Wednesday, 14 August 2019

Professor David Chalmers: "The Meta-Problem of Consciousness" | Talks at...

Annaka Harris On Consciousness | Rich Roll Podcast

More on Consciousness and the "hard problem of consciousness". What the mind is not!

(1) Scholarpedia is supported by Brain Corporation

Hard problem of consciousness

Robert J. Howell and Torin Alter (2009), Scholarpedia, 4(6):4948.

Dr. Robert J. Howell, Department of Philosophy, Southern Methodist University
Dr. Torin Alter, Department of Philosophy, University of Alabama

The hard problem of consciousness (Chalmers 1995) is the problem of explaining the relationship between physical phenomena, such as brain processes, and experience (i.e., phenomenal consciousness, or mental states/events with phenomenal qualities or qualia). Why are physical processes ever accompanied by experience? And why does a given physical process generate the specific experience it does—why an experience of red rather than green, for example?

(2) Hard problem of consciousness
From Wikipedia, the free encyclopedia
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For other uses, see Hard problem (disambiguation).

"...The hard problem of consciousness is the problem of explaining how and why sentient organisms have qualia or phenomenal experiences—how and why it is that some internal states are felt states, such as heat or pain, rather than unfelt states, as in a thermostat or a toaster.[1] The philosopher David Chalmers, who introduced the term "hard problem" of consciousness,[2] contrasts this with the "easy problems" of explaining the ability to discriminate, integrate information, report mental states, focus attention, etc. Easy problems are easy because all that is required for their solution is to specify a mechanism that can perform the function. That is, their proposed solutions, regardless of how complex or poorly understood they may be, can be entirely consistent with the modern materialistic conception of natural phenomena. Chalmers claims that the problem of experience is distinct from this set and that the problem of experience will "persist even when the performance of all the relevant functions is explained".[3]

The existence of a "hard problem" is controversial. It has been accepted by philosophers of mind such as Joseph Levine,[4] Colin McGinn,[5] and Ned Block[6] and cognitive neuroscientists such as Francisco Varela,[7] Giulio Tononi,[8][9] and Christof Koch,[8][9] but disputed by philosophers of mind such as Daniel Dennett[10] and cognitive neuroscientists such as Stanislas Dehaene[11] and Antonio Damasio.[12][failed verification][disputed (for: This contrasts with Damasio's acceptance of a "hard problem" in books such as "The Feeling of What Happens")  – discuss]

1 Chalmers' formulation
1.1 The hard problem
1.2 Easy problems
2 Other formulations
2.1 Historical predecessors
2.2 Similar recent arguments
3 Relationship to scientific frameworks
3.1 Neural correlates of consciousness
3.2 Integrated information theory
3.3 Global workspace theory
4 Responses
4.1 Proposed solutions
4.1.1 Weak reductionism
4.1.2 Dualism
4.1.3 Panpsychism and neutral monism
4.2 Rejection of the problem
4.2.1 Strong reductionism
4.2.2 Eliminative materialism
4.2.3 Other views
4.3 New mysterianism
5 See also
6 Notes
7 References
8 External links ..."


(3) The empty brain

Your brain does not process information, retrieve knowledge or store memories. In short: your brain is not a computer!

Your brain does not process information and it is not a computer – via @aeonmag

"...No matter how hard they try, brain scientists and cognitive psychologists will never find a copy of Beethoven’s 5th Symphony in the brain – or copies of words, pictures, grammatical rules or any other kinds of environmental stimuli. The human brain isn’t really empty, of course. But it does not contain most of the things people think it does – not even simple things such as ‘memories’. ..."

"...Worse still, even if we had the ability to take a snapshot of all of the brain’s 86 billion neurons and then to simulate the state of those neurons in a computer, that vast pattern would mean nothing outside the body of the brain that produced it. This is perhaps the most egregious way in which the IP metaphor has distorted our thinking about human functioning. Whereas computers do store exact copies of data – copies that can persist unchanged for long periods of time, even if the power has been turned off – the brain maintains our intellect only as long as it remains alive. There is no on-off switch. Either the brain keeps functioning, or we disappear. What’s more, as the neurobiologist Steven Rose pointed out in The Future of the Brain (2005), a snapshot of the brain’s current state might also be meaningless unless we knew the entire life history of that brain’s owner – perhaps even about the social context in which he or she was raised.

Think how difficult this problem is. To understand even the basics of how the brain maintains the human intellect, we might need to know not just the current state of all 86 billion neurons and their 100 trillion interconnections, not just the varying strengths with which they are connected, and not just the states of more than 1,000 proteins that exist at each connection point, but how the moment-to-moment activity of the brain contributes to the integrity of the system. Add to this the uniqueness of each brain, brought about in part because of the uniqueness of each person’s life history, and Kandel’s prediction starts to sound overly optimistic. (In a recent op-ed in The New York Times, the neuroscientist Kenneth Miller suggested it will take ‘centuries’ just to figure out basic neuronal connectivity.) ..."

Consciousness: The what, why and how
(Image: Nate Kitch)

THERE are a lot of hard problems in the world, but only one of them gets to call itself "the hard problem". And that is the problem of consciousness – how a kilogram or so of nerve cells conjures up the seamless kaleidoscope of sensations, thoughts, memories and emotions that occupy every waking moment.

The intractability of this problem prompted British psychologist Stuart Sutherland’s notorious 1989 observation: "Consciousness is a fascinating but elusive phenomenon… Nothing worth reading has been written on it."

The hard problem remains unsolved. Yet neuroscientists have still made incredible progress understanding consciousness, from the reasons it exists to the problems we have when it doesn’t work properly.

Is consciousness still fascinating? Yes. Elusive? Absolutely. But Sutherland’s final point no longer stands. Read on…

More on COGNITIVE SCIENCE and what it is not!

(A)  Cognitive Science

"...Cognitive Science
Cognitive science is the scientific study of the human mind. It is a highly interdisciplinary field, combining ideas and methods from psychology, computer science, linguistics, philosophy, and neuroscience. The broad goal of cognitive science is to characterize the nature of human knowledge – its forms and content – and how that knowledge is used, processed, and acquired.

Active areas of cognitive research in the Department include language, memory, visual perception and cognition, thinking and reasoning, social cognition, decision making, and cognitive development.

The study of cognitive science within BCS illustrates the department’s philosophy that understanding the mind and understanding the brain are ultimately inseparable, even with the gaps that currently exist between the core questions of human cognition and the questions that can be productively addressed in molecular, cellular or systems neuroscience. To bridge these gaps, several cognitive labs maintain a primary or secondary focus on cognitive neuroscience research. There are many opportunities for interaction and collaboration between cognitive and neuroscience labs across BCS and its related centers. ..."


"...Cognitive Science
First published Mon Sep 23, 1996; substantive revision Mon Sep 24, 2018
Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures. Its organizational origins are in the mid-1970s when the Cognitive Science Society was formed and the journal Cognitive Science began. Since then, more than one hundred universities in North America, Europe, Asia, and Australia have established cognitive science programs, and many others have instituted courses in cognitive science.

1. History
2. Methods
3. Representation and Computation
4. Theoretical Approaches
4.1 Formal logic
4.2 Rules
4.3 Concepts
4.4 Analogies
4.5 Images
4.6 Connectionism
4.7 Theoretical neuroscience
4.8 Bayesian
4.9 Deep learning
5. Philosophical Relevance
5.1 Philosophical Applications
5.2 Critique of Cognitive Science
5.3 Philosophy of Cognitive Science
Academic Tools
Other Internet Resources
Related Entries ..."

"...4.9 Deep learning
Artificial intelligence has been a central part of cognitive since the 1950s, and the most dramatic recent advances in AI have come from the approach of deep learning, which has produced major breakthroughs in fields that include game playing, object recognition, and translation. Deep learning builds on ideas from connectionism and theoretical neuroscience, but uses neural networks with more layers and improved algorithms, benefitting from faster computers and large data bases of examples. Another important innovation is combining learning from examples with reinforcement learning, resulting by 2016 in the world’s leading Go player, AlphaGo. Ideas from deep learning are spreading back into neuroscience and also beginning to influence research in cognitive psychology. The explanatory schema for deep learning is:

Explanation target:
How does the brain carry out functions such as cognitive tasks?
Explanatory pattern:
The brain has large numbers of neurons organized into 6–20 layers.
The brain has powerful mechanisms for learning from examples and for learning actions that are reinforced by their successes.
Applying learning mechanisms to layered neural networks makes them capable of human and sometimes even super-human performance.
Although deep learning has produced dramatic improvements in some AI systems, it is not clear how it can be applied to aspects of human thought that include imagery, emotion, and analogy. ..."

"...5.2 Critique of Cognitive Science
The claim that human minds work by representation and computation is an empirical conjecture and might be wrong. Although the computational-representational approach to cognitive science has been successful in explaining many aspects of human problem solving, learning, and language use, some philosophical critics have claimed that this approach is fundamentally mistaken. Critics of cognitive science have offered such challenges as:

The emotion challenge: Cognitive science neglects the important role of emotions in human thinking.
The consciousness challenge: Cognitive science ignores the importance of consciousness in human thinking.
The world challenge: Cognitive science disregards the significant role of physical environments in human thinking, which is embedded in and extended into the world.
The body challenge: Cognitive science neglects the contribution of embodiment to human thought and action.
The dynamical systems challenge: The mind is a dynamical system, not a computational system.
The social challenge: Human thought is inherently social in ways that cognitive science ignores.
The mathematics challenge: Mathematical results show that human thinking cannot be computational in the standard sense, so the brain must operate differently, perhaps as a quantum computer.
The first five challenges are increasingly addressed by advances that explain emotions, consciousness, action, and embodiment in terms of neural mechanisms. The social challenge is being met by the development of computational models of interacting agents. The mathematics challenge is based on misunderstanding of Gödel’s theorem and on exaggeration of the relevance of quantum theory to neural processes. ..."

Sunday, 11 August 2019

The Neuroscience of Consciousness – with Anil Seth

The Neuroscience of Consciousness – with Anil Seth


Published on 1 Feb 2017

Professor of Cognitive and Computational Neuroscience Anil Seth looks at the neuroscience of consciousness and how our biology gives rise to the unique experience of being you. You can also download this talk on our podcast: the Q&A here: for regular science videos: Anil provides an insight into the state-of-the-art research in the new science of consciousness. Distinguishing between conscious level, conscious content and conscious self, he describes how new experiments are shedding light on the underlying neural mechanisms in normal life as well as in neurological and psychiatric conditions. Anil Seth is Professor of Cognitive and Computational Neuroscience at the University of Sussex, where he is also Co-Director of the Sackler Centre for Consciousness Science. He is Editor-in-Chief of Neuroscience of Consciousness and is on the steering group and advisory board of the Human Mind Project. He has written popular science books, including 30 Second Brain, and contributes to a variety of media including the New Scientist, The Guardian, and the BBC. Subscribe for regular science videos: The Ri is on Twitter: Facebook: Tumblr: editorial policy: for the latest science videos:


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