Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance.

Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

Sleep pressure modulates single-neuron synapse number in zebrafish.

Sleep is a nearly universal behaviour with unclear functions1. The synaptic homeostasis hypothesis proposes that sleep is required to renormalize the increases in synaptic number and strength that occur during wakefulness2. Some studies examining either large neuronal populations3 or small patches of dendrites4 have found evidence consistent with the synaptic homeostasis hypothesis, but whether sleep merely functions as a permissive state or actively promotes synaptic downregulation at the scale of whole neurons is unclear. Here, by repeatedly imaging all excitatory synapses on single neurons across sleep-wake states of zebrafish larvae, we show that synapses are gained during periods of wake (either spontaneous or forced) and lost during sleep in a neuron-subtype-dependent manner. However, synapse loss is greatest during sleep associated with high sleep pressure after prolonged wakefulness, and lowest in the latter half of an undisrupted night. Conversely, sleep induced pharmacologically during periods of low sleep pressure is insufficient to trigger synapse loss unless adenosine levels are boosted while noradrenergic tone is inhibited. We conclude that sleep-dependent synapse loss is regulated by sleep pressure at the level of the single neuron and that not all sleep periods are equally capable of fulfilling the functions of synaptic homeostasis.

Modeling the effect of magnetoelectric nanoparticles on neuronal electrical activity: An analog circuit approach.

This paper introduces a physical neuron model that incorporates magnetoelectric nanoparticles (MENPs) as an essential electrical circuit component to wirelessly control local neural activity. Availability of such a model is important as MENPs, due to their magnetoelectric effect, can wirelessly and noninvasively modulate neural activity, which, in turn, has implications for both finding cures for neurological diseases and creating a wireless noninvasive high-resolution brain-machine interface. When placed on a neuronal membrane, MENPs act as magnetic-field-controlled finite-size electric dipoles that generate local electric fields across the membrane in response to magnetic fields, thus allowing to controllably activate local ion channels and locally initiate an action potential. Herein, the neuronal electrical characteristic description is based on ion channel activation and inhibition mechanisms. A MENP-based memristive Hodgkin-Huxley circuit model is extracted by combining the Hodgkin-Huxley model and an equivalent circuit model for a single MENP. In this model, each MENP becomes an integral part of the neuron, thus enabling wireless local control of the neuron's electric circuit itself. Furthermore, the model is expanded to include multiple MENPs to describe collective effects in neural systems.

Neurogenesis and pesticides: news of no new neurons.

New hippocampal neurons are continuously generated in the adult human brain. Several studies have demonstrated that the proliferation of hippocampal cells is strongly influenced by a variety of stimuli, including pesticides exposure. These effects are particularly important because neurogenesis dysregulation could be associated with the decline of neuronal and cognitive functions and the possible development of neuropsychiatric disorders.

Novos neurônios hipocampais são gerados continuamente no cérebro humano adulto. Vários estudos têm demonstrado que a proliferação de células do hipocampo é influenciada por uma variedade de estímulos, incluindo a exposição a pesticidas. Estes efeitos são particularmente importantes porque a desregulação da neurogênese pode estar associada ao declínio das funções neuronais e cognitivas e ao possível desenvolvimento de doenças neuropsiquiátricas.

Spiking Neural Membrane Systems with Adaptive Synaptic Time Delay.

Spiking neural membrane systems (or spiking neural P systems, SNP systems) are a new type of computation model which have attracted the attention of plentiful scholars for parallelism, time encoding, interpretability and extensibility. The original SNP systems only consider the time delay caused by the execution of rules within neurons, but not caused by the transmission of spikes via synapses between neurons and its adaptive adjustment. In view of the importance of time delay for SNP systems, which are a time encoding computation model, this study proposes SNP systems with adaptive synaptic time delay (ADSNP systems) based on the dynamic regulation mechanism of synaptic transmission delay in neural systems. In ADSNP systems, besides neurons, astrocytes that can generate adenosine triphosphate (ATP) are introduced. After receiving spikes, astrocytes convert spikes into ATP and send ATP to the synapses controlled by them to change the synaptic time delays. The Turing universality of ADSNP systems in number generating and accepting modes is proved. In addition, a small universal ADSNP system using 93 neurons and astrocytes is given. The superiority of the ADSNP system is demonstrated by comparison with the six variants. Finally, an ADSNP system is constructed for credit card fraud detection, which verifies the feasibility of the ADSNP system for solving real-world problems. By considering the adaptive synaptic delay, ADSNP systems better restore the process of information transmission in biological neural networks, and enhance the adaptability of SNP systems, making the control of time more accurate.

Implication of thermal signaling in neuronal differentiation revealed by manipulation and measurement of intracellular temperature.

Neuronal differentiation-the development of neurons from neural stem cells-involves neurite outgrowth and is a key process during the development and regeneration of neural functions. In addition to various chemical signaling mechanisms, it has been suggested that thermal stimuli induce neuronal differentiation. However, the function of physiological subcellular thermogenesis during neuronal differentiation remains unknown. Here we create methods to manipulate and observe local intracellular temperature, and investigate the effects of noninvasive temperature changes on neuronal differentiation using neuron-like PC12 cells. Using quantitative heating with an infrared laser, we find an increase in local temperature (especially in the nucleus) facilitates neurite outgrowth. Intracellular thermometry reveals that neuronal differentiation is accompanied by intracellular thermogenesis associated with transcription and translation. Suppression of intracellular temperature increase during neuronal differentiation inhibits neurite outgrowth. Furthermore, spontaneous intracellular temperature elevation is involved in neurite outgrowth of primary mouse cortical neurons. These results offer a model for understanding neuronal differentiation induced by intracellular thermal signaling.

Prelimbic cortex-nucleus accumbens core projection positively regulates itch and itch-related aversion.

Itch is one of the most common clinical symptoms in patients with diseases of the skin, liver, or kidney, and it strongly triggers aversive emotion and scratching behavior. Previous studies have confirmed the role of the prelimbic cortex (Prl) and the nucleus accumbens core (NAcC), which are reward and motivation regulatory centers, in the regulation of itch. However, it is currently unclear whether the Prl-NAcC projection, an important pathway connecting these two brain regions, is involved in the regulation of itch and its associated negative emotions. In this study, rat models of acute neck and cheek itch were established by subcutaneous injection of 5-HT, compound 48/80, or chloroquine. Immunofluorescence experiments determined that the number of c-Fos-immunopositive neurons in the Prl increased during acute itch. Chemogenetic inhibition of Prl glutamatergic neurons or Prl-NAcC glutamatergic projections can inhibit both histaminergic and nonhistaminergic itch-scratching behaviors and rectify the itch-related conditioned place aversion (CPA) behavior associated with nonhistaminergic itch. The Prl-NAcC projection may play an important role in the positive regulation of itch-scratching behavior by mediating the negative emotions related to itch.

Responsive regularity of neurons in the hindlimb region of primary somatosensory cortex to different temperature thermal needle stimulation of "Zusanli"(ST36) in mice. / å°é¼ åˆçº§ä½“æ„Ÿçš®å±‚åŽè‚¢åŒºç¥žç»å ƒå¯¹"足三里"不同温度热刺激的响应规律.

OBJECTIVES: To study the regularity of central response to thermal needle stimulation of "Zusanli" (ST36) at different temperature, and to analyze the temperature difference of central responses. METHODS: Six male C57BL/6j adult mice were used in the present study. For observing activities of neurons in the hindlimb region of left primary somatosensory cortex (S1HL, A/P=0.46 mm, M/L=1.32 mm, D/V=-0.14 mm) by using a fast high-resolution miniature two-photon microscopy (FHIRM-TPM), the mice were anesthetized with 3% isoflurane (inhalation), with its head fixed in a stereotaxic apparatus, then, adeno-associated virus (AAV-hSyn-GCaMP6f-WPRE-hGHpA, for showing intracellular calcium transients in neurons transfected) was injected into the left S1HL region using a micro-syringe after scalp surgical operation. The mice's right ST36 were stimulated using internal thermal needles with the temperature being 43 ℃, or 45 ℃, or 47 ℃, separately. Image J software and MATLAB 2020b software were used to process the image data of neuronal calcium activity (Ca2+ signaling) in the left S1HL region, including the instant maximum calcium peak value (ΔF/F) in 2 s, instant calcium spike frequency in 2 s, short-term calcium peak value (ΔF/F) in 3.5 min, short-term calcium spike frequency in 3.5 min, calcium peak duration in 3.5 min, maximum calcium peak value (ΔF/F) at the 1st , 2nd and 3rd min, and calcium spike frequency at the 1st, 2nd and 3rd min after thermal needle stimulation. RESULTS: In comparison with the normal temperature needle stimulation, the instant intracellular maximum calcium peak value, instant calcium spike frequency, short-term maximum calcium peak value, short-term calcium spike frequency, and calcium peak duration of S1HL neurons in response to 43 ℃, 45 ℃ and 47 ℃ internal thermal needle stimulation of ST36 were significantly increased (P<0.001, P<0.01). Comparison among the 43 ℃, 45 ℃ and 47 ℃ thermal needle stimulation showed that the 45 ℃ thermal needle stimulation was obviously superior to 43 ℃ and 47 ℃ thermal needle stimulation in increasing instant calcium spike frequency, short-term calcium spike frequency and calcium peak duration of S1HL neurons (P<0.001, P<0.01). The 47 ℃ thermal needle stimulation was stronger than 43 ℃ and 45 ℃ thermal needle stimulation in increasing the instant maximum calcium peak value (P<0.001). The maximum calcium peak value was apparently higher (P<0.001) at the 2nd min than that at the 1st and 3rd min after 43 ℃, 45 ℃ and 47 ℃ thermal needle stimulation. No significant differences were found in the short-term maximum calcium peak value among the 3 thermal needle stimulation and in the calcium spike frequency among the 3 time points after 43 ℃, 45 ℃ and 47 ℃ thermal needle stimulation. CONCLUSIONS: S1HL neurons respond to all 43 ℃, 45 ℃ and 47 ℃ thermal needle stimulation of ST36 in mice, while more actively to 45 ℃ thermal needle stimulation.

An electroencephalogram microdisplay to visualize neuronal activity on the brain surface.

Functional mapping during brain surgery is applied to define brain areas that control critical functions and cannot be removed. Currently, these procedures rely on verbal interactions between the neurosurgeon and electrophysiologist, which can be time-consuming. In addition, the electrode grids that are used to measure brain activity and to identify the boundaries of pathological versus functional brain regions have low resolution and limited conformity to the brain surface. Here, we present the development of an intracranial electroencephalogram (iEEG)-microdisplay that consists of freestanding arrays of 2048 GaN light-emitting diodes laminated on the back of micro-electrocorticography electrode grids. With a series of proof-of-concept experiments in rats and pigs, we demonstrate that these iEEG-microdisplays allowed us to perform real-time iEEG recordings and display cortical activities by spatially corresponding light patterns on the surface of the brain in the surgical field. Furthermore, iEEG-microdisplays allowed us to identify and display cortical landmarks and pathological activities from rat and pig models. Using a dual-color iEEG-microdisplay, we demonstrated coregistration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The iEEG-microdisplay holds promise to facilitate monitoring of pathological brain activity in clinical settings.

The homeostatic effects of the RE-1 silencing transcription factor on cortical networks are altered under ictogenic conditions in the mouse.

AIM: The Repressor Element-1 Silencing Transcription Factor (REST) is an epigenetic master regulator playing a crucial role in the nervous system. In early developmental stages, REST downregulation promotes neuronal differentiation and the acquisition of the neuronal phenotype. In addition, postnatal fluctuations in REST expression contribute to shaping neuronal networks and maintaining network homeostasis. Here we investigate the role of the early postnatal deletion of neuronal REST in the assembly and strength of excitatory and inhibitory synaptic connections. METHODS: We investigated excitatory and inhibitory synaptic transmission by patch-clamp recordings in acute neocortical slices in a conditional knockout mouse model (RestGTi) in which Rest was deleted by delivering PHP.eB adeno-associated viruses encoding CRE recombinase under the control of the human synapsin I promoter in the lateral ventricles of P0-P1 pups. RESULTS: We show that, under physiological conditions, Rest deletion increased the intrinsic excitability of principal cortical neurons in the primary visual cortex and the density and strength of excitatory synaptic connections impinging on them, without affecting inhibitory transmission. Conversely, in the presence of a pathological excitation/inhibition imbalance induced by pentylenetetrazol, Rest deletion prevented the increase in synaptic excitation and decreased seizure severity. CONCLUSION: The data indicate that REST exerts distinct effects on the excitability of cortical circuits depending on whether it acts under physiological conditions or in the presence of pathologic network hyperexcitability. In the former case, REST preserves a correct excitatory/inhibitory balance in cortical circuits, while in the latter REST loses its homeostatic activity and may become pro-epileptogenic.

Empirical modeling and prediction of neuronal dynamics.

Mathematical modeling of neuronal dynamics has experienced a fast growth in the last decades thanks to the biophysical formalism introduced by Hodgkin and Huxley in the 1950s. Other types of models (for instance, integrate and fire models), although less realistic, have also contributed to understand neuronal dynamics. However, there is still a vast volume of data that have not been associated with a mathematical model, mainly because data are acquired more rapidly than they can be analyzed or because it is difficult to analyze (for instance, if the number of ionic channels involved is huge). Therefore, developing new methodologies to obtain mathematical or computational models associated with data (even without previous knowledge of the source) can be helpful to make future predictions. Here, we explore the capability of a wavelet neural network to identify neuronal (single-cell) dynamics. We present an optimized computational scheme that trains the ANN with biologically plausible input currents. We obtain successful identification for data generated from four different neuron models when using all variables as inputs of the network. We also show that the empiric model obtained is able to generalize and predict the neuronal dynamics generated by variable input currents different from those used to train the artificial network. In the more realistic situation of using only the voltage and the injected current as input data to train the network, we lose predictive ability but, for low-dimensional models, the results are still satisfactory. We understand our contribution as a first step toward obtaining empiric models from experimental voltage traces.

Window into the songbird brain reveals superdiffusive migration of adult-born neurons.

In a recent study, Shvedov and colleagues used live two-photon imaging in transgenic zebra finches to reveal migration patterns of neuroblasts through the complex environment of the postembryonic brain. This study highlights the value of ubiquitin C/green fluorescent protein (UBC-GFP) transgenic zebra finches in studying adult neurogenesis and advances our understanding of dispersed long-distance neuronal migration in the adult brain, shedding light on this understudied phenomenon.

How to pause fertility.

Prolactin suppresses the ovarian cycles of lactating mice by directly repressing the activity of a cell population known as kisspeptin neurons.

Activation of lateral preoptic neurons is associated with nest-building in male mice.

Nest-building behavior is a widely observed innate behavior. A nest provides animals with a secure environment for parenting, sleep, feeding, reproduction, and temperature maintenance. Since animal infants spend their time in a nest, nest-building behavior has been generally studied as parental behaviors, and the medial preoptic area (MPOA) neurons are known to be involved in parental nest-building. However, nest-building of singly housed male mice has been less examined. Here we show that male mice spent longer time in nest-building at the early to middle dark phase and at the end of the dark phase. These two periods are followed by sleep-rich periods. When a nest was removed and fresh nest material was introduced, both male and female mice built nests at Zeitgeber time (ZT) 6, but not at ZT12. Using Fos-immunostaining combined with double in situ hybridization of Vgat and Vglut2, we found that Vgat- and Vglut2-positive cells of the lateral preoptic area (LPOA) were the only hypothalamic neuron population that exhibited a greater number of activated cells in response to fresh nest material at ZT6, compared to being naturally awake at ZT12. Fos-positive LPOA neurons were negative for estrogen receptor 1 (Esr1). Both Vgat-positive and Vglut2-positive neurons in both the LPOA and MPOA were activated at pup retrieval by male mice. Our findings suggest the possibility that GABAergic and glutamatergic neurons in the LPOA are associated with nest-building behavior in male mice.

Single neurons in the thalamus and subthalamic nucleus process cardiac and respiratory signals in humans.

Visceral signals are constantly processed by our central nervous system, enable homeostatic regulation, and influence perception, emotion, and cognition. While visceral processes at the cortical level have been extensively studied using non-invasive imaging techniques, very few studies have investigated how this information is processed at the single neuron level, both in humans and animals. Subcortical regions, relaying signals from peripheral interoceptors to cortical structures, are particularly understudied and how visceral information is processed in thalamic and subthalamic structures remains largely unknown. Here, we took advantage of intraoperative microelectrode recordings in patients undergoing surgery for deep brain stimulation (DBS) to investigate the activity of single neurons related to cardiac and respiratory functions in three subcortical regions: ventral intermedius nucleus (Vim) and ventral caudalis nucleus (Vc) of the thalamus, and subthalamic nucleus (STN). We report that the activity of a large portion of the recorded neurons (about 70%) was modulated by either the heartbeat, the cardiac inter-beat interval, or the respiration. These cardiac and respiratory response patterns varied largely across neurons both in terms of timing and their kind of modulation. A substantial proportion of these visceral neurons (30%) was responsive to more than one of the tested signals, underlining specialization and integration of cardiac and respiratory signals in STN and thalamic neurons. By extensively describing single unit activity related to cardiorespiratory function in thalamic and subthalamic neurons, our results highlight the major role of these subcortical regions in the processing of visceral signals.

Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function.

There is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. There is also great interest in using electric elements with memory, memelements, that can implement complex neuronal functions intrinsically. A feature not widely incorporated in neuromorphic systems is history-dependent action potential time adaptation which is widely seen in real cells. Previous theoretical work shows that power-law history dependent spike time adaptation, seen in several brain areas and species, can be modeled with fractional order differential equations. Here, we show that fractional order spiking neurons can be implemented using super-capacitors. The super-capacitors have fractional order derivative and memcapacitive properties. We implemented two circuits, a leaky integrate and fire and a Hodgkin-Huxley. Both circuits show power-law spiking time adaptation and optimal coding properties. The spiking dynamics reproduced previously published computer simulations. However, the fractional order Hodgkin-Huxley circuit showed novel dynamics consistent with criticality. We compared the responses of this circuit to recordings from neurons in the weakly-electric fish that have previously been shown to perform fractional order differentiation of their sensory input. The criticality seen in the circuit was confirmed in spontaneous recordings in the live fish. Furthermore, the circuit also predicted long-lasting stimulation that was also corroborated experimentally. Our work shows that fractional order memcapacitors provide intrinsic memory dependence that could allow implementation of computationally efficient neuromorphic devices. Memcapacitors are static elements that consume less energy than the most widely studied memristors, thus allowing the realization of energetically efficient neuromorphic devices.

Generation of induced pluripotent stem cells from rat fibroblasts and optimization of its differentiation into mature functional neurons.

BACKGROUND: Induced pluripotent stem cells (iPSCs) derived neural stem cells (NSCs) provide a potential for autologous neural transplantation therapy following neurological insults. Thus far, in preclinical studies the donor iPSCs-NSCs are mostly of human or mouse origin with concerns centering around graft rejection when applied to rat brain injury models. For better survival and integration of transplanted cells in the injured brain in rat models, use of rat-iPSC-NSCs and in combination with biomaterials is of advantageous. Herein, we report a detailed method in generating rat iPSCs with improved reprogramming efficiency and differentiation into neurons. NEW METHOD: Rat fibroblasts were reprogrammed into iPSCs with polybrene and EF1α-STEMCCA-LoxP lentivirus vector. Pluripotency characterization, differentiation into neuronal linage cells were assessed with RT-qPCR, Western blotting, immunostaining and patch-clamp methods. Cells were cultured in a custom-designed integrin array system as well as in a hydrogel-based 3D condition. RESULTS: We describe a thorough method for the generation of rat-iPSC-NSCs, and identify integrin αvß8 as a substrate for the optimal growth of rat-iPSC-NSCs. Furthermore, with hydrogel as the supporting biomaterial in the 3-D culture, when combined with integrin αvß8 binding peptide, it forms a conducive environment for optimal growth and differentiation of iPSC-NSCs into mature neurons. COMPARISON WITH EXISTING METHODS: Published studies about rat-iPSC-NSCs are rare. This study provides a detailed protocol for the generation of rat iPSC-NSCs and optimal growth conditions for neuronal differentiation. Our method is useable for studies to assess the utility of rat iPSC-NSCs for neural transplantation in rat brain injury models.

Brainstem control of vocalization and its coordination with respiration.

Phonation critically depends on precise controls of laryngeal muscles in coordination with ongoing respiration. However, the neural mechanisms governing these processes remain unclear. We identified excitatory vocalization-specific laryngeal premotor neurons located in the retroambiguus nucleus (RAmVOC) in adult mice as being both necessary and sufficient for driving vocal cord closure and eliciting mouse ultrasonic vocalizations (USVs). The duration of RAmVOC activation can determine the lengths of both USV syllables and concurrent expiration periods, with the impact of RAmVOC activation depending on respiration phases. RAmVOC neurons receive inhibition from the preBötzinger complex, and inspiration needs override RAmVOC-mediated vocal cord closure. Ablating inhibitory synapses in RAmVOC neurons compromised this inspiration gating of laryngeal adduction, resulting in discoordination of vocalization with respiration. Our study reveals the circuits for vocal production and vocal-respiratory coordination.

Adenosinergic Modulation of Layer 6 Microcircuitry in the Medial Prefrontal Cortex Is Specific to Presynaptic Cell Type.

Adenosinergic modulation in the PFC is recognized for its involvement in various behavioral aspects including sleep homoeostasis, decision-making, spatial working memory and anxiety. While the principal cells of layer 6 (L6) exhibit a significant morphological diversity, the detailed cell-specific regulatory mechanisms of adenosine in L6 remain unexplored. Here, we quantitatively analyzed the morphological and electrophysiological parameters of L6 neurons in the rat medial prefrontal cortex (mPFC) using whole-cell recordings combined with morphological reconstructions. We were able to identify two different morphological categories of excitatory neurons in the mPFC of both juvenile and young adult rats with both sexes. These categories were characterized by a leading dendrite that was oriented either upright (toward the pial surface) or inverted (toward the white matter). These two excitatory neuron subtypes exhibited different electrophysiological and synaptic properties. Adenosine at a concentration of 30 µM indiscriminately suppressed connections with either an upright or an inverted presynaptic excitatory neuron. However, using lower concentrations of adenosine (10 µM) revealed that synapses originating from L6 upright neurons have a higher sensitivity to adenosine-induced inhibition of synaptic release. Adenosine receptor activation causes a reduction in the probability of presynaptic neurotransmitter release that could be abolished by specifically blocking A1 adenosine receptors (A1ARs) using 8-cyclopentyltheophylline (CPT). Our results demonstrate a differential expression level of A1ARs at presynaptic sites of two functionally and morphologically distinct subpopulations of L6 principal neurons, suggesting the intricate functional role of adenosine in neuronal signaling in the brain.

Bridging the Gap: Local Field Potentials Offer a Peek Into the Brain of a Person With Parkinson Disease.

Clinically available deep brain recordings in patients with Parkinson disease (PD) offer insights into disease mechanisms and create a pathway for personalized treatment strategies. This case illustrates the transformative potential of recordings of neuronal firing in the form of local field potentials (LFPs) by detailing a patient's clinical trajectory for 6 months after deep brain stimulation (DBS) surgery to treat their PD symptoms. LFPs, obtained easily in clinic with a tablet interface to measure and track brain rhythms across the disease course, enriched the patient's clinical picture. Specifically, strong beta peaks were captured at initial programming, and, as the beta peaks diminished over the course of optimizing settings, symptoms improved. These signals may also reveal insights into the neural dynamics of PD such as hypersynchrony in basal ganglia circuitry. Furthermore, the ability to record chronically may unlock new understanding of neuronal dysfunction in PD, possibly enabling future adaptive DBS. In conclusion, identification, tracking, and modulation of LFPs correlated with subjective and objective clinical improvement in the case presented. The use of neurophysiologic signals in the future may lead to therapeutic innovations for our patients with PD.