Cellular mechanisms of information transfer: neuronal and synaptic plasticity

Credits: 
1.00
Date: 
07.04.2011
Organizers: 
SPU, Ioffe PTI
Coordinator: 
Ivan Pavlov
Speaker: 
Ivan Pavlov, Anton Chizhov, Pavel Zykin
Minimal requirements: 
Students are expected to have basic knowledge of cellular neurophysiology and have an understanding of electrical properties of excitable membranes. Experience in in vitro electrophysiology or imaging is an advantage. Good English language skills are essential.
Description: 

Course will be held in Auditorium 90, Faculty of Biology and Soil Science of SPbU 

9.00-12.30  April, 7-9, 2011

Language: Russian & English

Contact person: Ivan Pavlov, PhD, University College London, UK , i.pavlov(at)ion.ucl.ac.uk

 

Deadline for registration - 3.03.2010 

 Summary:

The ability of neuronal networks to receive, process and store information relies on the capacity of neurons to rapidly modify their intrinsic properties and to regulate the strength of synaptic connections between each other. Plastic changes are critical during the course of development, when neurons in the brain are “wiring” together, but are also vital for adaptation to the ever-changing environment. Different forms of plasticity are required for various behaviours and some are believed to provide a biological mechanism for memory formation. Current curse provides a comprehensive overview of different mechanisms of neuronal and synaptic plasticity from both functional and structural points of view. The course will also demonstrate how this mechanistic knowledge can be used to model the behaviour of individual neurons and their networks in computational studies. The course will highlight recent advances and latest trends in plasticity research.


Module 1 “Plastic neurons: global and site specific changes” (I. Pavlov and A. Chizhov)

1. Overview of different types of synaptic plasticity.

  •  Introduction: Scaling individual inputs and changing membrane properties to alter neuronal output.
  •  Short- and long-term synaptic plasticity;
  •  The Hebb rule for synaptic plasticity, properties of Hebbian LTP;
  •  Homo- and heterosynaptic plasticity;
  •  Bidirectional synaptic plasticity. BCM theory;
  •  NMDAR-dependent and independent forms of LTP;

2. Mechanisms of induction and expression of LTP and LTD

  •  pre- vs. postsynaptic debate
  •  Role of Ca2+;
  •  Mossy fiber LTP and the role of kainite receptors;
  •  mGluR-dependet forms of long-term plasticity 
  •  Receptor trafficking as a mechanism of plasticity;
  •  Changes in AMPA receptors function;
  •  Fusion pore modulation;
  •  Spillover of glutamate and the role of uptake mechanisms;
  •  Retrograde messengers;
  •  Cell surface and extracellular matrix molecules in synaptic plasticity.

3. Plasticity in interneurons: recent advances.

  •  The role of inhibition in synaptic plasticity;
  •  Unique features of interneuron signalling;
  •  Different subtypes of interneurons in hippocampus;
  •  Functional role of interneuronal long-term plasticity

4. Ion channels and neuronal plasticity

  •  non-synaptic plasticity,
  •  changes in neuronal intrinsic excitability;
  •  EPSP vs. E-S potentiation;
  •  Compartmentalization of neurons,  active dendrites;
  •  Homeostatic plasticity

5-6. Computational models of individual neurons

  •  Hodgkin-Huxley model of a neuron and neuronal plasticity
  •  Approximation of synaptic currents
  •  Models of synaptic plasticity Hebb’s synapses, STDP, BCM, Markram-Tsodyks

7. Neuronal plasticity at different stages of development

  •  Is there a role for LTP and LTD-like processes during brain maturation?
  •  Silent synapses hypothesis;
  •  LTP and aging brain;
  •  Plasticity and neurodegenerative disorders.

 

Module 2 “Morphological plasticity” (P. Zykin)


8. Plasticity of developing brain

  •  Epigenetic factors during cortical development
  •  Control of cortical development
  •  Developmental critical periods

9. Modular organisation of cerebral cortex. Plasticity in motor cortex

  • Topic organization of motor cortex
  • Physiological and morphological characterisation of motor cortex modules
  • Adult motor cortex re-mapping
  • Morphofunctional correlates of motor cortex plasticity

 

Module 3 “Plasticity and information processing in normal brain function and disease” (A. Chizhov and I. Pavlov)

10. Plasticity as a possible mechanism underlying learning and memory.

  • Why long-term plasticity is an attractive candidate mechanism for learning and memory?
  • Memory storage by a correlation matrix;
  • In vivo vs. in vitro experimental designs to study the link between synaptic plasticity and learning and memory;
  • Behavioural tests used to assess learning and memory;
  • Mutant mice approach to study plasticity and learning behaviour.

11-12. Modeling neuronal populations, implication for learning and memory

 

 

On-line streaming of the lectures could be viewed here (please, press button "Трансляция")

http://www.bio.pu.ru/news/detail.php?ID=2427

Presentation files could be downloaded here:

Lecture 1: Long-term and short-term synaptic plasticity. Part 1 (I. Pavlov)
Lecture 2: Long-term and short-term synaptic plasticity. Part 2 (I. Pavlov)
Lecture 3: Neuronal plasticity: global and local changes in neuronal excitability (I. Pavlov)
Lectures 4-6: Models of neuronal and synaptic plasticity (A. Chizhov)
Lecture 7: Synaptic plasticity during development (I. Pavlov)
Lecture 8: Factors of neuronal plasticity, development of neocortex (P. Zykin)
Lecture 9: Plasticity in interneurons (I. Pavlov)
Lecture 10: Synaptic plasticity and learning and memory (I. Pavlov)
Lecture 11: Minicolumnar organization of the neocortex (P. Zykin)
Lecture 12: Motor cortex neuronal plasticity (P. Zykin)


Duration(days): 
3
Learning outcomes: 
Students will learn about the main types of synaptic and neuronal plasticity and why changes in the neurotransmission and neuronal excitability are important for information transfer in the brain. They will be able to understand the major advantages and pitfalls of different modern techniques and experimental approaches commonly used in neurophysiology. Several case studies will be used as examples to illustrate how different approaches can complement each other. With the special focus on the experimental methods the course will enable PhD students to assess critically journal publications with the special attention to the details. The students will learn how computer modeling may help our understanding of the physiological processes.
Place: 
SPbSU