scholarly journals Emergence of qualia from brain activity or from an interaction of proto-consciousness with the brain: which one is the weirder? Available evidence and a research agenda

2016 ◽  
Author(s):  
Patrizio Tressoldi
Keyword(s):  
Cognitive Therapy ◽  
Placebo Effect ◽  
Neural Activity ◽  
Research Agenda ◽  
Brain Activity ◽  
Body Experiences ◽  
Brain Changes ◽  
The Brain

Abstract This contribution to the science of consciousness aims at comparing how two different theories can explain the emergence of different qualia experiences: meta-awareness, meta-cognition, the placebo effect, out-of-body experiences, cognitive therapy, meditation-induced brain changes, etc. The first theory postulates that qualia experiences derive from specific neural patterns, and the second one that qualia experiences derive from the interaction of a proto-consciousness with the brain’s neural activity. From this comparison, it will be possible to judge which one seems to better explain the different qualia experiences and to offer a more promising research agenda.

Mortal Body, Immortal Mind

2012 ◽  
Vol 17 (1) ◽  
pp. 5-26
Author(s):  
Hans Goller
Keyword(s):  
Brain Activity ◽  
The Body ◽  
Activity Data ◽  
Brain Functions ◽  
Body Experiences ◽  
Research Findings ◽  
The Relationship ◽  
Near Death Experiences ◽  
The Brain ◽  
Alternative Theories

Neuroscientists keep telling us that the brain produces consciousness and consciousness does not survive brain death because it ceases when brain activity ceases. Research findings on near-death-experiences during cardiac arrest contradict this widely held conviction. They raise perplexing questions with regard to our current understanding of the relationship between consciousness and brain functions. Reports on veridical perceptions during out-of-body experiences suggest that consciousness may be experienced independently of a functioning brain and that self-consciousness may continue even after the termination of brain activity. Data on studies of near-death-experiences could be an incentive to develop alternative theories of the body-mind relation as seen in contemporary neuroscience.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals Treating breathlessness via the brain: changes in brain activity over a course of pulmonary rehabilitation

2017 ◽  
Vol 50 (3) ◽  
pp. 1701029 ◽  
Author(s):  
Mari Herigstad ◽  
Olivia K. Faull ◽  
Anja Hayen ◽  
Eleanor Evans ◽  
F. Maxine Hardinge ◽  
...  
Keyword(s):  
Pulmonary Rehabilitation ◽  
Brain Activity ◽  
Brain Changes ◽  
The Brain

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals Macroscopic Cluster Organizations Change the Complexity of Neural Activity

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 214 ◽  
Author(s):  
Jihoon Park ◽  
Koki Ichinose ◽  
Yuji Kawai ◽  
Junichi Suzuki ◽  
Minoru Asada ◽  
...  
Keyword(s):  
Network Model ◽  
Neural Activity ◽  
Brain Activity ◽  
Inhibitory Neurons ◽  
Multiscale Entropy ◽  
Complex Network Theory ◽  
Macroscopic Structure ◽  
Specific Frequency ◽  
Neuron Group ◽  
The Brain

In this study, simulations are conducted using a network model to examine how the macroscopic network in the brain is related to the complexity of activity for each region. The network model is composed of multiple neuron groups, each of which consists of spiking neurons with different topological properties of a macroscopic network based on the Watts and Strogatz model. The complexity of spontaneous activity is analyzed using multiscale entropy, and the structural properties of the network are analyzed using complex network theory. Experimental results show that a macroscopic structure with high clustering and high degree centrality increases the firing rates of neurons in a neuron group and enhances intraconnections from the excitatory neurons to inhibitory neurons in a neuron group. As a result, the intensity of the specific frequency components of neural activity increases. This decreases the complexity of neural activity. Finally, we discuss the research relevance of the complexity of the brain activity.

scholarly journals Harmonic brain modes: a unifying framework for linking space and time in brain dynamics

2017 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

AbstractA fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at ‘rest’. Here, we introduce the concept of “harmonic brain modes” – fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; i.e. connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal and network-level changes in the brain across different mental states; (wakefulness, sleep, anaesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals Metacognition facilitates the exploitation of unconscious brain states

2019 ◽  
Author(s):  
Aurelio Cortese ◽  
Hakwan Lau ◽  
Mitsuo Kawato
Keyword(s):  
Reinforcement Learning ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Brain Activity ◽  
High Dimensional ◽  
Multivoxel Pattern Analysis ◽  
Brain States ◽  
Optimal Action ◽  
The Brain ◽  
Do So

AbstractCan humans be trained to make strategic use of unconscious representations in their own brains? We investigated how one can derive reward-maximizing choices from latent high-dimensional information represented stochastically in neural activity. In a novel decision-making task, reinforcement learning contingencies were defined in real-time by fMRI multivoxel pattern analysis; optimal action policies thereby depended on multidimensional brain activity that took place below the threshold of consciousness. We found that subjects could solve the task, when their reinforcement learning processes were boosted by implicit metacognition to estimate the relevant brain states. With these results we identified a frontal-striatal mechanism by which the brain can untangle tasks of great dimensionality, and can do so much more flexibly than current artificial intelligence.

Brain Activation Analysis of Voluntary Movement and Passive Movement Using Near-Infrared Spectroscopy

2012 ◽  
Author(s):  
Keiichi Watanuki ◽  
Kenta Hirayama ◽  
Kazunori Kaede
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Neural Activity ◽  
Near Infrared ◽  
Brain Activity ◽  
Brain Activation ◽  
Passive Movement ◽  
Color Mapping ◽  
The Subject ◽  
The Brain

During neural activity in the brain, humans transmit and process information and decide upon actions or responses. When neural activity occurs, blood flow and blood quantity increase in the tissue near the active neurons, and the ratio of oxygenated to deoxygenated hemoglobin in the blood changes. In this paper, we used near-infrared spectroscopy (NIRS) to determine the state of hemoglobin oxygenation at the cerebral surface and on that basis performed real-time color mapping of brain activity (the brain activation response) in the target regions. In this paper, we describe measurements of brain activation using NIRS so as to clarify any differences between conscious and unconscious movement. Bio-locomotion is divided into voluntary movements, which are made voluntarily and consciously, and passive movements, which are made passively and unconsciously. Accordingly, in this paper we investigate the brain activation associated with these two types of movements. The subject successively moves his/her lower legs through knee bends. We measure the brain activities while the subject, who is sitting on a chair moves back and forth. In addition, we carry out an experiment on the effects of the existence or nonexistence of movement caused by vibration on brain activities to consider the results.

scholarly journals Distinct Patterns of Neural Activity during Memory Formation of Nonwords versus Words

2007 ◽  
Vol 19 (11) ◽  
pp. 1776-1789 ◽  
Author(s):  
Leun J. Otten ◽  
Josefin Sveen ◽  
Angela H. Quayle
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Item Type ◽  
Event Related Potentials ◽  
Memory Formation ◽  
Electrical Brain Activity ◽  
Related Potentials ◽  
Neural Underpinnings ◽  
Incidental Encoding ◽  
The Brain

Research into the neural underpinnings of memory formation has focused on the encoding of familiar verbal information. Here, we address how the brain supports the encoding of novel information that does not have meaning. Electrical brain activity was recorded from the scalps of healthy young adults while they performed an incidental encoding task (syllable judgments) on separate series of words and “nonwords” (nonsense letter strings that are orthographically legal and pronounceable). Memory for the items was then probed with a recognition memory test. For words as well as nonwords, event-related potentials differed depending on whether an item would subsequently be remembered or forgotten. However, the polarity and timing of the effect varied across item type. For words, subsequently remembered items showed the usually observed positive-going, frontally distributed modulation from around 600 msec after word onset. For nonwords, by contrast, a negative-going, spatially widespread modulation predicted encoding success from 1000 msec onward. Nonwords also showed a modulation shortly after item onset. These findings imply that the brain supports the encoding of familiar and unfamiliar letter strings in qualitatively different ways, including the engagement of distinct neural activity at different points in time. The processing of semantic attributes plays an important role in the encoding of words and the associated positive frontal modulation.

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