Graduate Courses in the PhD Program
(Please be advised due to many variables courses are subject to change; courses may be removed or added on a yearly basis)
Introductory survey course of research in complex systems and brain sciences at Florida Atlantic University, aimed at first semester graduate students.
This course provides an introduction to nonlinear dynamical system theory. Topics of discussion are one-, two- and higher dimensional flows, oscillator theory, maps, attractors, bifurcations, chaos. Many examples will be presented from the areas of current research in physics, chemistry, biology and neuroscience. Prospective students will be expected to have an elementary knowledge of calculus and a passing familiarity with ordinary differential equations (ODEs). Homework problems will be selectively discussed in class, occasionally as a presentation by the students.
Experimental design and statistical analysis of linear and nonlinear systems. Presents the classical statistical analysis and inference of linear systems that have a small number of noninteracting pieces and how those statistical methods and analysis procedures are different for nonlinear complex systems with many pieces that interact strongly with each other, such as fractals and chaos.
This course is intended for Graduate Students and is the first of a two-part dequence (6 credits total) which covers in depth the principles of neural science, including structure and function of cells in the nervous system, neurotransmitter systems, functional neuroanatomy, sensory processes, higher brain function, neural development and cellular mechanisms of learning and memory. Senior Undergraduates interested in taking this course should consult the instructors.
This course continues on from Neuroscience I with Functional Neuroanatomy. The Senses -- Vision, Hearing, Somatosensory, Smell and Taste are covered in this course. The course concludes with lectures on Neural Development and the Cellular Mechanisms of Learning and Memory. If time permits, a few special topics such as Neuroimmunology and Neural Networks will be given by the instructor or guest lecturers. Neuroscience I is a pre-requisite for this course.
An interdisciplinary survey of the neural basis of cognitive functions such as perception, attention, memory and language.
A survey of the field of mathematical biology, including dominance of the slow manifolds. A discussion of aspects of brainstem anatomy and physiology pertinent to behavior. Class work is supplemented by extensive lab work where students learn techniques such as electroencephalographic recording from freely moving animals, horseradish peroxidase (HRP) injection and staining and mounting of tissue for light microscopy.
This course covers the basics of computational neuroscience and introduces many research topics of both biological and artificial neural networks.
This course will give students in depth understanding of the methods of computational neuroscience and hands-on experience of such research and will enable them to use some of the mehods in their own thesis research.
This course provides an introduction to the scientific study of perception, action, and cognition. It focuses on empirical methodologies related to development and evaluation of theories of mind. Examples are drawn from psychology, computation, linguistics, neuroscience, and philosophy.
This course is designed for Graduate and Senior Undergraduate students who have had some Psychobiology, Cellular Biology or Physiology ad now want to learn more about the development of the Brain and Nervous System. The topics covered begin in early embryogenesis and follow the development of the nervous system at the cellular and molecular level through to the development of behavior. Students are strongly encouraged to talk with the instructor before registering and will need to have some biological background such as Biological Bases of Behavior (PSB 4002), Anatomy and Physiology (APB 2085/6) or Cell Biology (PCB 4523) or similar.
Fractals and Chaos have attracted wide attention and excitement in mathematics and the physical sciences. These ideas are now being used to acheive a better understanding of DNA, proteins, ion channels, nerve cells, muscle cells, blood vessels, the heart, the lungs, and the brain. This course will explain the properties of Fractals and Chaos and illustrate them with biomedical applications. Mathematical level: elementary calculus.
This course will examine the perception and cognition of music from a psychological viewpoint. Topics include: Auditory Perception, Consonance and Dissonance, Musical Scales, Melody, Harmony, and Rhythm. We will also address relationships between music and language, the communication of emotion and meaning, and neurological and clinical findings. The first weeks of the course will consist of a survey of the field of music perception and cognition. We will then read classic papers representing work in experimental psychology, music theory, and neural networks.
A sound introduction to the imaging technologies used at the CCSBS and their application in research. Discussed in details are EEG, MEG, Magnetic Resonance Imaging (MRI) and functional MRI starting at the underlying physical processes of electric and magnetic fields and material properties. The material covers spin dynamics and pulse sequences, and their relation to MR contrast with an emphasis on echo planar sequences, the basis of fMRI recordings (including an afternoon of scanning of a phantom). The nature of the EEG and MEG signals are discussed and advanced analysis methods for spatiotemporal patterns are applied to them. Prerequisite: Introduction to Nonlinear Dynamics and Chaos.
A study of neural function, cortical electrogenesis, and theories of origin of the EEG, covering practical issues relating to EEG recording and basic methods of EEG analysis. Autocovariance, cross-covariance, Fourier analysis, autoregressive modeling, and digital filtering are some of the techniques covered.
An introduction to Synergetics, the theory of self-organizing structures, will be given along examples from biology, chemistry and physics. Deterministic and stochastic models will be studied, e.g. Laser equations, Navier-Stokes model, Ginzburg-Landau systems, Fokker-Planck theory, master equation. Prerequisite: Introduction to Nonlinear Dynamics and Chaos.
The perception and production of speech are studied, beginning with fundamentals of speech acoustics and physiology and including memory, perception, and the evolution of language systems. Other aspects explored include real-time language processing mechanisms; language acquisition; language after brain damage; language in other species; language in nonverbal domains (sign language; parsing by computers).
The dynamics of neural activity will be studied on different levels of organization such as single cells, pairs of neurons and large-scale continuum models. These models shall be compared in the light of traversing from one organizational scale to another. Prerequisite: Introduction to Dynamical Systems and Chaos.