scholarly journals Emotional salience modulates the forward flow of memory

2021 ◽  
Author(s):  
Alba Peris-Yague ◽  
Darya Frank ◽  
Bryan Andrew Strange

Conditional response probability (CRP) analyses applied to free recall data indicate that recall occurs for contiguous items with forward-directionality, thought to reflect the shared encoding context of nearby items. We hypothesized that a context disruption, produced by presenting infrequent oddballs, would modulate CRP curves, increasing the forward-flow of recall due to strong binding of items presented after these oddballs to the new encoding context. Seventy young, healthy male and female participants encoded word lists containing either emotional or perceptual oddballs at varying stimulus onset asynchronies (SOA) followed by free recall. Serial recall transitions from emotional, but not perceptual, oddballs were enhanced in the forward direction except at the shortest SOA (1s). The present results provide empirical evidence of CRP modulation selectively by emotional salience and suggest that recall patterns after presenting emotional and perceptual oddballs are mediated by different mechanisms.

Author(s):  
Gilles Vanwalleghem ◽  
Kevin Schuster ◽  
Michael A. Taylor ◽  
Itia A. Favre-Bulle ◽  
Ethan K. Scott

AbstractInformation about water flow, detected by lateral line organs, is critical to the behavior and survival of fish and amphibians. While certain specific aspects of water flow processing have been revealed through electrophysiology, we lack a comprehensive description of the neurons that respond to water flow and the network that they form. Here, we use brain-wide calcium imaging in combination with microfluidic stimulation to map out, at cellular resolution, all neurons involved in perceiving and processing water flow information in larval zebrafish. We find a diverse array of neurons responding to forward flow, reverse flow, or both. Early in this pathway, in the lateral line ganglia, these are almost exclusively neurons responding to the simple presence of forward or reverse flow, but later processing includes neurons responding specifically to flow onset, representing the accumulated volume of flow during a stimulus, or encoding the speed of the flow. The neurons reporting on these more nuanced details are located across numerous brain regions, including some not previously implicated in water flow processing. A graph theory-based analysis of the brain-wide water flow network shows that a majority of this processing is dedicated to forward flow detection, and this is reinforced by our finding that details like flow velocity and the total volume of accumulated flow are only encoded for the simulated forward direction. The results represent the first brain-wide description of processing for this important modality, and provide a departure point for more detailed studies of the flow of information through this network.Significance statementIn aquatic animals, the lateral line is important for detecting water flow stimuli, but the brain networks that interpret this information remain mysterious. Here, we have imaged the activity of individual neurons across the entire brains of larval zebrafish, revealing all response types and their brain locations as water flow processing occurs. We find some neurons that respond to the simple presence of water flow, and others that are attuned to the flow’s direction, speed, duration, or the accumulated volume of water that has passed during the stimulus. With this information, we modeled the underlying network, describing a system that is nuanced in its processing of water flow simulating forward motion but rudimentary in processing flow in the reverse direction.


2005 ◽  
Vol 67 (2) ◽  
pp. 335-340 ◽  
Author(s):  
Sibylle Klosterhalfen ◽  
Sandra Kellermann ◽  
Ursula Stockhorst ◽  
Jutta Wolf ◽  
Clemens Kirschbaum ◽  
...  

2011 ◽  
Vol 10 (01) ◽  
pp. 41-58 ◽  
Author(s):  
T. D. FRANK ◽  
T. RHODES

We examine the relationship between time-discrete nonlinear Markov processes defined in terms of nonlinear Markov chains and corresponding micro-dynamic models describing many-body systems composed of a finite number of units interacting with each other via a mean field. To this end, we consider a two-state model and examine appropriately defined measures for attractor strength and noise amplitude using variational calculus. We focus on a two-state model and demonstrate an application to free recall data from 8 participants.


1999 ◽  
Vol 31 (Supplement) ◽  
pp. S164 ◽  
Author(s):  
A. E. Shugarman ◽  
E. W. Askew ◽  
D. D. Stadler ◽  
M. J. Luetkemeier ◽  
R. C. Bullough ◽  
...  

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