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Background: Abnormal rapid eye movement (REM) sleep, including REM sleep behavior disorder (RBD) and reduced REM sleep, is common in Parkinson's disease (PD), highlighting the importance of further study on REM sleep. However, the biomarkers of REM disturbances remain unknown, leading to the lack of REM-specific neuromodulation interventions., Objective: This study aims to investigate the neurophysiological biomarkers of REM disturbance in parkinsonian patients., Methods: Ten PD patients implanted with bilateral subthalamic nucleus-deep brain stimulation (STN-DBS) were included in this study, of whom 4 were diagnosed with RBD. Sleep monitoring was conducted 1 month after surgery. Subthalamic local field potentials (LFP) were recorded through sensing-enabled DBS. The neurophysiological features of subthalamic LFP during phasic and tonic microstates of REM sleep and their correlation with REM sleep fragmentation and RBD were analyzed., Results: Differences in subthalamic γ oscillation between phasic and tonic REM correlated positively with the severity of REM sleep fragmentation. Patients with RBD also exhibited stronger γ oscillations during REM sleep compared with non-RBD patients, and both increased β and γ were found before the onset of RBD episodes. Stimulation changes in simulated γ-triggered feedback modulation followed more closely with phasic REM density, whereas an opposite trend was found in simulated β-triggered feedback modulation., Conclusion: Excess subthalamic γ oscillations may contribute to REM instability and RBD, suggesting that γ oscillation could serve as a feedback signal for adaptive DBS for REM sleep disorders. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes signal processing analyses across time (e.g., time-lock analysis), frequency (e.g., power spectrum), and connectivity (e.g., coherence) domains. It enables user-friendly data analysis on both laptop-based and high-performance computing systems. SyNCoPy is designed to facilitate trial-parallel workflows (parallel processing of trials), making it an ideal tool for large-scale analysis of electrophysiological data. Based on parallel processing of trials, the software can support very large-scale datasets via innovative out-of-core computation techniques. It also provides seamless interoperability with other standard software packages through a range of file format importers and exporters and open file formats. The naming of the user functions closely follows the well-established FieldTrip framework, which is an open-source MATLAB toolbox for advanced analysis of electrophysiological data., Competing Interests: PF has a patent on thin-film electrodes and is a member of the Advisory Board of CorTec GmbH (Freiburg, Germany). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mönke, Schäfer, Parto-Dezfouli, Kajal, Fürtinger, Schmiedt and Fries.)

Background/Objectives: Dopamine dysfunction (DA) is a hallmark of many neurological disorders. In this case, the mechanism of changes in dopamine transmission on behavior remains unclear. This study is a look into the intricate link between disrupted DA signaling, neuronal activity patterns, and behavioral abnormalities in a hyperdopaminergic animal model. Methods: To study the relationship between altered DA levels, neuronal activity, and behavioral deficits, local field potentials (LFPs) were recorded during four different behaviors in dopamine transporter knockout rats (DAT-KO). At the same time, local field potentials were recorded in the striatum and prefrontal cortex. Correlates of LFP and accompanying behavioral patterns in genetically modified (DAT-KO) and control animals were studied. Results: DAT-KO rats exhibited desynchronization between LFPs of the striatum and prefrontal cortex, particularly during exploratory behavior. A suppressive effect of high dopamine levels on the striatum was also observed. Wild-type rats showed greater variability in LFP patterns across certain behaviors, while DAT-KO rats showed more uniform patterns. Conclusions: The decisive role of the synchrony of STR and PFC neurons in the organization of motor acts has been revealed. The greater variability of control animals in certain forms of behavior probably suggests greater adaptability. More uniform patterns in DAT-KO rats, indicating a loss of striatal flexibility when adapting to specific motor tasks. It is likely that hyperdopaminergy in the DAT-KO rat reduces the efficiency of information processing due to less synchronized activity during active behavior.

Aim: Photopharmacology is a new technique for modulating biological phenomena through the photoconversion of substances in a specific target region at precise times. Caged compounds are thought to be compatible with photopharmacology as uncaged ligands are released and function in a light irradiation-dependent manner. Here, we investigated whether a microscale light-emitting diode (MicroLED) probe is applicable for the photoconversion of caged-glutamate (caged-Glu) in vivo., Methods: A needle-shaped MicroLED probe was fabricated and inserted into the mouse hippocampal dentate gyrus (DG) with a cannula for drug injection and a recording electrode for measuring the local field potential (LFP). Artificial cerebrospinal fluid (ACSF) or caged-Glu was infused into the DG and illuminated with light from a MicroLED probe., Results: In the caged-Glu-injected DG, the LFP changed in the 10-20 Hz frequency ranges after light illumination, whereas there was no change in the ACSF control condition., Conclusion: The MicroLED probe is applicable for photopharmacological experiments to modulate LFP with caged-Glu in vivo., (© 2024 The Author(s). Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Neuropsychopharmacology.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Shannon, Levine, Dirickson, Shen, Cotter, Rajjoub, Fitzgerald, Pardo-Manuel de Villena, Kokiko-Cochran and Gu.)

After more than 30 years of extensive investigation, impressive progress has been made in identifying the neural correlates of consciousness (NCC). However, the functional role of spatiotemporally distinct consciousness-related neural activity in conscious perception is debated. An influential framework proposed that consciousness-related neural activities could be dissociated into two distinct processes: phenomenal and access consciousness. However, though hotly debated, its authenticity has not been examined in a single paradigm with more informative intracranial recordings. In the present study, we employed a visual awareness task and recorded the local field potential (LFP) of patients with electrodes implanted in cortical and subcortical regions. Overall, we found that the latency of visual awareness-related activity exhibited a bimodal distribution, and the recording sites with short and long latencies were largely separated in location, except in the lateral prefrontal cortex (lPFC). The mixture of short and long latencies in the lPFC indicates that it plays a critical role in linking phenomenal and access consciousness. However, the division between the two is not as simple as the central sulcus, as proposed previously. Moreover, in 4 patients with electrodes implanted in the bilateral prefrontal cortex, early awareness-related activity was confined to the contralateral side, while late awareness-related activity appeared on both sides. Finally, Granger causality analysis showed that awareness-related information flowed from the early sites to the late sites. These results provide the first LFP evidence of neural correlates of phenomenal and access consciousness, which sheds light on the spatiotemporal dynamics of NCC in the human brain., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

We accurately reconstruct the Local Field Potential time series obtained from anesthetized and awake rats, both before and during CO 2 euthanasia. We apply the Eigensystem Realization Algorithm to identify an underlying linear dynamical system capable of generating the observed data. Time series exhibiting more intricate dynamics typically lead to systems of higher dimensions, offering a means to assess the complexity of the brain throughout various phases of the experiment. Our results indicate that anesthetized brains possess complexity levels similar to awake brains before CO 2 administration. This resemblance undergoes significant changes following euthanization, as signals from the awake brain display a more resilient complexity profile, implying a state of heightened neuronal activity or a last fight response during the euthanasia process. In contrast, anesthetized brains seem to enter a more subdued state early on. Our data-driven techniques can likely be applied to a broader range of electrophysiological recording modalities., (© 2024. The Author(s).)

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Sensorimotor beta oscillations are increased in Parkinson's disease (PD) due to the alteration of dopaminergic transmission. This electrophysiological read-out is reported both in patients and in animal models such as the 6-OHDA rat model obtained with unilateral nigral injection of 6-hydroxydopamine (6-OHDA). Current treatments, based on dopaminergic replacement, transiently normalize this pathological beta activity and improve patients' quality of life., Objectives: We wanted to assess in vivo whether the abnormal beta oscillations can be correlated with impaired striatal or cortical excitability of the sensorimotor system and modulated by the pharmacological manipulation of the dopaminergic system., Methods: In the unilateral 6-OHDA rat model and control animals, we used intra-striatal and intra-cortical single-pulse electrical stimulation (SPES) and concurrent local field potentials (LFP) recordings. In the two groups, we quantified basal cortico-striatal excitability from time-resolved spectral analyses of LFP evoked responses induced remotely by intracerebral stimulations. The temporal dependance of cortico-striatal excitability to dopaminergic transmission was further tested using electrophysiological recordings combined with levodopa injection., Results: LFP evoked responses after striatal stimulation showed a transient reduction of power in a large time-frequency domain in the 6-OHDA group compared to the sham group. This result was specific to the striatum, as no significant difference was observed in cortical LFP evoked responses between the two groups. This impaired striatal excitability in the 6-OHDA group was observed in the striatum at least during the first 3 months after the initial lesion. In addition, the striatum responses to SPES during a levodopa challenge showed a transient potentiation of the decrease of responsiveness in frequencies below 40 Hz., Conclusion: The spectral properties of striatal responses to SPES show high sensitivity to dopaminergic transmission in the unilateral 6-OHDA rat model. We thus propose that this approach could be used in preclinical models as a time-resolved biomarker of impaired dopaminergic transmission capable of monitoring progressive neurodegeneration and/or challenges to drug intake., Competing Interests: Declaration of Competing Interest EG, JV, CH, YR, CR and VD are employees of SynapCell. There is no other potential conflict of interest to be disclosed., (Copyright © 2023. Published by Elsevier Inc.)

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Perrenoud and Cardin.)

Background: Suppression of pathologically altered activity in the beta-band has previously been suggested as a biomarker for feedback-based neurostimulation in subthalamic deep brain stimulation (STN-DBS) for Parkinson's Disease (PD)., Objective: To assess the utility of beta-band suppression as a tool for contact selection in STN-DBS for PD., Methods: A sample of seven PD patients (13 hemispheres) with newly implanted directional DBS leads of the STN were recorded during a standardized monopolar contact review (MPR). Recordings were received from contact pairs adjacent to the stimulation contact. The degree of beta-band suppression for each investigated contact was then correlated to the respective clinical results. Additionally, we have implemented a cumulative ROC analysis, to test the predictive value of beta-band suppression on the clinical efficacy of the respective contacts., Results: Stimulation ramping led to frequency-specific changes in the beta-band, while lower frequencies remained unaffected. Most importantly, our results showed that the degree of low beta-band suppression from baseline activity (stimulation off) served as a predictor for clinical efficacy of the respective stimulation contact. In contrast suppression of high beta-band activity yielded no predictive power., Conclusion: The degree of low beta-band suppression can serve as a time-saving, objective tool for contact selection in STN-DBS., Competing Interests: Declaration of competing interest J.N.S. has received funding for an investigator-initiated trial (IIT; Reference number: ERP-2021-12740) and received speaker honoraria from Medtronic GmbH. T.A.D. received speaker honoraria from Medtronic GmbH. P.A. has received honoraria for lecturing fees and educational activities from Medtronic GmbH. V.V.V. received support für contributions to congresses from Boston Scientific and Medtronic GmbH. The authors declare that there are no additional disclosures to report., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Pain is an unpleasant sensory and emotional experience. One of the most critical regions of the brain for pain processing is the anterior cingulate cortex (ACC). Several studies have examined the role of this region in thermal nociceptive pain. However, studies on mechanical nociceptive pain have been very limited to date. Although several studies have investigated pain, the interactions between the two hemispheres are still not clear. This study aimed to investigate nociceptive mechanical pain in the ACC bilaterally., Methods: Local field potential (LFP) signals were recorded from seven male Wistar rats' ACC regions of both hemispheres. Mechanical stimulations with two intensities, high-intensity noxious (HN) and non-noxious (NN) were applied to the left hind paw. At the same time, the LFP signals were recorded bilaterally from awake and freely moving rats. The recorded signals were analyzed from different perspectives, including spectral analysis, intensity classification, evoked potential (EP) analysis, and synchrony and similarity of two hemispheres., Results: By using spectro-temporal features and support vector machine (SVM) classifier, HN vs. no-stimulation (NS), NN vs. NS, and HN vs. NN were classified with accuracies of 89.6, 71.1, and 84.7%, respectively. Analyses of the signals from the two hemispheres showed that the EPs in the two hemispheres were very similar and occurred simultaneously; however, the correlation and phase locking value (PLV) between the two hemispheres changed significantly after HN stimulation. These variations persisted for up to 4 s after the stimulation. In contrast, variations in the PLV and correlation for NN stimulation were not significant., Conclusions: This study showed that the ACC area was able to distinguish the intensity of mechanical stimulation based on the power activities of neural responses. In addition, our results suggest that the ACC region is activated bilaterally due to nociceptive mechanical pain. Additionally, stimulations above the pain threshold (HN) significantly affect the synchronicity and correlation between the two hemispheres compared to non-noxious stimuli., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Aminitabar, Mirmoosavi, Ghodrati and Shalchyan.)

Neural dynamics are altered in the primary visual cortex (V1) during critical period monocular deprivation (MD). Synchronization of neural oscillations is pertinent to physiological functioning of the brain. Previous studies have reported chronic disruption of V1 functional properties such as ocular dominance, spatial acuity, and binocular matching after long-term monocular deprivation (LTMD). However, the possible neuromodulation and neural synchrony has been less explored. Here, we investigated the difference between juvenile and adult experience-dependent plasticity in mice from intracellular calcium signals with fluorescent indicators. We also studied alterations in local field potentials power bands and phase-amplitude coupling (PAC) of specific brain oscillations. Our results showed that LTMD in juveniles causes higher neuromodulatory changes as seen by high-intensity fluorescent signals from the non-deprived eye (NDE). Meanwhile, adult mice showed a greater response from the deprived eye (DE). LTMD in juvenile mice triggered alterations in the power of delta, theta, and gamma oscillations, followed by enhancement of delta-gamma PAC in the NDE. However, LTMD in adult mice caused alterations in the power of delta oscillations and enhancement of delta-gamma PAC in the DE. These markers are intrinsic to cortical neuronal processing during LTMD and apply to a wide range of nested oscillatory markers., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Intra- and perioperatively recorded local field potential (LFP) activity of the nucleus subthalamicus (STN) has been suggested to guide contact selection in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD). Despite the invention of sensing capacities in chronically implanted devices, a comprehensible algorithm that enables contact selection using such recordings is still lacking. We evaluated a fully automated algorithm that uses the weighted average of bipolar recordings to determine effective monopolar contacts based on elevated activity in the beta band. LFPs from 14 hemispheres in seven PD patients with newly implanted directional DBS leads of the STN were recorded. First, the algorithm determined the stimulation level with the highest beta activity. Based on the prior determined level, the directional contact with the highest beta activity was chosen in the second step. The mean clinical efficacy of the contacts chosen using the algorithm did not statistically differ from the mean clinical efficacy of standard contact selection as performed in clinical routine. All recording sites were projected into MNI standard space to investigate the feasibility of the algorithm with respect to the anatomical boundaries of the STN. We conclude that the proposed algorithm is a first step towards LFP-based contact selection in STN-DBS for PD using chronically implanted devices.

The use of mean-field models to describe the activity of large neuronal populations has become a very powerful tool for large-scale or whole brain simulations. However, the calculation of brain signals from mean-field models, such as the electric and magnetic fields, is still under development. Thus, the emergence of new methods for an accurate and efficient calculation of such brain signals is currently of great relevance. In this paper we propose a novel method to calculate the local field potentials (LFP) and magnetic fields from mean-field models. The calculation of LFP is done via a kernel method based on unitary LFP's (the LFP generated by a single axon) that was recently introduced for spiking-networks simulations and that we adapt here for mean-field models. The calculation of the magnetic field is based on current-dipole and volume-conductor models, where the secondary currents (due to the conducting extracellular medium) are estimated using the LFP calculated via the kernel method and the effects of medium-inhomogeneities are incorporated. We provide an example of the application of our method for the calculation of LFP and MEG under slow-waves of neuronal activity generated by a mean-field model of a network of Adaptive-Exponential Integrate-and-Fire (AdEx) neurons. We validate our method via comparison with results obtained from the corresponding spiking neuronal networks. Finally we provide an example of our method for whole brain simulations performed with The Virtual Brain (TVB), a recently developed tool for large scale simulations of the brain. Our method provides an efficient way of calculating electric and magnetic fields from mean-field models. This method exhibits a great potential for its application in large-scale or whole-brain simulations, where calculations via detailed biological models are not feasible., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tesler, Tort-Colet, Depannemaecker, Carlu and Destexhe.)

Background and Objective: Local Field Potentials (LFPs) recorded from the primary motor cortex (M1) have been shown to be very informative for decoding movement parameters, and these signals can be used to decode forelimb kinematic and kinetic parameters accurately. Although locomotion is one of the most basic and important motor abilities of humans and animals, the potential of LFPs in decoding abstract hindlimb locomotor parameters has not been investigated. This study investigates the feasibility of decoding speed and slope of locomotion, as two important abstract parameters of walking, using the LFP signals., Methods: Rats were trained to walk smoothly on a treadmill with different speeds and slopes. The brain signals were recorded using the microwire arrays chronically implanted in the hindlimb area of M1 while rats walked on the treadmill. LFP channels were spatially filtered using optimal common spatial patterns to increase the discriminability of speeds and slopes of locomotion. Logarithmic wavelet band powers were extracted as basic features, and the best features were selected using the statistical dependency criterion before classification., Results: Using 5 s LFP trials, the average classification accuracies of four different speeds and seven different slopes reached 90.8% and 86.82%, respectively. The high-frequency LFP band (250-500 Hz) was the most informative band about these parameters and contributed more than other frequency bands in the final decoder model., Conclusions: Our results show that the LFP signals in M1 accurately decode locomotion speed and slope, which can be considered as abstract walking parameters needed for designing long-term brain-computer interfaces for hindlimb locomotion control., Competing Interests: Declaration of Competing Interest There is no conflict of interests to be declared., (Copyright © 2022. Published by Elsevier B.V.)

Neural synchronization has been engaged in several brain mechanisms. Previous studies have shown that the interaction between the time of spiking activity and phase of local field potentials (LFPs) plays a key role in many cognitive functions. However, the potential role of this spike-LFP phase coupling (SPC) in neural coding is not fully understood. Here, we sought to investigate the role of this SPC for encoding the sensory properties of visual stimuli. To this end, we measured SPC strength in the preferred and anti-preferred motion directions of stimulus presented inside the receptive field of middle temporal (MT) neurons. We found a selective response in terms of SPC strength for different directions of motion. Remarkably, this selective function is inverted with respect to the spiking activity. In other words, the least SPC occurs for the preferred direction (based on the spike rate), and vice versa; the strongest SPC is induced in the anti-preferred direction. Altogether, these findings imply that the neural system may use spike-LFP phase coupling in the primate visual cortex to encode sensory information., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Parkinson's disease (PD) is characterized by aberrant discharge patterns and exaggerated oscillatory activity within basal ganglia-thalamocortical circuits. We have previously observed substantial alterations in spike and local field potential (LFP) activities recorded in the thalamic parafascicular nucleus (PF) and motor cortex (M1), respectively, of hemiparkinsonian rats during rest or catching movements. This study explored whether the mutual effects of the PF and M1 depended on the amplitude and phase relationship in their identified neuron spikes or group rhythmic activities. Microwire electrode arrays were paired and implanted in the PF and M1 of rats with unilateral dopaminergic cell lesions. The results showed that the identified PF neurons exhibited aberrant cell type-selective firing rates and preferential and excessive phase-locked firing to cortical LFP oscillations mainly at 12-35 Hz (beta frequencies), consistent with the observation of identified M1 neurons with ongoing PF LFP oscillations. Experimental evidence also showed a decrease in phase-locking at 0.7-12 Hz and 35-70 Hz in the PF and M1 circuits in the hemiparkinsonian rats. Furthermore, anatomical evidence was provided for the existence of afferent and efferent bidirectional reciprocal connectivity pathways between the PF and M1 using an anterograde and retrograde neuroanatomical tracing virus. Collectively, our results suggested that multiple alterations may be present in regional anatomical and functional modes with which the PF and M1 interact, and that parkinsonism-associated changes in PF integrate M1 activity in a manner that varies with frequency, behavioral state, and integrity of the dopaminergic system., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Zhang, He, Chen, Chen, Wang, Sun, Sun, Li, Zhu, Fang, Shi, Yao, Sun and Wang.)

Adverse effects of drugs on the human nervous system are rarely possible to anticipate based on preclinical neurotoxicity data, thus propagating the centuries long single most important obstacle to drug discovery and development for disorders of the nervous system. An emerging body of evidence indicates that in vivo electrophysiology using chronically implanted high-density electrodes (ciHDE) in freely moving animals is a rigorous method with enhanced potential for use in translational research. In particular, the structure and function of the hippocampal trisynaptic circuit (HTC) is conserved from rodents to primates, including Homo sapiens , suggesting that the effects of therapeutic agents and other potential neurologically active agents, whether beneficial or adverse, are likely to translate across species when interrogated using a conserved neural circuitry platform. This review explores science advances in the rapidly moving field of in vivo ciHDE in animal models of learning and memory. For this reason we focus on the HTC, where substantial research has investigated neural circuitry level responses and specific behaviors that reflect memory permitting a test of the ground truth validity of the findings. Examples of changes in neural network activity induced by endogenous neurotoxicants associated with neurodegenerative diseases, as well as exogenous therapeutics, drugs, and neurotoxicants are presented. Several illustrative examples of relevant findings that involve longer range neural circuitry outside of the HTC are discussed. Lastly, the limitations of in vivo ciHDE as applied to preclinical neurotoxicology are discussed with a view toward leveraging circuitry level actions to enhance our ability to project the specificity of in vitro target engagement with the desired psychopharmacological or neurological outcome. At the same time, the goal of reducing or eliminating significant neurotoxic adverse events in human is the desired endpoint. We believe that this approach will lead to enhanced discovery of high value neuroactive therapeutics that target neural circuitry domains as their primary mechanism of action, thus enhancing their ultimate contribution toward discovery of precision therapeutics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ratner and Farb.)

Pain can be ignited by noxious chemical (e.g., acid), mechanical (e.g., pressure), and thermal (e.g., heat) stimuli and generated by the activation of sensory neurons and their axonal terminals called nociceptors in the periphery. Nociceptive information transmitted from the periphery is projected to the central nervous system (thalamus, somatosensory cortex, insular, anterior cingulate cortex, amygdala, periaqueductal grey, prefrontal cortex, etc.) to generate a unified experience of pain. Local field potential (LFP) recording is one of the neurophysiological tools to investigate the combined neuronal activity, ranging from several hundred micrometers to a few millimeters (radius), located around the embedded electrode. The advantage of recording LFP is that it provides stable simultaneous activities in various brain regions in response to external stimuli. In this study, differential LFP activities from the contralateral anterior cingulate cortex (ACC), ventral tegmental area (VTA), and bilateral amygdala in response to peripheral noxious formalin injection were recorded in anesthetized male rats. The results indicated increased power of delta, theta, alpha, beta, and gamma bands in the ACC and amygdala but no change of gamma-band in the right amygdala. Within the VTA, intensities of the delta, theta, and beta bands were only enhanced significantly after formalin injection. It was found that the connectivity (i.t. the coherence) among these brain regions reduced significantly under the formalin-induced nociception, which suggests a significant interruption within the brain. With further study, it will sort out the key combination of structures that will serve as the signature for pain state., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Freezing of gait (FOG) is a particularly debilitating symptom of Parkinson's disease (PD) and is often refractory to treatment. A striking feature of FOG is that external sensory cues can be used to overcome freezing and improve gait. Local field potentials (LFPs) recorded from the subthalamic nucleus (STN) and globus pallidus (GP) show that beta-band power modulates with gait phase. In the STN, beta-band oscillations are modulated by external cues, but it is unknown if this relationship holds in the globus pallidus (GP). Here we report LFP data recorded from the left GP, using a Medtronic PC + S device, in a 68-year-old man with PD and FOG during treadmill walking. A "stepping stone" task was used during which stepping was cued using visual targets of constant color or targets that unpredictably changed color, requiring a step length adjustment. Gait performance was quantified using measures of treadmill ground reaction forces and center of pressure and body kinematics from video monitoring. Beta-band power (12-30 Hz) and number of freezing episodes were measured. Cues which unpredictably changed color improved FOG more than conventional cues and were associated with greater modulation of beta-band power in phase with gait. This preliminary finding suggests that cueing-induced improvement of FOG may relate to beta-band modulation., Competing Interests: Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research., (© 2021. The Author(s).)

Deep brain stimulation (DBS) is used for the treatment of movement disorders, including Parkinson's disease, dystonia, and essential tremor, and has shown clinical benefits in other brain disorders. A natural path for the improvement of this technique is to continuously observe the stimulation effects on patient symptoms and neurophysiological markers. This requires the evolution of conventional deep brain stimulators to bidirectional interfaces, able to record, process, store, and wirelessly communicate neural signals in a robust and reliable fashion. Here, we present the architecture, design, and first use of an implantable stimulation and sensing interface (AlphaDBS R System) characterized by artifact-free recording and distributed data management protocols. Its application in three patients with Parkinson's disease (clinical trial n. NCT04681534) is shown as a proof of functioning of a clinically viable implanted brain-computer interface (BCI) for adaptive DBS. Reliable artifact free-recordings, and chronic long-term data and neural signal management are in place., Competing Interests: MA and MC were employed by Newronika and held stock options. AB is a consultant for Newronika. AP, SM, and PR are founders and shareholders of Newronika. The study was funded by Newronika SpA. The funder had the following involvement with the study: study design of NCT04681534, signal collection and analysis (clinical data collection is performed by a CRO), the writing of this article, and the decision to submit it for publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Arlotti, Colombo, Bonfanti, Mandat, Lanotte, Pirola, Borellini, Rampini, Eleopra, Rinaldo, Romito, Janssen, Priori and Marceglia.)

Sleep disturbances, specifically decreases in total sleep time and sleep efficiency as well as increased sleep onset latency and wakefulness after sleep onset, are highly prevalent in patients with Parkinson's disease (PD). Impairment of sleep significantly and adversely impacts several comorbidities in this patient population, including cognition, mood, and quality of life. Sleep disturbances and other non-motor symptoms of PD have come to the fore as the effectiveness of advanced therapies such as deep brain stimulation (DBS) optimally manage the motor symptoms. Although some studies have suggested that DBS provides benefit for sleep disturbances in PD, the mechanisms by which this might occur, as well as the optimal stimulation parameters for treating sleep dysfunction, remain unknown. In patients treated with DBS, electrophysiologic recording from the stimulating electrode, in the form of local field potentials (LFPs), has led to the identification of several findings associated with both motor and non-motor symptoms including sleep. For example, beta frequency (13-30 Hz) oscillations are associated with worsened bradykinesia while awake and decrease during non-rapid eye movement sleep. LFP investigation of sleep has largely focused on the subthalamic nucleus (STN), though corresponding oscillatory activity has been found in the globus pallidus internus (GPi) and thalamus as well. LFPs are increasingly being recognized as a potential biomarker for sleep states in PD, which may allow for closed-loop optimization of DBS parameters to treat sleep disturbances in this population. In this review, we discuss the relationship between LFP oscillations in STN and the sleep architecture of PD patients, current trends in utilizing DBS to treat sleep disturbance, and future directions for research. In particular, we highlight the capability of novel technologies to capture and record LFP data in vivo , while patients continue therapeutic stimulation for motor symptoms. These technological advances may soon allow for real-time adaptive stimulation to treat sleep disturbances., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Baumgartner, Kushida, Summers, Kern, Abosch and Thompson.)

The hippocampus-prefrontal cortex (HPC-PFC) pathway plays a fundamental role in executive and emotional functions. Neurophysiological studies have begun to unveil the dynamics of HPC-PFC interaction in both immediate demands and long-term adaptations. Disruptions in HPC-PFC functional connectivity can contribute to neuropsychiatric symptoms observed in mental illnesses and neurological conditions, such as schizophrenia, depression, anxiety disorders, and Alzheimer's disease. Given the role in functional and dysfunctional physiology, it is crucial to understand the mechanisms that modulate the dynamics of HPC-PFC communication. Two of the main mechanisms that regulate HPC-PFC interactions are synaptic plasticity and modulatory neurotransmission. Synaptic plasticity can be investigated inducing long-term potentiation or long-term depression, while spontaneous functional connectivity can be inferred by statistical dependencies between the local field potentials of both regions. In turn, several neurotransmitters, such as acetylcholine, dopamine, serotonin, noradrenaline, and endocannabinoids, can regulate the fine-tuning of HPC-PFC connectivity. Despite experimental evidence, the effects of neuromodulation on HPC-PFC neuronal dynamics from cellular to behavioral levels are not fully understood. The current literature lacks a review that focuses on the main neurotransmitter interactions with HPC-PFC activity. Here we reviewed studies showing the effects of the main neurotransmitter systems in long- and short-term HPC-PFC synaptic plasticity. We also looked for the neuromodulatory effects on HPC-PFC oscillatory coordination. Finally, we review the implications of HPC-PFC disruption in synaptic plasticity and functional connectivity on cognition and neuropsychiatric disorders. The comprehensive overview of these impairments could help better understand the role of neuromodulation in HPC-PFC communication and generate insights into the etiology and physiopathology of clinical conditions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ruggiero, Rossignoli, Marques, de Sousa, Romcy-Pereira, Lopes-Aguiar and Leite.)

Introduction: Up to 27% of individuals undergoing subthalamic nucleus deep brain stimulation (STN-DBS) have a genetic form of Parkinson's disease (PD). G lucocerebrosidase ( GBA ) mutation carriers, compared to sporadic PD, present with a more aggressive disease, less asymmetry, and fare worse on cognitive outcomes with STN-DBS. Evaluating STN intra-operative local field potentials provide the opportunity to assess and compare symmetry between GBA and non- GBA mutation carriers with PD; thus, providing insight into genotype and STN physiology, and eligibility for and programming of STN-DBS. The purpose of this pilot study was to test differences in left and right STN resting state beta power in non- GBA and GBA mutation carriers with PD. Materials and Methods: STN (left and right) resting state local field potentials were recorded intraoperatively from 4 GBA and 5 non- GBA patients with PD while off medication. Peak beta power expressed as a ratio to total beta power (peak beta ratio) was compared between STN hemispheres and groups while co-varying for age, age of disease onset, and disease severity. Results: Peak beta ratio was significantly different between the left and the right STN for the GBA group ( p < 0.01) but not the non- GBA group ( p = 0.56) after co-varying for age, age of disease onset, and disease severity. Discussion: Peak beta ratio in GBA mutation carriers was more asymmetric compared with non-mutation carriers and this corresponded with the degree of clinical asymmetry as measured by rating scales. This finding suggests that GBA mutation carriers have a physiologic signature that is distinct from that found in sporadic PD., Competing Interests: FD and MM received grant support from NIH. JS receives consulting fees from Medtronic. SS received grant support from NIH, Medtronic, Abbott, and Boston Scientific. LV has research support from Michael J. Fox Foundation, Medtronic, Inc., US WorldMeds LLC, Pfizer Inc, Boston Scientific, Avanir Pharmaceuticals, Inc., and Adamas Pharmaceuticals, Inc.; is on the scientific advisory board of Britannia Pharmaceuticals Ltd.; and consults for Medtronic, Inc., and Boston Scientific. DC received grant support from NIH and Michael J. Fox and receives lecture and reviewer fees from NIH. GP received grant support from NIH and the Parkinson's Disease Foundation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 David, Munoz, Shils, Pauciulo, Hale, Nichols, Afshari, Sani, Verhagen Metman, Corcos and Pal.)

Since its first experimental signatures, the so called "critical brain hypothesis" has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both multi-unit activities and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both multi-unit activities and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to a transient across-layers synchronization mode that appears to dominate the cortical representation of the single sensory input., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Mariani, Nicoletti, Bisio, Maschietto, Oboe, Leparulo, Suweis and Vassanelli.)

Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard "rate models" of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This "paradox of stereotaxic surgery" was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Magnusson and Leventhal.)

Background: Adaptive Deep Brain Stimulation (aDBS) is now considered as a new feasible and effective paradigm to deliver DBS to patients with Parkinson's disease (PD) in such a way that not only stimulation is personalized and finely tuned to the instantaneous patient's state, but also motor improvement is obtained with a lower amount of energy transferred to the tissue. Amplitude-controlled aDBS was shown to significantly decrease the amplitude-driven total electrical energy delivered to the tissue (aTEED), an objective measure of the amount of energy transferred by DBS amplitude to the patient's brain. However, there is no direct evidence of a relationship between aTEED and the occurrence of DBS-related adverse events in humans. Objective: In this work, we investigated the correlation of aTEED with the occurrence of levodopa-induced dyskinesias pooling all the data available from our previous experiments using aDBS and cDBS. Methods: We retrospectively analyzed data coming from 19 patients with PD undergoing surgery for STN-DBS electrode positioning and participating to experiments involving cDBS and aDBS delivery. Patients were all studied some days after the surgery (acute setting). The aTEED and dyskinesia assessments (Rush Dyskinesia Rating Scale, RDRS) considered in the Med ON-Stim ON condition. Results: We confirmed both that aTEED values and RDRS were significantly lower in the aDBS than in cDBS sessions (aTEED mean value, cDBS: 0.0278 ± 0.0011 j, vs. aDBS: 0.0071 ± 0.0003 j, p < 0.0001 Wilcoxon's rank sum; normalized RDRS mean score, cDBS: 0.66 ± 0.017 vs. aDBS: 0.45 ± 0.01, p = 0.025, Wilcoxon's rank sum test). In addition, we found a direct significant correlation between aTEED and RDRS (ρ = 0.44, p = 0.0032, Spearman's correlation). Conclusions: Our results provide a first piece of evidence that aTEED is correlated to the amount of levodopa-induced dyskinesias in patients with PD undergoing STN-DBS, thus supporting the role of aDBS as feasible and safe alternative to cDBS., Competing Interests: SM, AP, SB, FC, PR, and ML are founder and shareholder of Newronika SpA, a spin-off company of the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico and of the University of Milan. MA was employed by the company Newronika SpA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Prenassi, Arlotti, Borellini, Bocci, Cogiamanian, Locatelli, Rampini, Barbieri, Priori and Marceglia.)

Background: Cortico-cortical evoked potentials (CCEP) are becoming popular to infer brain connectivity and cortical excitability in implanted refractory epilepsy patients. Our goal was to transfer this methodology to the freely moving rodent., New Method: CCEP were recorded on freely moving Sprague-Dawley rats, from cortical and subcortical areas using depth electrodes. Electrical stimulation was applied using 1 ms biphasic current pulse, cathodic first, at a frequency of 0.5 Hz, with intensities ranging from 0.2 to 0.8 mA. Data were then processed in a similar fashion to human clinical studies, which included epoch selection, artefact correction and smart averaging., Results: For a large range of tested intensities, we recorded CCEPs with very good signal to noise ratio and reproducibility between animals, without any behavioral modification. The CCEP were composed of different components according to recorded and stimulated sites, similarly to human recordings., Comparison With Existing Methods: We minimally adapted a clinically-motivated methodology to a freely moving rodent model to achieve high translational relevance of future preclinical studies., Conclusions: Our results indicate that the CCEP methodology can be applied to freely moving rodents and transferred to preclinical research. This will be of interest to address various neuroscientific questions, in physiological and pathological conditions., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective. The brain operates via generation, transmission and integration of neuronal signals and most neurological disorders are related to perturbation of these processes. Neurostimulation by focused ultrasound (FUS) is a promising technology with potential to rival other clinically used techniques for the investigation of brain function and treatment of numerous neurological diseases. The purpose of this study was to characterize spatial and temporal aspects of causal electrophysiological signals directly stimulated by short, single pulses of FUS on ex vivo mouse hippocampal brain slices. Approach. Microelectrode arrays (MEAs) are used to study the spatio-temporal dynamics of extracellular neuronal activities both at the single neuron and neural networks scales. Hence, MEAs provide an excellent platform for characterization of electrical activity generated, modulated and transmitted in response to FUS exposure. In this study, a novel mixed FUS/MEA platform was designed for the spatio-temporal description of the causal responses generated by single 1.78 MHz FUS pulses in ex vivo mouse hippocampal brain slices. Main results. Our results show that FUS pulses can generate local field potentials (LFPs), sustained by synchronized neuronal post-synaptic potentials, and reproducing network activities. LFPs induced by FUS stimulation were found to be repeatable to consecutive FUS pulses though exhibiting a wide range of amplitudes (50-600 μ V), durations (20-200 ms), and response delays (10-60 ms). Moreover, LFPs were spread across the hippocampal slice following single FUS pulses thus demonstrating that FUS may be capable of stimulating different neural structures within the hippocampus. Significance. Current knowledge on neurostimulation by ultrasound describes neuronal activity generated by trains of repetitive ultrasound pulses. This novel study details the causal neural responses produced by single-pulse FUS neurostimulation while illustrating the distribution and propagation properties of this neural activity along major neural pathways of the hippocampus., (© 2021 IOP Publishing Ltd.)

Background: Brain-computer interfaces (BCIs) seek to establish a direct connection from brain to computer, to use in applications such as motor prosthesis control, control of a cursor on the monitor, and so on. Hence, the accuracy of movement decoding from brain signals in BCIs is crucial. The Kalman filter (KF) is often used in BCI systems to decode neural activity and estimate kinetic and kinematic parameters. To use the KF, the state transition matrix, the observation matrix and the covariance matrices of the process and measurement noises must be known in advance, however, in many applications these matrices are not known. Typically, to estimate these parameters, the ordinary least squares method and the sample covariance matrix estimator are used. Our purpose is to enhance the decoding performance of the KF in BCI systems by improving the estimation of the mentioned parameters., New Method: Here, we propose the Regularized Kalman Filter (RKF) which implements two fundamental features: 1) Regularizing the regression estimate of the state equation to improve the estimation of the state transition matrix, and 2) Use of shrinkage method to improve the estimation of the unknown measurement noise covariance matrix. We validated the performance of the proposed method using two datasets of local field potentials obtained from motor cortex of a monkey (Estimation of kinematic parameters during hand movement) and three rats (Estimation of the amount of force applied by hand as a kinetic parameter)., Results: The results demonstrate that the proposed method outperforms the conventional KF, the KF with feature selection, the Partial least squares, and the Ridge regression approaches., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Subthalamic local field potentials in the beta band are considered as potential biomarkers for closed-loop deep brain stimulation. To investigate the subthalamic beta band peak amplitudes in a Parkinson's disease patient over an extended period of time by using a novel and commercially available neurostimulator with permanent sensing capability. We recorded local field potentials of the subthalamic nucleus using the Medtronic Percept™ implantable neurostimulator at rest and during physical activity (gait) with and in response to deep brain stimulation. We found a double-peaked beta activity on both sides. Increasing stimulation and physical activity resulted in a decreased beta band amplitude, but was accompanied by the appearance of a second, and previously unrecognized peak at 13 Hz in the right hemisphere. Our results will support the investigation of distinct different peaks in the beta band and their relevance and usefulness as closed-loop biomarkers.

In recent years, aberrant neural oscillations in various cortical areas have emerged as a common physiological hallmark across mouse models of amyloid pathology and patients with Alzheimer's disease. However, much less is known about the underlying effect of amyloid pathology on single cell activity. Here, we used high-density silicon probe recordings from frontal cortex area of 9-month-old APP/PS1 mice to show that local field potential power in the theta and beta band is increased in transgenic animals, whereas single-cell firing rates, specifically of putative pyramidal cells, are significantly reduced. At the same time, these sparsely firing pyramidal cells phase-lock their spiking activity more strongly to the ongoing theta and beta rhythms. Furthermore, we demonstrated that the antiepileptic drug, levetiracetam, counteracts these effects by increasing pyramidal cell firing rates in APP/PS1 mice and uncoupling pyramidal cells and interneurons. Overall, our results highlight reduced firing rates of cortical pyramidal cells as a pathophysiological phenotype in APP/PS1 mice and indicate a potentially beneficial effect of acute levetiracetam treatment., (Copyright © 2020 Elsevier Inc. All rights reserved.)

We present a model-based method for inferring full-brain neural activity at millimeter-scale spatial resolutions and millisecond-scale temporal resolutions using standard human intracranial recordings. Our approach makes the simplifying assumptions that different people's brains exhibit similar correlational structure, and that activity and correlation patterns vary smoothly over space. One can then ask, for an arbitrary individual's brain: given recordings from a limited set of locations in that individual's brain, along with the observed spatial correlations learned from other people's recordings, how much can be inferred about ongoing activity at other locations throughout that individual's brain? We show that our approach generalizes across people and tasks, thereby providing a person- and task-general means of inferring high spatiotemporal resolution full-brain neural dynamics from standard low-density intracranial recordings., (© The Author(s) 2020. Published by Oxford University Press.)

Research has been focused on the effects of radiofrequency electromagnetic radiation (RF-EMR) emitted from a mobile phone on general health, especially the nervous system. The purpose of this study was to investigate the impact of RF-EMR on the brain mechanism of rats by recording local field potentials (LFPs) signals during working memory (WM) task. Subjects were exposed to 900 MHz from a dipole antenna daily for three hours. Exposure was applied, first on a short term base (1 week) and then on a long term base (4 weeks). Behavioral parameters were measured weekly while rats performed T-maze tasks in two types of normal and delayed. LFPs signals were simultaneously recorded by implanted microelectrode arrays on the medial prefrontal cortex (mPFC) of rats. Results showed a significant increase (*p < 0.05) in the task completion time of exposed rats which vanished shortly after the end of short term RF-EMR exposure. Before exposure, during correctly performed delayed tasks, an increase (peak) in power changes of theta band (4-12 Hz) was observed. But during correctly performed normal tasks, an increase appeared only by applying RF-EMR exposure. The similarity in power changes pattern of theta band in both types of tasks was observed after long term exposure. Classification accuracy of LFPs in truly done normal and delayed tasks was compared in pre and post-exposure states. Initial classification accuracy was 84.2 % which decreased significantly (*P < 0.05) after exposure. These observations indicated that RF-EMR may cause unusual brain functioning which is temporary at least for short term exposure., Competing Interests: Declaration of Competing Interest The authors declare no competing financial interests and there are no personal relationships with other people or organizations that could have inappropriately influenced the work., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the challenge of misalignment between current sources and mesh nodes in a finite-element or resistor-network method volume conduction model needs to be further investigated. Therefore, using a previously published and validated multi-scale model of the hippocampus, the authors have formulated an algorithm for LFP estimation, and by extension, bidirectional communication between discretized and numerically solved volume conduction models and biologically detailed neural circuit models constructed in NEURON. Development of this algorithm required that we assess meshes of (i) unstructured tetrahedral and grid-based hexahedral geometries as well as (ii) differing approaches for managing the spatial misalignment of current sources and mesh nodes. The resulting algorithm is validated through the comparison of Admittance Method predicted evoked potentials with analytically estimated LFPs. Establishing this method is a critical step toward closed-loop integration of volume conductor and NEURON models that could lead to substantial improvement of the predictive power of multi-scale stimulation models of cortical tissue. These models may be used to deepen our understanding of hippocampal pathologies and the identification of efficacious electroceutical treatments., (Copyright © 2020 Bingham, Paknahad, Girard, Loizos, Bouteiller, Song, Lazzi and Berger.)

Objective: We focused on a rare gene mutation causing dystonia in two siblings who received globus pallidus internus deep brain stimulation (GPi-DBS). The aim was to characterize the relationship between neuronal activity patterns and clinical syndromes., Methods: Whole exome sequencing was applied to identify the TWNK (previous symbol C10orf2) mutation; Two siblings with TWNK mutation presented as generalized dystonia with rigidity and bradykinesia; four other sporadic generalized dystonia patients underwent GPi-DBS and local field potentials (LFPs) were recorded. Oscillatory activities were illustrated with power spectra and temporal dynamics measured by the Lempel-Ziv complexity (LZC)., Results: Normalized power spectra of GPi LFPs differed between patients with TWNK mutation and dystonia over the low beta bands. Patients with TWNK mutation had higher low beta power (15-27 Hz, unpaired t-test, corrected P < 0.0022) and lower LZC (15-27 Hz, unpaired t-test, P < 0.01) than other patients with generalized dystonia. On the other hand, the TWNK mutation patients showed decreased low frequency and beta oscillation in the GPi after DBS, as well as improved movement performance., Conclusion: The LFPs were different in TWNK mutation dystonia siblings than other patients with generalized dystonia, which indicate the abnormal LFPs were related to symptoms rather than specific disease. In addition, the inhibited effect on oscillations also provided a potential evidence for DBS treatment on rare movement disorders., Significance: This study could potentially aid in the future development of adaptive DBS via rare disease LFPs comparison., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning methods for more accurate detection of rest tremor in PD., Methods: We analyzed the local field potential (LFP) recordings from the subthalamic nucleus region in 12 patients with PD (16 recordings). To explore the optimal biomarkers and the best performing classifier, the performance of state-of-the-art machine learning (ML) algorithms and various features of the subthalamic LFPs were compared. We further used a Kalman filtering technique in feature domain to reduce the false positive rate., Results: The Hjorth complexity showed a higher correlation with tremor, compared to other features in our study. In addition, by optimal selection of a maximum of five features with a sequential feature selection method and using the gradient boosted decision trees as the classifier, the system could achieve an average F1 score of up to 88.7% and a detection lead of 0.52 s. The use of Kalman filtering in feature space significantly improved the specificity by 17.0% (p = 0.002), thereby potentially reducing the unnecessary power dissipation of the conventional DBS system., Conclusion: The use of relevant features combined with Kalman filtering and machine learning improves the accuracy of tremor detection during rest., Significance: The proposed method offers a potential solution for efficient on-demand stimulation for PD tremor., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Neural decoding allows us to study the brain functions by investigating the relationship between a stimulus and the corresponding response. Recently, the local field potential (LFP) has been targeted as a hallmark of brain activity for neural decoding. Despite several decoding methods, there is still a lack of a comprehensive framework to decode cognitive functions in an integrated structure. Here, we addressed this issue by developing a dictionary-based method to represent the LFP signals via a bag-of-words (BOW) approach. First, we defined a general dictionary consisting of various Gabor wavelets as the words which enabled us to represent LFPs in word domain. For each trial, the LFP signal was convolved with the dictionary words. The integral of the absolute value and the mean phase of the complex output were considered as histogram weights. In the next step, using cross-validation leave-one-out method, the trials were split into the training and test sets. The weights of each individual word were swapped across trials within a certain category of the training set while the sequential order was maintained. Finally, the test trial was classified using label voting in the k-nearest training trials. We conducted the proposed method on two independent LFP data sets, recorded from the rat primary auditory cortex (A1) and monkey middle temporal area in order to evaluate its efficiency. In addition to the chance level, the proposed method was compared with a standard BOW approach that has been extended recently for biomedical signals classification. Results show a high efficiency (~ 15% improvement in decoding accuracy) of the proposed method. Together, the aforementioned method provides a comprehensive framework for single-trial decoding from short-length electrophysiological signals.

The cholinergic efferent network from the medial septal nucleus to the hippocampus has an important role in learning and memory processes. This cholinergic projection can generate theta oscillations in the hippocampus to efficiently encode novel information. Hippocampal cholinergic neurostimulating peptide (HCNP) induces acetylcholine synthesis in medial septal nuclei. HCNP is processed from the N-terminal region of a 186 amino acid, 21 kD HCNP precursor protein called HCNP-pp (also known as Raf kinase inhibitory protein (RKIP) and phosphatidylethanolamine-binding protein 1 (PEBP1)). In this study, we generated HCNP-pp knockout (KO) mice and assessed their cholinergic septo-hippocampal projection, local field potentials in CA1, and behavioral phenotypes. No significant behavioral phenotype was observed in HCNP-pp KO mice. However, theta power in the CA1 of HCNP-pp KO mice was significantly reduced because of fewer cholineacetyltransferase-positive axons in the CA1 stratum oriens. These observations indicated disruption of cholinergic activity in the septo-hippocampal network. Our study demonstrates that HCNP may be a cholinergic regulator in the septo-hippocampal network., Competing Interests: The authors declare no conflict of interest.

Sensorimotor control studies have predominantly focused on how motor regions of the brain relay basic movement-related information such as position and velocity. However, motor control is often complex, involving the integration of sensory information, planning, visuomotor tracking, spatial mapping, retrieval and storage of memories, and may even be emotionally driven. This suggests that many more regions in the brain are involved beyond premotor and motor cortices. In this study, we exploited an experimental setup wherein activity from over 87 non-motor structures of the brain were recorded in eight human subjects executing a center-out motor task. The subjects were implanted with depth electrodes for clinical purposes. Using training data, we constructed subject-specific models that related spectral power of neural activity in six different frequency bands as well as a combined model containing the aggregation of multiple frequency bands to movement speed. We then tested the models by evaluating their ability to decode movement speed from neural activity in the test data set. The best models achieved a correlation of 0.38 ± 0.03 (mean ± standard deviation). Further, the decoded speeds matched the categorical representation of the test trials as correct or incorrect with an accuracy of 70 ± 2.75% across subjects. These models included features from regions such as the right hippocampus, left and right middle temporal gyrus, intraparietal sulcus, and left fusiform gyrus across multiple frequency bands. Perhaps more interestingly, we observed that the non-dominant hemisphere (ipsilateral to dominant hand) was most influential in decoding movement speed.

Stimulus repetition suppresses the neural activity in different sensory areas of the brain. This mechanism of so-called stimulus-specific adaptation (SSA) has been observed in both spiking activity and local field potential (LFP) responses. However, much remains to be known about the effect of SSA on the spike-LFP relation. In this study, we approached this issue by investigating the spike-phase coupling (SPC) in control and adapting paradigms. For the control paradigm, pure tones were presented in a random unbiased sequence. In the adapting paradigm, the same stimuli were presented in a random pattern but it was biased to an adapter stimulus. In fact, the adapter occupied 80% of the adapting sequence. During the tasks, LFP and multi-unit activity were recorded simultaneously from the primary auditory cortex of 15 anesthetized rats. To clarify the effect of adaptation on the relation between spike and LFP responses, the SPC of the adapter stimulus in these two paradigms was evaluated. Here, we employed phase locking value method for calculating the SPC. Our data show a strong coupling of spikes to LFP phase most prominently in beta band. This coupling was observed to decrease in the adapting condition compared to the control one. Importantly, we found that adaptation reduces spikes dominantly from the preferred phase of LFP in which spikes are more likely to be present there. As a result, the preferred phase of LFP may play a key role in coordinating neuronal spiking activity in neural adaptation mechanism. This finding is important for interpretation of the underlying neural mechanism of adaptation and also can be used in the context of the network and related connectivity models.

Increased oscillatory activities in the beta frequency band (13-30 Hz) in the subthalamic nucleus (STN), and in particular prolonged episodes of increased synchrony in this frequency band, have been associated with motor symptoms such as bradykinesia and rigidity in Parkinson's disease (PD). Numerous studies have investigated sensorimotor cortical beta oscillations either as a control signal for Brain Computer Interfaces (BCI) or as target signal for neurofeedback training (NFB). However, it still remains unknown whether patients with PD can gain control of the pathological oscillations recorded from a subcortical site - the STN - with neurofeedback training. We tried to address this question in the current study. Specifically, we designed a simple basketball game, in which the position of a basketball changes based on the occurrence of events of temporally increased beta power quantified in real-time. Participants practised in the game to control the position of the basketball, which requires modulation of the beta oscillations recorded from STN local field potentials (LFPs). Our results suggest that it is possible to use neurofeedback training for PD patients to downregulate pathological beta oscillations in STN LFPs, and that this can lead to a reduction of beta oscillations in the cortical-STN motor network.

Exploration of brain dynamics patterns has attracted increasing attention due to its fundamental significance in understanding the working mechanism of the brain. However, due to the lack of effective modeling methods, how the simultaneously recorded LFP can inform us about the brain dynamics remains a general challenge. In this paper, we propose a novel sparse coding based method to investigate brain dynamics of freely-behaving mice from the perspective of functional connectivity, using super-long local field potential (LFP) recordings from 13 distinct regions of the mouse brain. Compared with surrogate datasets, six and four reproducible common functional connectivities were discovered to represent the space of brain dynamics in the frequency bands of alpha and theta respectively. Modeled by a finite state machine, temporal transition framework of functional connectivities was inferred for each frequency band, and evident preference was discovered. Our results offer a novel perspective for analyzing neural recording data at such high temporal resolution and recording length, as common functional connectivities and their transition framework discovered in this work reveal the nature of the brain dynamics in freely behaving mice.

Background: Dystonia and Huntington's disease (HD) are both hyperkinetic movement disorders but exhibit distinct clinical characteristics. Aberrant output from the globus pallidus internus (GPi) is involved in the pathophysiology of both HD and dystonia, and deep brain stimulation (DBS) of the GPi shows good clinical efficacy in both disorders. The electrode externalized period provides an opportunity to record local field potentials (LFPs) from the GPi to examine if activity patterns differ between hyperkinetic disorders and are associated with specific clinical characteristics. Methods: LFPs were recorded from 7 chorea-dominant HD and nine cervical dystonia patients. Differences in oscillatory activities were compared by power spectrum and Lempel-Ziv complexity (LZC). The discrepancy band power ratio was used to control for the influence of absolute power differences between groups. We further identified discrepant frequency bands and frequency band ratios for each subject and examined the correlations with clinical scores. Results: Dystonia patients exhibited greater low frequency power (6-14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26-43 Hz) ( p < 0.0298, corrected). United Huntington Disease Rating Scale chorea sub-score was positively correlated with 26-43 Hz frequency band power and negatively correlated with the 6-14 Hz/26-43 Hz band power ratio. Conclusion: Dystonia and HD are characterized by distinct oscillatory activity patterns, which may relate to distinct clinical characteristics. Specifically, chorea may be related to elevated high-beta and low-gamma band power, while dystonia may be related to elevated low frequency band power. These LFPs may be useful biomarkers for adaptive DBS to treat hyperkinetic diseases.

Background: The timing of action potentials ("spikes") of cortical neurons has been shown to be aligned to the phase of low-frequency (< 10 Hz) local field potentials (LFPs) in several cortical areas. However, across the areas, this alignment varies and the role of this spike-phase coupling (SPC) in cognitive functions is not well understood., Results: Here, we propose a role in the coordination of neural activity by selective attention. After refining previous analytical methods for measuring SPC, we show that first, SPC is present along the dorsal processing pathway in macaque visual cortex (area MT); second, spikes occur in falling phases of the low-frequency LFP independent of the location of spatial attention; third, switching spatial attention into the receptive field (RF) of MT neurons decreases this coupling; and finally, the LFP phase causally influences the spikes., Conclusions: Here, we show that spikes are coupled to the phase of low-frequency LFP along the dorsal visual pathway. Our data suggest that attention harnesses this spike-LFP coupling to de-synchronize neurons and thereby enhance the neural representation of the attended stimuli.