Projects and themes

In brief

(each link below gives, for each topic, a summary, a list of the published work in the laboratory, and PDFs copies of the corresponding publications)

• 1. Modeling ion channels and extracellular potentials
• 2. Modeling the integrative properties of single neurons
• 3. Network models
• 4. Mean-field and large-scale models
• 5. Computational methods to analyze experimental data
• 6. Dynamic-clamp experiments
• 7. Theoretical and numerical methods

1. Modeling ion channels and extracellular potentials

• 1.1 Biophysical models of synaptic transmission

• 1.2 Model of the hyperpolarization-activated current Ih and its regulation by calcium

• 1.3 Models of local field potentials

• 1.4 Models of neuronal magneticfields

2. Modeling the integrative properties of single neurons

• 2.1 The integrative properties of cortical neurons in vivo

• 2.2 Integrative properties of thalamic neurons

• 2.3 Model of hyperpolarization-activated persistent activity

• 2.4 Generalized cable equations for neurons

3. Network models

• 3.1 Models of thalamic oscillations

• 3.2 Thalamocortical oscillations

• 3.3 Role of sleep in memory consolidation

• 3.4 Models of epileptic discharges and absence seizures

• 3.5 Networks of “silicon” neurons

• 3.6 In vivo like states in cortical networks

4. Mean-field and large-scale models

• 4.1 Macroscopic models of neuronal activity

• 4.2 Mean-field models of neuronal populations

5. Computational methods to analyze experimental data

• 5.1 Spatiotemporal analysis of electrophysiological data

• 5.2 Analysis of synaptic noise from intracellular recordings

• 5.3 The Active Electrode Compensation (AEC) method for high-resolution intracellular recordings

• 5.4 Analysis of multi-electrode and ensemble recordings

• 5.5 Power-law and frequency scaling in electrophysiological data

6. Dynamic-clamp experiments

• 6.1 The Dynamic-clamp: real-time interaction between models and living neurons

• (see also The Active Electrode Compensation (AEC) method above)

7. Theoretical and numerical methods

• 7.1 Conductance-based integrate and fire models

• 7.2 Event-based integration algorithms for conductance-based integrate and fire networks