Embedded Files
Our Goal:
Our Goal:
Our research is dedicated to uncovering how long-term information is encoded in the brain, with a focus on associative spatial memory. Understanding the neural mechanisms underlying memory is essential not only for advancing neuroscience but also for tackling major societal challenges. Our work directly contributes to strategies for diagnosing and treating brain disorders by revealing how memory-related structures—such as the hippocampus and medial temporal lobe—function in both healthy and diseased states. Furthermore, by modeling neuronal representations and cognitive processes, our research fuels the development of next-generation artificial intelligence, providing biologically inspired algorithms for learning, adaptation, and decision-making. Leveraging advanced methodologies, including large-scale electrophysiological recordings, high-throughput behavioral assays, and computational modeling, we generate essential knowledge at the intersection of neuroscience, medicine, and AI—advancing both brain health and technological innovation.
Our research is dedicated to uncovering how long-term information is encoded in the brain, with a focus on associative spatial memory. Understanding the neural mechanisms underlying memory is essential not only for advancing neuroscience but also for tackling major societal challenges. Our work directly contributes to strategies for diagnosing and treating brain disorders by revealing how memory-related structures—such as the hippocampus and medial temporal lobe—function in both healthy and diseased states. Furthermore, by modeling neuronal representations and cognitive processes, our research fuels the development of next-generation artificial intelligence, providing biologically inspired algorithms for learning, adaptation, and decision-making. Leveraging advanced methodologies, including large-scale electrophysiological recordings, high-throughput behavioral assays, and computational modeling, we generate essential knowledge at the intersection of neuroscience, medicine, and AI—advancing both brain health and technological innovation.
Our research is based on three main methodologies:
Our research is based on three main methodologies:
1. Unsupervised high-throughput behavioral tasks
1. Unsupervised high-throughput behavioral tasks
2. Electrophysiology and calcium imaging recordings of large neuronal population in freely moving mice
2. Electrophysiology and calcium imaging recordings of large neuronal population in freely moving mice
3. Machine learning techniques to correlate neuronal population activity with animal behavior
3. Machine learning techniques to correlate neuronal population activity with animal behavior
1. High-throughput behavioral tasks
1. High-throughput behavioral tasks
a. Fully computer controlled freely moving behavioral task to measure spatial memory recall, during neural activity recordings
b. Parametric & hight number of trials test to measure learning and recall of spatial memories
c. Ability to measure memory accuracy over many trials per session (~20), for many daily sessions per animal (~200).
2. Neuronal recordings in freely moving mice
2. Neuronal recordings in freely moving mice
We perform tetrode based electrophysiological recordings and miniaturized 1-photon calcium-imaging recordings in freely moving mice.
See more details in our electrophysiology and calcium imaging published experiments
Freely moving calcium imaging recordings of hippocampal CA1 pyramidal cells during an association task (w/ T. Rogerson)
Freely moving calcium imaging recordings of entorhinal cortex during a foraging task
3. Neuronal population data analysis
3. Neuronal population data analysis
a. We utilized neuronal decoders to measure the amount of information encoded in the activity of the cells, to track learning over time at the population level (see reference).
b. We use information theory in high dimension neuron population vector spaces, to test which sensory input features better explain neuronal responses to understand how information is encoded (see reference).
Decoding animal position using population activity from hippocampal CA1 neurons
Google Sites
Report abuse