Modulation of high- and low-frequency components of the cortical local field potential via nicotinic and muscarinic acetylcholine receptors in anesthetized mice

Release of acetylcholine (ACh) in neocortex is important for learning, memory and attention tasks. The primary source of ACh in neocortex is axons ascending from the basal forebrain. Release of ACh from these axons evokes changes in the cortical local field potential (LFP), including a decline in low-frequency spectral power that is often referred to as desynchronization of the LFP and is thought to result from the activation of muscarinic ACh receptors. Using channelrhodopsin-2, we selectively stimulated the axons of only cholinergic basal forebrain neurons in primary somatosensory cortex of the urethane-anesthetized mouse while monitoring the LFP. Cholinergic stimulation caused desynchronization and two brief increases in higher-frequency power at stimulus onset and offset. Desynchronization (1–6 Hz) was localized, extending ≤ 1 mm from the edge of stimulation, and consisted of both nicotinic and muscarinic receptor-mediated components that were inhibited by mecamylamine and atropine, respectively. Hence we have identified a nicotinic receptor-mediated component to desynchronization. The increase in higher-frequency power (>10 Hz) at stimulus onset was also mediated by activation of nicotinic and muscarinic receptors. However, the increase in higher-frequency power (10–20 Hz) at stimulus offset was evoked by activation of muscarinic receptors and inhibited by activation of nicotinic receptors. We conclude that the activation of nicotinic and muscarinic ACh receptors in neocortex exerts several effects that are reflected in distinct frequency bands of the cortical LFP in urethane-anesthetized mice.

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Low-Frequency and High-Frequency Modulation of the Local Field Potential Spectrum of Genetically Engineered Rats Induced By Odor Stimuli

ECS Meeting Abstracts ◽

10.1149/ma2021-01621643mtgabs ◽

2021 ◽

Vol MA2021-01 (62) ◽

pp. 1643-1643

Author(s):

Ping Zhu ◽

Yu-lan Tian ◽

Shu-ge Liu ◽

Ya-ting Chen ◽

Wei Chen ◽

...

Keyword(s):

Local Field ◽

Frequency Modulation ◽

Local Field Potential ◽

High Frequency ◽

Field Potential ◽

Low Frequency ◽

Genetically Engineered

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Low-frequency phase-locking of selective human medial temporal lobe neurons to the local field potential of contralateral lateral prefrontal cortex during visual stimulation

Frontiers in Neuroinformatics ◽

10.3389/conf.fninf.2014.18.00046 ◽

2014 ◽

Vol 8 ◽

Author(s):

Sikkens Tom ◽

Possel Jessy ◽

Self Matthew ◽

Baeyen Hans ◽

Claus Steven ◽

...

Keyword(s):

Prefrontal Cortex ◽

Temporal Lobe ◽

Local Field ◽

Local Field Potential ◽

Medial Temporal Lobe ◽

Visual Stimulation ◽

Phase Locking ◽

Field Potential ◽

Low Frequency ◽

Frequency Phase

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Visual recognition is heralded by shifts in local field potential oscillations and inhibitory networks in primary visual cortex

10.1101/2020.12.22.423969 ◽

2020 ◽

Author(s):

Dustin J. Hayden ◽

Daniel P. Montgomery ◽

Samuel F. Cooke ◽

Mark F. Bear

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Local Field ◽

High Frequency ◽

Peak Power ◽

Field Potential ◽

Low Frequency ◽

Inhibitory Neurons ◽

Stimulus Familiarity ◽

Frequency Power

AbstractFiltering out familiar, irrelevant stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process. Oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. In awake mice, we find pronounced changes in LFP oscillatory activity present in layer 4 of primary visual cortex (V1) with progressive stimulus familiarity. Over days of repeated stimulus presentation, low frequency (alpha/beta ~15 Hz peak) power increases while high frequency (gamma ~65 Hz peak) power decreases. This high frequency activity re-emerges when a novel stimulus is shown. Thus, high frequency power is a marker of novelty while low frequency power signifies familiarity. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, consistent with their known role in gamma oscillations, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns, indicating a contribution to the emergence of lower frequency oscillations. We also reveal that stimulus familiarity and novelty have differential effects on oscillations and cell activity over a shorter timescale of seconds. Taken together with previous findings, we propose a model in which two interneuron circuits compete to drive familiarity or novelty encoding.

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Low-frequency subthalamic neural oscillations are involved in explicit and implicit facial emotional processing - a local field potential study

10.1101/2020.10.21.348755 ◽

2020 ◽

Author(s):

Thibaut Dondaine ◽

Joan Duprez ◽

Jean-François Houvenaghel ◽

Julien Modolo ◽

Claire Haegelen ◽

...

Keyword(s):

Cognitive Control ◽

Cognitive Processing ◽

Local Field ◽

Local Field Potential ◽

Emotional Processing ◽

Field Potential ◽

Low Frequency ◽

Emotional Valence ◽

Neural Oscillations ◽

Trial Phase

AbstractIn addition to the subthalamic nucleus’ (STN) role in motricity, STN deep brain stimulation (DBS) for Parkinson’s disease (PD) has also uncovered its involvement in cognitive and limbic processing. STN neural oscillations analyzed through local field potential (LFP) recordings have been shown to contribute to emotional (mostly in the alpha band [8-12 Hz]) and cognitive processing (theta [4-7 Hz] and beta [13-30 Hz] bands). In this study, we aimed at testing the hypothesis that STN oscillatory activity is involved in explicit and implicit processing of emotions. We used a task that presented the patients with emotional facial expressions and manipulated the cognitive demand by either asking them to identify the emotion (explicit task) or the gender of the face (implicit task). We evaluated emotion and task effects on STN neural oscillations power and inter-trial phase consistency. Our results revealed that STN delta power was influenced by emotional valence, but only in the implicit task. Interestingly, the strongest results were found for inter-trial phase consistency: we found an increased consistency for delta oscillations in the implicit task as compared to the explicit task. Furthermore, increased delta and theta consistency were associated with better task performance. These low-frequency effects are similar to the oscillatory dynamics described during cognitive control. We suggest that these findings might reflect a greater need for cognitive control, although an effect of greatest task difficulty in the implicit situation could have influenced the results as well. Overall, our study suggests that low-frequency STN neural oscillations, especially their functional organization, are involved in explicit and implicit emotional processing.Highlights-STN LFPs were recorded during an emotional/gender recognition task in PD patients-STN delta power increase depended on emotional valence in the implicit task only-STN delta inter-trial phase consistency increase was greater for the implicit task-Delta/theta inter-trial phase consistency was associated with task accuracy-The STN is involved in the interaction between emotional and cognitive processing

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Coupling of synaptic inputs to local cortical activity differs among neurons and adapts after stimulus onset

Journal of Neurophysiology ◽

10.1152/jn.00398.2017 ◽

2017 ◽

Vol 118 (6) ◽

pp. 3345-3359 ◽

Cited By ~ 4

Author(s):

Nathaniel C. Wright ◽

Mahmood S. Hoseini ◽

Tansel Baran Yasar ◽

Ralf Wessel

Keyword(s):

Local Field ◽

Visual Processing ◽

Local Field Potential ◽

Cortical Neurons ◽

Pyramidal Neurons ◽

Field Potential ◽

Cortical Activity ◽

Stimulus Onset ◽

Synaptic Inputs ◽

Network Properties

Cortical activity contributes significantly to the high variability of sensory responses of interconnected pyramidal neurons, which has crucial implications for sensory coding. Yet, largely because of technical limitations of in vivo intracellular recordings, the coupling of a pyramidal neuron’s synaptic inputs to the local cortical activity has evaded full understanding. Here we obtained excitatory synaptic conductance ( g) measurements from putative pyramidal neurons and local field potential (LFP) recordings from adjacent cortical circuits during visual processing in the turtle whole brain ex vivo preparation. We found a range of g-LFP coupling across neurons. Importantly, for a given neuron, g-LFP coupling increased at stimulus onset and then relaxed toward intermediate values during continued visual stimulation. A model network with clustered connectivity and synaptic depression reproduced both the diversity and the dynamics of g-LFP coupling. In conclusion, these results establish a rich dependence of single-neuron responses on anatomical, synaptic, and emergent network properties. NEW & NOTEWORTHY Cortical neurons are strongly influenced by the networks in which they are embedded. To understand sensory processing, we must identify the nature of this influence and its underlying mechanisms. Here we investigate synaptic inputs to cortical neurons, and the nearby local field potential, during visual processing. We find a range of neuron-to-network coupling across cortical neurons. This coupling is dynamically modulated during visual processing via biophysical and emergent network properties.

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Inflammatory pain by carrageenan recruits low-frequency local field potential changes in the anterior cingulate cortex

Neuroscience Letters ◽

10.1016/j.neulet.2016.08.016 ◽

2016 ◽

Vol 632 ◽

pp. 8-14 ◽

Cited By ~ 15

Author(s):

Amber L. Harris-Bozer ◽

Yuan B. Peng

Keyword(s):

Anterior Cingulate Cortex ◽

Local Field ◽

Local Field Potential ◽

Inflammatory Pain ◽

Field Potential ◽

Low Frequency ◽

Cingulate Cortex ◽

Anterior Cingulate

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Estimation of neural network model parameters from local field potentials (LFPs)

10.1101/564765 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jan-Eirik W. Skaar ◽

Alexander J. Stasik ◽

Espen Hagen ◽

Torbjørn V. Ness ◽

Gaute T. Einevoll

Keyword(s):

Network Model ◽

Local Field ◽

Local Field Potential ◽

Field Potential ◽

Low Frequency ◽

Network Models ◽

Neural Nets ◽

Model Parameters ◽

Neuron Network ◽

Local Field Potential Lfp

AbstractMost modeling in systems neuroscience has beendescriptivewhere neural representations, that is, ‘receptive fields’, have been found by statistically correlating neural activity to sensory input. In the traditional physics approach to modelling, hypotheses are represented bymechanisticmodels based on the underlying building blocks of the system, and candidate models are validated by comparing with experiments. Until now validation of mechanistic cortical network models has been based on comparison with neuronal spikes, found from the high-frequency part of extracellular electrical potentials. In this computational study we investigated to what extent the low-frequency part of the signal, the local field potential (LFP), can be used to infer properties of the neuronal network. In particular, we asked the question whether the LFP can be used to accurately estimate synaptic connection weights in the underlying network. We considered the thoroughly analysed Brunel network comprising an excitatory and an inhibitory population of recurrently connected integrate-and-fire (LIF) neurons. This model exhibits a high diversity of spiking network dynamics depending on the values of only three synaptic weight parameters. The LFP generated by the network was computed using a hybrid scheme where spikes computed from the point-neuron network were replayed on biophysically detailed multicompartmental neurons. We assessed how accurately the three model parameters could be estimated from power spectra of stationary ‘background’ LFP signals by application of convolutional neural nets (CNNs). All network parameters could be very accurately estimated, suggesting that LFPs indeed can be used for network model validation.Significance statementMost of what we have learned about brain networksin vivohave come from the measurement of spikes (action potentials) recorded by extracellular electrodes. The low-frequency part of these signals, the local field potential (LFP), contains unique information about how dendrites in neuronal populations integrate synaptic inputs, but has so far played a lesser role. To investigate whether the LFP can be used to validate network models, we computed LFP signals for a recurrent network model (the Brunel network) for which the ground-truth parameters are known. By application of convolutional neural nets (CNNs) we found that the synaptic weights indeed could be accurately estimated from ‘background’ LFP signals, suggesting a future key role for LFP in development of network models.

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Local Field Potential Activity Associated with Temporal Expectations in the Macaque Lateral Intraparietal Area

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00221 ◽

2012 ◽

Vol 24 (6) ◽

pp. 1314-1330 ◽

Cited By ~ 11

Author(s):

Elsie Premereur ◽

Wim Vanduffel ◽

Peter Janssen

Keyword(s):

Local Field ◽

Local Field Potential ◽

Visual Stimulation ◽

Brain Activity ◽

Field Potential ◽

Stimulus Onset ◽

Network Activity ◽

Local Network ◽

Saccade Target ◽

Lateral Intraparietal Area

Oscillatory brain activity is attracting increasing interest in cognitive neuroscience. Numerous EEG (magnetoencephalography) and local field potential (LFP) measurements have related cognitive functions to different types of brain oscillations, but the functional significance of these rhythms remains poorly understood. Despite its proven value, LFP activity has not been extensively tested in the macaque lateral intraparietal area (LIP), which has been implicated in a wide variety of cognitive control processes. We recorded action potentials and LFPs in area LIP during delayed eye movement tasks and during a passive fixation task, in which the time schedule was fixed so that temporal expectations about task-relevant cues could be formed. LFP responses in the gamma band discriminated reliably between saccade targets and distractors inside the receptive field (RF). Alpha and beta responses were much less strongly affected by the presence of a saccade target, however, but rose sharply in the waiting period before the go signal. Surprisingly, conditions without visual stimulation of the LIP-RF-evoked robust LFP responses in every frequency band—most prominently in those below 50 Hz—precisely time-locked to the expected time of stimulus onset in the RF. These results indicate that in area LIP, oscillations in the LFP, which reflect synaptic input and local network activity, are tightly coupled to the temporal expectation of task-relevant cues.

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