Local Field Potential Recordings Research Articles

Neurophysiological treatment effects of mesdopetam, pimavanserin and clozapine in a rodent model of Parkinson's disease psychosis

Psychosis in Parkinson's disease is a common phenomenon associated with poor outcomes. To clarify the pathophysiology of this condition and the mechanisms of antipsychotic treatments, we have here characterized the neurophysiological brain states induced by clozapine, pimavanserin, and the novel prospective antipsychotic mesdopetam in a rodent model of Parkinson's disease psychosis, based on chronic dopaminergic denervation by 6-OHDA lesions, levodopa priming, and the acute administration of an NMDA antagonist. Parallel recordings of local field potentials from eleven cortical and sub-cortical regions revealed shared neurophysiological treatment effects for the three compounds, despite their different pharmacological profiles, involving reversal of features associated with the psychotomimetic state, such as a reduction of aberrant high-frequency oscillations in prefrontal structures together with a decrease of abnormal synchronization between different brain regions. Other drug-induced neurophysiological features were more specific to each treatment, affecting network oscillation frequencies and entropy, pointing to discrete differences in mechanisms of action. These findings indicate that neurophysiological characterization of brain states is particularly informative when evaluating therapeutic mechanisms in conditions involving symptoms that are difficult to assess in rodents such as psychosis, and that mesdopetam should be further explored as a potential novel antipsychotic treatment option for Parkinson psychosis.

Dual Extracellular Recordings in the Mouse Hippocampus and Prefrontal Cortex.

The technique of recording local field potentials (LFPs) is an electrophysiological method used to measure the electrical activity of localized neuronal populations. It serves as a crucial tool in cognitive research, particularly in brain regions like the hippocampus and prefrontal cortex. Dual LFP recordings between these areas are of particular interest as they allow the exploration of interregional signal communication. However, methods for performing these recordings are rarely described, and most commercial recording devices are either expensive or lack adaptability to accommodate specific experimental designs. This study presents a comprehensive protocol for performing dual-electrode LFP recordings in the mouse hippocampus and the prefrontal cortex to investigate the effects of antipsychotic drugs and potassium channel modulators on LFP properties in these areas. The technique enables the measurement of LFP properties, including power spectra within each brain region and coherence between the two. Additionally, a low-cost, custom-designed recording device has been developed for these experiments. In summary, this protocol provides a means to record signals with high signal-to-noise ratios in different brain regions, facilitating the investigation of interregional information communication within the brain.

A comprehensive assessment of palmatine as anticonvulsant agent – In vivo and in silico studies

Previously, we demonstrated that palmatine (PALM) – an isoquinoline alkaloid from Berberis sibrica radix, exerted antiseizure activity in the pentylenetetrazole (PTZ)-induced seizure assay in larval zebrafish. The aim of the present study was to more precisely characterize PALM as a potential anticonvulsant drug candidate. A range of zebrafish and mouse seizure/epilepsy models were applied in the investigation. Immunostaining analysis was conducted to assess the changes in mouse brains, while in silico molecular modelling was performed to determine potential targets for PALM. Accordingly, PALM had anticonvulsant effect in ethyl 2-ketopent-4-enoate (EKP)-induced seizure assay in zebrafish larvae as well as in the 6 Hz-induced psychomotor seizure threshold and timed infusion PTZ tests in mice. The protective effect in the EKP-induced seizure assay was confirmed in the local field potential recordings. PALM did not affect seizures in the gabra1a knockout line of zebrafish larvae. In the scn1Lab-/- zebrafish line, pretreatment with PALM potentiated seizure-like behaviour of larvae. Repetitive treatment with PALM, however, did not reduce development of PTZ-induced seizure activity nor prevent the loss of parvalbumin-interneurons in the hippocampus of the PTZ kindled mice. In silico molecular modelling revealed that the noted anticonvulsant effect of PALM in EKP-induced seizure assay might result from its interactions with glutamic acid decarboxylase and/or via AMPA receptor non-competitive antagonism. Our study has demonstrated the anticonvulsant activity of PALM in some experimental models of seizures, including a model of pharmacoresistant seizures induced by EKP. These results indicate that PALM might be a suitable new drug candidate but the precise mechanism of its anticonvulsant activity has to be determined.

Gamma oscillation plasticity is mediated via parvalbumin interneurons.

Understanding the plasticity of neuronal networks is an emerging field of (patho-) physiological research, yet the underlying cellular mechanisms remain poorly understood. Gamma oscillations (30 to 80 hertz), a biomarker of cognitive performance, require and potentiate glutamatergic transmission onto parvalbumin-positive interneurons (PVIs), suggesting an interface for cell-to-network plasticity. In ex vivo local field potential recordings, we demonstrate long-term potentiation of hippocampal gamma power. Gamma potentiation obeys established rules of PVI plasticity, requiring calcium-permeable AMPA receptors (CP-AMPARs) and metabotropic glutamate receptors (mGluRs). A microcircuit computational model of CA3 gamma oscillations predicts CP-AMPAR plasticity onto PVIs critically outperforms pyramidal cell plasticity in increasing gamma power and completely accounts for gamma potentiation. We reaffirm this ex vivo in three PVI-targeting animal models, demonstrating that gamma potentiation requires PVI-specific signaling via a Gq/PKC pathway comprising mGluR5 and a Gi-sensitive, PKA-dependent pathway. Gamma activity-dependent, metabotropically mediated CP-AMPAR plasticity on PVIs may serve as a guiding principle in understanding network plasticity in health and disease.

An MRI Compatible Data Acquisition Device for Rat Brain Recording Inside 16.4T Magnet.

Concurrent recording of neural activities and functional magnetic resonance imaging (fMRI) data is useful for studying the neurovascular coupling relationship. This article presents a low-noise, frequency-shaping based neural recorder chip that is insensitive to radio frequency (RF) pulses and gradient echo artifacts under strong magnetic environment. To support simultaneous recording of local field potentials (LFPs), extracellular spikes, and fMRI data, a magnetic resonance imaging (MRI) compatible data acquisition (DAQ) device based on the designed recorder chip is developed with multiple circuit optimization techniques. Bench-top measurement shows that the designed DAQ device has 4.5 μV input-referred noise integrated from 300 Hz to 3000 Hz, which is not greatly affected by electromagnetic interference (EMI) at ultrahigh magnetic field (UMF, 16.4 T). In animal experiments, the designed DAQ device has been demonstrated to be capable of acquiring both the LFPs and extracellular spikes from a rat's brain before, during, and after MRI scanning. Besides, no obvious artifacts are seen from the designed DAQ device at multiple typical MRI scanning modes, and the system recovery time after gradient artifacts is reduced from more than 25 ms to less than 5 ms. The proposed DAQ device architecture based on the frequency-shaping neural recorder chip is MRI compatible and can provide highly competitive performance for concurrent recording of neural activities and fMRI data.

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition.

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible ( ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

Osl-dynamics, a toolbox for modeling fast dynamic brain activity.

Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.

Oscillatory Waveform Shape and Temporal Spike Correlations Differ across Bat Frontal and Auditory Cortex.

Neural oscillations are associated with diverse computations in the mammalian brain. The waveform shape of oscillatory activity measured in the cortex relates to local physiology and can be informative about aberrant or dynamically changing states. However, how waveform shape differs across distant yet functionally and anatomically related cortical regions is largely unknown. In this study, we capitalize on simultaneous recordings of local field potentials (LFPs) in the auditory and frontal cortices of awake, male Carollia perspicillata bats to examine, on a cycle-by-cycle basis, waveform shape differences across cortical regions. We find that waveform shape differs markedly in the fronto-auditory circuit even for temporally correlated rhythmic activity in comparable frequency ranges (i.e., in the delta and gamma bands) during spontaneous activity. In addition, we report consistent differences between areas in the variability of waveform shape across individual cycles. A conceptual model predicts higher spike-spike and spike-LFP correlations in regions with more asymmetric shapes, a phenomenon that was observed in the data: spike-spike and spike-LFP correlations were higher in the frontal cortex. The model suggests a relationship between waveform shape differences and differences in spike correlations across cortical areas. Altogether, these results indicate that oscillatory activity in the frontal and auditory cortex possesses distinct dynamics related to the anatomical and functional diversity of the fronto-auditory circuit.

FREQUENCY SYNCHRONIZATION REVEALS THAT SPIKE-WAVE DISCHARGES IN WAG/RIJ RATS ARE SIGNIFICANTLY NONLINEAR PHENOMENON

In this work, we studied the time-frequency dynamics of spike-wave discharges in rats with predisposition to absence epilepsy (WAG/Rij line) in two frequency ranges: 7–12,Hz and 14–24,Hz. The first and the second harmonics of the seizure main frequency lie in these ranges. Recordings of brain local field potentials of eight animals in eleven experiments of eight hour duration were analyzed. The method was based on the fast Fourier transform with a Hann’s window, and skeletons were constructed based on the obtained spectrograms. Using the skeletons, a visual and automated numerical assessment of the main frequency evolution was performed. As a result of this analysis, it was shown that temporal dynamics of the main frequency in the range 14–24,Hz follows the dynamics of the main frequency in the range 7–12,Hz. Since during the baseline activity the main frequencies in two considered ranges were developing independently, our finding indicates that the discharge is a significantly nonlinear process.

Synchronized LFP rhythmicity in the social brain reflects the context of social encounters

Mammalian social behavior is highly context-sensitive. Yet, little is known about the mechanisms that modulate social behavior according to its context. Recent studies have revealed a network of mostly limbic brain regions which regulates social behavior. We hypothesize that coherent theta and gamma rhythms reflect the organization of this network into functional sub-networks in a context-dependent manner. To test this concept, we simultaneously record local field potential (LFP) from multiple social brain regions in adult male mice performing three social discrimination tasks. While LFP rhythmicity across all tasks is dominated by a global internal state, the pattern of theta coherence between the various regions reflect the behavioral task more than other variables. Moreover, Granger causality analysis implicate the ventral dentate gyrus as a main player in coordinating the context-specific rhythmic activity. Thus, our results suggest that the pattern of coordinated rhythmic activity within the network reflects the subject’s social context.

Early hippocampal high-amplitude rhythmic spikes predict post-traumatic epilepsy in mice.

Oscillations, a highly conserved brain function across mammalian species, play a pivotal role in both brain physiology and pathology. Traumatic brain injury (TBI) frequently results in subacute and chronic alterations in brain oscillations, which are often associated with complications like post-traumatic epilepsy (PTE) in patients and animal models. We recently conducted longitudinal recordings of local field potential from the contralateral hippocampus of 12 strains of recombinant inbred Collaborative Cross (CC) mice and classical laboratory inbred C57BL/6 J mice after lateral fluid percussion injury. In this study, we profiled the acute (<12 h post-injury) and subacute (12-48 h post-injury) hippocampal oscillatory responses to TBI and evaluated their predictive value for PTE. We found dynamic high-amplitude rhythmic spikes with elevated power density and reduced signal complexity that prevailed exclusively during the acute phase in CC031 mice, which later developed PTE. This characteristic early brain oscillatory alteration was absent in CC031 sham controls, as well as in other CC strains and reference C57BL/6 J mice that did not develop PTE after TBI. Our findings offer quantitative measures linking early hippocampal brain oscillation to PTE at a population level in mice. These insights enhance understanding of circuit mechanisms and suggest potential targets for neuromodulatory intervention.

Quantifying network behavior in the rat prefrontal cortex.

The question of how consciousness and behavior arise from neural activity is fundamental to understanding the brain, and to improving the diagnosis and treatment of neurological and psychiatric disorders. There is significant murine and primate literature on how behavior is related to the electrophysiological activity of the medial prefrontal cortex and its role in working memory processes such as planning and decision-making. Existing experimental designs, specifically the rodent spike train and local field potential recordings during the T-maze alternation task, have insufficient statistical power to unravel the complex processes of the prefrontal cortex. We therefore examined the theoretical limitations of such experiments, providing concrete guidelines for robust and reproducible science. To approach these theoretical limits, we applied dynamic time warping and associated statistical tests to data from neuron spike trains and local field potentials. The goal was to quantify neural network synchronicity and the correlation of neuroelectrophysiology with rat behavior. The results show the statistical limitations of existing data, and the fact that making meaningful comparison between dynamic time warping with traditional Fourier and wavelet analysis is impossible until larger and cleaner datasets are available.

Whole-Brain Electrophysiology in Drosophila during Sleep and Wake.

Sleep studies in Drosophila melanogaster rely mostly on behavioral read-outs to support molecular or circuit-level investigations in this model. Electrophysiology can provide an additional level of understanding in these studies to, for example, investigate changes in brain activity associated with sleep manipulations. In this protocol, we describe a procedure for performing multichannel local field potential (LFP) recordings in the fruit fly, with a flexible system that can be adapted to different experimental paradigms and situations. The approach uses electrodes containing multiple recording sites (16), allowing the acquisition of large amounts of neuronal activity data from a transect through the brain while flies are still able to sleep. The approach starts by tethering the fly, followed by positioning it on an air-supported ball. A multichannel silicon probe is then inserted laterally into the fly brain via one eye, allowing for recording of electrical signals from the retina through to the central brain. These recordings can be acquired under spontaneous conditions or in the presence of visual stimuli, and the minimal surgery promotes long-term recordings (e.g., overnight). Sleep and wake can be tracked using infrared cameras, which allow for the measurement of locomotive activity as well as microbehaviors such as proboscis extensions during sleep. The protocol has been optimized to promote subject survivability, which is an important factor when performing long-term (∼16-h) recordings. The approach described here uses specific recording probes, data acquisition devices, and analysis tools. Although it is expected that some of these items might need to be adapted to the equipment available in different laboratories, the overall aim is to provide an overview on how to record electrical activity across the brain of behaving (and sleeping) flies using this kind of approach and technology.

A piezoelectric micromachined ultrasound transducer combined with recording electrodes for acute brain preparations in vitro

BackgroundUltrasound stimulation is used to noninvasively stimulate the local and deep areas of the brain. However, the detailed cellular mechanisms of neural activation are still unclear because studies on micro-stimulation at the cellular level are lacking. New methodTo modulate neural activity at the cellular level, we developed a piezoelectric micromachined ultrasound transducer (PMUT), having circular diaphragms for application on acute brain slice preparations. To monitor neural activities, additionally, we fabricated recording microelectrodes onto the same PMUT device for closed-loop application. ResultsTo examine the PMUT-driven cellular responses of a brain slice, intracellular calcium signals in individual cells were measured using two calcium indicators. We successfully observed the intracellular responses triggered by the ultrasound of our novel PMUT. In addition, we performed recordings of local field potentials in a brain slice, demonstrating its usefulness as a simultaneous recording interface. Comparison with existing method(s)Conventional ultrasound stimulators are open-loop systems that risk inducing excessive neural activity because of the absence of neural activity monitoring. In contrast, our PMUT is packaged in a single device with both stimulation and sensor interface for neuromodulation. Further, there are no published reports on in vitro microdevices that can be used for ultrasound stimulation in rodent cortical slices that are several hundred micrometers thick, which maintain the cortical laminar structure and intrinsic neural networks. ConclusionsOur findings suggest that this novel PMUT device has the potential for being a powerful tool for in vitro brain slice applications and effective closed loop ultrasound stimulation.

Towards automated sleep-stage classification for adaptive deep brain stimulation targeting sleep in patients with Parkinson’s disease

Sleep dysfunction affects over 90% of Parkinson’s disease patients. Recently, subthalamic nucleus deep brain stimulation has shown promise for alleviating sleep dysfunction. We previously showed that a single-layer neural network could classify sleep stages from local field potential recordings in Parkinson’s disease patients. However, it was unable to categorise non-rapid eye movement into its different sub-stages. Here we employ a larger hidden layer network architecture to distinguish the substages of non-rapid eye movement with reasonable accuracy, up to 88% for the lightest substage and 92% for deeper substages. Using Shapley attribution analysis on local field potential frequency bands, we show that low gamma and high beta are more important to model decisions than other frequency bands. These results suggest that the proposed neural network-based classifier can be employed for deep brain stimulation treatment in commercially available devices with lower local field potential sampling frequencies.

Multifractal characteristics of neuronal activity of the &lt;i&gt; globus pallidus &lt;/i&gt; in patients with dystonia

Dystonia is a movement disorder characterized by involuntary muscle contractions resulting in anomalous postures, often accompanied by dystonic tremors. Among the indicative dystonic postures is an involuntary tonic tilt or rotation of the head. Currently, the etiology and pathogenesis of the disease remain theories. Currently, only low-frequency (theta-alpha) oscillations in the globus pallidus are regarded as the possible biomarker of pathological activity in dystonia. In many patients with dystonia, the absence of rhythmic neuronal activity in the basal ganglia renders this biomarker unusable for surgical treatment of the disease. Additionally, the mechanisms underlying the rearrangement of temporary patterns of neural activity that result in pathological symptoms remain unclear. We propose that the appearance of these pathological rhythms is associated with the reduction of dynamic complexity in the pattern of neural activity within the globus pallidus. We aim to use multifractal analysis in this study to evaluate changes in the globus pallidus neural activity pattern’s dynamic complexity and their correlation with the clinical manifestations of dystonia. The study examined the electrical activity of the globus pallidus in 23 patients receiving deep brain stimulation (DBS) treatment. We used the microelectrode registration technique and local field potential (LFP) registration during intraoperative neuron monitoring to precisely identify the specific locations of the external and internal segments of the globus pallidus (GPe and GPi). In four patients, an additional postoperative recording of local field potentials (LFP) was conducted while performing DBS and vibrational impact on the neck muscles. A neurologist evaluated the patients to determine the severity of the disease using the Burke-Fahn-Mardsen Dystonia Rating Scale (BFMDRS). The LEAD DBS software package was employed for postoperative reconstruction of the DBS stimulating electrode positions and for simulating the optimal stimulation zone, selected by the neurologist (i.e., volume of tissue activated, VTA). Subsequently, we identified the region that presented the most significant variation in multifractal spectrum parameters following DBS to understand its correlation with the optimal VTA. A total of 745 local potential records were analyzed, with 433 in GPe and 312 in GPi. The severity of dystonia was found to be correlated with the parameters of the multifractal spectrum (rho: –0.5630882, p=0.005149 for GPe and rho: –0.5180609, p=0.01133 for GPi). Moreover, as the dystonia severity increased along the BFMDRS scale, the multifractal spectrum became narrower and more asymmetric. In post-surgery recordings, we observed changes in the shape of the multifractal spectrum during DBS stimulation or vibration. In particular, when exposed, the multifractal spectrum significantly widened, and its symmetry was restored. We identified the region with the greatest alteration in the width of the multifractal spectrum following DBS and discovered that this region considerably intersected or fully matched the neurologist’s chosen zone for optimal DBS stimulation. We demonstrated that multifractal analysis can serve as an ancillary approach to evaluate the extent of proprioceptive feedback impairment and as a biomarker of dystonia. The noteworthy and substantial correlation with dystonia severity underscores the considerable potential of multifractal spectrum features as a biomarker of dystonia. Additionally, the overlapping areas with the most significant DBS impact and the widest variation in the multifractal spectrum in DBS can be used as a tool for identifying the most favorable region for DBS stimulation.

Differences in neuronal activity of subthalamic nuclei in asymmetric manifestation of Parkinson’s disease

Parkinson’s disease (PD) is a widely prevalent condition that has spurred extensive research into identifying its biological markers. Different models posit that various patterns of subthalamic nucleus (STN) activity may constitute such markers, but as yet, none have been established definitively. One major limitation of human studies in this area is the lack of a reliable control group. Therefore, patients with asymmetric motor symptoms in Parkinson’s disease are of great interest. I.I. Koloman and A.Sh. Chimagomedova [1] demonstrated that motor malfunctions’ asymmetry is indicative of asymmetry in the degenerative process within the substantia nigra. Additionally, while the disease normally manifests unilaterally, only a limited number of patients maintain notable distinctions in motor symptom severity as the condition advances. In our study, we analyzed the single-unit activity (SUA) and local field potentials (LFP) recordings obtained duringdeep brain stimulation (DBS) surgeries in 12 patients. Neurologists assessed the severity of bradykinesia, rigidity, and tremor using the UPDRS 3 scale to meet the inclusion criteria, and the difference between hemibodies for each symptom had to be at least 25%. The median disease duration at the time of surgery ranged from 6 to 22 years. The subthalamic nucleus that exhibits more pronounced disturbances on the contralateral side of the body is labeled as “affected”, while the opposite STN, acting as the conditional control, is labeled as “nonaffected”. For analysis, we used a hierarchical clustering method following Ward’s algorithm [2] to classify the recorded neurons into three groups based on their activity type: tonic, burst, and pause cells. We observed no significant differences in neuron activity between hemispheres, as well as the predicted hyperactivity of affected STN neurons outlined by the classical model [3] of basal ganglia functioning. However, the research demonstrates a significant increase in pause neurons and decrease in burst neurons within the affected nucleus. Furthermore, both of these types were found to be situated in the upper half of the STN, which is recognized as the motor region of the nucleus. Our hypothesis is that as the disease advances, some STN neurons (specifically burst neurons in our sample) modify their activity patterns towards a more rhythmic activity (pause neurons in our sample). This supports the notion that rhythmic STN neuron activity is linked to Parkinson’s disease [4]. LFPs were analyzed by estimating oscillation synchrony (o-scores) in multiple spectral bands following 1/f correction. Parkinson’s disease is typically associated with boosted oscillation power in the beta range (13–30 Hz). Our findings established that the power of oscillations in the low-frequency beta range (13–20 Hz) were indeed increased in the affected nucleus, but, in contrast to expectations, the power in the high-frequency part (20–30 Hz) of the band was significantly lower. This is in line with the modern theory of distinct physiological functions of oscillations in these subbands [5]. Additionally, we noticed a rise in frequency spectrum in the alpha range (8–12 Hz) and a decrease in the gamma range (30–60 Hz) in the impacted nucleus. Our findings indicate that a more rhythmic burst neuron activity mode and an increased number of pause neurons in the motor zone of the STN can serve as a marker for PD. Increased power oscillation in alpha and low-frequency beta bands, along with reduced synchronization in high-beta and gamma bands, may also be linked to this disorder. However, further investigation is necessary to determine their association with disease symptoms.

Usefulness of thalamic beta activity for closed-loop therapy in essential tremor

A partial loss of effectiveness of deep brain stimulation of the ventral intermediate nucleus of the thalamus (VIM) has been reported in some patients with essential tremor (ET), possibly due to habituation to permanent stimulation. This study focused on the evolution of VIM local-field potentials (LFPs) data over time to assess the long-term feasibility of closed-loop therapy based on thalamic activity. We performed recordings of thalamic LFPs in 10 patients with severe ET using the ACTIVA™ PC + S (Medtronic plc.) allowing both recordings and stimulation in the same region. Particular attention was paid to describing the evolution of LFPs over time from 3 to 24 months after surgery when the stimulation was Off. We demonstrated a significant decrease in high-beta LFPs amplitude during movements inducing tremor in comparison to the rest condition 3 months after surgery (1.91 ± 0.89 at rest vs. 1.27 ± 1.37 µV2/Hz during posture/action for N = 8/10 patients; p = 0.010), 12 months after surgery (2.92 ± 1.75 at rest vs. 2.12 ± 1.78 µV2/Hz during posture/action for N = 7/10 patients; p = 0.014) and 24 months after surgery (2.32 ± 0.35 at rest vs 0.75 ± 0.78 µV2/Hz during posture/action for 4/6 patients; p = 0.017). Among the patients who exhibited a significant decrease of high-beta LFP amplitude when stimulation was Off, this phenomenon was observed at least twice during the follow-up. Although the extent of this decrease in high-beta LFPs amplitude during movements inducing tremor may vary over time, this thalamic biomarker of movement could potentially be usable for closed-loop therapy in the long term.

Correlation dimension of high-dimensional and high-definition experimental time series

The correlation dimension (CD) is a nonlinear measure of the complexity of invariant sets. First introduced for describing low-dimensional chaotic attractors, it has been later extended to the analysis of experimental electroencephalographic (EEG), magnetoencephalographic (MEG), and local field potential (LFP) recordings. However, its direct application to high-dimensional (dozens of signals) and high-definition (kHz sampling rate) 2HD data revealed a controversy in the results. We show that the need for an exponentially long data sample is the main difficulty in dealing with 2HD data. Then, we provide a novel method for estimating CD that enables orders of magnitude reduction of the required sample size. The approach decomposes raw data into statistically independent components and estimates the CD for each of them separately. In addition, the method allows ongoing insights into the interplay between the complexity of the contributing components, which can be related to different anatomical pathways and brain regions. The latter opens new approaches to a deeper interpretation of experimental data. Finally, we illustrate the method with synthetic data and LFPs recorded in the hippocampus of a rat.

Interneuron hyperexcitability in an APP/PS1 mouse model of Alzheimer’s disease

AbstractBackgroundNeuronal hyperexcitability is commonly observed in Alzheimer’s disease (AD) patients and in mouse models of AD. What is not clear yet is whether hyperexcitability occurs in all neurons or whether certain types of neurons are selectively vulnerable towards developing a hyperexcitable phenotype.MethodElectrophysiological recordings were performed in hippocampal slices from APP/PS1 mice to measure intrinsic and network properties of excitatory pyramidal neurons and of inhibitory parvalbumin (PV)‐positive interneurons. Cell type‐specific chemogenetic interventions were used to selectively reverse the hyperexcitable phenotype of these neurons. The outcome of these interventions was measured using hippocampal slice physiology, local field potential (LFP) recordings and behavioral assessment.ResultThe intrinsic excitability of hippocampal PV interneurons was significantly higher in APP/PS1 mice at 3‐4 months of age whereas pyramidal neurons were not affected at this age. Increased excitability of PV interneurons coincided with impaired learning and memory in the Morris water maze. Reducing the activity of PV neurons using chemogenetics resulted in a complete and long‐lasting rescue of PV cell excitability, network properties and learning and memory. LFP recordings revealed changes in oscillatory power and excitation/inhibition balance that could be related to early PV cell hyperexcitability and may translate to novel EEG biomarkers to detect AD at an early stage in humans.ConclusionHyperexcitability of hippocampal PV interneurons is an early cellular phenotype in APP/PS1 mice that is causally related to neuronal network and memory impairments, whereas pyramidal cells only become hyperexcitable at later disease stages. These findings are relevant for AD as they may help to identify neuronal activity markers that are specific for early disease stages as well as cell type‐specific ion channels or receptors that can be targeted to treat AD in its earliest stage.