High-frequency oscillation of local field potential (LFP) and phase-locked spikes in a songbird basal ganglia nucleus Area X during sleep

2010 ◽  
Vol 68 ◽  
pp. e405
Author(s):  
Shin Yanagihara ◽  
Neal Hessler
2009 ◽  
Vol 102 (2) ◽  
pp. 155-176 ◽  
Author(s):  
George L. Tsirogiannis ◽  
George A. Tagaris ◽  
Damianos Sakas ◽  
Konstantina S. Nikita

2019 ◽  
Author(s):  
Agrita Dubey ◽  
Supratim Ray

AbstractElectrocorticogram (ECoG), obtained from macroelectrodes placed on the cortex, is typically used in drug-resistant epilepsy patients, and is increasingly being used to study cognition in humans. These studies often use power in gamma (30-70 Hz) or high-gamma (>80 Hz) ranges to make inferences about neural processing. However, while the stimulus tuning properties of gamma/high-gamma power have been well characterized in local field potential (LFP; obtained from microelectrodes), analogous characterization has not been done for ECoG. Using a hybrid array containing both micro and ECoG electrodes implanted in the primary visual cortex of two female macaques, we compared the stimulus tuning preferences of gamma/high-gamma power in LFP versus ECoG and found them to be surprisingly similar. High-gamma power, thought to index the average firing rate around the electrode, was highest for the smallest stimulus (0.3° radius), and decreased with increasing size in both LFP and ECoG, suggesting local origins of both signals. Further, gamma oscillations were similarly tuned in LFP and ECoG to stimulus orientation, contrast and spatial frequency. This tuning was significantly weaker in electroencephalogram (EEG), suggesting that ECoG is more like LFP than EEG. Overall, our results validate the use of ECoG in clinical and basic cognitive research.


2021 ◽  
Author(s):  
Hiroshi Tamura

AbstractNeuron activity in the sensory cortices mainly depends on feedforward thalamic inputs. High-frequency activity of a thalamic input can be temporally integrated by a neuron in the sensory cortex and is likely to induce larger depolarization. However, feedforward inhibition (FFI) and depression of excitatory synaptic transmission in thalamocortical pathways attenuate depolarization induced by the latter part of high-frequency spiking activity and the temporal summation may not be effective. The spiking activity of a thalamic neuron in a specific temporal pattern may circumvent FFI and depression of excitatory synapses. The present study determined the relationship between the temporal pattern of spiking activity of a single thalamic neuron and the degree of cortical activation as well as that between the firing rate of spiking activity of a single thalamic neuron and the degree of cortical activation. Spiking activity of a thalamic neuron was recorded extracellularly from the lateral geniculate nucleus (LGN) in male Long-Evans rats. Degree of cortical activation was assessed by simultaneous recording of local field potential (LFP) from the visual cortex. A specific temporal pattern appearing in three consecutive spikes of an LGN neuron induced larger cortical LFP modulation than high-frequency spiking activity during a short period. These findings indicate that spiking activity of thalamic inputs is integrated by a synaptic mechanism sensitive to an input temporal pattern.Significance StatementSensory cortical activity depends on thalamic inputs. Despite the importance of thalamocortical transmission, how spiking activity of thalamic inputs is integrated by cortical neurons remains unclear. Feedforward inhibition and synaptic depression of excitatory transmission may not allow simple temporal summation of membrane potential induced by consecutive spiking activity of a thalamic neuron. A specific temporal pattern appearing in three consecutive spikes of a thalamic neuron induced larger cortical local field potential modulation than high-frequency spiking activity during a short period. The findings indicate the importance of the temporal pattern of spiking activity of a single thalamic neuron on cortical activation.


Materials ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 542 ◽  
Author(s):  
Sung Lee ◽  
Kyeong-Seok Lee ◽  
Saurav Sorcar ◽  
Abdul Razzaq ◽  
Maan-Gee Lee ◽  
...  

Intracerebral local field potential (LFP) measurements are commonly used to monitor brain activity, providing insight into the flow of information across neural networks. Herein we describe synthesis and application of a neural electrode possessing a nano/micro-scale porous surface topology for improved LFP measurement. Compared with conventional brain electrodes, the porous electrodes demonstrate higher measured amplitudes with lower noise levels.


2014 ◽  
Vol 112 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Ramanujan Srinath ◽  
Supratim Ray

Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors—phase consistency as well as amplitude covariation across trials—but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over- or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.


2019 ◽  
Vol 121 (6) ◽  
pp. 2364-2378 ◽  
Author(s):  
N. V. Swindale ◽  
M. A. Spacek

It is generally thought that apart from receptive field differences, such as preferred orientation and spatial frequency selectivity, primary visual cortex neurons are functionally similar to each other. However, the genetic diversity of cortical neurons plus the existence of inputs additional to those required to explain known receptive field properties might suggest otherwise. Here we report the existence of desynchronized states in anesthetized cat area 17 lasting up to 45 min, characterized by variable narrow-band local field potential (LFP) oscillations in the range 2–100 Hz and the absence of a synchronized 1/ f frequency spectrum. During these periods, spontaneously active neurons phase-locked to variable subsets of LFP oscillations. Individual neurons often ignored frequencies that others phase-locked to. We suggest that these desynchronized periods may correspond to REM sleep-like episodes occurring under anesthesia. Frequency-selective codes may be used for signaling during these periods. Hence frequency-selective combination and frequency-labeled pathways may represent a previously unsuspected dimension of cortical organization. NEW & NOTEWORTHY We investigated spontaneous neuronal firing during periods of desynchronized local field potential (LFP) activity, resembling REM sleep, in anesthetized cats. During these periods, neurons synchronized their spikes to specific phases of multiple LFP frequency components, with some neurons ignoring frequencies that others were synchronized to. Some neurons fired at phase alignments of frequency pairs, thereby acting as phase coincidence detectors. These results suggest that internal brain signaling may use frequency combination codes to generate temporally structured spike trains.


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