ASSC 14
Tutorials well be held during the morning and
afternoon of Thursday the 24th of June. The exact scheduling will be
announced at a later date.
TUTORIAL 1
Informational Measures of
Consciousness: Integration,
Causality and State Structures
·
Igor Aleksander (
·
Summary: It has been suggested by Tononi (2008) that a network property, called information integration, closely corresponds to the amount and quality of consciousness in a system. The tutorial explains and examines this claim and shows participants how they can do simulations and experiments in this area. The strength of the above claim is briefly examined in the first part of the tutorial, as is the limited amount of evidence for the link between information integration and consciousness from EEG studies. Tononi has also supported his claim through comparisons between high-integration networks and areas of the brain that have been linked to consciousness. The second part of this tutorial will summarise the informational constructs that go into Tononi’s measurement of integration and familiarize the attendees with such constructs. The tutorial will introduce Anil Seth’s method of measurement using Granger Causality in networks and Murray Shanahan’s ideas on network structures that optimise their small-world topologies. The next part of the tutorial introduces the work done by the presenters on defining and measuring integration through discrete automata-theoretic models, simulations of which allow the results of integration (and lack thereof) to be displayed to the audience. There will be considerable opportunity for discussion and a practical demonstration in the last part of the tutorial.
Intended Audience: People working within consciousness who have come across algorithmic theories of consciousness, but not fully understood their motivation or applications. People who are sceptical about being able to approach consciousness through algorithmic approaches. People who have some knowledge of information and automata but would enjoy a revision of such concepts in the context of consciousness studies.
TUTORIAL 2
Neural Basis of
Suppression, Repression and Dissociation
·
Heather Berlin (
·
Michael C. Anderson (MRC
Cognition and Brain Sciences Unit,
Summary: A great deal of complex cognitive processing occurs at the unconscious level and affects how humans behave, think and feel. But scientists are only beginning to understand how this occurs on the neural level. Understanding the neural basis of consciousness requires an account of the neural mechanisms that underlie both conscious and unconscious thought, and their dynamic interaction. For example, how do conscious impulses, thoughts, or desires become unconscious (e.g. repression) or, conversely, how do unconscious impulses, desires, or motives become conscious (e.g. Freudian slips)? Reseach taking advantage of advances in technologies, like functional magnetic resonance imaging, has led to a revival and re-conceptualization of some of the key concepts of psychoanalytic theory, and progress at understanding their neural basis. According to psychoanalytic theory, unconscious dynamic processes defensively remove anxiety-provoking thoughts and impulses from consciousness in response to one’s conflicting attitudes. Within this classical framework, the processes that keep unwanted thoughts from entering consciousness include repression, suppression and dissociation. We will discuss studies from psychology and cognitive neuroscience in both healthy and patient populations that are beginning to elucidate the neural basis of these phenonema. Reconceptualizing classical psychoanalytic concepts within the context of modern cognitive psychology and cognitive neuroscience may facilitate their empirical study, allowing us to characterize the neural basis of the dynamic unconscious. This will ultimately lead to more effective treatment options for certain psychological disorders, and help us better understand our own consciousness.
Intended Audience: This tutorial will be aimed at neuroscientists, psychologists, philosophers, and clinicians who are interested in the relationship between neuroscience and psychoanalytic theories. After a brief introduction to the basic psychoanalytic concepts, we will present experimental evidence that is beginning to elucidate the neural basis of classic psychodynamic processes such suppression, repression and dissociation. Finally we will propose a clear trajectory for future neuroscientific studies in this emerging field.
TUTORIAL 3
What are mental
representations, and does the mind need them?
·
Paula Droege (
Summary: One serious obstacle to interdisciplinary research is disagreement or misunderstanding about pivotal terms. ‘Representation’ is central to many philosophical theories of consciousness and figures importantly in psychology and neuroscience as well. Some questions raised by the role of representation in these fields are: What does it mean to say the mind is ‘representational’? Are we conscious only of our own mental representations and indirectly aware of the world, or are we conscious of the world itself by means of our representations? Is the content of a representation determined by computational or functional relations, by consciousness, or in some other way? What is the difference between representation and meta-representation? The tutorial will begin with a discussion of how the concept of ‘representation’ is used in each of the participants’ fields. We will then survey a variety of ways ‘representation’ is defined in philosophy of mind (Locke, Husserl, Fodor, Millikan), psychology (Plyshyn, Perner), and neuroscience (Hebb, Tononi, Varela). Finally, we will consider some objections to representation as necessary to the nature of the mind (Noë).
Intended Audience: The presentations will assume no background in any of the fields considered. The level of the workshop will be introductory with an aim toward clarifying concepts across fields. Discussion is the means toward achievement of this aim as participants evaluate the use of ‘representation’ in their own fields and compare this use with the way the term figures in other fields.
TUTORIAL 4
Train your brain ! Understanding and applying the neurofeedback technique
·
Kerstin Hoedlmoser (
·
Manuel Schabus (
Summary: Neurofeedback (NF) is a very sophisticated type of biofeedback and refers to an operant conditioning paradigm. Patients are instructed to learn to self regulate distinct parameters of their cortical activity (e.g., amplitude, frequency or coherence) as assessed by the means of electroencephalography (EEG). Today NF is mainly used as a therapeutic tool to treat different types of disorders like epilepsy, ADHD or insomnia. Furthermore, the exciting progress in the field of brain-computer-interface enabling “locked-in” and partly paralysed patients to communicate or to produce movements, respectively, by voluntarily controlling neuronal activity benefits from this specific method. More recent research focused on healthy individuals providing evidence that subjects who are able to gain control over different EEG parameters might even succeed in increasing performance levels in various cognitive tasks. Taken together there is a growing body of evidence suggesting that it is feasible to learn to regulate specific brain oscillations. Thereby it becomes possible to directly counteract the maladaptive brain activity which is associated with various disorders such as epilepsy, ADHD or insomnia.
Intended Audience: Researchers from behavioural/experimental, neuroscientific, and philosophical backgrounds, psychologists, physicians and students who wish to build up basic knowledge concerning the field of Neurofeedback. This workshop will provide an introduction to the field of Neurofeedback and therefore participation does not require any expert knowledge.
TUTORIAL 5
Solving the Inverse
Problem in Human EEG/MEG and applications to brain connectivity
·
Stanley Klein (UC Berkley, USA)
Summary: In the past two years several groups have made progress in combining MRI/fMRI with EEG/MEG to localize human cortical activity with msec accuracy in time and mm accuracy in position in response to visual stimuli. This major step forward in solving the nearly ill-conditioned inverse problem will be the topic of this tutorial. If one had: a) perfect fMRI for V1, V2, V3, V3a retinotopy; b) perfect MRI specifying cortical shape; c) perfect boundary element forward model (BEM) for EEG and MEG; d) perfect stimuli that only activate V1, V2, V3, V3a, etc. then the inverse problem would be easily solved. The first two thirds of the tutorial will discuss methods for solving the inverse problem in an imperfect world and in the process substantially improving fMRI , MRI and BEM accuracies. Discrete dipole methods will be compared to distributed dipole methods. The last third of the tutorial will discuss important implications of the ability to isolate signals in source space rather than electrode/sensor space. In particular we will discuss issues of determining brain connectivity through phase coherence and issues of the causal flow of information across brain areas. These latter approaches are especially useful for isolating the neural correlates of awareness. Some familiarity with the above issues, including principle component analysis, would be helpful, but not essential.
Intended Audience: This tutorial is aimed for people with some familiarity with issues of EEG/MEG source localization. I will use some math, but nothing fancy.
TUTORIAL 6
Decoding visual and
mental content from human brain activity
· Frank Tong (Vanderbilt University, USA)
Summary: Is it possible to determine what a person is seeing,
experiencing, attending to, or actively remembering, from noninvasive
measures of that person’s brain activity? Might it even be possible to
reconstruct what a person is seeing or imagining from fMRI measures of
brain activity? This tutorial will discuss recent advances in
neuroimaging that allow for the extraction of detailed visual
information from fMRI activity patterns obtained from the human visual
cortex. From these activity patterns, it is possible to determine what
basic visual features, complex objects or natural scenes a person might
be looking at with very high accuracy. Moreover, it is possible to
decode top-down aspects of processing, such as attended or remembered
visual items from measured patterns of brain activity. This tutorial
will survey the methods and findings of recent fMRI decoding studies,
including those by the Dr. Tong’s lab and other labs. The tutorial will
cover both the technical and conceptual fundamentals of “brain
reading”, and should be suitable for people from a broad range of
backgrounds, with one component emphasizing the more technical and
mathematical aspects of pattern classification. There will be extensive
opportunity for questions and open discussion about the strengths and
limitations of these fMRI decoding methods, and how they might
contribute to scientific understanding of how mental states are
represented by different brain states.
Intended Audience: Introductory session aimed at a multi-level
audience. The tutorial should be suitable for novices and experts
alike, covering state of the art methods and findings, but described in
a way that should be accessible to a broad audience.
TUTORIAL 7
Attention and Consciousness:
Two Distinct Brain Processes
·
Christof Koch (
Building upon the successful tutorial at ASSC 10&11, we review and update the recent evidence showing 1) that invisible stimuli can be attended with top-down attention and can influence subsequent behavior, 2) that to observe some behavioral evidence of unconscious processing, top-down attention to invisible stimuli is necessary and 3) that under some conditions top-down attention and consciousness can result in opposite effects.
The philosopher Ned Block has argued on conceptual grounds for two forms of consciousness, access (A) and phenomenal (P) consciousness. Given the data, it may be possible that A is equivalent to top-down attention and read-out (which usually, but not always, goes hand-in-hand with P) while P can occur with or without top-down attention.
Intended Audience: Philosopher, psychologists, and neuroscientists who are interested in the relationship between attention and consciousness. We also aim to introduce various methods with ample examples on how to manipulate the two processes independently for future empirical neuroscientific studies of attention and consciousness.
TUTORIAL 8
Signal detection theory and
distinguishing conscious vs. unconscious
·
Hakwan Lau (
Summary: Signal detection theory (SDT) is a standard tool for analyzing psychophysical data. Applying detection-theoretic analysis (i.e. reporting d', decision criterion) is the gold standard in research in sensory perception, be it neuroimaging or neurophysiology. SDT analysis is also often applied to studies in consciousness, and has crucial implications for distinguishing conscious vs. unconscious processes. Moreover, SDT approaches sometimes yield importantly counter-intuitive interpretations. In this tutorial we will go through the basic formalisms of detection theory, assuming no background in the area. We will ensure that participants without mathematical training will be able to acquire the graphical intuitions that are needed to understand advanced analyses. We then review several topics in consciousness where detection-theoretic analysis has provided critical and important insights. These include identifying and distinguishing conscious vs. unconscious processes, blindsight, change blindness, time perception, Libet's experiments on volition, postdecision wagering, confidence ratings, exclusion tasks, and the topic of unconscious inhibition. The relationship between signal detection theory and Bayesian decision theory will also be discussed. We encourage participants to discuss their own research paradigms so that SDT applications can be explored.
Intended Audience: We intend to begin with a basic introduction to SDT accessible to everyone, but also to discuss various advanced applications to consciousness research.
