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Related Concept Videos

Stability of structures01:14

Stability of structures

196
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
196
Stability01:28

Stability

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The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
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Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

482
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
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BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

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System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
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Pole and System Stability01:24

Pole and System Stability

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The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
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Engram stability and maturation during systems consolidation.

Ron Refaeli1, Tirzah Kreisel1, Maya Groysman2

  • 1Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem 91904, Israel.

Current Biology : CB
|August 16, 2023
PubMed
Summary
This summary is machine-generated.

Engrams, the brain cells storing memories, remain stable from recent to remote recall. Their maturation involves specific cell connections, not random additions, impacting memory consolidation.

Keywords:
CA1CLARITYanterior cingulate cortexengrampseudo-rabiesrecent memoryremote memoryretro-AAV

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Area of Science:

  • Neuroscience
  • Systems Neuroscience
  • Memory Research

Background:

  • Remote memories are crucial for perception and are stored in brain engrams.
  • Engram cell ensembles in the hippocampus (CA1) and anterior cingulate cortex (ACC) are key to memory recall.
  • The evolution of these engrams during systems consolidation is not fully understood.

Purpose of the Study:

  • To investigate the dynamics and stability of CA1 engrams during systems consolidation.
  • To understand the maturation processes of engrams from recent to remote memory.
  • To elucidate the circuit-level changes associated with memory consolidation.

Main Methods:

  • Utilized transgenic approaches for engram identification.
  • Employed CLARITY, retro-AAV, and pseudo-rabies virus for circuit mapping.
  • Applied chemogenetics for functional interrogation of engram cells.

Main Results:

  • CA1 engrams demonstrated stability between recent and remote memory recall.
  • Inhibiting recent recall engrams during remote recall impaired memory function.
  • Engram maturation involved non-random addition of cells based on connectivity.
  • Observed growth in anterograde CA1 → ACC projections.
  • Found reduced ACC input and increased input from the entorhinal cortex and PVN to CA1 engram cells.

Conclusions:

  • CA1 engrams are stable over time, preserving memory traces.
  • Engram maturation is a selective process involving specific circuit modifications.
  • These findings offer new insights into the mechanisms of systems consolidation and memory persistence.