LFP publications

Brain function relies on coordinated activity across spatial and temporal scales. Single neurons integrate local and long-range connectivity and reflect activity across brain-wide networks. Understanding integrated brain function requires tools capable of recording from anatomically connected populations in distributed brain areas to bridge local and global dynamics. Here, we present high-density, micro-electrocorticography arrays that facilitate multi-scale studies of brain activity. The hybrid arrays integrate the desirable features of silicone elastomers and polyimide films: silicone provides optical transparency and permits repeated penetration with intracortical arrays, while polyimide enables fine photolithographic feature definition. This combination facilitates high-throughput functional mapping to identify targets and insertion of intracortical arrays for dense local sampling. We demonstrate functional mapping in rats, cats, and marmosets, showing how functional maps guide multi-area laminar recordings. Finally, we demonstrate local and feedforward optogenetic stimulation to investigate cortico-cortical interactions. These capabilities establish the hybrid μECoG as a compelling tool for systems neuroscience.

Pain management strategies have progressed beyond traditional pharmacologic and physical interventions, integrating advanced neuromodulation techniques such as deep brain stimulation, peripheral nerve stimulation, and high‐frequency spinal cord stimulation (hSCS). Despite its clinical efficacy, the supraspinal mechanisms underlying hSCS remain poorly understood. Prior work in sheep demonstrated that hSCS modulates gamma (γ) band (70–150 Hz) activity in the primary somatosensory and association cortices, implicating cortical involvement in pain modulation. Given the interaction between low‐ and high‐oscillations, we hypothesized that hSCS modulates γ activity in a region‐ and time‐dependent manner through specific coupling with theta rhythms (θ, 4–8 Hz). To test this, we quantified θ–γ phase‐amplitude coupling (PAC) during tibial nerve stimulation (TNS) before (TNS 0 ) and after (TNS 1 ) hSCS to assess cortical processing of TNS‐evoked activity, while recording cortical (association and somatosensory cortices) neural activity using 96‐channel subdural electrocorticography (ECoG). We then computed the corresponding modulation index (MI) to quantify PAC strength. While the preferred θ phase of γ activity remained consistent across conditions in both cortical areas, θ‐γ coupling was more robust and stable in the association than the somatosensory cortex. However, MI increased significantly post‐hSCS in both cortices, indicating enhanced θ‐γ coupling during TNS 1 . Temporally, both cortices showed distinct response patterns: the somatosensory cortex exhibited strongest coupling increase early post‐hSCS, followed by a progressive decline, whereas the association cortex showed a more delayed and temporally distributed enhancement. These findings indicate that hSCS modulates cortical cross‐frequency interactions during TNS‐evoked sensory processing, wherein somatosensory and association cortices show distinct temporal coupling dynamics that may contribute to supraspinal mechanisms of pain modulation.

The cortex generates diverse neural dynamics, ranging from broadband fluctuations to narrowband oscillations at specific frequencies. Here, we investigated whether broadband and oscillatory dynamics play different roles in the encoding and transmission of visual information. We used information-theoretical measures to dissociate neural signals sharing common information (i.e., redundancy) from signals encoding complementary information (i.e., synergy). We analyzed electrocorticography (ECoG) and local field potentials (LFP) in the visual cortex of human and non-human primates (macaque) to investigate the extent to which broadband signals (BB) and narrowband gamma (NBG) oscillations conveyed synergistic or redundant information about images. In both species, the information conveyed by BB signals was highly synergistic within and between visual areas. By contrast, the information carried by NBG was primarily redundant within and between the same visual areas. Finally, the information conveyed by BB signals emerged early after stimulus onset, while NBG sustained information at later time points. These results suggest a potential dual role of BB and NBG cortical dynamics in visual processing, with broadband dynamics supporting nonlinear pattern recognition and oscillations facilitating information maintenance across the cortex.

Flexible behavior requires decision-making that integrates both perceptual and mnemonic-related information. While the dorsal premotor cortex (PMd) is known to support perceptual decision-making, its contributions to decisions based on mnemonic information for motor planning remain underexplored. Here, we investigate local field potential (LFP) oscillations in the PMd of monkeys performing a transitive inference task requiring the formation and retrieval of mnemonic representations of an arbitrarily defined rank order among perceptual items. The difficulty of this operation depends on the distance of the items in the mnemonic representation. We tested the hypothesis that this symbolic distance (SD) systematically modulates PMd oscillatory activity in a frequency-specific manner during decisions that combine perceptual identification with mnemonic retrieval. Consistent with this hypothesis, PMd exhibited local and reliable SD-dependent changes across low (Theta, Alpha, Beta) and high-Gamma (h-Gamma) frequency bands, and related to behavioral performance. These findings provide evidence that the PMd integrates perceptual and mnemonic information through coordinated modulations of oscillatory activity, extending its role beyond perceptual mapping to support abstract, memory-guided decisions.

Speech production entails several processing steps that encode linguistic and articulatory structure, but whether these computations correspond to spatiotemporally discrete patterns of neural activity is unclear. To address this issue, we use electrocorticography to directly measure the brains of neurosurgical participants performing an interactive speech paradigm. We observe a broad range of cortical modulation profiles, and subsequent clustering analyses establish that responses comprised distinct classes associated with sensory perception, planning, motor execution, and task-related suppression. These activity classes are also localized to separate neural substrates, indicating their status as specialized networks. We then parse dynamics in the planning and motor networks using unsupervised dimensionality reduction, which reveals subnetworks that are sequentially active throughout preparation and articulation. These results therefore support and extend a localizationist model of speech production where cortical activity "flows" within and across discrete pathways during language use.

The non-rapid-eye movement (NREM) sleep power spectrum is composed of rhythmic and arrhythmic components, respectively associated with brain rhythms and scale-free dynamics. Both components are hypothesized to represent distinct processes underlying sleep-dependent memory consolidation as well as other brain complex processes. Recent advancements in spectral parametrization techniques and the use of multifractal models have enabled new insights into these components and their connection to brain networks. Aging impacts NREM sleep oscillations, but no animal studies considered the impact of age on rhythmic and arrhythmic components. In this study, we assessed the effects of age on the power spectrum and its two components using local field potential recordings in mice. We recorded across the cerebral cortex and within the hippocampus—a central brain hub involved in NREM sleep-dependent cognitive processing. Ten younger (7.6 months) and eleven older (15.7 months) C57BL/6 J male and female mice were continuously recorded over a 24-hour period. We extracted the NREM sleep standard and rhythmic spectra, controlled for scale-free activity, and estimated multifractal arrhythmic properties during NREM sleep using the Wavelet Leader and Bootstrap based MultiFractal analysis toolbox. Older mice showed specific alterations in both components compared to younger animals: reduced rhythmic gamma power in the anterior cortex, greater regional differentiation of scaling exponents, and higher multifractal dispersion of the arrhythmic component in the hippocampus. These findings demonstrate that aging alters rhythmic and arrhythmic properties of NREM sleep in distinct brain regions, suggesting that both contribute to age-related changes in sleep-dependent cognition.

Advancements in the field of implantable neurotechnologies have enabled the integration of hundreds of microelectrodes on ultra-thin and flexible substrates. Besides implantable components, also connectors, headstages and cables have to comply with the high-count demand, resulting in a complex and compact chain with reduced line spacing and smaller safety margins. Here, we show that epicortical recordings acquired from anesthetized rat brains with a state-of-art neural acquisition system are undoubtedly compromised by crosstalk, with signal coherence maps exhibiting a strong dependency to the routing layout. A crosstalk back-correction algorithm is developed, allowing to infer on how signals would look like under a zero-crosstalk scenario. We found that signal coherence between closely routed channels effectively drops after correction, corroborating crosstalk contamination. Our work stresses the importance of validating recorded data against the routing layout as a crucial step of data quality control, helping to come closer to ground truth data.

Flexible behaviour requires decision-making that integrates both perceptual and mnemonic-related information. While the dorsal premotor cortex (PMd) is known to support decision-making based on perceptual computations, its contributions to decisions based on mnemonic information for motor planning are underexplored. Here, investigating local field potential (LFP) oscillations in PMd of monkeys performing a transitive inference task required the formation and retrieval of mnemonic representations of an arbitrarily defined rank order among perceptual items. Our results highlight that a dynamic interplay between lower frequencies (Theta, Alpha, Beta) and high-Gamma oscillatory activity of LFP reflects a mechanism for accessing and manipulating memory-related information underlying decision-making. These findings provide evidence that the PMd plays a role in multiplexing both perceptual and mnemonic information, extending its competence beyond the association of perceptual input with motor decisions.

Animacy perception, the ability to discern living from non-living entities, is crucial for survival and social interaction, as it includes recognizing abstract concepts such as movement, purpose, and intentions. This process involves interpreting cues that may suggest the intentions or actions of others. It engages the temporal cortex (TC), particularly the superior temporal sulcus (STS) and the adjacent region of the inferior temporal cortex (ITC), as well as the dorsomedial prefrontal cortex (dmPFC). However, it remains unclear how animacy is dynamically encoded over time in these brain areas and whether its processing is distributed or localized. In this study, we addressed these questions by employing a symbolic categorization task involving animate and inanimate objects using natural movie stimuli. Simultaneously, electrocorticography were conducted in both the TC and dmPFC. Time-frequency analysis revealed region-specific frequency representations throughout the observation of the movies. Spatial searchlight decoding analysis demonstrated that animacy processing is represented in a distributed manner. Regions encoding animacy information were found to be dispersed across the fundus and lip of the STS, as well as in the ITC. Next, we examined whether these dispersed regions form functional networks. Independent component analysis revealed that the spatial distribution of the component with the most significant animacy information corresponded with the dispersed regions identified by the spatial decoding analysis. Furthermore, Granger causality analysis indicated that these regions exhibit frequency-specific directional functional connectivity, with a general trend of causal influence from the ITC to STS across multiple frequency bands. Notably, a prominent feedback flow in the alpha band from the ITC to both the ventral bank and fundus of the STS was identified. These findings suggest a distributed and functionally interconnected neural substrate for animacy processing across the STS and ITC.

Collective studies have demonstrated that transcranial ultrasound stimulation (TUS) can elicit activation in hemodynamics, implying its potential in treating cerebral or peripheral vessel-related malfunction. The theory for hemodynamic response to TUS is neurovascular coupling (NVC) following the ultrasound-induced cellular (de)polarization. However, it was not conclusive due to the co-existence of the pathway of direct ultrasound-vessel interactions. This study thus aims to investigate and provide direct evidence for NVC pathway in a rodent model of TUS by inhibiting neural activity with sodium valproate (VPA), a GABAergic agent. Twenty Sprague-Dawley rats were randomly assigned to VPA and Saline groups. Microelectrode and optical imaging were utilized to record local field potential and relative cerebral blood flow (rCBF) during baseline, before, and after TUS periods. We found the attenuated neural activity was associated with reduced rCBF responses. These results provided direct evidence for the presence of NVC pathway in hemodynamic modulation by TUS.

Objective . Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable better therapy. However, it is challenging to understand which irregular patterns are most effective for different therapeutic applications given the massively high-dimensional parameter space. Approach . Here we applied many irregular stimulation patterns in a single neural circuit to demonstrate how they can enable new dimensions of neural control compared to conventional stimulation, to guide future exploration of novel stimulation patterns in translational settings. We optogenetically excited the septohippocampal circuit with constant-frequency, nested pulse, sinusoidal, and randomized stimulation waveforms, systematically varying their amplitude and frequency parameters. Main results. We first found equal entrainment of hippocampal oscillations: all waveforms provided similar gamma-power increase, whereas no parameters increased theta-band power above baseline (despite the mechanistic role of the medial septum in driving hippocampal theta oscillations). We then compared each of the effects of each waveform on high-dimensional multi-band activity states using dimensionality reduction methods. Strikingly, we found that conventional stimulation drove predominantly ‘artificial’ (different from behavioral activity) effects, whereas all irregular waveforms induced activity patterns that more closely resembled behavioral activity. Significance . Our findings suggest that irregular stimulation patterns are not useful when the desired mechanism is to suppress or enhance a single frequency band. However, novel stimulation patterns may provide the greatest benefit for neural control applications where entraining a particular mixture of bands (e.g. if they are associated with different symptoms) or behaviorally-relevant activity is desired.

Hand movements are associated with modulations of neuronal activity across several interconnected cortical areas, including the primary motor cortex (M1) and the dorsal and ventral premotor cortices (PMd and PMv). Local field potentials (LFPs) provide a link between neuronal discharges and synaptic inputs. Our current understanding of how LFPs vary in M1, PMd, and PMv during contralateral and ipsilateral movements is incomplete. To help reveal unique features in the pattern of modulations, we simultaneously recorded LFPs in these areas in two macaque monkeys performing reach and grasp movements with either the right or left hand. The greatest effector-dependent differences were seen in M1, at low (≤13 Hz) and γ frequencies. In premotor areas, differences related to hand use were only present in low frequencies. PMv exhibited the greatest increase in low frequencies during instruction cues and the smallest effector-dependent modulation during movement execution. In PMd, δ oscillations were greater during contralateral reach and grasp, and β activity increased during contralateral grasp. In contrast, β oscillations decreased in M1 and PMv. These results suggest that while M1 primarily exhibits effector-specific LFP activity, premotor areas compute more effector-independent aspects of the task requirements, particularly during movement preparation for PMv and production for PMd. The generation of precise hand movements likely relies on the combination of complementary information contained in the unique pattern of neural modulations contained in each cortical area. Accordingly, integrating LFPs from premotor areas and M1 could enhance the performance and robustness of brain-machine interfaces.

Melody is a core component of music in which discrete pitches are serially arranged to convey emotion and meaning. Perception varies along several pitch-based dimensions: (i) the absolute pitch of notes, (ii) the difference in pitch between successive notes, and (iii) the statistical expectation of each note given prior context. How the brain represents these dimensions and whether their encoding is specialized for music remains unknown. We recorded high-density neurophysiological activity directly from the human auditory cortex while participants listened to Western musical phrases. Pitch, pitch-change, and expectation were selectively encoded at different cortical sites, indicating a spatial map for representing distinct melodic dimensions. The same participants listened to spoken English, and we compared responses to music and speech. Cortical sites selective for music encoded expectation, while sites that encoded pitch and pitch-change in music used the same neural code to represent equivalent properties of speech. Findings reveal how the perception of melody recruits both music-specific and general-purpose sound representations.

Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesized that attentional and contextual signals interact in V1 in a manner that primarily benefits the representation of natural stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes, but not by synthetic stimuli lacking higher-order statistical regularities. Population analysis revealed that neuronal responses converged to a low-dimensional subspace only for natural stimuli. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the natural-scene subspace, indicating an alignment between the attentional and natural stimulus variance. These results suggest that attentional and contextual signals interact in V1 in a manner optimized for natural vision.

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

Episodic Ataxia Type 2 (EA2) is a rare neurological disorder caused by a mutation in the CACNA1A gene, encoding the P/Q-type voltage-gated Ca 2+ channel important for neurotransmitter release. Patients with this channelopathy exhibit both cerebellar and cerebral pathologies, suggesting the condition affects both regions. The tottering ( tg / tg) mouse is the most commonly used EA2 model due to an orthologous mutation in the cacna1a gene. The tg / tg mouse has three prominent behavioral phenotypes: a dramatic episodic dystonia; absence seizures with generalized spike and wave discharges (GSWDs); and mild ataxia. We previously observed a novel brain state, transient low-frequency oscillations (LFOs) in the cerebellum and cerebral cortex under anesthesia. In this study, we examine the relationships among the dystonic attack, GSWDs, and LFOs in the cerebral cortex. Previous studies characterized LFOs in the motor cortex of anesthetized tg / tg mice using flavoprotein autofluorescence imaging testing the hypothesis that LFOs provide a mechanism for the paroxysmal dystonia. We sought to obtain a more direct understanding of motor cortex (M1) activity during the dystonic episodes. Using two-photon Ca 2+ imaging to investigate neuronal activity in M1 before, during, and after the dystonic attack, we show that there is not a significant change in the activity of M1 neurons from baseline through the attack. We also conducted simultaneous, multi-electrode recordings to further understand how M1 cellular activity and local field potentials change throughout the progression of the dystonic attack. Neither putative pyramidal nor inhibitory interneuron firing rate changed during the dystonic attack. However, we did observe a near complete loss of GSWDs during the dystonic attack in M1. Finally, using spike triggered averaging to align simultaneously recorded limb kinematics to the peak Ca 2+ response, and vice versa , revealed a reduction in the spike triggered average during the dystonic episodes. Both the loss of GSWDs and the reduction in the coupling suggest that, during the dystonic attack, M1 is effectively decoupled from other structures. Overall, these results indicate that the attack is not initiated or controlled in M1, but elsewhere in the motor circuitry. The findings also highlight that LFOs, GSWDs, and dystonic attacks represent three brain states in tg / tg mice.

Hippocampal theta and gamma rhythms are hypothesized to play a role in the physiology of higher cognition. Prior research has reported that an offset in theta cycles between the entorhinal cortex, CA3, and CA1 regions promotes independence of population activity across the hippocampus. In line with this idea, it has recently been observed that CA1 pyramidal cells can establish and maintain coordinated place cell activity intrinsically, with minimal reliance on afferent input. Counter to these observations is the contemporary hypothesis that CA1 neuron activity is driven by a gamma oscillation arising from the medial entorhinal cortex (MEC) that relays information by providing precisely timed synchrony between MEC and CA1. Reinvestigating this in rats during appetitive track running, we found that theta is the dominant frequency of cross-frequency coupling between the MEC and hippocampus, with hippocampal gamma largely independent of entorhinal gamma.

Circuits of excitatory and inhibitory neurons generate gamma-rhythmic activity (30–80 Hz). Gamma-cycles show spontaneous variability in amplitude and duration. To investigate the mechanisms underlying this variability, we recorded local-field-potentials (LFPs) and spikes from awake macaque V1. We developed a noise-robust method to detect gamma-cycle amplitudes and durations, which showed a weak but positive correlation. This correlation, and the joint amplitude-duration distribution, is well reproduced by a noise-driven damped harmonic oscillator. This model accurately fits LFP power-spectra, is equivalent to a linear, noise-driven E-I circuit, and recapitulates two additional features of gamma: (1) Amplitude-duration correlations decrease with oscillation strength; (2) amplitudes and durations exhibit strong and weak autocorrelations, respectively, depending on oscillation strength. Finally, longer gamma-cycles are associated with stronger spike-synchrony, but lower spike-rates in both (putative) excitatory and inhibitory neurons. In sum, V1 gamma-dynamics are well described by the simplest possible model of gamma: A damped harmonic oscillator driven by noise.

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quantify stimulus predictability for natural images based on self-supervised, generative neural networks. We find that neuronal firing rates were mainly modulated by the contextual predictability of higher-order image features, which correlated strongly with human perceptual similarity judgments. By contrast, V1 gamma (γ)-synchronization increased monotonically with the contextual predictability of low-level image features and emerged exclusively for larger stimuli. Consequently, γ-synchronization was induced by natural images that are highly compressible and low-dimensional. Natural stimuli with low predictability induced prominent, late-onset beta (β)-synchronization, likely reflecting cortical feedback. Our findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

Objective. Extracellular microelectrode techniques are the most widely used approach to interrogate neuronal populations. However, regardless of the manufacturing method used, damage to the vasculature and circuit function during probe insertion remains a concern. This issue can be mitigated by minimising the footprint of the probe used. Reducing the size of probes typically requires either a reduction in the number of channels present in the probe, or a reduction in the individual channel area. Both lead to less effective coupling between the probe and extracellular signals of interest. Approach. Here, we show that continuously drawn SiO 2 -insulated ultra-microelectrode fibres offer an attractive substrate to address these challenges. Individual fibres can be fabricated to >10 m continuous stretches and a selection of diameters below 30 µ m with low resistance (<100 Ω mm −1 ) continuously conductive metal core of <10 µ m and atomically flat smooth shank surfaces. To optimize the properties of the miniaturised electrode-tissue interface, we electrodeposit rough Au structures followed by ∼20 nm IrOx film resulting in the reduction of the interfacial impedance to <500 kΩ at 1 kHz. Main results . We demonstrate that these ultra-low impedance electrodes can record and stimulate both single and multi-unit activity with minimal tissue disturbance and exceptional signal-to-noise ratio in both superficial (∼40 µ m) and deep (∼6 mm) structures of the mouse brain. Further, we show that sensor modifications are stable and probe manufacturing is reproducible. Significance. Minimally perturbing bidirectional neural interfacing can reveal circuit function in the mammalian brain in vivo.