaping pattern would be great importance. To that end, we studied learning dynamics emergent recurrent connectivity a sensory model based on first-principle information theoretic approach. As test case, applied...

The finding of power law scaling in neural recordings lends support to the hypothesis critical brain dynamics. However, laws are not unique systems and can arise from alternative mechanisms. Here, we investigate whether a common time-varying external drive set Poisson units give rise neuronal avalanches exhibit apparent criticality. To this end, analytically derive avalanche size duration distributions, as well additional measures, first for homogeneous activity, then slowly varying...

Abstract Localist models of spreading activation (SA) and assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition memory research. In this study, we implemented SA an attractor neural network model with created unified framework for the two approaches. Our assume synaptic depression mechanism leading to autonomous transitions between encoded patterns (latching dynamics), which account major characteristics...

In recent years, numerous studies have found that the brain at resting state displays many features characteristic of a critical state. Here we examine whether stimulus-evoked activity can also be regarded as critical. Additionally, investigate relation between resting-state and from perspective criticality. We cortical measured by magnetoencephalography (MEG) is near organizes neuronal avalanches both activities. Moreover, significantly high intrasubject similarity avalanche size duration...

Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian cortex, one type dynamics that spontaneously emerges from neuronal interactions has been characterized as avalanches. Several aspects avalanches such their size and life time distributions are described by power laws with unique exponents, indicating an underlying critical branching process governs avalanche formation. Here, we show also reflect organization brain close to...

The framework of criticality provides a unifying perspective on neuronal dynamics from in vitro cortical cultures to functioning human brains. Recent findings suggest that healthy cortex displays critical dynamics, giving rise scale-free spatiotemporal cascades activity, termed avalanches. Pharmacological manipulations the excitation-inhibition balance (EIB) were previously shown result deviations and power law scaling avalanche size distribution. To examine sensitivity metrics altered EIB...

The conventional approach to sleep analysis relies on pre-defined, visually scored stages derived from electrophysiological signals. This manual method demands substantial effort and is influenced by subjective assessments, implicitly assuming that these categories accurately reflect underlying biological processes. Recent advancements indicate low-dimensional representations of complex brain activity can provide objective means identifying states. These approaches potentially uncover...

Epilepsy, a neurological disorder characterized by recurrent unprovoked seizures, significantly impacts patient quality of life. Current classification methods focus primarily on clinical observations and electroencephalography (EEG) analysis, often overlooking the underlying dynamics driving seizures. This study uses surface EEG data to identify seizure transitions using dynamical systems–based framework—the taxonomy dynamotypes—previously examined only in invasive data. We applied...

Abstract During flight, spatial disorientation (SD) commonly occurs when a pilot’s perception conflicts with the aircraft’s actual motion, attitude, or position. A prevalent form of SD is somatogyral illusion, which elicited by constant speed rotation and causes false motion in opposite direction ceases. This research aimed to investigate changes brain activity that occur experiencing illusion simulating conditions closely mimicking flight gain insight into how better manage this during...

The conventional approach to sleep analysis relies on pre-defined, visually scored stages derived from electrophysiological signals. This manual method demands substantial effort and is influenced by subjective assessments, implicitly assuming that these categories accurately reflect underlying biological processes. Recent advancements indicate low-dimensional representations of complex brain activity can provide objective means identifying states. These approaches potentially uncover...

Abstract Prolonged wakefulness is known to adversely affect basic cognitive abilities such as object recognition and decision making. It affects the dynamics of neuronal networks in brain can even lead hallucinations epileptic seizures. In cognitive-intensive workplaces, there a requirement refine an objective method quantifying current level capabilities, rather than relying on subjective self-reporting. this study, we compiled EEG recordings from several sleep deprivation workshops held by...

Abstract Non-stationarity in EEG signals poses significant challenges for the performance and implementation of brain computer– interfaces (BCIs). In this study, we propose a novel method cross-session BCI tasks that employs supervised autoencoder to reduce session-specific information while preserving task-related signals. Our approach compresses high-dimensional inputs reconstructs them, thereby mitigating non-stationary variability data. addition unsupervised minimization reconstruction...

Alpha oscillations are a distinctive feature of the awake resting state human brain. However, their functional role in resting-state neuronal dynamics remains poorly understood. Here we show that, during wakefulness, alpha drive an alternation attenuation and amplification bouts neural activity. Our analysis indicates that inhibition is activated pulses last for single cycle gradually suppress activity, while excitation successively enhanced over few cycles to amplify Furthermore, long-term...

Motor imagery (MI) based brain computer interfaces (BCI) detect changes in activity associated with imaginary limb movements, and translate them into device commands. MI BCIs require training, during which the user gradually learns how to control his or her help of feedback. Additionally, machine learning techniques are frequently used boost BCI performance adapt decoding algorithm user's brain. Thus, both need order improve performance. To study utility co-adaptive training paradigm time...

Understanding how populations of neurons encode sensory information is a major goal systems neuroscience. Attempts to answer this question have focused on responses measured over several hundred milliseconds, duration much longer than that frequently used by animals make decisions about the environment. How reliably encoded briefer time scales, and best extract information, unknown. Although it has been proposed neuronal response latency provides cue for fast in visual system, hypothesis not...

For the last four decades, semantic priming-the facilitation in recognition of a target word when it follows presentation semantically related prime word-has been central topic research human cognitive processing. Studies have drawn complex picture findings which demonstrated sensitivity this priming effect to unique combination variables, including, but not limited to, type relatedness between primes and targets, prime-target Stimulus Onset Asynchrony (SOA), proportion (RP) stimuli list...