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Cognitive Neurodynamics

ISSN 1871-4080, 1871-4099

16 papers in the library · 124 citations · publishing 2007-2025

Papers

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Neural oscillations predict flow experience.

Cognitive Neurodynamics December 1, 2025 Bingxin Lin, Baoshun Guo, Lingyun Zhuang et al.

Flow experience, characterized by immersion in the activity at hand, provides a motivational boost and promotes positive behaviors. However, the oscillatory representations of flow experience are still poorly understood. In this study, the difficulty of the video game was adjusted to manipulate the individual's personalized flow or non-flow state, and EEG data was recorded throughout. Our...

DOI: 10.1007/s11571-024-10205-x (opens in new tab) Full text (opens in new tab) Flow experience Machine learning Oscillatory representation Quantitative prediction +1

Mind-brain identity theory confirmed?

Cognitive Neurodynamics August 1, 2024 Wiesław L Galus

Presented here is a novel graphical, structural, and functional model of the embodied mind. Despite strictly adhering to a physicalistic and reductionist approach, this model successfully resolves the apparent contradiction between the thesis regarding the causal closure of the physical realm and the widely held common-sense belief that the mental realm can influence physical behavior....

DOI: 10.1007/s11571-023-09992-6 (opens in new tab) Full text (opens in new tab) Mind-brain identity theory Motivated, emotional mind Phenomenal awareness Stream of thoughts

A systematic approach to brain dynamics: cognitive evolution theory of consciousness.

Cognitive Neurodynamics August 10, 2022 Sergey B. Yurchenko

The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism,...

DOI: 10.1007/s11571-022-09863-6 (opens in new tab) Full text (opens in new tab) Complexity Mental disorders Consciousness Metastability +3

Biophysical mechanism of the interaction between default mode network and working memory network

Cognitive Neurodynamics December 1, 2021 Yue Yuan, Xiaochuan Pan, Rubin Wang

Default mode network (DMN) is a functional brain network with a unique neural activity pattern that shows high activity in resting states but low activity in task states. This unique pattern has been proved to relate with higher cognitions such as learning, memory and decision-making. But neural mechanisms of interactions between the default network and the task-related network are still poorly...

DOI: 10.1007/s11571-021-09674-1 (opens in new tab) Full text (opens in new tab) Default mode network Working memory Contained energy Task positive/negative network +1

Towards new concepts for a biological neuroscience of consciousness

Cognitive Neurodynamics June 10, 2020 C. M. Signorelli, Daniel Meling

In the search for a sound model of consciousness, we aim at introducing new concepts: closure, compositionality, biobranes and autobranes. This is important to overcome reductionism and to bring life back into the neuroscience of consciousness. Using these definitions, we conjecture that consciousness co-arises with the non-trivial composition of biological closure in the form of biobranes and...

Analysis of heart rate signals during meditation using visibility graph complexity.

Cognitive Neurodynamics February 2019 Mahda Nasrolahzadeh, Zeynab Mohammadpoory, Javad Haddadnia

In the dynamics analysis of heart rate, the complexity of visibility graphs (VGs) is seen as a sign of short term variability in signals. The present study was conducted to investigate the possible impact of meditation on heart rate signals complexity using VG method. In this study, existing heart rate signals in Physionet database were used. The dynamics of the signals were then studied both...

Measures of entropy and complexity in altered states of consciousness

Cognitive Neurodynamics October 20, 2017 Diego M. Mateos, Ramon Guevara Erra, Richard Wennberg et al. 124 citations

Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied...

Relationships between short and fast brain timescales.

Cognitive Neurodynamics August 23, 2017 Éva Déli, Arturo Tozzi, James F Peters

Brain electric activity exhibits two important features: oscillations with different timescales, characterized by diverse functional and psychological outcomes, and a temporal power law distribution. In order to further investigate the relationships between low- and high- frequency spikes in the brain, we used a variant of the Borsuk-Ulam theorem which states that, when we assess the nervous...

DOI: 10.1007/s11571-017-9450-4 (opens in new tab) Full text (opens in new tab) Consciousness Emotion regulation Quantum mechanics Behavioral neuroscience +3

Reflections on a giant of brain science: How lucky we are having Walter J. Freeman as our beacon in cognitive neurodynamics research.

Cognitive Neurodynamics December 2016 Robert Kozma

Walter J. Freeman was a giant of the field of neuroscience whose visionary work contributed various experimental and theoretical breakthroughs to brain research in the past 60 years. He has pioneered a number of Electroencephalogram and Electrocorticogram tools and approaches that shaped the field, while "Freeman Neurodynamics" is a theoretical concept that is widely known, used, and respected...

DOI: 10.1007/s11571-016-9403-3 (opens in new tab) Full text (opens in new tab) Electrocorticogram ecog Electroencephalogram EEG Freeman neurodynamics Intentionality +2

Towards a fourth spatial dimension of brain activity.

Cognitive Neurodynamics June 2016 Arturo Tozzi, James F Peters

Current advances in neurosciences deal with the functional architecture of the central nervous system, paving the way for general theories that improve our understanding of brain activity. From topology, a strong concept comes into play in understanding brain functions, namely, the 4D space of a "hypersphere's torus", undetectable by observers living in a 3D world. The torus may be compared...

DOI: 10.1007/s11571-016-9379-z (opens in new tab) Full text (opens in new tab) Borsuk-ulam theorem Brain Central nervous system Fourth dimension +2

Multi-dimensional modulations of α and γ cortical dynamics following mindfulness-based cognitive therapy in Major Depressive Disorder.

Cognitive Neurodynamics February 2015 Poppy L A Schoenberg, Anne E. M. Speckens

To illuminate candidate neural working mechanisms of Mindfulness-Based Cognitive Therapy (MBCT) in the treatment of recurrent depressive disorder, parallel to the potential interplays between modulations in electro-cortical dynamics and depressive symptom severity and self-compassionate experience. Linear and nonlinear α and γ EEG oscillatory dynamics were examined concomitant to an affective...

DOI: 10.1007/s11571-014-9308-y (opens in new tab) Full text (opens in new tab) EEG Power Erd/ers Oscillatory EEG Α-band coherence +1

Modulation of induced frontocentral theta (Fm-θ) event-related (de-)synchronisation dynamics following mindfulness-based cognitive therapy in Major Depressive Disorder.

Cognitive Neurodynamics October 2014 Poppy L A Schoenberg, Anne E. M. Speckens

Depressive severity has been associated with attenuated neocortical frontal midline theta (Fm-θ) power/evoked activity. Mindfulness-Based Cognitive Therapy (MBCT) has shown to be a successful novel intervention for Major Depressive Disorder (MDD), albeit precise working mechanisms remain elusive. We examined the hypothesis that MBCT would have modulating effects upon evoked Fm-θ power, in...

DOI: 10.1007/s11571-014-9294-0 (opens in new tab) Full text (opens in new tab) Event-related de-synchronisation erd/ers Fm-theta Oscillatory EEG Rumination

The neural binding problem(s).

Cognitive Neurodynamics September 1, 2012 Jerome A Feldman

The famous Neural Binding Problem (NBP) comprises at least four distinct problems with different computational and neural requirements. This review discusses the current state of work on General Coordination, Visual Feature-Binding, Variable Binding, and the Subjective Unity of Perception. There is significant continuing progress, partially masked by confusing the different versions of the NBP.

Sleep, neuroengineering and dynamics.

Cognitive Neurodynamics June 2012 Jens Christian Claussen, Ulrich G Hofmann

Modeling of consciousness-related phenomena and neuroengineering are fields that are rapidly growing together. We review recent approaches and developments and point out some promising directions of future research: Understanding the dynamics of consciousness states and associated oscillations, pathological oscillations as well as their treatment by stimulation, neuroprosthetics and...

DOI: 10.1007/s11571-012-9204-2 (opens in new tab) Full text (opens in new tab) Brain-computer interface Computational neuroscience Consciousness Dynamics +5

Consciousness related neural events viewed as brain state space transitions.

Cognitive Neurodynamics April 13, 2008 Gerhard Werner

This theoretical and speculative essay addresses a categorical distinction between neural events of sensory-motor cognition and those presumably associated with consciousness. It proposes to view this distinction in the framework of the branch of Statistical Physics currently referred to as Modern Critical Theory (Stanley, Introduction to phase transitions and critical phenomena, 1987; Marro...

Causal networks in simulated neural systems.

Cognitive Neurodynamics October 20, 2007 Anil K. Seth

Neurons engage in causal interactions with one another and with the surrounding body and environment. Neural systems can therefore be analyzed in terms of causal networks, without assumptions about information processing, neural coding, and the like. Here, we review a series of studies analyzing causal networks in simulated neural systems using a combination of Granger causality analysis and...