Reticular facilitation of cat visual cortical responses is mediated by nicotinic and muscarinic cholinergic mechanisms

1993 ◽  
Vol 96 (1) ◽  
pp. 1-7 ◽  
Author(s):  
M. H. Lewandowski ◽  
C. M. Müller ◽  
W. Singer
2021 ◽  
pp. 1-12
Author(s):  
Joonkoo Park ◽  
Sonia Godbole ◽  
Marty G. Woldorff ◽  
Elizabeth M. Brannon

Abstract Whether and how the brain encodes discrete numerical magnitude differently from continuous nonnumerical magnitude is hotly debated. In a previous set of studies, we orthogonally varied numerical (numerosity) and nonnumerical (size and spacing) dimensions of dot arrays and demonstrated a strong modulation of early visual evoked potentials (VEPs) by numerosity and not by nonnumerical dimensions. Although very little is known about the brain's response to systematic changes in continuous dimensions of a dot array, some authors intuit that the visual processing stream must be more sensitive to continuous magnitude information than to numerosity. To address this possibility, we measured VEPs of participants viewing dot arrays that changed exclusively in one nonnumerical magnitude dimension at a time (size or spacing) while holding numerosity constant and compared this to a condition where numerosity was changed while holding size and spacing constant. We found reliable but small neural sensitivity to exclusive changes in size and spacing; however, changing numerosity elicited a much more robust modulation of the VEPs. Together with previous work, these findings suggest that sensitivity to magnitude dimensions in early visual cortex is context dependent: The brain is moderately sensitive to changes in size and spacing when numerosity is held constant, but sensitivity to these continuous variables diminishes to a negligible level when numerosity is allowed to vary at the same time. Neurophysiological explanations for the encoding and context dependency of numerical and nonnumerical magnitudes are proposed within the framework of neuronal normalization.


NeuroImage ◽  
2016 ◽  
Vol 134 ◽  
pp. 532-539 ◽  
Author(s):  
Yoshihito Shigihara ◽  
Hideyuki Hoshi ◽  
Semir Zeki

2013 ◽  
Vol 10 (5) ◽  
pp. 056011 ◽  
Author(s):  
Sam E John ◽  
Mohit N Shivdasani ◽  
Chris E Williams ◽  
John W Morley ◽  
Robert K Shepherd ◽  
...  

Pain ◽  
1985 ◽  
Vol 21 (2) ◽  
pp. 196
Author(s):  
J. W. Lewis ◽  
J. T. Cannon ◽  
J. C. Liebeskind

1983 ◽  
Vol 270 (2) ◽  
pp. 289-293 ◽  
Author(s):  
J.W. Lewis ◽  
J.T. Cannon ◽  
J.C. Liebeskind

1993 ◽  
Vol 71 (5-6) ◽  
pp. 352-364 ◽  
Author(s):  
Peter H. Kelly ◽  
Jan Malanowski

In their first swim in an unfamiliar circular swimming pool, control rats showed declines in average swimming speed and in the time spent in the perimeter of the pool. Both declines were antagonized by the muscarinic antagonist scopolamine, but not by methylscopolamine, a muscarinic antagonist that crosses the blood–brain barrier only poorly, indicating that these declines depend upon central cholinergic activity. In the first minute of a second swim 3 days later, control rats spent a much longer time in the central region of the pool than in the first minute of the first swim. This modification of behaviour by previous experience suggests that a long-term memory of the first swim was formed. Scopolamine, but not methylscopolamine, administered before the first swim attenuated this modification of behaviour. Pilocarpine, administered shortly after scopolamine before the first swim, significantly normalized all the scopolamine-induced changes, whereas oxotremorine and arecoline normalized only habituation of perimeter preference; agonists administered alone decreased swimming speed and perimeter preference without affecting their rates of decline. The results suggest that in this test, different cholinergic mechanisms are involved in habituation of swimming speed and habituation of perimeter preference.Key words: scopolamine, muscarinic cholinergic agonists, swimming exploration pattern, habituation, memory.


Cortex ◽  
2013 ◽  
Vol 49 (4) ◽  
pp. 1013-1024 ◽  
Author(s):  
Éva M. Bankó ◽  
Judit Körtvélyes ◽  
János Németh ◽  
Béla Weiss ◽  
Zoltán Vidnyánszky

2005 ◽  
Vol 22 (1) ◽  
pp. 37-43 ◽  
Author(s):  
S.V. GIRMAN ◽  
R.D. LUND

In the Royal College of Surgeons, rat photoreceptor degeneration occurs over the first several months of life, causing deterioration of visual cortical responsiveness seen as greater numbers of cells being nonresponsive to visual stimulation, poor tuning of those cells that do respond, and an overall tendency for domination by the contralateral visual input. If the progress of degeneration in one eye is slowed by intraretinal cell transplantation, cortical responses to stimulation of the remaining, untreated, eye are much stronger, better tuned and histograms of ocular dominance resemble more those in normal rats. This suggests that the rescued eye is able to enhance performance in the untreated eye by some form of postsynaptic mechanism.


2017 ◽  
Author(s):  
Haiguang Wen ◽  
Junxing Shi ◽  
Wei Chen ◽  
Zhongming Liu

Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the specific subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while deep residual neural network driven by image recognition was used to model the visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish subject-specific or populationwide predictive models of cortical representations of high-dimensional and hierarchical visual features.


2020 ◽  
Vol 20 (11) ◽  
pp. 618
Author(s):  
Rachel Denison ◽  
Karen Tian ◽  
David Heeger ◽  
Marisa Carrasco

Sign in / Sign up

Export Citation Format

Share Document