The main goal of our laboratory is to provide a deep understanding of how groups of neurons interact and tune their connections to generate neural representations of the world, and ultimately, learning and memories. We seek to reveal the neuronal mechanisms underlying cognition and how imbalances in the network lead to pathological conditions.
Addressing these questions calls for complementary approaches and novel technologies, so we are implementing and developing electrophysiological, optogenetic and computations tools for accessing the activity of neurons at a large scale in animal models and humans solving memory tasks.
Currently, our main research topics are:
- Principles of neuronal connectivity. Inhibitory neurons present the highest degree of neuronal diversity in the cortex. Developing tools to identify the distinct inhibitory neuron types is a bottle neck to be able to decipher their role in circuit dynamics (rhythms) and network computation (algorithms). To tackle this question, we are manipulating several neuronal types of the hippocampal area CA1 by optogenetic approaches and inferring their connectivity by high-resolution optogenetics. Ultimately, we are building a general classifier for identifying multiple inhibitory and excitatory cell types in cortical recordings from different species, including humans.
- Synaptic dynamics during learning. Understanding how excitatory and inhibitory inputs are integrated by neurons requires access to their subthreshold behavior. We have developed a method to reveal the subthreshold dynamics of large numbers of neurons based on high-resolution optogenetic stimulation. Using this technology, we are monitoring the changes in the synaptic integration of single neurons during learning events in normal and diverse neuropathological conditions, including epilepsy and Alzheimer's disease. With this technology, we expect to provide a mechanistic link between synaptic changes and learning.
- Artificial neural operations. In the brain, information from the environment and its relationship with the subject is represented by the activation of different neuronal assemblies. Little is known about how these assemblies are formed, and the operations they perform. To address this question, we are combining pattern-detection methods with high resolution optogenetic circuit interventions to experimentally recreate and manipulate neuronal assemblies operations in animal models solving cognitive tasks. Knowing the basic rules of brain assemblies processing will help identify the essential processes underlying cognition and its alterations upon several pathologies.
