A possible relation between new neuronal recruitment and migratory behavior inAcrocephaluswarblers

2014 ◽  
Vol 74 (12) ◽  
pp. 1194-1209 ◽  
Author(s):  
Shay Barkan ◽  
Yoram Yom-Tov ◽  
Anat Barnea
1996 ◽  
Vol 16 (1) ◽  
pp. 23-33 ◽  
Author(s):  
Norihiro Sadato ◽  
Vicente Ibañez ◽  
Marie-Pierre Deiber ◽  
Gregory Campbell ◽  
Marc Leonardo ◽  
...  

To study the effect of the repetition rate of a simple movement on the distribution and magnitude of neuronal recruitment, we measured regional CBF (rCBF) in eight normal volunteers, using positron emission tomography and 15O-labeled water. An auditory-cued, repetitive flexion movement of the right index finger against the thumb was performed at very slow (0.25 and 0.5 Hz), slow (0.75 and 1 Hz), fast (2 and 2.5 Hz), and very fast (3 and 4 Hz) rates. The increase of rCBF during movement relative to the resting condition was calculated for each pair of movement conditions. Left primary sensorimotor cortex showed no significant activation at the very slow rates. There was a rapid rise of rCBF between the slow and the fast rates, but no further increase at the very fast rates. The right cerebellum showed similar changes. Changes in the left primary sensorimotor cortex and the cerebellum likely reflect the effect of the movement rate. The posterior supplementary motor area (SMA) showed its highest activation at the very slow rates but no significant activation at the very fast rates. Changes correlating with those in the SMA were found in the anterior cingulate gyrus, right prefrontal area, and right thalamus. The decreases in CBF may reflect a progressive change in performance from reactive to predictive.


Cell ◽  
2021 ◽  
Vol 184 (2) ◽  
pp. 303-305
Author(s):  
Olivia S. Harringmeyer ◽  
Maya L. Woolfolk ◽  
Hopi E. Hoekstra

1998 ◽  
Vol 195 (2) ◽  
pp. 168-173 ◽  
Author(s):  
R. A. Tankersley ◽  
M. G. Wieber ◽  
M. A. Sigala ◽  
K. A. Kachurak

2000 ◽  
Vol 70 ◽  
pp. A63-A63
Author(s):  
A.D. Ebert ◽  
C. Wechselberger ◽  
B. Wallace-Jones ◽  
M. Nees ◽  
T. Clair ◽  
...  

2008 ◽  
Vol 7 (2) ◽  
pp. 444-450 ◽  
Author(s):  
M.L. Camparoto ◽  
B. Fulan ◽  
C.M. Colli ◽  
M.L. Paludo ◽  
A.L. Falavigna-Guilherme ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Eliezer Gurarie ◽  
Sriya Potluri ◽  
George Christopher Cosner ◽  
Robert Stephen Cantrell ◽  
William F. Fagan

Seasonal migrations are a widespread and broadly successful strategy for animals to exploit periodic and localized resources over large spatial scales. It remains an open and largely case-specific question whether long-distance migrations are resilient to environmental disruptions. High levels of mobility suggest an ability to shift ranges that can confer resilience. On the other hand, a conservative, hard-wired commitment to a risky behavior can be costly if conditions change. Mechanisms that contribute to migration include identification and responsiveness to resources, sociality, and cognitive processes such as spatial memory and learning. Our goal was to explore the extent to which these factors interact not only to maintain a migratory behavior but also to provide resilience against environmental changes. We develop a diffusion-advection model of animal movement in which an endogenous migratory behavior is modified by recent experiences via a memory process, and animals have a social swarming-like behavior over a range of spatial scales. We found that this relatively simple framework was able to adapt to a stable, seasonal resource dynamic under a broad range of parameter values. Furthermore, the model was able to acquire an adaptive migration behavior with time. However, the resilience of the process depended on all the parameters under consideration, with many complex trade-offs. For example, the spatial scale of sociality needed to be large enough to capture changes in the resource, but not so large that the acquired collective information was overly diluted. A long-term reference memory was important for hedging against a highly stochastic process, but a higher weighting of more recent memory was needed for adapting to directional changes in resource phenology. Our model provides a general and versatile framework for exploring the interaction of memory, movement, social and resource dynamics, even as environmental conditions globally are undergoing rapid change.


2010 ◽  
Author(s):  
Geoffrey A. McMichael ◽  
Ryan A. Harnish ◽  
Brian J. Bellgraph ◽  
Jessica A. Carter ◽  
Kenneth D. Ham ◽  
...  

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