LFP publications

Background: Hippocampal and cortical slice-based models are widely used to study seizures and epilepsy. Seizure detection and quantification are essential components for studying mechanisms of epilepsy and assessing therapeutic interventions. To obtain meaningful signals and maximize experimental throughput, variability should be minimized. Some electrical recording methods require insertion of an electrode into neuronal tissue, change in slice chemical microenvironment, and transients in temperature and pH. These perturbations can cause acute and long-term alterations of the neuronal network which may be reflected in the variability of the recorded signal. New method: In this study we investigated the effect of experimental perturbations in three local field potential (LFP) recording methods including substrate micro-wires (s-MWs), multiple electrode arrays (MEAs), and inserted micro wire electrodes (i-MW). These methods enabled us to isolate effects of different perturbations. We used organotypic hippocampal slices (OHCs) as an in-vitro model of posttraumatic epilepsy. To investigate the effect of the disturbances caused by the recording method on the paroxysmal events, we introduced jitter analysis, which is sensitive to small differences in the seizure spike timing. Results: Medium replacement can introduce long-lasting perturbations. Electrode insertion increased variability on a shorter time scale. OHCs also underwent spontaneous state transitions characterized by transient increases in variability. Comparison with existing methods: This new method of seizure waveform analysis allows for more sensitive assessment of variability of ictal events than simply measuring seizure frequency and duration. Conclusion: We demonstrated that some of the variability in OHC recordings are due to experimental perturbations while some are spontaneous and independent of recording method.

A major frontier in neuroscience is to find neural correlates of perception, learning, decision making, and a variety of other types of behavior. In the last decades, modern devices allow simultaneous recordings of different operant responses and the electrical activity of large neuronal populations. However, the commercially available instruments for studying operant conditioning are expensive, and the design of low-cost chambers has emerged as an appealing alternative to resource-limited laboratories engaged in animal behavior. In this article, we provide a full description of a platform that records the operant behavior and synchronizes it with the electrophysiological activity. The programming of this platform is open source, flexible, and adaptable to a wide range of operant conditioning tasks. We also show results of operant conditioning experiments with freely moving rats with simultaneous electrophysiological recordings.

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1-4 Hz), beta (13-30 Hz), low gamma (30-70 Hz), and high gamma (70-200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Mammalian cortex has both local and cross-area connections, suggesting vital roles for both local and cross-area neural population dynamics in cortically-dependent tasks, like movement learning. Prior studies of movement learning have focused on how single-area population dynamics change during short-term adaptation. It is unclear how cross-area dynamics contribute to movement learning, particularly long-term learning and skill acquisition. Using simultaneous recordings of rodent motor (M1) and premotor (M2) cortex and computational methods, we show how cross-area activity patterns evolve during reach-to-grasp learning in rats. The emergence of reach-related modulation in cross-area activity correlates with skill acquisition, and single-trial modulation in cross-area activity predicts reaction time and reach duration. Local M2 neural activity precedes local M1 activity, supporting top–down hierarchy between the regions. M2 inactivation preferentially affects cross-area dynamics and behavior, with minimal disruption of local M1 dynamics. Together, these results indicate that cross-area population dynamics are necessary for learned motor skills.

Neural implants that deliver multi-site electrical stimulation to the nervous systems are no longer the last resort but routine treatment options for various neurological disorders. Multi-site electrical stimulation is also widely used to study nervous system function and neural circuit transformations. These technologies increasingly demand dynamic electrical stimulation and closed-loop feedback control for real-time assessment of neural function, which is technically challenging since stimulus-evoked artifacts overwhelm the small neural signals of interest. We report a novel and versatile artifact removal method that can be applied in a variety of settings, from single- to multi-site stimulation and recording and for current waveforms of arbitrary shape and size. The method capitalizes on linear electrical coupling between stimulating currents and recording artifacts, which allows us to estimate a multi-channel linear Wiener filter to predict and subsequently remove artifacts via subtraction. We confirm and verify the linearity assumption and demonstrate feasibility in a variety of recording modalities, including in vitro sciatic nerve stimulation, bilateral cochlear implant stimulation, and multi-channel stimulation and recording between the auditory midbrain and cortex. We demonstrate a vast enhancement in the recording quality with a typical artifact reduction of 25-40 dB. The method is efficient and can be scaled to arbitrary number of stimulus and recording sites, making it ideal for applications in large-scale arrays, closed-loop implants, and high-resolution multi-channel brain-machine interfaces.

The mechanical mismatch between implantable interfaces and neural tissues may be reduced by employing soft polymeric materials. Here, we report on a simple strategy to prepare and pattern a soft electrode coating of neural interfacing devices based on a screen-printable conducting hydrogel. The coating formulation, based on polyacrylamide and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate, is suitable to additive manufacturing and exhibits excellent adhesion to polydimethylsiloxane, an elastomer commonly used as a substrate in soft neural interfaces. The soft conductive coating displays a tunable elastic modulus in the 10–100 kPa range and electrochemical properties on a par with stiff conductive inks while supporting good neural cell attachment and proliferation in vitro. Next, the soft printable hydrogel is integrated within a 4 × 4 microelectrode array for electrocorticography with 250 μm-diameter contacts. Acute recording of cortical local field potentials and electrochemical characterization preimplantation and postimplantation highlight the stability of the soft organic conductor. The overall robustness of the soft coating and its patterning method provide a promising route for a range of implantable bioelectronic applications.

Sensory information–driven spikes are synchronized across cortical layers by distinct subtypes of interneurons.

We investigated whether contrast gain control is mediated by shunting inhibition from parvalbumin-positive interneurons in auditory cortex. We performed extracellular and intracellular recordings in mouse auditory cortex while presenting sensory stimuli with varying contrasts and manipulated parvalbumin-positive interneuron activity using optogenetics. We show that while parvalbumin-positive interneuron activity modulates the gain of cortical responses, this activity is not the primary mechanism for contrast gain control in auditory cortex.

Accumulation of amyloid β oligomers (AβO) in Alzheimer’s disease (AD) impairs hippocampal theta and gamma oscillations. These oscillations are important in memory functions and depend on distinct subtypes of hippocampal interneurons such as somatostatin-positive (SST) and parvalbumin-positive (PV) interneurons. Here, we investigated whether AβO causes dysfunctions in SST and PV interneurons by optogenetically manipulating them during theta and gamma oscillations in vivo in AβO-injected SST-Cre or PV-Cre mice. Hippocampal in vivo multi-electrode recordings revealed that optogenetic activation of channelrhodopsin-2 (ChR2)-expressing SST and PV interneurons in AβO-injected mice selectively restored AβO-induced reduction of the peak power of theta and gamma oscillations, respectively, and resynchronized CA1 pyramidal cell (PC) spikes. Moreover, SST and PV interneuron spike phases were resynchronized relative to theta and gamma oscillations, respectively. Whole-cell voltage-clamp recordings in CA1 PC in ex vivo hippocampal slices from AβO-injected mice revealed that optogenetic activation of SST and PV interneurons enhanced spontaneous inhibitory postsynaptic currents (IPSCs) selectively at theta and gamma frequencies, respectively. Furthermore, analyses of the stimulus–response curve, paired-pulse ratio, and short-term plasticity of SST and PV interneuron-evoked IPSCs ex vivo showed that AβO increased the initial GABA release probability to depress SST/PV interneuron’s inhibitory input to CA1 PC selectively at theta and gamma frequencies, respectively. Our results reveal frequency-specific and interneuron subtype-specific presynaptic dysfunctions of SST and PV interneurons’ input to CA1 PC as the synaptic mechanisms underlying AβO-induced impairments of hippocampal network oscillations and identify them as potential therapeutic targets for restoring hippocampal network oscillations in early AD.

Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of beta-waves (15–30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.

Animal behavioral paradigms, such as classical conditioning and operant conditioning, are an important tool to study the neural basis of cognition and behavior. These paradigms involve manipulating sensory stimuli in a way that learning processes are induced under controlled experimental conditions. However, the majority of the commercially available equipment did not offer flexibility to manipulate stimuli. Therefore, the development of most versatile devices would allow the study of more complex cognitive functions. The purpose of this work is to present a low-cost, customized and wireless-operated chamber for animal behavior conditioning, based on the joint operation of two microcontroller modules: Arduino Due and ESP8266-12E. Our results showed that the auditory stimulation system allows setting the carrier frequency in the range of 1 Hz up to more than 100 kHz and the sound stimulus can be modulated in amplitude, also over a wide range of frequencies. Likewise, foot-shock could be precisely manipulated regarding its amplitude (from ∼200 μA to ∼1500 μA) and frequency (up to 20 pulses per second). Finally, adult rats exposed to a protocol of cued fear conditioning in our device showed consistent behavioral response and electrophysiological evoked responses in the midbrain auditory pathway. Furthermore, the device developed in the current study represents an open source alternative to develop customized protocols to study fear memory under conditions of varied sensory stimuli.

The gaseous free radical, nitric oxide ( NO ) acts as a ubiquitous neuromodulator, contributing to synaptic plasticity in a complex way that can involve either long term potentiation or depression. It is produced by neuronal nitric oxide synthase ( nNOS ) which is presynaptically expressed and also located postsynaptically in the membrane and cytoplasm of a subpopulation of each major neuronal type in the ventral cochlear nucleus ( VCN ). We have used iontophoresis in vivo to study the effect of the NOS inhibitor L‐ NAME (L‐ NG ‐Nitroarginine methyl ester) and the NO donors SIN ‐1 (3‐Morpholinosydnonimine hydrochloride) and SNOG (S‐Nitrosoglutathione) on VCN units under urethane anaesthesia. Collectively, both donors produced increases and decreases in driven and spontaneous firing rates of some neurones. Inhibition of endogenous NO production with L‐ NAME evoked a consistent increase in driven firing rates in 18% of units without much effect on spontaneous rate. This reduction of gain produced by endogenous NO was mirrored when studying the effect of L‐ NAME on NMDA ( N ‐Methyl‐D‐aspartic acid)‐evoked excitation, with 30% of units showing enhanced NMDA ‐evoked excitation during L‐ NAME application (reduced NO levels). Approximately 25% of neurones contain nNOS and the NO produced can modulate the firing rate of the main principal cells: medium stellates (choppers), large stellates (onset responses) and bushy cells (primary‐like responses). The main endogenous role of NO seems to be to partly suppress driven firing rates associated with NMDA channel activity but there is scope for it to increase neural gain if there were a pathological increase in its production following hearing loss.

The studies described in this paper for the first time characterize the acute and chronic performance of optically transparent thin-film micro-electrocorticography (μECoG) grids implanted on a thinned skull as both an electrophysiological complement to existing thinned skull preparation for optical recordings/manipulations, and a less invasive alternative to epidural or subdurally placed μECoG arrays. In a longitudinal chronic study, μECoG grids placed on top of a thinned skull maintain impedances comparable to epidurally placed μECoG grids that are stable for periods of at least 1 month. Optogenetic activation of cortex is also reliably demonstrated through the optically transparent μECoG grids acutely placed on the thinned skull. Finally, spatially distinct electrophysiological recordings were evident on μECoG electrodes placed on a thinned skull separated by 500-750 μm, as assessed by stimulation evoked responses using optogenetic activation of cortex as well as invasive and epidermal stimulation of the sciatic and median nerve at chronic time points. Neural signals were collected through a thinned skull in mice and rats, demonstrating potential utility in neuroscience research applications such as in vivo imaging and optogenetics.

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.

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.

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.

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.

In Parkinson's disease, the degeneration of the midbrain dopaminergic neurons is consistently associated with modified metabolic activity in the cerebellum. Here we examined the functional reorganization taking place in the cerebello-cerebral circuit in a murine model of Parkinson's disease with 6-OHDA lesion of midbrain dopaminergic neurons. Cerebellar optogenetic stimulations evoked similar movements in control and lesioned mice, suggesting a normal coupling of cerebellum to the motor effectors after the lesion. In freely moving animals, the firing rate in the primary motor cortex was decreased after the lesion, while cerebellar nuclei neurons showed an increased firing rate. This increase may result from reduced inhibitory Purkinje cells inputs, since a population of slow and irregular Purkinje cells was observed in the cerebellar hemispheres of lesioned animals. Moreover, cerebellar stimulations generated smaller electrocortical responses in the motor cortex of lesioned animals suggesting a weaker cerebello-cerebral coupling. Overall these results indicate the presence of functional changes in the cerebello-cerebral circuit, but their ability to correct cortical dysfunction may be limited due to functional uncoupling between the cerebellum and cerebral cortex.

Mesoscale cortical activity can be defined as the organization of activity of large neuron populations into collective action, forming time-dependent patterns such as traveling waves. Although collective action may play an important role in the cross-scale integration of brain activity and in the emergence of cognitive behavior, a comprehensive formulation of the laws governing its dynamics is still lacking. Because collective action processes are macroscopic with respect to neuronal activity, these processes cannot be described directly with methods and models developed for the microscale (individual neurons).To identify the characteristic features of mesoscopic dynamics, and to lay the foundations for a theoretical description of mesoscopic activity in the hippocampus, we conduct a comprehensive examination of observational data of hippocampal local field potential (LFP) recordings. We use the strong correlation between rat running-speed and the LFP power to parameterize the energy input into the hippocampus, and show that both the power and non-linearity of collective action (e.g., theta and gamma rhythms) increase with increased speed. Our results show that collective-action dynamics are stochastic (the precise state of a single neuron is irrelevant), weakly non-linear, and weakly dissipative. These are the principles of the theory of weak turbulence. Therefore, we propose weak turbulence a theoretical framework for the description of mesoscopic activity in the hippocampus. The weak turbulence framework provides a complete description of the cross-scale energy exchange (the energy cascade). It uncovers the mechanism governing major features of LFP spectra and bispectra, such as the physical meaning of the exponent α of power-law LFP spectra (e.g., f -α, where f is the frequency), the strengthening of theta-gamma coupling with energy input into the hippocampus, as well as specific phase lags associated with their interaction. Remarkably, the weak turbulence framework is consistent with the theory of self organized criticality, which provides a simple explanation for the existence of the power-law background spectrum. Together with self-organized criticality, weak turbulence could provide a unifying approach to modeling the dynamics of mesoscopic activity.

Cerebellar plasticity underlies motor learning. However, how the cerebellum operates to enable learned changes in motor output is largely unknown. We developed a sensory-driven adaptation protocol for reflexive whisker protraction and recorded Purkinje cell activity from crus 1 and 2 of awake mice. Before training, simple spikes of individual Purkinje cells correlated during reflexive protraction with the whisker position without lead or lag. After training, simple spikes and whisker protractions were both enhanced with the spiking activity now leading behavioral responses. Neuronal and behavioral changes did not occur in two cell-specific mouse models with impaired long-term potentiation at their parallel fiber to Purkinje cell synapses. Consistent with cerebellar plasticity rules, increased simple spike activity was prominent in cells with low complex spike response probability. Thus, potentiation at parallel fiber to Purkinje cell synapses may contribute to reflex adaptation and enable expression of cerebellar learning through increases in simple spike activity.