Muscimol and baclofen differentially suppress retinotopic and nonretinotopic responses in visual cortex

2005 ◽  
Vol 22 (6) ◽  
pp. 839-858 ◽  
Author(s):  
TAKUJI KASAMATSU ◽  
KEIKO MIZOBE ◽  
ERICH E. SUTTER

This study relates to local field potentials and single-unit responses in cat visual cortex elicited by contrast reversal of bar gratings that were presented in single, double, or multiple discrete patch (es) of the visual field. Concurrent stimulation of many patches by means of the pseudorandom, binary m-sequence technique revealed interactions between their respective responses. An analysis identified two distinct components of local field potentials: a fast local component (FLC) and a slow distributed component (SDC). The FLC is thought to be a primarily postsynaptic response, as judged by its relatively short latency. It is directly generated by thalamocortical volleys following retinotopic stimulation of receptive fields of a small cluster of single cells, combined with responses to recurrent excitation and inhibition derived from the cells under study and immediately neighboring cells. In contrast, the SDC is thought to be an aggregate of dendritic potentials related to the long-range lateral connections (i.e. long-range coupling). We compared the suppressive effects of a GABAA-receptor agonist, muscimol, on the FLC and SDC with those of a GABAB-receptor agonist, baclofen, and found that muscimol more strongly suppressed the FLC than the SDC, and that the reverse was the case for baclofen. The differential suppression of the FLC and SDC found in the present study is consistent with the notion that intracortical electrical signals related to the FLC terminate on the somata and proximal/basal dendrites, while those related to the SDC terminate on distal dendrites.

2010 ◽  
Vol 9 (8) ◽  
pp. 740-740
Author(s):  
F. A. Khawaja ◽  
J. M. G. Tsui ◽  
C. C. Pack

2018 ◽  
Vol 120 (4) ◽  
pp. 1625-1639 ◽  
Author(s):  
Vanessa L. Mock ◽  
Kimberly L. Luke ◽  
Jacqueline R. Hembrook-Short ◽  
Farran Briggs

Correlations and inferred causal interactions among local field potentials (LFPs) simultaneously recorded in distinct visual brain areas can provide insight into how visual and cognitive signals are communicated between neuronal populations. Based on the known anatomical connectivity of hierarchically organized visual cortical areas and electrophysiological measurements of LFP interactions, a framework for interareal frequency-specific communication has emerged. Our goals were to test the predictions of this framework in the context of the early visual pathways and to understand how attention modulates communication between the visual thalamus and primary visual cortex. We recorded LFPs simultaneously in retinotopically aligned regions of the visual thalamus and primary visual cortex in alert and behaving macaque monkeys trained on a contrast-change detection task requiring covert shifts in visual spatial attention. Coherence and Granger-causal interactions among early visual circuits varied dynamically over different trial periods. Attention significantly enhanced alpha-, beta-, and gamma-frequency interactions, often in a manner consistent with the known anatomy of early visual circuits. However, attentional modulation of communication among early visual circuits was not consistent with a simple static framework in which distinct frequency bands convey directed inputs. Instead, neuronal network interactions in early visual circuits were flexible and dynamic, perhaps reflecting task-related shifts in attention. NEW & NOTEWORTHY Attention alters the way we perceive the visual world. For example, attention can modulate how visual information is communicated between the thalamus and cortex. We recorded local field potentials simultaneously in the visual thalamus and cortex to quantify the impact of attention on visual information communication. We found that attentional modulation of visual information communication was not static, but dynamic over the time course of trials.


2016 ◽  
Vol 115 (3) ◽  
pp. 1587-1595 ◽  
Author(s):  
Teresa H. Sanders

Interactions between neural oscillations in the brain have been observed in many structures including the hippocampus, amygdala, motor cortex, and basal ganglia. In this study, one popular approach for quantifying oscillation interactions was considered: phase-amplitude coupling. The goals of the study were to use simulations to examine potential causes of elevated phase-amplitude coupling in parkinsonism, to compare simulated parkinsonian signals with recorded local field potentials from animal models of parkinsonism, to investigate possible relationships between increased bursting in parkinsonian single cells and elevated phase-amplitude coupling, and to uncover potential noise and artifact effects. First, a cell model that integrates incremental input currents and fires at realistic voltage thresholds was modified to allow control of stochastic parameters related to firing and burst rates. Next, the input currents and distribution of integration times were set to reproduce firing patterns consistent with those from parkinsonian subthalamic nucleus cells. Then, local field potentials were synthesized from the output of multiple simulated cells with varying degrees of synchronization and compared with subthalamic nucleus recordings from animal models of parkinsonism. The results showed that phase-amplitude coupling can provide important information about underlying neural activity. In particular, signals synthesized from synchronized bursting neurons showed increased oscillatory interactions similar to those observed in parkinsonian animals. Additionally, changes in bursting parameters such as the intraburst rate, the mean interburst period, and the amount of synchronization between neurons influenced the phase-amplitude coupling in predictable ways. Finally, simulation results revealed that small periodic signals can have a surprisingly large masking effect on phase-amplitude coupling.


2008 ◽  
Vol 28 (22) ◽  
pp. 5696-5709 ◽  
Author(s):  
A. Belitski ◽  
A. Gretton ◽  
C. Magri ◽  
Y. Murayama ◽  
M. A. Montemurro ◽  
...  

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