Low-frequency Local Field Potentials Research Articles

Information content and temporal structure of face selective local field potentials frequency bands in IT cortex.

Sensory stimulation triggers synchronized bioelectrical activity in the brain across various frequencies. This study delves into network-level activities, specifically focusing on local field potentials as a neural signature of visual category representation. Specifically, we studied the role of different local field potential frequency oscillation bands in visual stimulus category representation by presenting images of faces and objects to three monkeys while recording local field potential from inferior temporal cortex. We found category selective local field potential responses mainly for animate, but not inanimate, objects. Notably, face-selective local field potential responses were evident across all tested frequency bands, manifesting in both enhanced (above mean baseline activity) and suppressed (below mean baseline activity) local field potential powers. We observed four different local field potential response profiles based on frequency bands and face selective excitatory and suppressive responses. Low-frequency local field potential bands (1-30Hz) were more prodominstaly suppressed by face stimulation than the high-frequency (30-170Hz) local field potential bands. Furthermore, the low-frequency local field potentials conveyed less face category informtion than the high-frequency local field potential in both enhansive and suppressive conditions. Furthermore, we observed a negative correlation between face/object d-prime values in all the tested local field potential frequency bands and the anterior-posterior position of the recording sites. In addition, the power of low-frequency local field potential systematically declined across inferior temporal anterior-posterior positions, whereas high-frequency local field potential did not exhibit such a pattern. In general, for most of the above-mentioned findings somewhat similar results were observed for body, but not, other stimulus categories. The observed findings suggest that a balance of face selective excitation and inhibition across time and cortical space shape face category selectivity in inferior temporal cortex.

A Hyperflexible Electrode Array for Long-Term Recording and Decoding of Intraspinal Neuronal Activity.

Neural interfaces for stable access to the spinal cord (SC) electrical activity can benefit patients with motor dysfunctions. Invasive high-density electrodes can directly extract signals from SC neuronal populations that can be used for the facilitation, adjustment, and reconstruction of motor actions. However, developing neural interfaces that can achieve high channel counts and long-term intraspinal recording remains technically challenging. Here, a biocompatible SC hyperflexible electrode array (SHEA) with an ultrathin structure that minimizes mechanical mismatch between the interface and SC tissue and enables stable single-unit recording for more than 2 months in mice is demonstrated. These results show that SHEA maintains stable impedance, signal-to-noise ratio, single-unit yield, and spike amplitude after implantation into mouse SC. Gait analysis and histology show that SHEA implantation induces negligible behavioral effects and Inflammation. Additionally, multi-unit signals recorded from the SC ventral horn can predict the mouse's movement trajectory with a high decoding coefficient of up to 0.95. Moreover, during step cycles, it is found that the neural trajectory of spikes and low-frequency local field potential (LFP) signal exhibits periodic geometry patterns. Thus, SHEA can offer an efficient and reliable SC neural interface for monitoring and potentially modulating SC neuronal activity associated with motor dysfunctions.

Effects of anterior thalamic nuclei stimulation on hippocampal activity: Chronic recording in a patient with drug-resistant focal epilepsy.

Implanted neurostimulation devices are gaining traction as palliative treatment options for certain forms of drug-resistant epilepsy, but clinical utility of these devices is hindered by incomplete mechanistic understanding of their therapeutic effects. Approved devices for anterior thalamic nuclei deep brain stimulation (ANT DBS) are thought to work at a network level, but limited sensing capability precludes characterization of neurophysiological effects outside the thalamus. Here, we describe a patient with drug-resistant temporal lobe epilepsy who was implanted with a responsive neurostimulation device (RNS System), involving hippocampal and ipsilateral temporal neocortical leads, and subsequently received ANT DBS. Over 1.5years, RNS System electrocorticography enabled multiscale characterization of neurophysiological effects of thalamic stimulation. In brain regions sampled by the RNS System, ANT DBS produced acute, phasic, frequency-dependent responses, including suppression of hippocampal low frequency local field potentials. ANT DBS modulated functional connectivity between hippocampus and neocortex. Finally, ANT DBS progressively suppressed hippocampal epileptiform activity in relation to the extent of hippocampal theta suppression, which informs stimulation parameter selection for ANT DBS. Taken together, this unique clinical scenario, involving hippocampal recordings of unprecedented chronicity alongside ANT DBS, sheds light on the therapeutic mechanism of thalamic stimulation and highlights capabilities needed in next-generation devices.

Insular responses to transient painful and non-painful thermal and mechanical spinothalamic stimuli recorded using intracerebral EEG

Brief thermo-nociceptive stimuli elicit low-frequency phase-locked local field potentials (LFPs) and high-frequency gamma-band oscillations (GBOs) in the human insula. Although neither of these responses constitute a direct correlate of pain perception, previous findings suggest that insular GBOs may be strongly related to the activation of the spinothalamic system and/or to the processing of thermal information. To disentangle these different features of the stimulation, we compared the insular responses to brief painful thermonociceptive stimuli, non-painful cool stimuli, mechano-nociceptive stimuli, and innocuous vibrotactile stimuli, recorded using intracerebral electroencephalograpic activity in 7 epileptic patients (9 depth electrodes, 58 insular contacts). All four types of stimuli elicited consistent low-frequency phase-locked LFPs throughout the insula, possibly reflecting supramodal activity. The latencies of thermo-nociceptive and cool low-frequency phase-locked LFPs were shorter in the posterior insula compared to the anterior insula, suggesting a similar processing of thermal input initiating in the posterior insula, regardless of whether the input produces pain and regardless of thermal modality. In contrast, only thermo-nociceptive stimuli elicited an enhancement of insular GBOs, suggesting that these activities are not simply related to the activation of the spinothalamic system or to the conveyance of thermal information.

Phase‐amplitude coupling profiles differ in frontal and auditory cortices of bats

Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1-4Hz), theta (4-8Hz) or gamma (>30Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase-amplitude coupling (PAC) is one such plausible and well-described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal-auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local-field potentials (LFPs), we show that the amplitude of gamma-band activity couples with the phase of low-frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high-gamma frequencies (1-4/75-100Hz), whereas in the AC the coupling is strongest in the delta-theta/low-gamma (2-8/25-55Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal-auditory cortex network.

Attention strengthens across-trial pre-stimulus phase coherence in visual cortex, enhancing stimulus processing

Attention selectively routes the most behaviorally relevant information from the stream of sensory inputs through the hierarchy of cortical areas. Previous studies have shown that visual attention depends on the phase of oscillatory brain activities. These studies mainly focused on the stimulus presentation period, rather than the pre-stimulus period. Here, we hypothesize that selective attention controls the phase of oscillatory neural activities to efficiently process relevant information. We document an attentional modulation of pre-stimulus inter-trial phase coherence (a measure of deviation between instantaneous phases of trials) of low frequency local field potentials (LFP) in visual area MT of macaque monkeys. Our data reveal that phase coherence increases following a spatial cue deploying attention towards the receptive field of the recorded neural population. We further show that the attentional enhancement of phase coherence is positively correlated with the modulation of the stimulus-induced firing rate, and importantly, a higher phase coherence is associated with a faster behavioral response. These results suggest a functional utilization of intrinsic neural oscillatory activities for an enhanced processing of upcoming stimuli.

Spatial attention enhances network, cellular and subthreshold responses in mouse visual cortex

Internal brain states strongly modulate sensory processing during behaviour. Studies of visual processing in primates show that attention to space selectively improves behavioural and neural responses to stimuli at the attended locations. Here we develop a visual spatial task for mice that elicits behavioural improvements consistent with the effects of spatial attention, and simultaneously measure network, cellular, and subthreshold activity in primary visual cortex. During trial-by-trial behavioural improvements, local field potential (LFP) responses to stimuli detected inside the receptive field (RF) strengthen. Moreover, detection inside the RF selectively enhances excitatory and inhibitory neuron responses to task-irrelevant stimuli and suppresses noise correlations and low frequency LFP fluctuations. Whole-cell patch-clamp recordings reveal that detection inside the RF increases synaptic activity that depolarizes membrane potential responses at the behaviorally relevant location. Our study establishes that mice display fundamental signatures of visual spatial attention spanning behavioral, network, cellular, and synaptic levels, providing new insight into rapid cognitive enhancement of sensory signals in visual cortex.

On the Relationship between MRI and Local Field Potential Measurements of Spatial and Temporal Variations in Functional Connectivity

Correlations between fluctuations in resting state BOLD fMRI signals are interpreted as measures of functional connectivity (FC), but the neural basis of their origins and their relationships to specific features of underlying electrophysiologic activity, have not been fully established. In particular, the dependence of FC metrics on different frequency bands of local field potentials (LFPs), and the relationship of dynamic changes in BOLD FC to underlying temporal variations of LFP correlations, are not known. We compared the spatial profiles of resting state coherences of different frequency bands of LFP signals, with high resolution resting state BOLD FC measurements. We also compared the probability distributions of temporal variations of connectivity in both modalities using a Markov chain model-based approach. We analyzed data obtained from the primary somatosensory (S1) cortex of monkeys. We found that in areas 3b and 1 of S1 cortex, low frequency LFP signal fluctuations were the main contributions to resting state LFP coherence. Additionally, the dynamic changes of BOLD FC behaved most similarly to the LFP low frequency signal coherence. These results indicate that, within the S1 cortex meso-scale circuit studied, resting state FC measures from BOLD fMRI mainly reflect contributions from low frequency LFP signals and their dynamic changes.

Using High-Frequency Local Field Potentials From Multicortex to Decode Reaching and Grasping Movements in Monkey

Intracortical brain–machine interfaces (iBMIs) hold the promise to restore communication and movement ability of paralyzed people. Recent studies showed that local field potentials (LFPs) could be a reliable neural signal for movement intention decoding in iBMIs. However, previous studies investigated primarily on low-frequency LFPs, while the LFPs used were recorded from only one or two cortices. The aim of this paper is to investigate the potential of high-frequency LFPs (200–300 Hz) from multicortex in movement intention decoding. In this paper, LFPs were recorded via microelectrode arrays chronically implanted into the primary motor cortex (M1), somatosensory cortex (S1), and posterior parietal cortex of two monkeys while they were trained to perform 3-D reaching and grasping movements. The wavelet packet transform (WPT) method was used to extract the time and frequency information of the high-frequency LFP signals and the node energy of the WPT coefficients was selected as the features. After feature reduction by the principal component analysis, a support vector machine decoder was used to classify discrete reaching positions and grasping postures. Our results indicate that high decoding accuracy can be achieved by the high-frequency LFPs with WPT method and this kind of LFPs could serve as useful signals in iBMIs for movement intention decoding. Moreover, better and more robust decoding performance can be achieved by LFPs from multicortex than single-cortex.

Low-Frequency Spike-Field Coherence Is a Fingerprint of Periodicity Coding in the Auditory Cortex

SummaryThe extraction of temporal information from sensory input streams is of paramount importance in the auditory system. In this study, amplitude-modulated sounds were used as stimuli to drive auditory cortex (AC) neurons of the bat species Carollia perspicillata, to assess the interactions between cortical spikes and local-field potentials (LFPs) for the processing of temporal acoustic cues. We observed that neurons in the AC capable of eliciting synchronized spiking to periodic acoustic envelopes were significantly more coherent to theta- and alpha-band LFPs than their non-synchronized counterparts. These differences occurred independently of the modulation rate tested and could not be explained by power or phase modulations of the field potentials. We argue that the coupling between neuronal spiking and the phase of low-frequency LFPs might be important for orchestrating the coding of temporal acoustic structures in the AC.

Attention decouples action potentials from the phase of local field potentials in macaque visual cortical area MT

BackgroundThe timing of action potentials (“spikes”) of cortical neurons has been shown to be aligned to the phase of low-frequency (< 10 Hz) local field potentials (LFPs) in several cortical areas. However, across the areas, this alignment varies and the role of this spike-phase coupling (SPC) in cognitive functions is not well understood.ResultsHere, we propose a role in the coordination of neural activity by selective attention. After refining previous analytical methods for measuring SPC, we show that first, SPC is present along the dorsal processing pathway in macaque visual cortex (area MT); second, spikes occur in falling phases of the low-frequency LFP independent of the location of spatial attention; third, switching spatial attention into the receptive field (RF) of MT neurons decreases this coupling; and finally, the LFP phase causally influences the spikes.ConclusionsHere, we show that spikes are coupled to the phase of low-frequency LFP along the dorsal visual pathway. Our data suggest that attention harnesses this spike-LFP coupling to de-synchronize neurons and thereby enhance the neural representation of the attended stimuli.

P69. High-frequency (>500 Hz) recordings from deep brain macroelectrodes reveal local interactions of subcortical multi-unit activity

Introduction While low-frequency local field potentials (LFPs) are generated mainly by postsynaptic potentials, high-frequency (hf-) LFP-activity (>500 Hz) is thought to be a correlate of multi-unit spiking activity. Here, we explore hf-recordings from electrodes implanted for deep brain stimulation for the presence of local interactions of multi-unit activity. Methods LFPs were recorded postoperatively after implantation of deep brain stimulation electrodes (each featuring 4 linearly arranged contacts) in 2 patients (#1: globus pallidus internus for multisegmental dystonia; #2: subthalamic nucleus for Parkinson’s disease) using a dedicated low-noise signal amplifier at a sampling rate of 10 kHz. Imaginary part of coherency was calculated between electrodes as a measure of true brain interactions without interference from volume conduction effects. To rule out competing technical and biological mechanisms, the analysis was repeated on recordings from a dummy head and, resp., on surface-EMG recordings. Results The power spectral density of the recordings significantly deviated from a 1/f-characteristic exhibiting a plateau at 150–2.000 Hz. Moreover, at frequencies >500 Hz, imaginary part of coherency indicated the presence of ‘true’ interactions between neighboring pairs of bipolar chain derivations. These signal characteristics were neither present in the dummy-head recordings nor in the surface-EMG recordings. Discussion and significance LFP recordings from two different subcortical sites and in two different diseases indicated the detectability of locally interacting multi-unit activity using macroelectrodes. Major competing mechanisms could be ruled out in control measurements. Further recordings will address the general consistency of these findings and explore potential correlations with clinical data. Acknowledgement This work was supported by KFO 247 (DFG grant Ni 1308/1-2 ).

Habituation of phase-locked local field potentials and gamma-band oscillations recorded from the human insula

Salient nociceptive and non-nociceptive stimuli elicit low-frequency local field potentials (LFPs) in the human insula. Nociceptive stimuli also elicit insular gamma-band oscillations (GBOs), possibly preferential for thermonociception, which have been suggested to reflect the intensity of perceived pain. To shed light on the functional significance of these two responses, we investigated whether they would be modulated by stimulation intensity and temporal expectation – two factors contributing to stimulus saliency. Insular activity was recorded from 8 depth electrodes (41 contacts) implanted in the left insula of 6 patients investigated for epilepsy. Thermonociceptive, vibrotactile, and auditory stimuli were delivered using two intensities. To investigate the effects of temporal expectation, the stimuli were delivered in trains of three identical stimuli (S1-S2-S3) separated by a constant 1-s interval. Stimulation intensity affected intensity of perception, the magnitude of low-frequency LFPs, and the magnitude of nociceptive GBOs. Stimulus repetition did not affect perception. In contrast, both low-frequency LFPs and nociceptive GBOs showed a marked habituation of the responses to S2 and S3 as compared to S1 and, hence, a dissociation with intensity of perception. Most importantly, although insular nociceptive GBOs appear to be preferential for thermonociception, they cannot be considered as a correlate of perceived pain.

Multimodal Encoding of Novelty, Reward, and Learning in the Primate Nucleus Basalis of Meynert.

Associative learning is crucial for daily function, involving a complex network of brain regions. One region, the nucleus basalis of Meynert (NBM), is a highly interconnected, largely cholinergic structure implicated in multiple aspects of learning. We show that single neurons in the NBM of nonhuman primates (NHPs; n = 2 males; Macaca mulatta) encode learning a new association through spike rate modulation. However, the power of low-frequency local field potential (LFP) oscillations decreases in response to novel, not-yet-learned stimuli but then increase as learning progresses. Both NBM and the dorsolateral prefrontal cortex encode confidence in novel associations by increasing low- and high-frequency LFP power in anticipation of expected rewards. Finally, NBM high-frequency power dynamics are anticorrelated with spike rate modulations. Therefore, novelty, learning, and reward anticipation are separately encoded through differentiable NBM signals. By signaling both the need to learn and confidence in newly acquired associations, NBM may play a key role in coordinating cortical activity throughout the learning process.SIGNIFICANCE STATEMENT Degradation of cells in a key brain region, the nucleus basalis of Meynert (NBM), correlates with Alzheimer's disease and Parkinson's disease progression. To better understand the role of this brain structure in learning and memory, we examined neural activity in the NBM in behaving nonhuman primates while they performed a learning and memory task. We found that single neurons in NBM encoded both salience and an early learning, or cognitive state, whereas populations of neurons in the NBM and prefrontal cortex encode learned state and reward anticipation. The NBM may thus encode multiple stages of learning. These multimodal signals might be leveraged in future studies to develop neural stimulation to facilitate different stages of learning and memory.

Subthalamic Neural Activity Patterns Anticipate Economic Risk Decisions in Gambling.

Economic decision-making is disrupted in individuals with gambling disorder, an addictive behavior observed in Parkinson’s disease (PD) patients receiving dopaminergic therapy. The subthalamic nucleus (STN) is involved in the inhibition of impulsive behaviors; however, its role in impulse control disorders and addiction is still unclear. Here, we recorded STN local field potentials (LFPs) in PD patients with and without gambling disorder during an economic decision-making task. Reaction times analysis showed that for all patients, the decision whether to risk preceded task onset. We compared then for both groups the STN LFP preceding high- and low-risk economic decisions. We found that risk avoidance in gamblers correlated with larger STN LFP low-frequency (<12-Hz) fluctuations preceding task onset. In particular, the amplitude of low-frequency LFP fluctuations carried significant information about future decisions. Decisions of patients not affected by gambling disorder were instead not correlated with pretask STN LFP. Our results suggest that STN activity preceding task onset affects risk decisions by preemptively inhibiting attraction to high but unlikely rewards in favor of a long-term payoff.

Delta Rhythm Orchestrates the Neural Activity Underlying the Resting State BOLD Signal via Phase-amplitude Coupling.

Spontaneous ongoing neuronal activity is a prominent feature of the mammalian brain. Temporal and spatial patterns of such ongoing activity have been exploited to examine large-scale brain network organization and function. However, the neurophysiological basis of this spontaneous brain activity as detected by resting-state functional Magnetic Resonance Imaging (fMRI) remains poorly understood. To this end, multi-site local field potentials (LFP) and blood oxygenation level-dependent (BOLD) fMRI were simultaneously recorded in the rat striatum along with local pharmacological manipulation of striatal activity. Results demonstrate that delta (δ) band LFP power negatively, while beta (β) and gamma (γ) band LFPs positively correlated with BOLD fluctuation. Furthermore, there was strong cross-frequency phase-amplitude coupling (PAC), with the phase of δ LFPs significantly modulating the amplitude of the high frequency signal. Enhancing dopaminergic neuronal activity significantly reduced ventral striatal functional connectivity, δ LFP-BOLD correlation, and the PAC effect. These data suggest that different frequency bands of the LFP contribute distinctively to BOLD spontaneous fluctuation and that PAC is the organizing mechanism through which low frequency LFPs orchestrate neural activity that underlies resting state functional connectivity.

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

Brain state has profound effects on neural processing and stimulus encoding in sensory cortices. While the synchronized state is dominated by low-frequency local field potential (LFP) activity, low-frequency LFP power is suppressed in the desynchronized state, where a concurrent enhancement in gamma power is observed. Recently, it has been shown that cortical desynchronization co-occurs with enhanced between-trial reliability of spiking activity in sensory neurons, but it is currently unclear whether this effect is also evident in LFP signals. Here, we address this question by recording both spike trains and LFP in primary visual cortex during natural movie stimulation, and using isoflurane anesthesia and basal forebrain (BF) electrical activation as proxies for synchronized and desynchronized brain states. We show that indeed, low-frequency LFP modulations ("LFP events") also occur more reliably following BF activation. Interestingly, while being more reliable, these LFP events are smaller in amplitude compared to those generated in the synchronized brain state. We further demonstrate that differences in reliability of spiking activity between cortical states can be linked to amplitude and probability of LFP events. The correlated temporal dynamics between low-frequency LFP and spiking response reliability in visual cortex suggests that these effects may both be the result of the same neural circuit activation triggered by BF stimulation, which facilitates switching between processing of incoming sensory information in the desynchronized and reverberation of internal signals in the synchronized state.

Correlated inter-regional variations in low frequency local field potentials and resting state BOLD signals within S1 cortex of monkeys.

The hypothesis that specific frequency components of the spontaneous local field potentials (LFPs) underlie low frequency fluctuations of resting state fMRI (rsfMRI) signals was tested. The previous analyses of rsfMRI signals revealed differential inter-regional correlations among areas 3a, 3b, and 1 of primary somatosensory cortex (S1) in anesthetized monkeys (Wang et al. [2013]: Neuron 78:1116-1126). Here LFP band(s) which correlated between S1 regions, and how these inter-regional correlation differences covaried with rsfMRI signals were examined. LFP signals were filtered into seven bands (delta, theta, alpha, beta, gamma low, gamma high, and gamma very high), and then a Hilbert transformation was applied to obtain measures of instantaneous amplitudes and temporal lags between regions of interest (ROI) digit-digit pairs (areas 3b-area 1, area 3a-area 1, area 3a-area 3b) and digit-face pairs (area 3b-face, area 1-face, and area 3a-face). It was found that variations in the inter-regional correlation strengths between digit-digit and digit-face pairs in the delta (1-4 Hz), alpha (9-14 Hz), beta (15-30 Hz), and gamma (31-50 Hz) bands parallel those of rsfMRI signals to varying degrees. Temporal lags between digit-digit area pairs varied across LFP bands, with area 3a mostly leading areas 1/2 and 3b. In summary, the data demonstrates that the low and middle frequency range (1-50 Hz) of spontaneous LFP signals similarly covary with the low frequency fluctuations of rsfMRI signals within local circuits of S1, supporting a neuronal electrophysiological basis of rsfMRI signals. Inter-areal LFP temporal lag differences provided novel insights into the directionality of information flow among S1 areas at rest. Hum Brain Mapp 37:2755-2766, 2016. © 2016 Wiley Periodicals, Inc.

Low-Dimensional Models of "Neuro-Glio-Vascular Unit" for Describing Neural Dynamics under Normal and Energy-Starved Conditions.

The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low-­dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an “energy” variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising KATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛp, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛp could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed “neuron-energy” unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as non-invasive brain stimulation for stroke patients.

Encoding of natural sounds by variance of the cortical local field potential.

Neural encoding of sensory stimuli is typically studied by averaging neural signals across repetitions of the same stimulus. However, recent work has suggested that the variance of neural activity across repeated trials can also depend on sensory inputs. Here we characterize how intertrial variance of the local field potential (LFP) in primary auditory cortex of awake ferrets is affected by continuous natural sound stimuli. We find that natural sounds often suppress the intertrial variance of low-frequency LFP (<16 Hz). However, the amount of the variance reduction is not significantly correlated with the amplitude of the mean response at the same recording site. Moreover, the variance changes occur with longer latency than the mean response. Although the dynamics of the mean response and intertrial variance differ, spectro-temporal receptive field analysis reveals that changes in LFP variance have frequency tuning similar to multiunit activity at the same recording site, suggesting a local origin for changes in LFP variance. In summary, the spectral tuning of LFP intertrial variance and the absence of a correlation with the amplitude of the mean evoked LFP suggest substantial heterogeneity in the interaction between spontaneous and stimulus-driven activity across local neural populations in auditory cortex.