LFP publications

Previous studies have reported that rearing infant rat pups in continuous moderate-level noise delayed the formation of topographic representational order and the refinement of response selectivity in the primary auditory (A1) cortex. The present study further verified that exposure to long-term moderate-intensity white noise (70 dB sound pressure level) from postnatal day (P) 12 to P30 elevated the hearing thresholds of infant rats. Compared with age-matched control rats, noise exposure (NE) rats had elevated hearing thresholds ranging from low to high frequencies, accompanied by decreased amplitudes and increased latencies of the two initial auditory brainstem response waves. The power of raw local field potential oscillations and high-frequency β oscillation in the A1 cortex of NE rats were larger, whereas the power of high-frequency γ oscillation was smaller than that of control rats. In addition, the expression levels of five glutamate receptor (GluR) subunits in the A1 cortex of NE rats were decreased with laminar specificity. These results suggest that the altered neural excitability and decreased GluR expression may underlie the delay of functional maturation in the A1 cortex, and may have implications for the treatment of hearing impairment induced by environmental noise.

In the rodent auditory system, the primary cortex is subdivided into two regions, both receiving direct inputs from the auditory thalamus: the primary auditory cortex (A1) and the anterior auditory field (AAF). Although neurons in the two regions display different response properties, like response latency, firing threshold or tuning bandwidth, it is still not clear whether they process sound in a distinct way. Using in vivo electrophysiological recordings in the mouse auditory cortex, we found that AAF neurons have significantly stronger responses to tone offset than A1 neurons. AAF neurons also display faster and more transient responses than A1 neurons. Additionally, offset responses in AAF – unlike in A1, increase with sound duration. Local field potential (LFP) and laminar analyses suggest that the differences in sound responses between these two primary cortices are both of subcortical and intracortical origin. These results emphasize the potentially critical role of AAF for temporal processing. Our study reveals a distinct role of two primary auditory cortices in tone processing and highlights the complexity of sound encoding at the cortical level.

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25- to 50-Hz range (“slow γ”) are proposed to support memory retrieval independent of other frequencies. However, θ harmonics extend up to 48 Hz, necessitating a study to determine whether these oscillations are fundamentally the same. We compared the spectral analysis methods of wavelet, ensemble empirical-mode decomposition (EEMD), and Fourier transform. EEMD, as previously applied, failed to account for the θ harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order θ harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25- to 50-Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted slow γ in a synthetic dataset that only contained θ and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120- to 250-Hz events. When Fourier is applied to high power, 25- to 50-Hz events, only θ harmonics are resolved. This analysis challenges the identification of the slow γ rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow γ is present in the rat hippocampus, the analysis presented here shows that unless care is exerted in the application of EEMD and wavelet techniques, the results may be misleading, in this case misrepresenting θ harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent γ bands.

A key challenge in neuroscience is understanding how sensory stimuli give rise to perception, especially when the process is supported by neural activity from an extended network of brain areas. Perception is inherently subjective, so interrogating its neural signatures requires, ideally, a combination of three factors: (1) behavioral tasks that separate stimulus-driven activity from perception per se; (2) human subjects who self-report their percepts while performing those tasks; and (3) concurrent neural recordings acquired at high spatial and temporal resolution. In this study, we analyzed human electrocorticographic recordings obtained during an auditory task which supported mutually exclusive perceptual interpretations. Eight neurosurgical patients (5 male; 3 female) listened to sequences of repeated triplets where tones were separated in frequency by several semitones. Subjects reported spontaneous alternations between two auditory perceptual states, 1-stream and 2-stream, by pressing a button. We compared averaged auditory evoked potentials (AEPs) associated with 1-stream and 2-stream percepts and identified significant differences between them in primary and nonprimary auditory cortex, surrounding auditory-related temporoparietal cortex, and frontal areas. We developed classifiers to identify spatial maps of percept-related differences in the AEP, corroborating findings from statistical analysis. We used one-dimensional embedding spaces to perform the group-level analysis. Our data illustrate exemplar high temporal resolution AEP waveforms in auditory core region; explain inconsistencies in perceptual effects within auditory cortex, reported across noninvasive studies of streaming of triplets; show percept-related changes in frontoparietal areas previously highlighted by studies that focused on perceptual transitions; and demonstrate that auditory cortex encodes maintenance of percepts and switches between them.SIGNIFICANCE STATEMENT The human brain has the remarkable ability to discern complex and ambiguous stimuli from the external world by parsing mixed inputs into interpretable segments. However, one's perception can deviate from objective reality. But how do perceptual discrepancies occur? What are their anatomical substrates? To address these questions, we performed intracranial recordings in neurosurgical patients as they reported their perception of sounds associated with two mutually exclusive interpretations. We identified signatures of subjective percepts as distinct from sound-driven brain activity in core and non-core auditory cortex and frontoparietal cortex. These findings were compared with previous studies of auditory bistable perception and suggested that perceptual transitions and maintenance of perceptual states were supported by common neural substrates.

The extent to which the primary auditory cortex (A1) participates in instructing animal behavior remains debated. Although multiple studies have shown A1 activity to correlate with animals' perceptual judgments (Jaramillo and Zador, 2011; Bizley et al., 2013; Rodgers and DeWeese, 2014), others have found no relationship between A1 responses and reported auditory percepts (Lemus et al., 2009; Dong et al., 2011). To address this ambiguity, we performed chronic recordings of evoked local field potentials (eLFPs) in A1 of head-fixed female rats performing a two-alternative forced-choice auditory discrimination task. Rats were presented with two interleaved sequences of pure tones from opposite sides and had to indicate the side from which the higher-frequency target stimulus was played. Animal performance closely correlated (rrm = 0.68) with the difference between the target and distractor eLFP responses: the more the target response exceeded the distractor response, the better the animals were at identifying the side of the target frequency. Reducing the evoked response of either frequency through stimulus-specific adaptation affected performance in the expected way: target localization accuracy was degraded when the target frequency was adapted and improved when the distractor frequency was adapted. Target frequency eLFPs were stronger on hit trials than on error trials. Our results suggest that the degree to which one stimulus stands out over others within A1 activity may determine its perceptual saliency for the animals and accordingly bias their behavioral choices.SIGNIFICANCE STATEMENT The brain must continuously calibrate the saliency of sensory percepts against their relevance to the current behavioral goal. The inability to ignore irrelevant distractors characterizes a spectrum of human attentional disorders. Meanwhile, the connection between the neural underpinnings of stimulus saliency and sensory decisions remains elusive. Here, we record local field potentials in the primary auditory cortex of rats engaged in auditory discrimination to investigate how the cortical representation of target and distractor stimuli impacts behavior. We find that the amplitude difference between target- and distractor-evoked activity predicts discrimination performance (rrm = 0.68). Specific adaptation of target or distractor shifts performance either below or above chance, respectively. It appears that recent auditory history profoundly influences stimulus saliency, biasing animals toward diametrically-opposed decisions.

The acoustic dimensions that distinguish speech sounds (like the vowel differences in “boot” and “boat”) also differentiate speakers’ voices. Therefore, listeners must normalize across speakers without losing linguistic information. Past behavioral work suggests an important role for auditory contrast enhancement in normalization: preceding context affects listeners’ perception of subsequent speech sounds. Here, using intracranial electrocorticography in humans, we investigate whether and how such context effects arise in auditory cortex. Participants identified speech sounds that were preceded by phrases from two different speakers whose voices differed along the same acoustic dimension as target words (the lowest resonance of the vocal tract). In every participant, target vowels evoke a speaker-dependent neural response that is consistent with the listener’s perception, and which follows from a contrast enhancement model. Auditory cortex processing thus displays a critical feature of normalization, allowing listeners to extract meaningful content from the voices of diverse speakers.

Maintaining average activity within a set-point range constitutes a fundamental property of central neural circuits. However, whether and how activity set points are regulated remains unknown. Integrating genome-scale metabolic modeling and experimental study of neuronal homeostasis, we identified mitochondrial dihydroorotate dehydrogenase (DHODH) as a regulator of activity set points in hippocampal networks. The DHODH inhibitor teriflunomide stably suppressed mean firing rates via synaptic and intrinsic excitability mechanisms by modulating mitochondrial Ca2+ buffering and spare respiratory capacity. Bi-directional activity perturbations under DHODH blockade triggered firing rate compensation, while stabilizing firing to the lower level, indicating a change in the firing rate set point. In vivo, teriflunomide decreased CA3-CA1 synaptic transmission and CA1 mean firing rate and attenuated susceptibility to seizures, even in the intractable Dravet syndrome epilepsy model. Our results uncover mitochondria as a key regulator of activity set points, demonstrate the differential regulation of set points and compensatory mechanisms, and propose a new strategy to treat epilepsy.

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed comparison task. Rats compared the speeds of two vibrissal vibrations, stimulus1 and stimulus2, separated by a delay of 2 s. Neuronal firing rates in vS1 and PL encode both stimuli in real time. Across the delay, the stimulus1 representation declines more precipitously in vS1 than in PL. Theta-band local field potential (LFP) coherence between vS1 and PL peaks at trial onset and remains elevated during the interstimulus interval; simultaneously, vS1 spikes become phase locked to PL LFP. Phase locking is stronger on correct (versus error) trials. Tactile working memory in rats appears to be mediated by a posterior (vS1) to anterior (PL) flow of information, with performance facilitated through coherent LFP oscillation.

Background: Repetitive somatosensory electrical stimulation (SES) of forelimb peripheral nerves is a promising therapy; studies have shown that SES can improve motor function in stroke subjects with chronic deficits. However, little is known about how SES can directly modulate neural dynamics. Past studies using SES have primarily used noninvasive methods in human subjects. Here we used electrophysiological recordings from the rodent primary motor cortex (M1) to assess how SES affects neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. Methods: We performed acute extracellular recordings in 7 intact adult Long Evans rats under ketamine-xylazine anesthesia while they received transcutaneous SES. We recorded single unit spiking and local field potentials (LFP) in the M1 contralateral to the stimulated arm. We then compared neural firing rate, spike-field coherence (SFC), and power spectral density (PSD) before and after stimulation. Results: Following SES, the firing rate of a majority of neurons changed significantly from their respective baseline values. There was, however, a diversity of responses; some neurons increased while others decreased their firing rates. Interestingly, SFC, a measure of how a neuron's firing is coupled to mesoscale oscillatory dynamics, increased specifically in the δ-band, also known as the low frequency band (0.3- 4 Hz). This increase appeared to be driven by a change in the phase-locking of broad-spiking, putative pyramidal neurons. These changes in the low frequency range occurred without a significant change in the overall PSD. Conclusions: Repetitive SES significantly and persistently altered the local cortical dynamics of M1 neurons, changing both firing rates as well as the SFC magnitude in the δ-band. Thus, SES altered the neural firing and coupling to ongoing mesoscale dynamics. Our study provides evidence that SES can directly modulate cortical dynamics.

Throughout the past decade, silicon-based neural probes have become a driving force in neural engineering. Such probes comprise sophisticated, integrated CMOS electronics which provide a large number of recording sites along slender probe shanks. Using such neural probes in a chronic setting often requires them to be mechanically anchored with respect to the skull. However, any relative motion between brain and implant causes recording instabilities and tissue responses such as glial scarring, thereby shielding recordable neurons from the recording sites integrated on the probe and thus decreasing the signal quality. In the current work, we present a comparison of results obtained using mechanically fixed and floating silicon neural probes chronically implanted into the cortex of a non-human primate. We demonstrate that the neural signal quality estimated by the quality of the spiking and local field potential (LFP) recordings over time is initially superior for the floating probe compared to the fixed device. Nonetheless, the skull-fixed probe also allowed long-term recording of multi-unit activity (MUA) and low frequency signals over several months, especially once pulsations of the brain were properly controlled.

Partial hearing loss can cause neurons in the auditory and audiovisual cortices to increase their responsiveness to visual stimuli; however, behavioral studies in hearing-impaired humans and rats have found that the perceptual ability to accurately judge the relative timing of auditory and visual stimuli is largely unaffected. To investigate the neurophysiological basis of how audiovisual temporal acuity may be preserved in the presence of hearing loss-induced crossmodal plasticity, we exposed adult rats to loud noise and two weeks later performed in vivo electrophysiological recordings in two neighboring regions within the lateral extrastriate visual (V2L) cortex—a multisensory zone known to be responsive to audiovisual stimuli (V2L-Mz) and a predominantly auditory zone (V2L-Az). To examine the cortical layer-specific effects at the level of postsynaptic potentials, a current source density (CSD) analysis was applied to the local field potential (LFP) data recorded in response to auditory and visual stimuli presented at various stimulus onset asynchronies (SOAs). As predicted, differential effects were observed in the neighboring cortical regions’ postnoise exposure. Most notably, an analysis of the strength of multisensory response interactions revealed that V2L-Mz lost its sensitivity to the relative timing of the auditory and visual stimuli, due to an increased responsiveness to visual stimulation that produced a prominent audiovisual response irrespective of the SOA. In contrast, not only did the V2L-Az in noise-exposed rats become more responsive to visual stimuli but neurons in this region also inherited the capacity to process audiovisual stimuli with the temporal precision and specificity that was previously restricted to the V2L-Mz. Thus, the present study provides the first demonstration that audiovisual temporal processing can be preserved following moderate hearing loss via compensatory plasticity in the higher-order sensory cortices that is ultimately characterized by a functional transition in the cortical region capable of temporal sensitivity.

To effectively interact with their environment, humans must often select actions from multiple incompatible options. Existing theories propose that during motoric response-conflict, inappropriate motor activity is actively (and perhaps non-selectively) suppressed by an inhibitory fronto-basal ganglia mechanism. We here tested this theory across three experiments. First, using scalp-EEG, we found that both outright action-stopping and response-conflict during action-selection invoke low-frequency activity of a common fronto-central source, whose activity relates to trial-by-trial behavioral indices of inhibition in both tasks. Second, using simultaneous intracranial recordings from the basal ganglia and motor cortex, we found that response-conflict increases the influence of the subthalamic nucleus on M1-representations of incorrect response-tendencies. Finally, using transcranial magnetic stimulation, we found that during the same time period when conflict-related STN-to-M1 communication is increased, cortico-spinal excitability is broadly suppressed. Together, these findings demonstrate that fronto-basal ganglia networks buttress action-selection under response-conflict by rapidly and non-selectively net-inhibiting inappropriate motor tendencies.

Reward modulation (M1) could be exploited in developing an autonomously updating brain-computer interface (BCI) based on a reinforcement learning (RL) architecture. For an autonomously updating RL-based BCI system, we would need a reward prediction error, or a state-value representation from the user’s neural activity, which the RL-BCI agent could use to update its BCI decoder. In order to understand the multifaceted effects of reward on M1 activity, we investigated how neural spiking, oscillatory activities and their functional interactions are modulated by conditioned stimuli related reward expectation. To do so, local field potentials (LFPs) and single/multi-unit activities were recorded simultaneously and bilaterally from M1 cortices while four non-human primates (NHPs) performed cued center-out reaching or grip force tasks either manually using their right arm/hand or observed passively. We found that reward expectation influenced the strength of α (8–14 Hz) power, α-γ comodulation, α spike-field coherence (SFC), and firing rates (FRs) in general in M1. Furthermore, we found that an increase in α-band power was correlated with a decrease in neural spiking activity, that FRs were highest at the trough of the α-band cycle and lowest at the peak of its cycle. These findings imply that α oscillations modulated by reward expectation have an influence on spike FR and spike timing during both reaching and grasping tasks in M1. These LFP, spike, and spike-field interactions could be used to follow the M1 neural state in order to enhance BCI decoding (An et al., 2018; Zhao et al., 2018).

The central gain model of hyperacusis proposes that loss of auditory input can result in maladaptive neuronal gain increases in the central auditory system, leading to the over-amplification of sound-evoked activity and excessive loudness perception. Despite the attractiveness of this model, and supporting evidence for it, a critical test of the central gain theory requires that changes in sound-evoked activity be explicitly linked to perceptual alterations of loudness. Here we combined an operant conditioning task that uses a subject's reaction time to auditory stimuli to produce reliable measures of loudness growth with chronic electrophysiological recordings from the auditory cortex and inferior colliculus of awake, behaviorally-phenotyped animals. In this manner, we could directly correlate daily assessments of loudness perception with neurophysiological measures of sound encoding within the same animal. We validated this novel psychophysical-electrophysiological paradigm with a salicylate-induced model of hearing loss and hyperacusis, as high doses of sodium salicylate reliably induce temporary hearing loss, neural hyperactivity, and auditory perceptual disruptions like tinnitus and hyperacusis. Salicylate induced parallel changes to loudness growth and evoked response-intensity functions consistent with temporary hearing loss and hyperacusis. Most importantly, we found that salicylate-mediated changes in loudness growth and sound-evoked activity were correlated within individual animals. These results provide strong support for the central gain model of hyperacusis and demonstrate the utility of using an experimental design that allows for within-subject comparison of behavioral and electrophysiological measures, thereby making inter-subject variability a strength rather than a limitation.

Prominent 7-12 Hz oscillations in frontal cortical networks in rats have been reported. However, the mechanism of generation and the physiological function of this brain rhythm have not yet been clarified. Multichannel extracellular field potentials of the ACC were recorded and analyzed using the current source density method in halothane-anesthetized rats. Spontaneous high-current spikes (HCSs) were localized in the deep part of layer II/III and upper part of layer V of the ACC. The frequency of HCSs in the ACC was 7-12 Hz, with an amplitude of 6.5 ± 0.76 mV/mm2 and duration of 55.24 ± 2.43 ms. The power density significantly decreased (84.56 ± 6.93%, p < 0.05, t test) after pinching the hindpaw and significantly increased (149.28 ± 15.96%) after treatment with morphine. The suppressive effect of pinching was reversed by naloxone (0.7 mg/kg, i.p.). HCSs coincided with initiation of the depolarization of cingulate neurons and remained in a depolarized upstate. The occurrence of cingulate HCSs was persistently preceded by a hyperpolarization phase and a burst of multiunit spike activity in the medial dorsal thalamic nucleus. Spontaneous field-potential oscillations changed from 10 Hz to a lower band (i.e., ∼7.5 Hz) when a central poststroke pain condition was induced. The central poststroke pain group had a higher average coherence coefficient compared with the control group. Our results indicate that spontaneous cingulate cortical HCSs could be initiated by thalamocortical synaptic inputs from the medial dorsal thalamic nucleus and maintained by intracortical neuronal upstate mechanisms in physiological and pathological pain states.SIGNIFICANCE STATEMENT This study elucidated the mechanism of generation and physiological function of prominent 7-12 Hz frequency oscillations in frontal cortical networks in rats. Spontaneous cingulate cortical high-current spikes in anesthetized rats could be initiated by thalamocortical synaptic inputs from the medial dorsal thalamic nucleus and maintained by intracortical neuronal upstate mechanisms. Suppression of the anterior cingulate cortex-filtered EEG during noxious stimulation may have resulted from the desynchronization of high-current spikes in the ACC. The enhancement of fast Fourier transform power after a systemic morphine injection suggested that the opioid system may play an important role in synchronizing cingulate cortical neuronal networks. Spontaneous cingulate high-current spikes may also play an important role in thalamocortical dysrhythmia in central poststroke pain.

Technology that translates neural activity into speech would be transformative for people who are unable to communicate as a result of neurological impairments. Decoding speech from neural activity is challenging because speaking requires very precise and rapid multi-dimensional control of vocal tract articulators. Here we designed a neural decoder that explicitly leverages kinematic and sound representations encoded in human cortical activity to synthesize audible speech. Recurrent neural networks first decoded directly recorded cortical activity into representations of articulatory movement, and then transformed these representations into speech acoustics. In closed vocabulary tests, listeners could readily identify and transcribe speech synthesized from cortical activity. Intermediate articulatory dynamics enhanced performance even with limited data. Decoded articulatory representations were highly conserved across speakers, enabling a component of the decoder to be transferrable across participants. Furthermore, the decoder could synthesize speech when a participant silently mimed sentences. These findings advance the clinical viability of using speech neuroprosthetic technology to restore spoken communication.

Synchronized states are marked by large-amplitude low-frequency oscillations in the cortex. These states can be seen during quiet waking or slow-wave sleep. Within synchronized states, previous studies have noted a plethora of different types of activity, including delta oscillations (0.5-4 Hz) and slow oscillations (<1 Hz) in the neocortex and large- and small- irregular activity in the hippocampus. However, it is not still fully characterized how neural populations contribute to the synchronized state. Here we apply independent component analysis to parse which populations are involved in different kinds of neocortical activity, and find two populations that alternate throughout synchronized states. One population broadly affects neocortical deep layers, and is associated with larger amplitude slower neocortical oscillations. The other population exhibits theta-frequency oscillations that are not easily observed in raw field potential recordings. These theta oscillations apparently come from below the neocortex, suggesting hippocampal origin, and are associated with smaller amplitude faster neocortical oscillations. Relative involvement of these two alternating populations may indicate different modes of operation within synchronized states.

The accuracy of the neural code depends on the relative embedding of signal and noise in the activity of neural populations. Despite a wealth of theoretical work on population codes, there are few empirical characterizations of the high-dimensional signal and noise subspaces. We studied the geometry of population codes in the rat auditory cortex across brain states along the activation-inactivation continuum, using sounds varying in difference and mean level across the ears. As the cortex becomes more activated, single-hemisphere populations go from preferring contralateral loud sounds to a symmetric preference across lateralizations and intensities, gain-modulation effectively disappears, and the signal and noise subspaces become approximately orthogonal to each other and to the direction corresponding to global activity modulations. Level-invariant decoding of sound lateralization also becomes possible in the active state. Our results provide an empirical foundation for the geometry and state-dependence of cortical population codes.

What determines how we move in the world? Motor neuroscience often focusses either on intrinsic rhythmical properties of motor circuits or extrinsic sensorimotor feedback loops. Here we show that the interplay of both intrinsic and extrinsic dynamics is required to explain the intermittency observed in continuous tracking movements. Using spatiotemporal perturbations in humans, we demonstrate that apparently discrete submovements made 2–3 times per second reflect constructive interference between motor errors and continuous feedback corrections that are filtered by intrinsic circuitry in the motor system. Local field potentials in monkey motor cortex revealed characteristic signatures of a Kalman filter, giving rise to both low-frequency cortical cycles during movement, and delta oscillations during sleep. We interpret these results within the framework of optimal feedback control, and suggest that the intrinsic rhythmicity of motor cortical networks reflects an internal model of external dynamics, which is used for state estimation during feedback-guided movement. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We engineered ‘See-Shells’—digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>300 days) optical access to 45 mm 2 of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. See-Shells allow calcium imaging from multiple, non-contiguous regions across the cortex. Perforated See-Shells enable introducing penetrating neural probes to perturb or record neural activity simultaneously with whole cortex imaging. See-Shells are constructed using common desktop fabrication tools, providing a powerful tool for investigating brain structure and function.