ACADEMIC COURSES FOR 2015Course

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International Conference 2015

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The following Courses will be offered by NIAS Consciousness Studies Programme during the second half of 2015. If you wish to enroll for any of the Courses below write to niasconsciousnessprogramme@gmail.com Please read the Course details to know about Course requisites. Last date to send your statement of interest is 7 August 2015.

Course CSP-2-1: An Introduction to Consciousness Studies (2 credits) Coordination and Concept: Sangeetha Menon
Course Instructors: Sangeetha Menon, V V Binoy, Sisir Roy, Lalit M Patnaik, Venkat Rayudu, Anindya Sinha, and Gagan Deep Kaur
Course CSP-1-2: Conceptual Mathematics for Cognitive Neuroscience ( 1 credit) Course Instructor and Concept: Venkat Rayudu
Course CSP-2-3: Computation and Cognition: An Introduction  (2 credits) Course Instructor and Concept: Lalit Patnaik
Course CSP-2-4: Brain, Self and Cognition: Building Concepts & Frameworks ( 2 credits) Course Intructor and Concept: Sangeetha Menon and Gagan Deep Kaur


Course CSP-2-1: An Introduction to Consciousness Studies (2credits)
Timing: Wednesdays 3.30 pm (NIAS Lecture Hall) - To enrol write to niasconsciousnessprogramme@gmail.com before 7 August 2015
Coordination and Concept: Sangeetha Menon
Course Instructors: Sangeetha Menon, V V Binoy, Sisir Roy, Lalit M Patnaik, Venkat Rayudu,
Anindya Sinha and Gagan Deep Kaur
The Course on "An Introduction to Consciousness Studies" will focus on the fundamental challenges and questions in the field that pertain to disciplines such as cognitive sciences, computational neuroscience, neurophilosophy, neuropsychology and social cognition. There will 2 SCH per week and enrolled students are expected to credit the course attending not only the classes but also participating in the course assignments. Course instructors will introduce students to multiple topics in the filed.
Pre-requisites: A strong interest in consciousness studies, and a flair to ask fundamental questions on mind.
Subject & Course Instructor Description Recommended Reading Assignments

Introduction to Consciousness

Sangeetha Menon
(1 class)

In the recent times the central question that fundamental disciplines such as neuroscience, philosophy and psychology ask about mind are centred on the notion and experience of the person. While an important correlate of consciousness that all disciplines and all people are interested is awareness and different degrees of it, there are other aspects that explain consciousness in finer ways. The character of the person, his or her ability to exercise choice-making, freewill, and take responsibility of the acts and its consequences take us to the realm of social cognition, decision-making, and the wellbeing itself. In this class we will explore basic definitions, functions and nature of the puzzle of consciousness.

Chalmers, D. (1995). The Puzzle of Conscious Experience. Scientific American(273), pp. 62-68.

McGinn, C. (1997). The Character of Mind: An Introduction to the Philosophy of Mind. Oxford University Press.

Cole, J. (2004). Still Lives: Narratives of Spinal Cord Injury. MIT Press.

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Social Cognition

V V Binoy
(2 classes)

Life of social species, including human beings, demand higher degrees of cognitive abilities, especially for encoding socially relevant information, consolidating it into memory, retrieving such information while taking decisions regarding him/herself or others, for a stress free life and survival. The importance of the branch of social psychology focusing “mental processes involved in perceiving, attending to, remembering, thinking about”, and making sense of the actions and activities of conspecifics and heterospecific individuals, popularly known as social cognition is manifold in this age of enhanced interaction between diverse cultures brought in by the modern technologies that helped the humankind to tide over the spatial and temporal constrains. The two-lecture module will elaborate various dimensions of social cognition such as perception of social contexts, mechanisms and neural correlates of meaning making, familiarity and social memory, personality traits, theory of mind, influence of culture on cognition, social decision-making etc. and its implication for the wellbeing of both humans and other social organisms.

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Computational Neuroscience

Lalit M Patnaik
(2 classes)

 

Computational neuroscience is the study of approaches to understand the functions of the nervous system at biophysical, circuit, and system levels that guide the foundations of information processing in the brain. Methods adopted include theoretical analysis and modeling of neurons and their networks.
Topics:
- Basic neurobiology techniques for understanding the behavior of cells and circuits in the brain
- Neural encoding and decocding techniques
- Single neuron models
- Network models
- Plasticity and learning

Fundamentals of Computational Neuroscience, Thomas Trappenberg, Oxford University Press,2002

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems,Peter Dayan  and Larry Abbott, MIT Press,2001

Term paper from literature survey,  and assignment problems on numerical computations

Neurobiology

Venkat Rayudu
(3 classes)

The goal of neuroscience is to understand how we see, think, feel, and act in terms of the electrical activity of neurons in our brains. The Neurophysiology component of the course  introduces various methods of recording electrical activity from neurons.  The Neurophysiology component consists of three lectures.  In Lecture I, we give an overview of neuronal electrical signaling such as synaptic potentials and action potentials.  In Lecture II, we will discuss the techniques used to record electrical signals such as patch-clamp recording of ionic currents and single-unit recording from the brains of awake-behaving primates.  In Lecture III, we will illustrate how these recording methods are used in the neuroscientific investigations of learning and perception.  The course lectures are based on selected chapters from the Principles of Neural Science textbook.

Kandel ER et al. (2012) Principles of Neural Science, 5th edn. McGraw Hill Education, New York.
Chapters:
Nerve Cells, Neural Circuitry, and Behavior, pp. 21-38
Ion Channels, pp. 100-124
Membrane Potential and the Passive Electrical Properties of the Neuron, pp. 126-147
Propagated Signaling: The Action Potential, pp. 148-171
Overview of Synaptic Transmission, pp. 177-188
Synaptic Integration in the Central Nervous System, pp. 210-235

Write a review, in the format of Nature Neuroscience News and Views , of a recent paper in Nature Neuroscience on Neurophysiology.

Vision

Venkat Rayudu
(4 classes)

Vision research, beginning with the cones of color vision and orientation-tuned visual cortical neurons, has been paving the way for neuroscientific investigations of consciousness.  Foundational questions of consciousness studies, such as the binding problem, are addressed in terms of the modality of vision.  The Vision component of the course consist of four lectures.  In Lecture I, we provide an overview of how our brains construct, based on given visual stimuli, what we see.  In Lecture II, retinal processing of visual information is discussed.  In Lecture III, orientation-sensitive neurons of the striate cortex and motion direction-sensitive neurons of the middle temporal area are studied in depth.  In Lecture IV, neural mechanisms mediating the influences of context, meaning, and memory on visual perception are examined.  The course lectures are based on selected chapters from the Principles of Neural Science textbook.

Kandel ER et al. (2012) Principles of Neural Science, 5th edn. McGraw Hill Education, New York.
Chapters:
The Constructive Nature of Visual Processing, pp. 556-576
Low-Level Visual Processing: The Retina, pp. 577-601
Intermediate-Level Visual Processing and Visual Primitives, pp. 602-620
High-Level Visual Processing: Cognitive Influences, pp. 621-637

Write a review, in the format of Neuron Previews, of a recent paper in Neuron on Vision.

Social Cognition and Consciousness in Nonhuman Primates

Anindya Sinha
(2 classes)

Social primates appear to be knowledgeable about one another's behaviour to different extents. But do they know as much about one another's beliefs and intentions? Are they adept at recognising the similarities and differences between their own and others' states of mind? What are the mental mechanisms that allow them to establish cultural traditions? Attribution of mental states to other individuals could manifest itself in diverse situations as, for example, when individual animals closely observe the actions of others or when they deceive each other in the social sphere. Explorations into the phenomena of social learning and phenotypic flexibility also contribute to our understanding of distributed cognition, a relatively new approach that treats behavioural coordination and communicative interactions in primates as directly observable cognitive events. Can consciousness be defined in non-verbal primates? What characterises nonhuman primate consciousness? This module will examine some of the theoretical and philosophical issues in animal cognitive psychology, with a particular focus on our understanding of social cognition in wild bonnet macaques, a primate species found commonly in peninsular India.

 

 

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Decision making and modeling in cognitive science
Sisir Roy

(2 to 3 classes)

The process of making a decision is a deliberative process whose ultimate goal is the results in the commitment to a categorical proposition. A closest analogy to this process is a judge or jury that must take time to weigh the evidences for there is always possible a set of alternatives, among which one needs to choose a preferred option or course of action out of this set of alternatives.  Since decision making is a basic mental process, the decision with precision is one of the fundamental requirements for cognitive processes of human beings. Hence, it is necessary to model the uncertainty so as to make a precise decision.

Yingxu Wang, Guenther Ruhe(2007)The Cognitive Process of DecisionMaking : Int’l Journal of Cognitive Informatics and Natural Intelligence, 1(2), 73-85

Roberts, F. S. (1979); Measurement theory with applications to decision making, utility and the social sciences.; London, UK: Addison-Wesley.

Nick Chater, Joshua B.Tenebaum and Alan Yulle,p(2006).; Probabilistic models of cognition : conceptual foundations : Trends in cognitive sciences,10(7), 287-291

Körding KP, Wolpert DM (2006); “Bayesian decision theory in  sensorimotor control.” Trends Cogn. Sci, 10(7):319-26.

Review of a Paper & Discussion

Can Machines be Conscious?

LM Patnaik
(2 classes)

The development of conscious machines faces a number of challenging issues. Consciousness-related cognitive processes  such as perception, imagination, motivation, and inner speech are a technical challenge. An artificially conscious machine should incorporate all these processes  and motor responses in a seamless interactive manner. We present an overview of the various underlying issues and discuss whether machines with consciousness can be built.

Topics:
Testing consciousness, artificial consciousness cognition, cognitive architectures.

Consciousness and Robot Sentience, Pentti O Haikonen,World Scientific,2012

Term paper from survey of the latest literature
Cognitive Ethnography
Gagan Deep Kaur

(2 classes)

Cognitive Ethnography is a research methodology which investigates the socio-cultural influences on cognition through ethnographic methods, viz. participant observation and semi-structured interviews. Pioneerd by Edwin Hutchins in 1990s, it takes cognition to be situated and distributed among people, artifacts, culture  etc. and uncovers how cognition occurs in real-world settings. Interpretative Phenomenological Analysis (IPA), through ethnographic methods, explores how participants create meanings in their day-to-day world and thus display close ties with Cognitive Ethnography.  

Edwin Hutchins. Cognition in the Wild. (Excerpt)

Morana A and Hutchins E. 2004. ‘I See What You Are Saying: Action as Cognition in fMRI Brain Mapping Practice.’

Williams R. 2006. ‘Using Cognitive Ethnography to Study Instruction.’ Proceedings of the 7
The International Conference of the Learning Sciences. . Mahwah, NJ: Lawrence Erlbaum Associates

Smith JA and Osborne M. 2003. Interpretative Phenomenological Analysis. . In J.A. Smith (Ed.), Qualitative Psychology: A Practical Guide to Research Methods. London: Sage.

Larkin M, Eatough V and Osborn M. 2011. ‘Interpretative Phenomenological Analysis and

Embodied, Active, Situated Cognition.’ Theory and Psychology. 21[3]: 318-337
Review of a Paper & Discussion
Science and Signs of Self in Consciousness Studies

Sangeetha Menon
(2 classes)

This class will help raise fundamental questions that connect behaviour with the body and the self. We will do a critical appraisal of some of the mainstream thinking in neuroscience, and neuropsychology, on body, experience, and consciousness. In the process we will try and develop an open-ended thinking pattern to develop basic concepts in conceiving the exteriority of the self and interiority of the body, in the light of studies on the subjective nature of consciousness. Some of the questions that will engage us in this discussion are:

  1. What is body? Is it interior, exterior, or both?
  2. What is self? Is it interior, exterior, or both?
  3. How is body different from self?
  4. What is personal identity?
  5. Does experience belong to body or self?
  6. What is body-sense constituted of?
  7. What is self-sense constituted of?
  8. To which sense does ‘experience’ belong?
  9. What is experience? Who owns it? Who is the agent?
  10. Is there a minimal self?
  11. Is there an extended self?
  12. Is self a ‘bland’ entity or is it rich with feelings, emotions, perspectives, free-will and purpose-orientation?
  13. Why is it important to distinguish body from self?
  14. What is behaviour? Are we mechanistic entities who have behaviours and controlled by genetically and environmentally determined factors?
  15. Who is a person? Are behaviourism and behaviour oriented approach adequate to represent human self-hood? Is ‘behaviour’ an out-dated expression with a biological overload but less humanistic tones?

Gallagher, S. (2000). Philosophical Conceptions of the Self: Implications for Cognitive Science. Trends in the Cognitive Sciences, 4(1), 14-21.

Metzinger, T. (2003). Being no One: The Self-model Theory of Subjectivity. MIT Press.

Science of Consciousness

Minimal Self

William James' concept of Self

Thought Experiment study

Case study (written)

Final Course Assignment: Term paper/essay
(Grading will be based on class attendance, class participation, completion of assignments given by the Course instructors, and the final term paper/essay
 
Course CSP-1-2: Conceptual Mathematics for Cognitive Neuroscience (1 credit)
Course Instructor and Concept: Venkat Rayudu
To enrol write to niasconsciousnessprogramme@gmail.com before 7 August 2015

The Conceptual Mathematics for Cognitive Neuroscience course provides a first introduction to category theory and its applications to cognitive neuroscience.  Basic concepts of category theory are introduced in a manner comprehensible to a student body of diverse academic backgrounds.  Major topics of category theory that are covered in the course include: category of dynamical systems, structure-preserving map, universal mapping properties, and truth value object.  Simple category theoretic formalizations of the problems of cognitive neuroscience such as neural dynamics, learning, perception, memory, and the binding problem are discussed throughout the course.

Pre-requisites: The course is based on Lawvere & Schanuel’s Conceptual Mathematics textbook, which is addressed to total beginners.  The concepts and constructions of category theory are introduced informally in terms of examples drawn from everyday experience.  No mathematical training beyond that of high school mathematics is required for registering / auditing the course.
Subject & Course Instructor Description Recommended Reading Assignments
Conceptual Mathematics for Cognitive Neuroscience

Course Instructor:
Venkat Rayudu

Objectives of the Course:
One of the main objectives of the Conceptual Mathematics for Cognitive Neuroscience course is to demystify mathematics and make mathematical sciences more user-friendly, especially to students of cognitive neuroscience.  Upon completion of the course, students will have a clear understanding of: (i) the basics of category theory, which embodies the general principles of mathematical calculations, and (ii) the basics of extracting the mathematical content of the subject matter of cognitive neuroscience.  The course will prepare students for an in-depth study of advanced category theoretic accounts of consciousness such as Ehresmann & Vanbremeersch’s Memory Evolutive Systems.

Student Workload:
The course syllabus will be covered in 16 weeks, with one 1-hour lecture per week.  Successful completion of the course involves: (i) class participation, (ii) take-home assignments, (iii) class presentation, (iv) exams, and (v) term paper.  There will be two take-home assignments of exercises from the Conceptual Mathematics textbook and one class presentation of exercises selected by the student.  The topic of the term paper is also selected by the student and in consultation with the instructor.

Topics:
Course lectures are based on the corresponding material in Lawvere & Schanuel’s Conceptual Mathematics textbook.

  1. Sets, Functions, and Composition
  2. Definition of CATEGORY
  3. Category of Dynamical Systems
  4. Structure-Preserving Map
  5. Neural Dynamics
  6. Universal Mapping Property
  7. Subjective Instruments of Knowing
  8. Definition of SUM
  9. Definition of PRODUCT
  10. Colimits and The Binding Problem
  11. Definition of ACTION
  12. Recognition: Action of Memory on Sensation
  13. Part-Whole Relations and Truth Value Objects
  14. Objectification of Observations: Kinship
  15. Three-Stage Variable Sets and Perception
  16. Memory Evolutive Systems


Class Participation: 5%
Take-home Assignments: 10% (2 x 5)
Class Presentation: 10%
Mid-term Exam: 20%
Term Paper: 25%
Final Exam: 30%

 
Course CSP-2-3: Computation and Cognition: An Introduction  (2 credits)
Course Instructor and Concept: Lalit Patnaik
To enrol write to niasconsciousnessprogramme@gmail.com before 7 August 2015

The goal of cognitive science is to understand how the mind works.  The nature of mental representations and their transformations constitute the core content of the course.  This course discusses some of the foundational frameworks for thinking about the mind in computational terms.  Models of learning, memory, reasoning, and decision-making involved in cognition are introduced from a computational perspective.  Major topics covered in the course include Content-Addressable Memory, Hopfield model, Perceptron network, Back-propagation algorithm, Unsupervised learning, Adaptive resonance theory, and Topographic mapping.  A suite of mathematical and computational tools used in cognitive and information sciences will be introduced.

Pre-requisites: Familiarity with basic Linear Algebra, Discrete Mathematics and Matlab programming is helpful, though these will be specifically introduced in the course.
Subject & Course Instructor Description Recommended Reading Assignments
Computation and Cognition: An Introduction  

Course Instructor: Lalit M Patnaik

Objectives of the Course:
The content-addressable memories of neural networks, wherein content itself serves as the address of memory location, brought about a paradigm-shift in the way we think about memory.  So did unsupervised learning algorithms, which showed how learning can take place even in the absence of explicit error correction.  With clear illustrations such as these, the course aims to enable students appreciate the advances in our understanding of the workings of the mind brought about by computational approaches.

Student Workload:
The course syllabus will be covered in 15-16 weeks, with two 1-hour lectures per week.  In addition to class participation, successful completion of the course requires the following: (i) a mid-term and final exam, (ii) a seminar presentation, (iii) a take-home assignment, and (iv) Matlab simulation.


Topics:

  1. Neuroscientific Roots
  2. Historical Overview of Neural Networks
  3. Associative Memory
  4. Hebbian Learning
  5. Hopfield Model
  6. Content-Addressable Memories
  7. Introduction to Matlab
  8. Feed-Forward Networks
  9. Perceptrons
  10. Back-Propagation Algorithm
  11. Unsupervised Learning
  12. Competitive Learning
  13. Adaptive Resonance Theory
  14. Topographic Feature Mapping
  15. Review of Computer Organization and Architecture
  16. Problem Solving Methodology
  17. Mathematical Logic and Reasoning
  18. Knowledge Representation
  19. Basic Principles of Theory of Computation
  20. Basic Concepts of Artificial Intelligence

Hertz, J. A., Krogh, A. S., and Palmer, R. G. (1991) Introduction to the Theory of Neural Computation. New York: Addison-Wesley.

References:
Kandel, E. R., Schwartz, J. H., Jessell, T. M., Siegelbaum, S. A., and Hudspeth, A. J. (2012) Principles of Neural Science (5th edn). New York: McGraw Hill Education, pp. 1581-1617.

Bechtel, W., and Graham, G. (2006) A Companion to Cognitive Science. New York: Blackwell Publishing.

Michael I. Posner(Ed.)(1989) Foundations of  Cognitive Science.Cambridge,Massachusetts:The MIT Press

Take-home Assignment: 15%
Seminar Presentation: 20%
Mid-term Exam: 15%
Matlab Simulation: 10%
Final Exam: 40%

 

Course CSP-2-4: Brain, Self and Cognition: Building Concepts & Frameworks ( 2 credits Writing Course) 
Course Instructor and Concept: Sangeetha Menon & Gagan Deep Kaur

The fundamental question for philosophy of mind and contemporary cognitive science is how knowledge is represented in the brain? How mind is related to brain, body and world? In what senses, cognition is embodied and situated? Is cognition extended as well as some recent theorists held? Within this large spectrum of debates and perspectives hailing from philosophy and cognitive science, this Course will focus on building philosophical concepts and frameworks to understand self.

Pre-requisites: This Course being primarily a Writing Course is open only to students who are doctoral scholars at NIAS and preferably working (or intend to work) under the NIAS Consciousness Studies Programme.
Subject & Course Instructor Description Recommended Reading Assignments

Brain, Self and Cognition: Building Concepts & Frameworks

Sangeetha Menon & Gagan Deep Kaur

Objectives of the Course: The goal of this Course is to equip the student to build concepts and frameworks in the area of philosophy of mind, and also neurophilosophical approaches to the concept of self.

Student Workload: This Course being primarily a writing course is intended to build concepts and frameworks that help the student to develop the proposal for the doctoral study, will involve several writing assignments based on case studies and literature survey.

Topics:
There are 3 broad sections of the course. Every section has one guiding question which directs the unfolding of the various approaches related to it over the time. We discuss these approaches in terms of theories that tried to answer that guiding question. Every section will analyse case study of a particular cognitive disorder/phenomena in which the relevance of those philosophical theories will be tested.

1. Knowledge representation:
Guiding question: how knowledge is represented in the brain?

o Rationalism
o Empiricism
o A skeptic’s challenge!

Case study: Change-Blindness

2. Mind and brain
Guiding question: how mind is related to brain?

- Dualism
o Interactionism (Descartes)
o Parallelism (Leibniz)

- Monism
o Idealism
o Physicalism
 Behaviourism (Ryle, Skinner)
 Mind-Brain Identity (Place, Smart and Armstrong)
 Functionalism (Putnam)
o Computational Theory of Mind (Putnam)
 Emergentism
 Eliminative materialism (Churchlands)

- Embodied cognition
o Embodied cognition (Merleau Ponty)
o Situated cognition (Heidegger)
o Extended mind (Clark and Chalmers)

Case study: Experiential Blindness, Blindsight

3. Self
Guiding question: how self relates to brain and body?

- Self and its brain
o Neural basis of self
o Self-awareness
 Self-recognition tasks
 Self-reference effects
o Fragmented selves

Case study: Schizophrenia

- Body and self
o Embodiment
o Body schema and Body-ownership
o Cyborg bodies

Case study: Proprioception



Descartes: Meditations (2, 3 and 4), Discourse on Method (V)
Locke J. Essay Concerning Human Understanding (Book 2, Chapter 27)
Hume D.1739 Treatise of Human Nature. (Book 1, Part 4, Chapter 6
Ryle G. Concept of Mind.
Merleau-Ponty: The Phenomenology of Perception ( Intro., Part-2:Ch.1, )

Armstrong DM. 1968. ‘The Headless Woman Illusion and the Defence of Materialism’. Analysis. 29: 48–49

Churchland P. 1981. ‘Eliminative Materialism and the Propositional Attitudes.’ The Journal of Philosophy. 78(2) 67-90.

Holt J. 2003. Blindsight and the Nature of Consciousness. US: Broadview Press. (Ch. 1)

McNeill D. Queaghebeur L. Duncan S. 2009. ‘The Man Who Lost His Body.’ In Handbook of Phenomenology and Cognitive Sciences. Gallagher
S & Schmickin D (Eds.). Springer. 519-545

Place UT. 1956. ‘Is Consciousness a Brain Process?’ British Journal of Psychology. 47:44-5050.

Putnam H, 1961. ‘Brains and Behavior.’ In Ned Block, ed. (1983). Readings in Philosophy of Psychology, Volume 1. Cambridge, MA: Harvard University Press

Putnam H. 1960. ‘Minds and Machines’. In Dimensions of Mind. Hook I(Ed.) New York: New York University Press.

Simons DJ, Levin DT. 1997. Change blindness. Trends in Cognitive Sciences. 1(7):261–267
Smart JJC . 1959. Sensations and Brain Processes”. The Philosophical Review. 68(2):141-156

Smart JJC. 1981, ‘Physicalism and Emergence’. Neuroscience. 6:109–113.
Strawson G. 1999. ‘The Self and the Sesmet.’ Journal of Consciousness Studies.
6(4): 99–135

Wilson M. 2002. ‘Six views of embodied cognition.’ Psychonomic Bulletin & Review. 9 (4): 625–636



Written concept papers and reviews based on case studies and readings for the 3 sections of the Course.

Case study: Change-Blindness

Case study: Experiential Blindness, Blindsight

Case study: Proprioception

Term paper: Defining research problem for the proposal (writing first draft)