Publications using the PZ2

Anxiety disorders involve distorted perception of the world including increased saliency of stress-associated cues. However, plasticity in the initial sensory regions of the brain following a fearful experience has never been examined. The cochlear nucleus (CN) is the first station in the central auditory system, with heterogeneous collections of neurons that not only project to but also receive projections from cortico-limbic regions, suggesting a potential for experience-dependent plasticity. Using wireless neural recordings in freely behaving rats, we demonstrate for the first time that neural gain in the CN is significantly altered by fear conditioning to auditory sequences. Specifically, the ventral subnuclei significantly increased firing rate to the conditioned tone sequence, while the dorsal subnuclei significantly decreased firing rate during the conditioning session overall. These findings suggest subregion-specific changes in the balance of inhibition and excitation in the CN as a result of conditioning experience. Heart rate was measured as the conditioned response (CR), which showed that while pre-conditioned stimulus (CS) responding did not change across baseline and conditioning sessions, significant changes in heart rate were observed to the tone sequence followed by shock. Heart-rate findings support acquisition of conditioned fear. Taken together, the present study presents first evidence for potential experience-dependent changes in auditory perception that involve novel plasticity within the first site of processing auditory information in the brain.

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.

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.

Evidence suggests that the pathophysiology associated with epileptic susceptibility may disturb the functional connectivity of neural circuits and compromise the brain functions, even when seizures are absent. Although memory impairment is a common comorbidity found in patients with epilepsy, it is still unclear whether more caudal structures may play a role in cognitive deficits, particularly in those cases where there is no evidence of hippocampal sclerosis. This work used a genetically selected rat strain for seizure susceptibility (Wistar audiogenic rat, WAR) and distinct behavioral (motor and memory-related tasks) and electrophysiological (inferior colliculus, IC) approaches to access acoustic primary integrative network properties. The IC neural assemblies' response was evaluated by auditory transient (focusing on bottom-up processing) and steady-state evoked response (ASSR, centering on feedforward and feedback forces over neural circuitry). The results show that WAR displayed no disturbance in motor performance or hippocampus-dependent memory tasks. Nonetheless, WAR animals exhibited significative impairment for auditory fear conditioning (AFC) along with no indicative of IC plastic changes between the pre-conditioning and test phases (ASSR coherence analysis). Furthermore, WAR's IC response to transient stimuli presented shorter latency and higher amplitude compared with Wistar; and the ASSR analysis showed similar results for WAR and Wistar animals under subthreshold dose of pentylenetetrazol (pro-convulsive drug) for seizure-induction. Our work demonstrated alterations at WAR IC neural network processing, which may explain the associated disturbance on AFC memory.

Scientists find how syllable timing and stress are represented in human speech cortex.

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.

Humans and other animals effortlessly identify natural sounds and categorize them into behaviorally relevant categories. Yet, the acoustic features and neural transformations that enable sound recognition and the formation of perceptual categories are largely unknown. Here, using multichannel neural recordings in the auditory midbrain of unanesthetized female rabbits, we first demonstrate that neural ensemble activity in the auditory midbrain displays highly structured correlations that vary with distinct natural sound stimuli. These stimulus-driven correlations can be used to accurately identify individual sounds using single-response trials, even when the sounds do not differ in their spectral content. Combining neural recordings and an auditory model, we then show how correlations between frequency-organized auditory channels can contribute to discrimination of not just individual sounds but sound categories. For both the model and neural data, spectral and temporal correlations achieved similar categorization performance and appear to contribute equally. Moreover, both the neural and model classifiers achieve their best task performance when they accumulate evidence over a time frame of approximately 1-2 seconds, mirroring human perceptual trends. These results together suggest that time-frequency correlations in sounds may be reflected in the correlations between auditory midbrain ensembles and that these correlations may play an important role in the identification and categorization of natural sounds.

Spreading depolarization (SD) accompanies numerous neurological conditions, including migraine, stroke, and traumatic brain injury. There is significant interest in understanding the relationship between SD and neuronal injury. However, characteristics underlying SD and repolarization (RP) induced by global cerebral ischemia (e.g., cardiac arrest (CA)) and reperfusion are not well understood. Quantifying features of SD and RP during CA and cardiopulmonary resuscitation (CPR) may provide important metrics for diagnosis and prognosis of neurological injury from hypoxia-ischemia. We characterized SD and RP in a rodent model of asphyxial CA+CPR using a multimodal platform including electrocorticography (ECoG) and optical imaging. We detected SD and RP by (1) alternating current (AC), (2) direct current (DC), and (3) optical imaging of spreading ischemia, spreading edema, and vasoconstriction. Earlier SD (r=−0.80; p<0.001) and earlier RP (r=−0.71, p<0.001) were associated with better neurological recovery after 24hrs. SD+RP onset times predicted good vs poor neurological recovery with 82% sensitivity and 91% specificity. To our knowledge, this is the first preclinical study to link SD and RP characteristics with neurological recovery post-CA. These data suggest that SD and RP may be ultra-early, real-time prognostic markers of post-CA outcome, meriting further investigation into translational implications during global cerebral ischemia.

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.

Kinase signaling plays an important role in acquired epilepsy, but only a small percentage of the total kinome has been investigated in this context. A major roadblock that prevents the systematic investigation of the contributions of kinase signaling networks is the slow speed of experiments designed to test the chronic effects of target inhibition in epilepsy models. We developed a novel in vitro screening platform based on microwire recordings from an organotypic hippocampal culture model of acquired epilepsy. This platform enables the direct, parallel determination of the effects of compounds on spontaneous epileptiform activity. The platform also enables repeated recordings from the same culture over two-week long experiments. We screened 45 kinase inhibitors and quantified their effects on seizure duration, the frequency of paroxysmal activity, and electrographic load. We identified several inhibitors with previously unknown antiepileptic properties. We also used kinase inhibition profile cross-referencing to identify kinases that are inhibited by seizure-suppressing compounds, but not by compounds that had no effect on seizures.

Predictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom-up interactions in sensory processing. The theory suggests there are differences in message passing up versus down the cortical hierarchy. These differences result from the linear feedforward of prediction errors, and the nonlinear feedback of predictions. This implies that cross-frequency interactions should predominate top-down. But it remains unknown whether these differences are expressed in cross-frequency interactions in the brain. Here we examined bidirectional cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase–amplitude coupling (PAC) and amplitude–amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up interactions made prominent use of low frequencies: low-to-low-frequency (theta, alpha, beta) and low-frequency-to-high- gamma couplings were predominant top-down, while low-frequency-to-low-gamma couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting that they are a general feature of information processing in auditory cortex. Our findings suggest the modulatory effect of low frequencies on gamma-rhythms in distant regions is important for bidirectional information transfer. The finding of low-frequency-to-low-gamma interactions in the bottom-up direction suggest that nonlinearities may also play a role in feedforward message passing. Altogether, the patterns of cross-frequency interaction we observed across the auditory hierarchy are largely consistent with the predictive coding framework.

The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30–80 Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization between neuronal populations receiving mutually predictable inputs. We show that large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma synchronization in macaque V1, particularly when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma synchronization while increasing firing rates. Differences between responses to different colors, including strong gamma-responses to red, arose from stimulus adaptation to a full-screen background, suggesting prominent differences in adaptation between M- and L-cone signaling pathways. Thus, synchrony signaled whether RF inputs were predicted from spatial context, while firing rates increased when stimuli were unpredicted from context.

Microelectrode arrays designed to map and modulate neuronal circuitry have enabled greater understanding and treatment of neurological injury and disease. Reliable detection of neuronal activity over time is critical for the successful application of chronic recording devices. Here, we assess device-related plasticity by exploring local changes in ion channel expression and their relationship to device performance over time. We investigated four voltage-gated ion channels (Kv1.1, Kv4.3, Kv7.2, and Nav1.6) based on their roles in regulating action potential generation, firing patterns, and synaptic efficacy. We found that a progressive increase in potassium channel expression and reduction in sodium channel expression accompanies signal loss over 6 weeks (both LFP amplitude and number of units). This motivated further investigation into a mechanistic role of ion channel expression in recorded signal instability. We employed siRNA in neuronal culture to find that Kv7.2 knockdown (as a model for the transient downregulation observed at 1 day in vivo) mimics excitatory synaptic remodeling around devices. This work provides new insight into the mechanisms underlying signal loss over time.

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.

Glassy carbon (GC) has high potential to serve as a biomaterial in neural applications because it is biocompatible, electrochemically inert and can be incorporated in polyimide-based implantable devices. Miniaturization and applicability of GC is, however, thought to be partially limited by its electrical conductivity. For this study, ultra-conformable polyimide-based electrocorticography (ECoG) devices with different-diameter GC electrodes were fabricated and tested in vitro and in rat models. For achieving conformability to the rat brain, polyimide was patterned in a finger-like shape and its thickness was set to 8 µm. To investigate different electrode sizes, each ECoG device was assigned electrodes with diameters of 50, 100, 200 and 300 µm. They were electrochemically characterized and subjected to 10 million biphasic pulses—for achieving a steady-state—and to X-ray photoelectron spectroscopy, for examining their elemental composition. The electrodes were then implanted epidurally to evaluate the ability of each diameter to detect neural activity. Results show that their performance at low frequencies (up to 300 Hz) depends on the distance from the signal source rather than on the electrode diameter, while at high frequencies (above 200 Hz) small electrodes have higher background noises than large ones, unless they are coated with poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS).

Electrical nerve recording and stimulation technologies are critically needed to monitor and modulate nerve activity to treat a variety of neurological diseases. However, current neuromodulation technologies presented in the literature or commercially available products cannot support simultaneous recording and stimulation on the same nerve. To solve this problem, a new bidirectional neuromodulation system-on-chip (SoC) is proposed in this paper, which includes a frequency-shaping neural recorder and a fully integrated neural stimulator with charge balancing capability. In addition, auxiliary circuits consisting of power management and data transmission circuits are designed to provide the necessary power supply for the SoC and the bidirectional data communication between the SoC and an external computer via a universal serial bus (USB) interface, respectively. To achieve sufficient low input noise for sensing nerve activity at a sub-10 μ V range, several noise reduction techniques are developed in the neural recorder. The designed SoC was fabricated in a 0.18 μ m high-voltage Bipolar CMOS DMOS (BCD) process technology that was described in a previous publication and it has been recently tested in animal experiments that demonstrate the proposed SoC is capable of achieving reliable and simultaneous electrical stimulation and recording on the same nerve.

Background: Numerous studies have demonstrated that individuals exhibit structured neural activity in many brain regions during rest that is also observed during different tasks, however it is still not clear whether and how resting state activity patterns may relate to underlying tuning for specific stimuli. In the posterior superior temporal gyrus (STG), distinct neural activity patterns are observed during the perception of specific linguistic speech features. We hypothesized that spontaneous resting-state neural dynamics of the STG would be structured to reflect its role in speech perception, exhibiting an organization along speech features as seen during speech perception. Methods: Human cortical local field potentials were recorded from the superior temporal gyrus (STG) in 8 patients undergoing surgical treatment of epilepsy. Signals were recorded during speech perception and rest. Patterns of neural activity (high gamma power: 70-150 Hz) during rest, extracted with spatiotemporal principal component analysis, were compared to spatiotemporal neural responses to speech features during perception. Hierarchical clustering was applied to look for patterns in rest that corresponded to speech feature tuning. Results: Significant correlations were found between neural responses to speech features (sentence onsets, consonants, and vowels) and the spontaneous neural activity in the STG. Across subjects, these correlations clustered into five groups, demonstrating tuning for speech features-most robustly for acoustic onsets. These correlations were not seen in other brain areas, or during motor and spectrally-rotated speech control tasks. Conclusions: In this study, we present evidence that the RS structure of STG activity robustly recapitulates its stimulus-evoked response to acoustic onsets. Further, secondary patterns in RS activity appear to correlate with stimulus-evoked responses to speech features. The role of these spontaneous spatiotemporal activity patterns remains to be elucidated.

Until recently, hypocretin (Hcrt) neurons were the only known wake-promoting neuronal population in the lateral hypothalamus (LH), but subpopulations of inhibitory neurons in this area and glutamatergic neurons in the nearby supramammillary nucleus (SuM) have recently been found that also promote wakefulness. We performed chemogenetic excitation of LH neurons in mice and observed increased wakefulness that lasted more than 4 h without unusual behavior or EEG anomalies. The increased wakefulness was similar in the presence or absence of the dual orexin receptor blocker almorexant (ALM). Analysis of hM3Dq transfection and c-FOS expression in LH inhibitory neurons and in the SuM failed to confirm that the increased wakefulness was due to these wake-promoting populations, although this possibility cannot be completely excluded. To evaluate the relationship to the Hcrt system, we repeated the study in Orexin-tTA mice in the presence or absence of dietary doxycycline (DOX), which enabled us to manipulate the percentage of Hcrt neurons that expressed hM3Dq. In DOX-fed mice, 18% of Hcrt neurons as well as many other LH neurons expressed hM3Dq; these mice showed a profound increase in wake after hM3Dq activation even in the presence of ALM. In mice switched to normal chow, 62% of Hcrt neurons expressed hM3Dq along with other LH cells; chemogenetic activation produced even more sustained arousal which could be reduced to previous levels by ALM treatment. Together, these results indicate an LH neuron population that promotes wakefulness through an Hcrt-independent pathway that can act synergistically with the Hcrt system to prolong arousal.