Coñecer as formas de reproducir nas computadoras as estructuras e funcionamento dos circuitos do cerebro. Para a investigación do sistema nervioso e para diseñar sistemas intelixentes baseados no funcionamento cerebral.
Study programme competencies
Code
Study programme competences
A4
Explicar o funcionamento das neuronas dende o nivel molecular ao celular.
A5
Describir a relación entre as canles iónicas e o comportamento neuronal.
B4
Saiban ler e obter información relevante de publicacións científicas.
B5
Saiban aplicar os coñecementos adquiridos e a súa capacidade de resolución de problemas en ámbitos novos ou pouco coñecidos dentro de contextos máis amplos (ou multidisciplinares) relacionados coa neurociencia.
B7
Teñan competencia na presentación oral e escrita de resultados científicos a públicos especializados e non especializados dun modo claro e sen ambigüidades.
B8
Saiban traballar en grupos de carácter multidisciplinar
B9
Posúan capacidade de reflexión sobre as responsabilidades éticas e sociais da aplicación da investigación.
C3
Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida.
C4
Desenvolverse para o exercicio dunha cidadanía aberta, culta, crítica, comprometida, democrática e solidaria, capaz de analizar a realidade, diagnosticar problemas, formular e implantar solucións baseadas no coñecemento e orientadas ao ben común.
C6
Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse.
C7
Asumir como profesional e cidadán a importancia da aprendizaxe ao longo da vida.
C8
Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade.
Learning aims
Learning outcomes
Study programme competences
- Capacidade de abstracción e formalización do fenómeno ou sistema real a modelizar.
AR5
BR4 BR5 BR8
CR3 CR6 CR7 CR8
- Ser capaz de relacionarse e traballar en equipo con científicos de diferentes ámbitos.
BR8 BR9
CR4 CR6 CR8
- Capacidade para comprender e expoñer os resultados das modelizacións e establecer relacións co coñecemento existente ata o momento do sistema biolóxico.
AR4 AR5
BR4 BR7
CR6
Contents
Topic
Sub-topic
1. Introduction to Computational Neuroscience
2. Models at the molecular level
3. Membrane-level models: from Boltzmann to Hodgkin-Huxley
4. Models at the neuron level: cable theory and model
Compartmental of Rall
5. Synapse level models
6. Microcircuit models
7. Macrocircuit models
8. Coding in sensory receptors
9. Types of neural activity
10. Transmission of information in the brain
11. Spatial and temporal coding
12. Encoding by populations of neurons
Espoñerase e comentaranse cos alumnos as diapositivas relacionadas con cada tema.
PRACTICUM
Understand how modeling is done.
Practices with neurosimulators.
Report on the Application of the modeling process
Exposure after analysis and criticism.
Planning
Methodologies / tests
Competencies
Ordinary class hours
Student’s personal work hours
Total hours
Guest lecture / keynote speech
A4 A5 B4 C3 C8
20
25
45
Seminar
B5 B7 B8 B9 C4 C6 C7
9
18
27
Personalized attention
3
0
3
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.
Methodologies
Methodologies
Description
Guest lecture / keynote speech
Conduct a master class and use of multimedia teaching materials, taking advantage of the advantages of new technologies and encouraging the participation of students in each subject. This activity will be supported by the rest of the methodologies.
Seminar
It consists of the representation of a phenomenon of electrophysiological nature, which allows a more sinxel analysis, which if carried out on the orixinal or in reality. He puts his money in the presence of hypothetical conditions in the limes, and his behavior is tested against concrete situations. It is, therefore, based on the configuration of situations similar to those that occur in a real context, for the purpose of using them as learning experiences.
Personalized attention
Methodologies
Seminar
Description
Resolution of doubts that arise both in the master classes and in the realization of two jobs. Attendanse students through tutorials in person, as well as through virtual tutorials through e-mail.
Assessment
Methodologies
Competencies
Description
Qualification
Guest lecture / keynote speech
A4 A5 B4 C3 C8
Attendance and participation in classes of practices and lectures will account for 40% of the final grade.
40
Seminar
B5 B7 B8 B9 C4 C6 C7
The quality of the works, as well as their exposure, is 60% of the final mark.
60
Assessment comments
Casos excepcionais: no caso de que o estudante, por razóns
debidamente xustificadas, non puidera realizar todas as probas de
avaliación continua, o alumno contactará coa profesora para establecer datas de defensa dos traballos.
Bower
J. M. y Koch C. “Experimentalists
and modelers: can we all just get along?”. Trends in Neuroscience. 15(11):
458-461.1992.
Bower, J.M., and Beeman: “The Book of GENESIS:
Exploring Realistic Neural Models with the GEneral NEural SImulation
System”. Second edition. New York: Springer-Verlag. 1998
COUCH, L.W. Sistemas de comunicación digitales y
analógicos. Prentice Hall, 1998.
DIMITRIEV, V.I. Teoría de información aplicada. Ed. MIR, Moscú, 1991.
DRURY,
G., MARKARIAN, G y PICKAVANCE, K. Coding and modulation for digital
television. Kluwer, 2001.
Hines, M.: “NEURON—A program for simulation of
nerve equations”. In: Neural Systems: Analysis and Modeling, edited by F.
Eeckman. Norwell, MA: Kluwer, p. 127-136. 1993.
Hines, M.: “The NEURON simulation program”. In:
Neural Network Simulation Environments, edited by J. Skrzypek. Norwell,
MA: Kluwer, p. 147-163. 1994.
Koch, C. Biophysics of Computation: Information Processing in Single
Neurons. Oxford University Press, 1999.
LeRay, D., Fernández, D., Porto, A. & Buño, W.
“Metaplastic regulation of synaptic efficacy between convergent Schaffer
collaterals in rat hippocampal CA1 neurons.” Soc. Neurosci. Abstr., Vol.
29. 2003.
LeRay, D., Fernández, D., Porto, A., Fuenzalida, M.
& Buño, W. “Heterosynaptic Metaplastic Regulation of Synaptic Efficacy
in CA1 Pyramidal Neurons of Rat Hippocampus”. Hippocampus. 2004.
MacKay, DJC. Information Theory, Inference, and
Learning Algorithms. Cambridge University Press, 2003.
PROAKIS,
J.G. Digital communications, McGraw Hill, 1995
Sah
P., Bekkers J.M.: “Apical dendritic location of slow
afterhyperpolarization current in hippocampal pyramidal neurons:
implications for the integration of long-term potentiation”. J.
Neuroscience. 16:4537-4542. 1996.
F Rieke, D Warland, R de Ruyter van Steveninck
& W Bialek.
Spikes: Exploring the Neural Code. MIT Press, Cambridge, 1997.
Schwartz,
Eric L. “Computational Neuroscience”. MIT Press. 1990.
Storm
J. F.: “Potassium currents in hippocampal pyramidal cells”. Prog.
Brain Res. 83, 161-187. 1990.
STREMLER, F.G. Introducción a los sistemas de
comunicación. Addison-Wesley, 1993.
Wessel R., Kristan Jr. W.B., Kleinfeld D.:
“Dendritic Ca2+-acticvated K+ conductances regulate electrical signal
propagation in an invertebrate neuron”. J. Neuroscience. 19:8319-8326.
1999.
WILSON,
S.G. Digital modulation and coding, Prentice Hall, 1996.
Complementary
Recommendations
Subjects that it is recommended to have taken before
Subjects that are recommended to be taken simultaneously
Sistemas adaptativos complexos/610411231
Bioinformática aplicada á neurociencia/610411204
Subjects that continue the syllabus
Fisioloxía do sistema nervioso/610411105
Other comments
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.