scholarly journals Basal forebrain activation enhances between-trial reliability of low-frequency local field potentials (LFP) and spiking activity in tree shrew primary visual cortex (V1)

2017 ◽  
Vol 222 (9) ◽  
pp. 4239-4252 ◽  
Author(s):  
Paolo De Luna ◽  
Julia Veit ◽  
Gregor Rainer
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
Basal Forebrain ◽  
Tree Shrew ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Field Potentials ◽  
Spiking Activity

scholarly journals Low-Frequency Local Field Potentials and Spikes in Primary Visual Cortex Convey Independent Visual Information

2008 ◽  
Vol 28 (22) ◽  
pp. 5696-5709 ◽  
Author(s):  
A. Belitski ◽  
A. Gretton ◽  
C. Magri ◽  
Y. Murayama ◽  
M. A. Montemurro ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
Visual Information ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Field Potentials

scholarly journals Dynamic communication of attention signals between the LGN and V1

2018 ◽  
Vol 120 (4) ◽  
pp. 1625-1639 ◽  
Author(s):  
Vanessa L. Mock ◽  
Kimberly L. Luke ◽  
Jacqueline R. Hembrook-Short ◽  
Farran Briggs
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
Visual Information ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Information Communication ◽  
Attentional Modulation ◽  
Visual Thalamus ◽  
The Impact

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.

scholarly journals Response Properties of Local Field Potentials and Neighboring Single Neurons in Awake Primary Visual Cortex

2012 ◽  
Vol 32 (33) ◽  
pp. 11396-11413 ◽  
Author(s):  
R. Lashgari ◽  
X. Li ◽  
Y. Chen ◽  
J. Kremkow ◽  
Y. Bereshpolova ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Single Neurons ◽  
Response Properties

scholarly journals Inferring Spike Trains From Local Field Potentials

2008 ◽  
Vol 99 (3) ◽  
pp. 1461-1476 ◽  
Author(s):  
Malte J. Rasch ◽  
Arthur Gretton ◽  
Yusuke Murayama ◽  
Wolfgang Maass ◽  
Nikos K. Logothetis
Keyword(s):  
Spontaneous Activity ◽  
Local Field ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Spike Trains ◽  
Dorsal Lateral Geniculate Nucleus ◽  
Support Vector ◽  
Field Potentials ◽  
Data Set ◽  
Spiking Activity

We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100-ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high γ-range (40–90 Hz) and information contained in low-frequency oscillations (<10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during seminatural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of non-anesthetized monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g., LFPs derived from recordings in the dorsal lateral geniculate nucleus) hold no useful information for predicting spiking activity.

scholarly journals fMRI correlates for low frequency local field potentials appear as a spatiotemporal dynamic under multiple anesthetic conditions

2012 ◽  
Vol 13 (S1) ◽  
Author(s):  
Garth J Thompson ◽  
Wen-Ju Pan ◽  
Matthew E Magnuson ◽  
Shella D Keilholz
Keyword(s):  
Local Field ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Field Potentials ◽  
Spatiotemporal Dynamic
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