Unique Contributions of Brain Stimulation to the Study of Consciousness: Where Neuroscience Meets Philosophy

CNS Spectrums ◽  
2010 ◽  
Vol 15 (3) ◽  
pp. 154-156
Author(s):  
Stefano Pallanti
Keyword(s):  
Ancient Greek ◽  
Eyes Closed ◽  
Technical Procedure ◽  
Eyes Open ◽  
Definition Of ◽  
The Individual ◽  
The Brain ◽  
Integrated Information Theory ◽  
Field Of Inquiry ◽  
Integrated Information

True progress in understanding how experience arises from the brain has been relatively slow when viewed from a historical perspective. Recently, several technologies to study and stimulate the brain have been applied to this field of inquiry. Such progress was made only 2,500 years after the ancient Greek philosopher Parmenides first adopted a technical procedure involving the application of formal logic instruments to explore the perception of experiences.At the phenomenological level, consciousness has been referred to as “what vanishes every night when we fall into dreamless sleep and reappears when we wake up or when we dream. It is also all we are and all we have: lose consciousness and, as far as you are concerned, your own self, and the entire world dissolves into nothingness”. According to the integrated information theory, consciousness is integrated information.The term “consciousness” therefore has two key senses: wakefulness and awareness. Wakefulness is a state of consciousness distinguished from coma or sleep. Having one's eyes open is generally an indication of wakefulness and we usually assume that anyone who is awake will also be aware. Awareness implies not merely being conscious but also being conscious of something. The broad definition of consciousness includes a large range of processes that we normally regard as unconscious (eg, blindsight or priming by neglected or masked stimuli).Both sleep and anesthesia are reversible states of eyes-closed unresponsiveness to environmental stimuli in which the individual lacks both wakefulness and awareness. In contrast to sleep, where sufficient stimulation will return the individual to wakefulness, even the most vigorous exogenous stimulation cannot produce awakening in a patient under an adequate level of general anesthesia.

scholarly journals The Mathematical Structure of Integrated Information Theory

2021 ◽  
Vol 6 ◽  
Author(s):  
Johannes Kleiner ◽  
Sean Tull
Keyword(s):  
Information Theory ◽  
Conscious Experience ◽  
Mathematical Structure ◽  
Starting Point ◽  
Special Cases ◽  
Axiomatic Definition ◽  
Definition Of ◽  
The Brain ◽  
Integrated Information Theory ◽  
Integrated Information

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution, we propound the mathematical structure of the theory, separating the essentials from auxiliary formal tools. We provide a definition of a generalized IIT which has IIT 3.0 of Tononi et al., as well as the Quantum IIT introduced by Zanardi et al. as special cases. This provides an axiomatic definition of the theory which may serve as the starting point for future formal investigations and as an introduction suitable for researchers with a formal background.

scholarly journals On the Operational Utility of Measures of EEG Integrated Information

2021 ◽  
Author(s):  
David Darmon ◽  
Tomas Watanabe ◽  
Christopher Cellucci ◽  
Paul E Rapp
Keyword(s):  
Principal Component ◽  
Information Criterion ◽  
Model Order ◽  
Information Measures ◽  
Eyes Closed ◽  
Condition Effect ◽  
Eyes Open ◽  
Open Versus ◽  
Healthy Participants ◽  
Integrated Information

Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel-Ziv measures of the first principal component and with three measures of integrated information including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes closed condition. If the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in common with other measures, integrated synergy was greater in the eyes open condition. Eyes open versus eyes closed separation was quantified by calculation of the between-condition effect size. Lempel-Ziv complexity of the first principal component showed greater separation than the measures of integrated information. The performance of the integrated information measures investigated here when distinguishing between indisputably different physiological states encourages caution when advocating for their use as measures of consciousness.

scholarly journals On the Non-uniqueness Problem in Integrated Information Theory

2021 ◽  
Author(s):  
Jake Hanson ◽  
Sara Imari Walker
Keyword(s):  
Information Theory ◽  
Logic Gate ◽  
Full Range ◽  
Mathematical Concept ◽  
Uniqueness Problem ◽  
Gate System ◽  
Optimization Routine ◽  
Definition Of ◽  
Integrated Information Theory ◽  
Integrated Information

Integrated Information Theory is currently the leading mathematical theory of conscious- ness. The core of the theory relies on the calculation of a scalar mathematical measure of consciousness, Φ, which is deduced from the phenomenological axioms of the theory. Here, we show that despite its widespread use, Φ is not a well-defined mathematical concept in the sense that the value it specifies is neither unique nor specific. This problem, occasionally referred to as “undetermined qualia”, is the result of degeneracies in the optimization routine used to calculate Φ, which leads to ambiguities in determining the consciousness of systems under study. As demonstration, we first apply the mathematical definition of Φ to a simple AND+OR logic gate system and show 83 non-unique Φ values result, spanning a substantial portion of the range of possibilities. We then introduce a Python package called PyPhi-Spectrum which, unlike currently available packages, delivers the entire spectrum of possible Φ values for a given system. We apply this to a variety of examples of recently published calculations of Φ and show how virtually all Φ values from the sampled literature are chosen arbitrarily from a set of non-unique possibilities, the full range of which often includes both conscious and unconscious predictions. Lastly, we review proposed solutions to this degeneracy problem, and find none to provide a satisfactory solution, either because they fail to specify a unique Φ value or yield Φ = 0 for systems that are clearly integrated. We conclude with a discussion of requirements moving forward for scientifically valid theories of consciousness that avoid these degeneracy issues.

scholarly journals Fronto-Temporal Analysis of EEG Signals of Patients with Depression: Characterisation, Nonlinear Dynamics and Surrogate Analysis

2020 ◽  
Author(s):  
Subha D. Puthankattil
Keyword(s):  
Time Series ◽  
Unipolar Depression ◽  
Temporal Analysis ◽  
Mental States ◽  
Eeg Signals ◽  
Biosignal Analysis ◽  
Eyes Closed ◽  
Eyes Open ◽  
Eeg Recordings ◽  
The Brain

The recent advances in signal processing techniques have enabled the analysis of biosignals from brain so as to enhance the predictive capability of mental states. Biosignal analysis has been successfully used to characterise EEG signals of unipolar depression patients. Methods of characterisation of EEG signals and the use of nonlinear parameters are the major highlights of this chapter. Bipolar frontopolar-temporal EEG recordings obtained under eyes open and eyes closed conditions are used for the analysis. A discussion on the reliability of the use of energy distribution and Relative Wavelet Energy calculations for distinguishing unipolar depression patients from healthy controls is presented. The potential of the application of Wavelet Entropy to differentiate states of the brain under normal and pathologic condition is introduced. Details are given on the suitability of ascertaining certain nonlinear indices on the feature extraction, assuming the time series to be highly nonlinear. The assumption of nonlinearity of the measured EEG time series is further verified using surrogate analysis. The studies discussed in this chapter indicate lower values of nonlinear measures for patients. The higher values of signal energy associated with the delta bands of depression patients in the lower frequency range are regarded as a major characteristic indicative of a state of depression. The chapter concludes by presenting the important results in this direction that may lead to better insight on the brain activity and cognitive processes. These measures are hence posited to be potential biomarkers for the detection of depression.

scholarly journals Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory

Entropy ◽  
2018 ◽  
Vol 20 (3) ◽  
pp. 173 ◽  
Author(s):  
Jun Kitazono ◽  
Ryota Kanai ◽  
Masafumi Oizumi
Keyword(s):  
Information Theory ◽  
Information Integration ◽  
Computational Cost ◽  
Simulated Data ◽  
Essential Property ◽  
Minimum Information ◽  
Neural Data ◽  
The Brain ◽  
Integrated Information Theory ◽  
Integrated Information

The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to the level of consciousness. IIT proposes that, to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that, if a measure of Φ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of Φ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of Φ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure Φ in large systems within a practical amount of time.

Individual differences in subjective and objective alertness during sleep deprivation are stable and unrelated

2003 ◽  
Vol 284 (2) ◽  
pp. R280-R290 ◽  
Author(s):  
Rachel Leproult ◽  
Egidio F. Colecchia ◽  
Anna Maria Berardi ◽  
Robert Stickgold ◽  
Stephen M. Kosslyn ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Performance Tasks ◽  
Performance Deficits ◽  
Circadian Phase ◽  
Eyes Closed ◽  
Eyes Open ◽  
And Performance ◽  
Independent Effects ◽  
The Individual ◽  
Subjective Alertness

This study examines the individual reproducibility of alterations of subjective, objective, and EEG measures of alertness during 27 h of continuous wakefulness and analyzes their interrelationships. Eight subjects were studied twice under similar constant-routine conditions. Scales and performance tasks were administered at hourly intervals to define temporal changes in subjective and objective alertness. The wake EEG was recorded every 2 h, 2 min with eyes open and 2 min with eyes closed. Plasma glucose and melatonin levels were measured to estimate brain glucose utilization and individual circadian phase, respectively. Decrements of subjective alertness and performance deficits were found to be highly reproducible for a given individual. Remarkably, there was no relationship between the impairments of subjective and objective alertness. With increased duration of wakefulness, EEG activity with eyes closed increased in the delta range and decreased in the alpha range, but the magnitudes of these changes were also unrelated. These findings indicate that sleep deprivation has highly reproducible, but independent, effects on brain mechanisms controlling subjective and objective alertness.

scholarly journals On the Operational Utility of Measures of Multichannel EEGs

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1434
Author(s):  
David Darmon ◽  
Tomas Watanabe ◽  
Christopher Cellucci ◽  
Paul E. Rapp
Keyword(s):  
Principal Component ◽  
Information Criterion ◽  
Task Condition ◽  
Model Order ◽  
Eyes Closed ◽  
Condition Effect ◽  
Eyes Open ◽  
Open Versus ◽  
Healthy Participants ◽  
Integrated Information

Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition and in the eyes-open condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel–Ziv measures of the first principal component, and with three measures of integrated information, including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes-closed condition. When the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in line with the other measures, integrated synergy was greater in the eyes-open condition. Eyes-open versus eyes-closed separation was quantified by calculating the between-condition effect size. The Lempel–Ziv complexity of the first principal component showed greater separation than the measures of integrated information.

scholarly journals How Morphological Computation Shapes Integrated Information in Embodied Agents

2021 ◽  
Vol 12 ◽  
Author(s):  
Carlotta Langer ◽  
Nihat Ay
Keyword(s):  
Information Integration ◽  
The Body ◽  
Information Flows ◽  
Morphological Computation ◽  
The One ◽  
Goal Directed Behavior ◽  
The Brain ◽  
Integrated Information Theory ◽  
Embodied Agent ◽  
Integrated Information

The Integrated Information Theory provides a quantitative approach to consciousness and can be applied to neural networks. An embodied agent controlled by such a network influences and is being influenced by its environment. This involves, on the one hand, morphological computation within goal directed action and, on the other hand, integrated information within the controller, the agent's brain. In this article, we combine different methods in order to examine the information flows among and within the body, the brain and the environment of an agent. This allows us to relate various information flows to each other. We test this framework in a simple experimental setup. There, we calculate the optimal policy for goal-directed behavior based on the “planning as inference” method, in which the information-geometric em-algorithm is used to optimize the likelihood of the goal. Morphological computation and integrated information are then calculated with respect to the optimal policies. Comparing the dynamics of these measures under changing morphological circumstances highlights the antagonistic relationship between these two concepts. The more morphological computation is involved, the less information integration within the brain is required. In order to determine the influence of the brain on the behavior of the agent it is necessary to additionally measure the information flow to and from the brain.

scholarly journals The Eastern heart and Galen's ventricle: a historical review of the purpose of the brain

2007 ◽  
Vol 23 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Mirza N. Baig ◽  
Faheem Chishty ◽  
Phillip Immesoete ◽  
Chris S. Karas
Keyword(s):  
Historical Review ◽  
Western Philosophy ◽  
Religious Literature ◽  
Medical Texts ◽  
Ancient Greek ◽  
Legal Proceedings ◽  
The Central Nervous System ◽  
Definition Of ◽  
The Brain

✓The seat of consciousness has not always been thought to reside in the brain. Its “source” is as varied as the cultures of those who have sought it. At present, although most may agree that the central nervous system is held to be the root of individualism in much of Western philosophy, this has not always been the case, and this viewpoint is certainly not unanimously accepted across all cultures today. In this paper the authors undertook a literary review of ancient texts of both Eastern and Western societies as well as modern writings on the organic counterpart to the soul. The authors have studied both ancient Greek and Roman material as well as Islamic and Eastern philosophy. Several specific aspects of the human body have often been proposed as the seat of consciousness, not only in medical texts, but also within historical documents, poetry, legal proceedings, and religious literature. Among the most prominently proposed have been the heart and breath, favoring a cardiopulmonary seat of individualism. This understanding was by no means stagnant, but evolved over time, as did the role of the brain in the definition of what it means to be human. Even in the 21st century, no clear consensus exists between or within communities, scientific or otherwise, on the brain's capacity for making us who we are. Perhaps, by its nature, our consciousness—and our awareness of our surroundings and ourselves—is a function of what surrounds us, and must therefore change as the world changes and as we change.

scholarly journals Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG)

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Ahmed M. A. Mohamed ◽  
Osman N. Uçan ◽  
Oğuz Bayat ◽  
Adil Deniz Duru
Keyword(s):  
Resting State ◽  
Sample Entropy ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Linear Discriminant ◽  
Frequency Bands ◽  
Eyes Closed ◽  
Eeg Data ◽  
Eyes Open ◽  
The Brain

An electroencephalogram (EEG) is a significant source of diagnosing brain issues. It is also a mediator between the external world and the brain, especially in the case of any mental illness; however, it has been widely used to monitor the dynamics of the brain in healthy subjects. This paper discusses the resting state of the brain with eyes open (EO) and eyes closed (EC) by using sixteen channels by the use of conventional frequency bands and entropy of the EEG signal. The Fast Fourier Transform (FFT) and sample entropy (SE) of each sensor are computed as methods of feature extraction. Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. EEG data were epoched with one-second-length windows, and they were used to compute the features to classify EO and EC conditions. Results showed that the LR and SVM classifiers had the highest average classification accuracy (97%). Accuracies of LD, KNN, and DT were 95%, 93%, and 92%, respectively. GNB gained the least accuracy (86%) when conventional frequency bands were used. On the other hand, when SE was used, the average accuracies of SVM, LD, LR, GNB, KNN, and DT algorithms were 92% 90%, 89%, 89%, 86%, and 86%, respectively.

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