Electrophysiology 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.

Purpose: In anesthesia research and clinical practice, the level of consciousness is often assessed by stimulating subjects and observing their responses. It is possible that such stimulation alters the very state of consciousness being assessed. Whether this phenomenon is accompanied by specific cortical activities remains unknown. Here, we tested the effects of behavioral assessments on neuronal activity in the rat primary auditory cortex (A1) and perirhinal cortex (PrC). Methods: Neuronal spiking activity was recorded from microwire arrays targeting A1 and/or PrC in rats (n = 9), whilst presenting 40 Hz click-trains and gradually increasing infusion rates of propofol, remifentanil, ketamine or dexmedetomidine. We assessed righting reflex, pain withdrawal, whisking reflex, and corneal reflex every 12 minutes (every 360 auditory trials). We searched for significant changes in baseline firing rate and stimulus-evoked activities (where present) due to the behavioral assessments, by comparing 4 min intervals before and after the behavioral tests. Results: Out of 1004 units in 20 sessions, we found significantly elevated activity (p < 0.01) following behavioral tests in 32% and 20% of A1 auditory-responsive units and 8.6% and 5.3% of auditory-unresponsive units under propofol and dexmedetomidine, respectively, but not under remifentanil or ketamine. A higher proportion of units modulated their firing following behavioral tests in A1 compared to PrC, with median gains ranging from +0.23 to +1.06, depending on the specific response feature. Conclusion: Behavioral testing increases ongoing firing rate and responses to sounds in some cortical neurons. This increase is more prevalent in A1 than in PrC, mirroring clinical observations that patients exhibit basic responses under sedation, while complex processing, such as memory encoding, is impaired. The degree of neuronal modulation due to behavioral testing varies between anesthetic agents, mirroring their clinical phenotypes.

Platinum electrodes are used in many bionic devices; however, they have limited charge injection capacity (CIC) and signal‐to‐noise ratio (SNR), restricting performance. Iridium oxide has substantially larger CIC and reduced impedance compared to platinum. While these types of electrochemical measurements are typically used to infer improved electrophysiological performance, there are no studies demonstrating this correlation. This article compares the electrochemical and acute electrophysiological recording performance of iridium and electrochemically activated IrOx. Increased iridium activation reduced total impedance at low‐intermediate frequencies and steady‐state electroactive area but had no impact on linear diffusion electroactive area. The total impedance had a poor correlation with background noise, SNR and spike count. The results contribute to the previous literature indicating linear diffusion electroactive area determines the number of neurons within recording distance of the electrode, impacting SNR and spike count. Measurements of impedance are mainly of benefit as an indirect measure of linear diffusion electroactive area, in which case the measurement and analysis must be performed appropriately. A wide range of IrOx activation states can be produced with increased CIC, without concern of neural recording performance impacts. However, higher oxidation states resulting in electrode dissolution or increase in electrode resistance may limit IrOx chronic performance.

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.

Animals synchronize their movements with external rhythms to coordinate perception and action, but the neural population mechanisms that allow them to attend and then initiate and sustain these rhythms remain unclear. Using recordings from the medial premotor cortex (MPC) of two macaque monkeys, we investigated neural dynamics during an attend‐then‐synchronize tapping task with visual metronomes. We found low‐dimensional neural manifolds that captured neural population trajectories. During the attention epoch, trajectories exhibited increasing amplitude and oscillatory strength with the successive stimuli, which is consistent with a dynamic system using a resonant mechanism. Then, the transition from perception to tapping synchronization was marked by a reliable shift into a distinct manifold subspace with rotatory dynamics, enabling accurate decoding of the switch in behavior. In addition, correct tapping trials were characterized by a more robust oscillatory structure not seen in incorrect trials. These findings demonstrate that the geometry and coherence of MPC neural trajectories encode different perceptual and motor aspects of tapping synchronization.

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.

The locus coeruleus–norepinephrine (LC-NE) system regulates arousal and awakening; however, it remains unclear whether the LC does this in a global or circuit-specific manner. We hypothesized that sensory-evoked awakenings are predominantly regulated by specific LC-NE efferent pathways. Anatomical, physiological, and functional modularities of LC-NE pathways involving the mouse basal forebrain (BF) and pontine reticular nucleus (PRN) were tested. We found partial anatomical segregation between the LC → PRN and LC → BF circuits. Extracellular NE dynamics in BF and PRN exhibited distinct sound-evoked activation during sleep, including a fast sound-evoked NE peak specific to PRN. Causal optogenetic interrogation of LC efferent pathways, by retro-channelrhodopsin (ChR2) activation or Platynereis dumerilii ciliary opsin (PdCO) silencing of synapses in target regions, revealed a role for early LC → PRN activity in driving arousal and sound-evoked awakenings. Together, our results uncover a role for early LC-NE PRN activity in connecting sensory and arousal pathways and establish LC heterogeneity in regulating arousal.

Electroanalytical methods are used to understand, modify, and control bionic devices. Bionic devices can record or stimulate cells to understand and/or control normal or abnormal biological processes. These devices contain electrodes that transduce electrical current within the electrical circuit into ionic current within a tissue. Despite the similarity between electroanalysis and electrophysiology, there remains a poor understanding of the relationship between the two techniques, including their methodology and theory. This paper investigates the electrochemical and acute electrophysiological recording performance of neural electrodes. A range of behaviors is achieved by modifying electrodes with the conducting polymer poly(3,4‐ethylenedioxythiophene) (PEDOT) doped with chondroitin sulfate, dextran sulfate, or para ‐toluene sulfonate. The results support previous studies showing that increased electrode area reduced total impedance below the Maxwell–Wagner relaxation frequency and thermal noise while increasing the signal‐to‐noise ratio and neural spike count. The results allowed novel investigation of relative contributions of biological and electrode properties to electrophysiological performance, with increased electrode area having a larger impact on neural population within recording range rather than reducing thermal noise. The utility of measuring electrode impedance for predicting electrophysiological performance is mainly for an indirect measure of electrode area. The results provide insight into noise sources from electrophysiological recordings and limitations in cable theory in neuroscience.

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.

Distinguishing between nectar and non-nectar odors is challenging for animals due to shared compounds and varying ratios in complex mixtures. Changes in nectar production throughout the day and over the animal’s lifetime add to the complexity. The honeybee olfactory system, containing fewer than 1000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational model, tuned by in vivo electrophysiological data, and live imaging of the honeybee’s AL, we explored the neural mechanisms of plasticity in the AL. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses responses to shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise neural code. Our calcium imaging data support these predictions. Analysis of a graph convolutional neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors.

Mammals can execute intended limb movements despite the fact that spinal reflexes involuntarily modulate muscle activity. To generate appropriate muscle activity, the cortical descending motor output must coordinate with spinal reflexes, yet the underlying neural mechanism remains unclear. We simultaneously recorded activities in motor-related cortical areas, afferent neurons, and forelimb muscles of monkeys performing reaching movements. Motor-related cortical areas, predominantly primary motor cortex (M1), encode subsequent afferent activities attributed to forelimb movement. M1 also encodes a subcomponent of muscle activity evoked by these afferent activities, corresponding to spinal reflexes. Furthermore, selective disruption of the afferent pathway specifically reduced this subcomponent of muscle activity, suggesting that M1 output drives muscle activity not only through direct descending pathways but also through the “transafferent” pathway composed of descending plus subsequent spinal reflex pathways. Thus, M1 provides optimal motor output based on an internal forward model that prospectively computes future spinal reflexes.

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.

Cortical feedback connections are extremely numerous but the logic of connectivity between higher and lower areas remains poorly understood. Feedback from higher visual areas to primary visual cortex (V1) has been shown to enhance responses on perceptual figures compared to backgrounds, an effect known as figure-background modulation (FBM). A likely source of this feedback are border-ownership (BO) selective cells in mid-tier visual areas (e.g. V4) which represent the location of figures. We examined the connectivity between V4 cells and V1 cells using noise-correlations and micro-stimulation to estimate connectivity strength. We show that connectivity is consistent with a model in which BO-tuned V4 cells send positive feedback in the direction of their preferred figure and negative feedback in the opposite direction. This connectivity scheme can recreate patterns of FBM observed in previous studies. These results provide insights into the cortical connectivity underlying figure-background perception and establish a link between FBM and BO-tuning.

Before selecting a saccadic target, we often acquire partial information about the location of the forthcoming target and preselect a region of visual space even before the target becomes visible. To determine whether the supplementary eye field (SEF) represents information signifying the potential target space, we examined neuronal activity in the SEF of monkeys performing a behavioral task designed to isolate the process of visuospatial preselection under uncertainty from the process of selecting a specified location. Our data showed that the activity of SEF neurons represented information about the potential target space instructed by symbolic cues. Increased activity of visuospatially selective SEF neurons encoded the potential target space, which could be a mechanism facilitating subsequent selection of an appropriate target. Furthermore, electrical stimulation of the SEF during the preselection period disrupted subsequent target selection. These results demonstrate that the SEF contributes to the preselection of potential target spaces based on partial information.

Cognitive functions depend on neuronal communication, which is subserved by the synchronization of neuronal rhythms. Rhythms are characterized by their frequency, power and phase. If the phase of a rhythm just preceding an input is predictive of the neuronal or behavioral response to the input, this provides strong evidence for a functional role of the rhythm. Yet, this requires estimating the phase of a rhythm at the edge of the epoch. This is challenging, because any phase estimation that is spectrally specific requires a finite window length often combined with tapers that de-emphasize the signal close to the edge. To overcome this, we propose a method that builds on previously described approaches based on autoregressive modeling of the data and corresponding extrapolation beyond the edge. In contrast to related previous approaches, the modeling is based on the broadband signals, avoiding filtering-related group delays, and the extrapolation is performed multiple times, allowing averaging and thereby the reduction of extrapolation noise. The new method provided more accurate phase estimation at the edge for most simulated datasets, and for an empirical dataset from awake macaque area V4. We propose that the enhanced phase estimation accuracy at the edge might help to investigate the functional roles of brain rhythms and potentially also to improve phase-specific stimulation for clinical applications.

Homeostatic plasticity represents a set of mechanisms thought to stabilize some function of neural activity. Here, we identified the specific features of cellular or network activity that were maintained after the perturbation of GABAergic blockade in two different systems: mouse cortical neuronal cultures where GABA is inhibitory and motoneurons in the isolated embryonic chick spinal cord where GABA is excitatory (males and females combined in both systems). We conducted a comprehensive analysis of various spiking activity characteristics following GABAergic blockade. We observed significant variability in many features after blocking GABA A receptors (e.g., burst frequency, burst duration, overall spike frequency in culture). These results are consistent with the idea that neuronal networks achieve activity goals using different strategies (degeneracy). On the other hand, some features were consistently altered after receptor blockade in the spinal cord preparation (e.g., overall spike frequency). Regardless, these features did not express strong homeostatic recoveries when tracking individual preparations over time. One feature showed a consistent change and homeostatic recovery following GABA A receptor block. We found that spike rate within a burst (SRWB) increased after receptor block in both the spinal cord preparation and cortical cultures and then returned to baseline within hours. These changes in SRWB occurred at both single cell and population levels. Our findings indicate that the network prioritizes the burst spike rate, which appears to be a variable under tight homeostatic regulation. The result is consistent with the idea that networks can maintain an appropriate behavioral response in the face of challenges.