Behavioral states are thought to be encoded by the activity of neuronal ensembles. A neuronal ensemble is a group of neurons with coordinated activity that could be causally related to a brain function including learning. Even though the study of neuronal ensembles has started to emerge recently in the neuroscience field, the systematic characterization of the functional connectivity of neuronal ensembles and the changes in pattern completion and pattern separation neurons evoked by learning and their relation to the performance of a learned task remain unknown. For this reason, it is important to propose an integrated framework for the study of neuronal ensembles to allow the characterization of microcircuit properties at different stages of the learning processes.
In the last decade the refinement of population recordings in vivo has allowed the chronic characterization of neuronal microcircuit activity with single cell resolution. However, despite the ability to describe the changes in activity of neuronal ensembles at different times, most of the studies using population recordings with single cell resolution use averaged population recordings or pair correlations. It has been suggested that throughout learning the patterns of activity of neuronal ensembles related to the learned task become more reliable indicating the necessity to further develop experimental and analytical tools to visualize and understand the causal relation of the changes in functional connectivity of neuronal ensembles at different times. Recent experiments using two-photon optogenetics and population recordings have shown that the targeted activation of pattern completion neurons can change the overall network dynamics and affect learned behaviors in a predictive way, suggesting that these tools could also be applied to characterize different learning stages.
The call of this proposal is to present research or review articles that contribute to the understanding of changes in neuronal ensemble activity throughout learning. Research manuscripts describing the implementation of experimental or analytical tools to visualize the changes in functional connectivity from chronic recordings of neuronal ensembles using different learning paradigms as well as review manuscripts summarizing population activity at different learning stages will be welcome. These contributions could be appealing to researchers that look forward to identifying neuronal ensembles and the properties of its elements such as pattern completion or pattern separation for future interventional experiments.
Behavioral states are thought to be encoded by the activity of neuronal ensembles. A neuronal ensemble is a group of neurons with coordinated activity that could be causally related to a brain function including learning. Even though the study of neuronal ensembles has started to emerge recently in the neuroscience field, the systematic characterization of the functional connectivity of neuronal ensembles and the changes in pattern completion and pattern separation neurons evoked by learning and their relation to the performance of a learned task remain unknown. For this reason, it is important to propose an integrated framework for the study of neuronal ensembles to allow the characterization of microcircuit properties at different stages of the learning processes.
In the last decade the refinement of population recordings in vivo has allowed the chronic characterization of neuronal microcircuit activity with single cell resolution. However, despite the ability to describe the changes in activity of neuronal ensembles at different times, most of the studies using population recordings with single cell resolution use averaged population recordings or pair correlations. It has been suggested that throughout learning the patterns of activity of neuronal ensembles related to the learned task become more reliable indicating the necessity to further develop experimental and analytical tools to visualize and understand the causal relation of the changes in functional connectivity of neuronal ensembles at different times. Recent experiments using two-photon optogenetics and population recordings have shown that the targeted activation of pattern completion neurons can change the overall network dynamics and affect learned behaviors in a predictive way, suggesting that these tools could also be applied to characterize different learning stages.
The call of this proposal is to present research or review articles that contribute to the understanding of changes in neuronal ensemble activity throughout learning. Research manuscripts describing the implementation of experimental or analytical tools to visualize the changes in functional connectivity from chronic recordings of neuronal ensembles using different learning paradigms as well as review manuscripts summarizing population activity at different learning stages will be welcome. These contributions could be appealing to researchers that look forward to identifying neuronal ensembles and the properties of its elements such as pattern completion or pattern separation for future interventional experiments.
