Topic in Neuroscience: Neuroinformatics
NEUR 689 Tuesdays 1:30-4:10p, Krasnow 229
Prerequisites: Psyc 372 (Biopsychology), NSCI 210 (Introduction to Neuroscience) or permission of the instructor.
Course Goals: This is a hands-on overview of the available and developing informatics infrastructure for neuroscience research, recommended for all graduate neuroscience students. The aim is to provide students with sufficient practical understanding to appreciate the range of tools and electronic resources that are part of the contemporary scientific approach to the investigation of the brain. Students will start using this knowledge immediately, continuing to update and augment it throughout their professional development.
Method of Instruction and Evaluation: Weekly class will consist of a combination of lectures and live demonstrations. There is no assigned textbook. Student attendance, punctuality, completion and reporting of homework assignments, and active participation in class discussion are all required. Each student will be assigned a project to be demonstrated at the end of the semester. Final grades will be based on 45% class participation and homework discussion, and 55% project preparation and presentation. Letter grades will be assigned as follows: A+ and A, 4.00; A-, 3.67; B+, 3.33; B, 3.00; C, 2.00; F, 0.00.
Instructor: Dr. Giorgio Ascoli - Ph. x3-4383, E-mail: firstname.lastname@example.org
Office location: Krasnow Institute, Rm. 223
Office hours: Monday 3-4p, Tuesday 4:15-5:15p, or by appointment.
Technology Requirement: Ability to access the web and email communication.
Honor Code: GMU Academic Policies apply in full (http://www.gmu.edu/catalog/apolicies/)
If you are a student with a disability and you
accommodations, please see me and contact the Disability Resource
(Approx.) Class Schedule of Topics and
1) 1/26: Introduction: overview of neuroinformatics challenges and opportunities. List of suitable final projects and presentation template.
2) 2/2: Neuronal reconstructions I: from image stacks to digital vector traces. ImageJ, Neuron_Morpho plug-in, Neuromantic, V3D, Neuronland, CVAPP. Homework assignment: begin tracing example data set.
Last day to drop without penalty and last day to add: 2/2.
3) 2/16: Neuronal reconstructions II: morphometric analysis and data mining. NeuroMorpho.Org, L-Measure, neuroConstruct. Homework assignment: Complete tracing example data set and extract normalized Sholl-like plots.
4) 2/23: Electrophysiology and biophysics I: Compartmental simulations. NEURON, ModelDB. Homework assignment: spike propagation and synaptic integration in the reconstructed data set.
Last day to drop: 2/19?.
5) 3/2: System neuroanatomy: Contours, surfaces,
volumes. BrainMaps.Org, VIAS, Reconstruct. Homework assignment:
cytoarchitectonic gradients in mouse, rat, and monkey hippocampus.
Spring Break 3/9.
6) 3/16: Electrophysiology and biophysics II:
by Dr. Michele Migliore. Homework assignment: Draft project proposal.
7) 3/30: Neuroscience bioinformatics: BLAST, Swissprot, microarrays, Allen Brain Atlas. Homework assignment: Search and compare Ih and NMDA sequences in DG, CA3, CA1.
9) 4/6: Neuroscience knowledge bases II: Senselab, Whole Brain Catalog, BrainInfo, BAMS, Textpresso, Google Scholar, PMC. Homework assignment: Finalize project proposal.
10) 4/13: Neuroscience data sharing I: Source discovery, policy issues, and access infrastructure. NeuroCommons and journal requirements. Homework assignment: Request and examine available data from 10 articles published in 2009.
11) 4/20: Neuroscience data sharing II: Guest lecture by Dr. Ken Smith. Homework assignment: Preview project presentation.
12) 4/27: Non-invasive human brain imaging. fMRI-DC, ICBM, BIRN, NITRC. Homework assignment: Search and propose activation foci for value and arousal.
13) 5/4: Project presentation and feedback.