Blue Brain Seminar - A multi-modal fitting approach to construct single-neuron models with patch-clamp and high-density microelectrode arrays
Event details
| Date | 29.07.2022 |
| Hour | 11:00 › 12:00 |
| Speaker | Alessio Buccino |
| Location |
Blue Brain Project, Campus Biotech, Geneva.
Online
|
| Category | Conferences - Seminars |
| Event Language | English |
Abstract
In computational neuroscience, multicompartment models are among the biophysically most realistic representations of single neurons.
Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions.
The experimental data are then used to fit the many parameters of the model. While patching of the soma is the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections.
Recording from the soma alone makes it hard to observe and correctly parameterize the activity of non-somatic compartments.
In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs).
HD-MEAs enable to observe extracellular potentials and neural activity of neuronal compartments at subcellular resolution.
In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models.
We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone.
We also demonstrate our procedure experimentally by constructing cell models from in vitro cell cultures.
The proposed multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated.
Biography
Alessio Buccino is a research engineer and software developer focused on methods and analysis tools for neuroscience research, especially for extracellular electrophysiology.
He is passionate about science, software, and engineering, and his mission is to support neuroscientists and facilitate their research efforts by providing state-of-the-art analysis methods and software tools.
Among these, he is the core developer of several open-source scientific tools, including SpikeInterface, a widely used software framework to unify and simplify the analysis of extracellular electrophysiology data.
In March 2022, Alessio joined the Allen Institute for Neural Dynamics team as an electrophysiology pipeline development engineer consultant, with the goal of building open-source and computationally efficient processing pipelines to analyze large amounts of electrophysiological data.
Since July 2020, he has also been working part-time at CatalystNeuro, a consulting company with the mission of facilitating collaborations in neuroscience and standardizing data analysis and data storage solutions.
Previously, Alessio was a Postdoctoral Fellow at the Bio Engineering Lab at ETH with Prof. Andreas Hierlemann, working on multimodal approaches to probe neural activity and to construct detailed biophysical models.
Before that, he was at the Center for Integrated Neuroplasticity CINPLA, at the University of Oslo, where he received his PhD with a thesis titled "A computationally-assisted approach to extracellular neural electrophysiology with multi-electrode arrays".
Register here to join with zoom
In computational neuroscience, multicompartment models are among the biophysically most realistic representations of single neurons.
Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions.
The experimental data are then used to fit the many parameters of the model. While patching of the soma is the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections.
Recording from the soma alone makes it hard to observe and correctly parameterize the activity of non-somatic compartments.
In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs).
HD-MEAs enable to observe extracellular potentials and neural activity of neuronal compartments at subcellular resolution.
In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models.
We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone.
We also demonstrate our procedure experimentally by constructing cell models from in vitro cell cultures.
The proposed multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated.
Biography
Alessio Buccino is a research engineer and software developer focused on methods and analysis tools for neuroscience research, especially for extracellular electrophysiology.
He is passionate about science, software, and engineering, and his mission is to support neuroscientists and facilitate their research efforts by providing state-of-the-art analysis methods and software tools.
Among these, he is the core developer of several open-source scientific tools, including SpikeInterface, a widely used software framework to unify and simplify the analysis of extracellular electrophysiology data.
In March 2022, Alessio joined the Allen Institute for Neural Dynamics team as an electrophysiology pipeline development engineer consultant, with the goal of building open-source and computationally efficient processing pipelines to analyze large amounts of electrophysiological data.
Since July 2020, he has also been working part-time at CatalystNeuro, a consulting company with the mission of facilitating collaborations in neuroscience and standardizing data analysis and data storage solutions.
Previously, Alessio was a Postdoctoral Fellow at the Bio Engineering Lab at ETH with Prof. Andreas Hierlemann, working on multimodal approaches to probe neural activity and to construct detailed biophysical models.
Before that, he was at the Center for Integrated Neuroplasticity CINPLA, at the University of Oslo, where he received his PhD with a thesis titled "A computationally-assisted approach to extracellular neural electrophysiology with multi-electrode arrays".
Register here to join with zoom
Practical information
- General public
- Registration required
Organizer
- Blue Brain Project, Host: Werner Van Geit
Contact
- Dace Stiebrina: [email protected]