Microcircuit Network Dynamics
Microcircuit Network Dynamics - Related Videos
02:30
Optogenetic Control of Hippocampal Network Dynamics
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2025
This video demonstrates the method to use optogenetics to modulate hippocampal network dynamics by activating genetically modified light-sensitive interneurons in a mouse brain slice, enhancing theta oscillation synchronization and studying neural circuit behavior.
10:24
Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings
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Cited by 28 •
2015
Patch-clamp recordings and simultaneous intracellular biocytin filling of synaptically coupled neurons in acute brain slices allow a correlated analysis of their structural and functional properties. The aim of this protocol is to describe the essential technical steps of electrophysiological recording from neuronal microcircuits and their subsequent morphological analysis.
00:07
Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Cited by 14 •
2019
Quantitative Multiplex Immunoprecipitation (QMI) uses flow cytometry for sensitive detection of differences in the abundance of targeted protein-protein interactions between two samples. QMI can be performed using a small amount of biomaterial, does not require genetically engineered tags, and can be adapted for any previously defined protein interaction network.
02:26
Protein Networks
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2020
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions. These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
02:18
Network Covalent Solids
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2020
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds. To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
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Excitatory and inhibitory signaling shape microcircuit dynamics by regulating whether local neuronal activity is amplified or restrained. The resulting balance influences the timing, strength, and persistence of network responses. Shifts in connectivity or synaptic effectiveness can therefore alter collective activity, helping explain why similar cells may produce different patterns under different circuit conditions.
Synaptic connectivity determines which cells influence one another, while intrinsic cellular properties affect how individual excitable cells respond to those inputs. Feedback then links successive responses within the circuit, allowing activity to be sustained, redirected, or terminated. Together, these factors help generate oscillations, synchrony, and transient states rather than isolated cellular events.
Activity states change when the interactions among excitation, inhibition, cellular properties, connectivity, and feedback shift over time. A circuit may move from coordinated activity to a brief transient state or a recurring oscillation as these influences change. Studying such transitions helps researchers examine how local biological networks adapt to changing conditions and regulate function.
Researchers combine experimental recordings with computational models and circuit-manipulation methods. Recordings reveal patterns of activity, models help examine how cellular interactions could produce those patterns, and targeted manipulation tests the contribution of circuit components. Comparing these approaches connects cellular behavior with network-level activity and strengthens interpretation of observed oscillations, synchrony, or transient states.
Computational models provide a way to examine how connectivity, excitation, inhibition, intrinsic properties, and feedback jointly influence activity over time. By relating modeled cellular interactions to network patterns, investigators can explore possible mechanisms underlying synchrony, oscillations, and changing activity states. This approach complements recordings by linking observed dynamics to circuit-level explanations.
Microcircuit dynamics provide a framework for connecting local cellular interactions with information encoding and behavioral regulation. When normal patterns of activity become disrupted, the resulting changes may help investigators study mechanisms associated with neurological and psychiatric disorders. Combining recordings, modeling, and circuit manipulation can clarify how altered network activity relates to biological function and dysfunction.