Focal cooling: An alternative treatment for drug-resistant epilepsy in a mesial temporal lobe epilepsy primate model-A preliminary study.

OBJECTIVE: Focal cooling is emerging as a relevant therapy for drug-resistant epilepsy (DRE). However, we lack data on its effectiveness in controlling seizures that originate in deep-seated areas like the hippocampus. We present a thermoelectric solution for focal brain cooling that specifically targets these brain structures. METHODS: A prototype implantable device was developed, including temperature sensors and a cannula for penicillin injection to create an epileptogenic zone (EZ) near the cooling tip in a non-human primate model of epilepsy. The mesial temporal lobe was targeted with repeated penicillin injections into the hippocampus. Signals were recorded from an sEEG (Stereoelectroencephalography) lead placed 2 mm from the EZ. Once the number of seizures had stabilized, focal cooling was applied, and temperature and electroclinical events were monitored using a customized detection algorithm. Tests were performed on two Macaca fascicularis monkeys at three temperatures. RESULTS: Hippocampal seizures were observed 40-120 min post-injection, their duration and frequency stabilized at around 120 min. Compared to the control condition, a reduction in the number of hippocampal seizures was observed with cooling to 21°C (Control: 4.34 seizures, SD 1.704 per 20 min vs Cooling to 21°C: 1.38 seizures, SD 1.004 per 20 min). The effect was more pronounced with cooling to 17°C, resulting in an almost 80% reduction in seizure frequency. Seizure duration and number of interictal discharges were unchanged following focal cooling. After several months of repeated penicillin injections, hippocampal sclerosis was observed, similar to that recorded in humans. In addition, seizures were identified by detecting temperature variations of 0.3°C in the EZ correlated with the start of the seizures. SIGNIFICANCE: In epilepsy therapy, the ultimate aim is total seizure control with minimal side effects. Focal cooling of the EZ could offer an alternative to surgery and to existing neuromodulation devices.

Unsupervised adaptation of an ECoG based brain-computer interface using neural correlates of task performance.

Brain-computer interfaces (BCIs) translate brain signals into commands to external effectors, and mainly target severely disabled users. The usability of BCIs may be improved by reducing their major constraints, such as the necessity for special training sessions to initially calibrate and later keep up to date the neural signal decoders. In this study, we show that it is possible to train and update BCI decoders during free use of motor BCIs. In addition to the neural signal decoder controlling effectors (control decoder), one more classifier is proposed to detect neural correlates of BCI motor task performances (MTP). MTP decoders reveal whether the actions performed by BCI effectors matched the user's intentions. The combined outputs of MTP and control decoders allow forming training datasets to update the control decoder online and in real time during free use of BCIs. The usability of the proposed auto-adaptive BCI (aaBCI) is demonstrated for two principle BCIs paradigms: with discrete outputs (4 classes BCI, virtual 4-limb exoskeleton), and with continuous outputs (cursor 2D control). The proof of concept was performed in an online simulation study using an ECoG dataset collected from a tetraplegic during a BCI clinical trial. The control decoder reached a multiclass area under the ROC curve of 0.7404 using aaBCI, compared to a chance level of 0.5173 and to 0.8187 for supervised training for the multiclass BCI, and a cosine similarity of 0.1211 using aaBCI, compared to a chance level of 0.0036 and to 0.2002 for supervised training for the continuous BCI.

An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic.

Objective.The article aims at addressing 2 challenges to step motor brain-computer interface (BCI) out of laboratories: asynchronous control of complex bimanual effectors with large numbers of degrees of freedom, using chronic and safe recorders, and the decoding performance stability over time without frequent decoder recalibration.Approach.Closed-loop adaptive/incremental decoder training is one strategy to create a model stable over time. Adaptive decoders update their parameters with new incoming data, optimizing the model parameters in real time. It allows cross-session training with multiple recording conditions during closed loop BCI experiments. In the article, an adaptive tensor-based recursive exponentially weighted Markov-switching multi-linear model (REW-MSLM) decoder is proposed. REW-MSLM uses a mixture of expert (ME) architecture, mixing or switching independent decoders (experts) according to the probability estimated by a 'gating' model. A Hidden Markov model approach is employed as gating model to improve the decoding robustness and to provide strong idle state support. The ME architecture fits the multi-limb paradigm associating an expert to a particular limb or action.Main results.Asynchronous control of an exoskeleton by a tetraplegic patient using a chronically implanted epidural electrocorticography (EpiCoG) recorder is reported. The stable over a period of six months (without decoder recalibration) eight-dimensional alternative bimanual control of the exoskeleton and its virtual avatar is demonstrated.Significance.Based on the long-term (>36 months) chronic bilateral EpiCoG recordings in a tetraplegic (ClinicalTrials.gov, NCT02550522), we addressed the poorly explored field of asynchronous bimanual BCI. The new decoder was designed to meet to several challenges: the high-dimensional control of a complex effector in experiments closer to real-world behavior (point-to-point pursuit versus conventional center-out tasks), with the ability of the BCI system to act as a stand-alone device switching between idle and control states, and a stable performance over a long period of time without decoder recalibration.

Long-term stability of the chronic epidural wireless recorder WIMAGINE in tetraplegic patients.

Objective.The evaluation of the long-term stability of ElectroCorticoGram (ECoG) signals is an important scientific question as new implantable recording devices can be used for medical purposes such as Brain-Computer Interface (BCI) or brain monitoring.Approach.The long-term clinical validation of wireless implantable multi-channel acquisition system for generic interface with neurons (WIMAGINE), a wireless 64-channel epidural ECoG recorder was investigated. The WIMAGINE device was implanted in two quadriplegic patients within the context of a BCI protocol. This study focused on the ECoG signal stability in two patients bilaterally implanted in June 2017 (P1) and in November 2019 (P2).Methods. The ECoG signal was recorded at rest prior to each BCI session resulting in a 32 month and in a 14 month follow-up for P1 and P2 respectively. State-of-the-art signal evaluation metrics such as root mean square (RMS), the band power (BP), the signal to noise ratio (SNR), the effective bandwidth (EBW) and the spectral edge frequency (SEF) were used to evaluate stability of signal over the implantation time course. The time-frequency maps obtained from task-related motor activations were also studied to investigate the long-term selectivity of the electrodes.Mainresults.Based on temporal linear regressions, we report a limited decrease of the signal average level (RMS), spectral distribution (BP) and SNR, and a remarkable steadiness of the EBW and SEF. Time-frequency maps obtained during motor imagery, showed a high level of discrimination 1 month after surgery and also after 2 years.Conclusions.The WIMAGINE epidural device showed high stability over time. The signal evaluation metrics of two quadriplegic patients during 32 months and 14 months respectively provide strong evidence that this wireless implant is well-suited for long-term ECoG recording.Significance.These findings are relevant for the future of implantable BCIs, and could benefit other patients with spinal cord injury, amyotrophic lateral sclerosis, neuromuscular diseases or drug-resistant epilepsy.

The Riemannian spatial pattern method: mapping and clustering movement imagery using Riemannian geometry.

Objective. Over the last decade, Riemannian geometry has shown promising results for motor imagery classification. However, extracting the underlying spatial features is not as straightforward as for applying common spatial pattern (CSP) filtering prior to classification. In this article, we propose a simple way to extract the spatial patterns obtained from Riemannian classification: the Riemannian spatial pattern (RSP) method, which is based on the backward channel selection procedure.Approach. The RSP method was compared to the CSP approach on ECoG data obtained from a quadriplegic patient while performing imagined movements of arm articulations and fingers.Main results.Similar results were found between the RSP and CSP methods for mapping each motor imagery task with activations following the classical somatotopic organization. Clustering obtained by pairwise comparisons of imagined motor movements however, revealed higher differentiation for the RSP method compared to the CSP approach. Importantly, the RSP approach could provide a precise comparison of the imagined finger flexions which added supplementary information to the mapping results.Significance.Our new RSP method illustrates the interest of the Riemannian framework in the spatial domain and as such offers new avenues for the neuroimaging community. This study is part of an ongoing clinical trial registered with ClinicalTrials.gov, NCT02550522.

An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration.

BACKGROUND: Approximately 20% of traumatic cervical spinal cord injuries result in tetraplegia. Neuroprosthetics are being developed to manage this condition and thus improve the lives of patients. We aimed to test the feasibility of a semi-invasive technique that uses brain signals to drive an exoskeleton. METHODS: We recruited two participants at Clinatec research centre, associated with Grenoble University Hospital, Grenoble, France, into our ongoing clinical trial. Inclusion criteria were age 18-45 years, stability of neurological deficits, a need for additional mobility expressed by the patient, ambulatory or hospitalised monitoring, registration in the French social security system, and signed informed consent. The exclusion criteria were previous brain surgery, anticoagulant treatments, neuropsychological sequelae, depression, substance dependence or misuse, and contraindications to magnetoencephalography (MEG), EEG, or MRI. One participant was excluded because of a technical problem with the implants. The remaining participant was a 28-year-old man, who had tetraplegia following a C4-C5 spinal cord injury. Two bilateral wireless epidural recorders, each with 64 electrodes, were implanted over the upper limb sensorimotor areas of the brain. Epidural electrocorticographic (ECoG) signals were processed online by an adaptive decoding algorithm to send commands to effectors (virtual avatar or exoskeleton). Throughout the 24 months of the study, the patient did various mental tasks to progressively increase the number of degrees of freedom. FINDINGS: Between June 12, 2017, and July 21, 2019, the patient cortically controlled a programme that simulated walking and made bimanual, multi-joint, upper-limb movements with eight degrees of freedom during various reach-and-touch tasks and wrist rotations, using a virtual avatar at home (64·0% [SD 5·1] success) or an exoskeleton in the laboratory (70·9% [11·6] success). Compared with microelectrodes, epidural ECoG is semi-invasive and has similar efficiency. The decoding models were reusable for up to approximately 7 weeks without recalibration. INTERPRETATION: These results showed long-term (24-month) activation of a four-limb neuroprosthetic exoskeleton by a complete brain-machine interface system using continuous, online epidural ECoG to decode brain activity in a tetraplegic patient. Up to eight degrees of freedom could be simultaneously controlled using a unique model, which was reusable without recalibration for up to about 7 weeks. FUNDING: French Atomic Energy Commission, French Ministry of Health, Edmond J Safra Philanthropic Foundation, Fondation Motrice, Fondation Nanosciences, Institut Carnot, Fonds de Dotation Clinatec.

Evaluation of chronically implanted subdural boron doped diamond/CNT recording electrodes in miniature swine brain.

When implantable recording devices for brain or neural electrical activity are designed, the number of available materials for electrodes is quite limited. The material must be biocompatible with respect to ISO10993, its electrochemical properties must remain stable and the response of cells or tissues can be mitigated, especially on the glial scar. This involves electrode characterization pre- implantation and impedance spectroscopy during chronic implantation, in order to evaluate both electrode properties and performance. This study was aimed at a comparison of the long-term behavior of a nanostructured boron-doped diamond (BDD) with a nanostructured Platinum Iridium (PtIr) electrode. Firstly, a batch of cortical grids with bare and modified contacts (2 mm in diameter) was engineered for implantation. Secondly a miniature swine model was developed. This study highlighted the predominant role of electrode surface roughness on the quality of recordings. Rough PtIr contacts and BDD coated ones showed comparable behavior after three-month implantation with a slight increase of the modulus of the impedance and a tissue capsule. Nevertheless, immunohistochemistry analysis did not exhibit either a toxic or irritation reaction. With regard to biocompatibility, promising long term results are shown for both materials.

A novel neural prosthesis providing long-term electrocorticography recording and cortical stimulation for epilepsy and brain-computer interface.

OBJECTIVE: Wireless technology is a novel tool for the transmission of cortical signals. Wireless electrocorticography (ECoG) aims to improve the safety and diagnostic gain of procedures requiring invasive localization of seizure foci and also to provide long-term recording of brain activity for brain-computer interfaces (BCIs). However, no wireless devices aimed at these clinical applications are currently available. The authors present the application of a fully implantable and externally rechargeable neural prosthesis providing wireless ECoG recording and direct cortical stimulation (DCS). Prolonged wireless ECoG monitoring was tested in nonhuman primates by using a custom-made device (the ECoG implantable wireless 16-electrode [ECOGIW-16E] device) containing a 16-contact subdural grid. This is a preliminary step toward large-scale, long-term wireless ECoG recording in humans. METHODS: The authors implanted the ECOGIW-16E device over the left sensorimotor cortex of a nonhuman primate (Macaca fascicularis), recording ECoG signals over a time span of 6 months. Daily electrode impedances were measured, aiming to maintain the impedance values below a threshold of 100 KΩ. Brain mapping was obtained through wireless cortical stimulation at fixed intervals (1, 3, and 6 months). After 6 months, the device was removed. The authors analyzed cortical tissues by using conventional histological and immunohistological investigation to assess whether there was evidence of damage after the long-term implantation of the grid. RESULTS: The implant was well tolerated; no neurological or behavioral consequences were reported in the monkey, which resumed his normal activities within a few hours of the procedure. The signal quality of wireless ECoG remained excellent over the 6-month observation period. Impedance values remained well below the threshold value; the average impedance per contact remains approximately 40 KΩ. Wireless cortical stimulation induced movements of the upper and lower limbs, and elicited fine movements of the digits as well. After the monkey was euthanized, the grid was found to be encapsulated by a newly formed dural sheet. The grid removal was performed easily, and no direct adhesions of the grid to the cortex were found. Conventional histological studies showed no cortical damage in the brain region covered by the grid, except for a single microscopic spot of cortical necrosis (not visible to the naked eye) in a region that had undergone repeated procedures of electrical stimulation. Immunohistological studies of the cortex underlying the grid showed a mild inflammatory process. CONCLUSIONS: This preliminary experience in a nonhuman primate shows that a wireless neuroprosthesis, with related long-term ECoG recording (up to 6 months) and multiple DCSs, was tolerated without sequelae. The authors predict that epilepsy surgery could realize great benefit from this novel prosthesis, providing an extended time span for ECoG recording.

A Long-Term BCI Study With ECoG Recordings in Freely Moving Rats.

BACKGROUND: Brain Computer Interface (BCI) studies are performed in an increasing number of applications. Questions are raised about electrodes, data processing and effectors. Experiments are needed to solve these issues. OBJECTIVE: To develop a simple BCI set-up to easier studies for improving the mathematical tools to process the ECoG to control an effector. METHOD: We designed a simple BCI using transcranial electrodes (17 screws, three mechanically linked to create a common reference, 14 used as recording electrodes) to record Electro-Cortico-Graphic (ECoG) neuronal activities in rodents. The data processing is based on an online self-paced non-supervised (asynchronous) BCI paradigm. N-way partial least squares algorithm together with Continuous Wavelet Transformation of ECoG recordings detect signatures related to motor activities. Signature detection in freely moving rats may activate external effectors during a behavioral task, which involved pushing a lever to obtain a reward. RESULTS: After routine training, we showed that peak brain activity preceding a lever push (LP) to obtain food reward was located mostly in the cerebellar cortex with a higher correlation coefficient, suggesting a strong postural component and also in the occipital cerebral cortex. Analysis of brain activities provided a stable signature in the high gamma band (∼180Hz) occurring within 1500 msec before the lever push approximately around -400 msec to -500 msec. Detection of the signature from a single cerebellar cortical electrode triggers the effector with high efficiency (68% Offline and 30% Online) and rare false positives per minute in sessions about 30 minutes and up to one hour (∼2 online and offline). CONCLUSIONS: In summary, our results are original as compared to the rest of the literature, which involves rarely rodents, a simple BCI set-up has been developed in rats, the data show for the first time long-term, up to one year, unsupervised online control of an effector.

Recursive Exponentially Weighted N-way Partial Least Squares Regression with Recursive-Validation of Hyper-Parameters in Brain-Computer Interface Applications.

A tensor-input/tensor-output Recursive Exponentially Weighted N-Way Partial Least Squares (REW-NPLS) regression algorithm is proposed for high dimension multi-way (tensor) data treatment and adaptive modeling of complex processes in real-time. The method unites fast and efficient calculation schemes of the Recursive Exponentially Weighted PLS with the robustness of tensor-based approaches. Moreover, contrary to other multi-way recursive algorithms, no loss of information occurs in the REW-NPLS. In addition, the Recursive-Validation method for recursive estimation of the hyper-parameters is proposed instead of conventional cross-validation procedure. The approach was then compared to state-of-the-art methods. The efficiency of the methods was tested in electrocorticography (ECoG) and magnetoencephalography (MEG) datasets. The algorithms are implemented in software suitable for real-time operation. Although the Brain-Computer Interface applications are used to demonstrate the methods, the proposed approaches could be efficiently used in a wide range of tasks beyond neuroscience uniting complex multi-modal data structures, adaptive modeling, and real-time computational requirements.

Near-infrared light is neuroprotective in a monkey model of Parkinson disease.

OBJECTIVE: To examine whether near-infrared light (NIr) treatment reduces clinical signs and/or offers neuroprotection in a subacute 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) monkey model of Parkinson disease. METHODS: We implanted an optical fiber device that delivered NIr (670 nm) to the midbrain of macaque monkeys, close to the substantia nigra of both sides. MPTP injections (1.5-2.1mg/kg) were made over a 5- to 7-day period, during which time the NIr device was turned on. This was then followed by a 3-week survival period. Monkeys were evaluated clinically (eg, posture, bradykinesia) and behaviorally (open field test), and their brains were processed for immunohistochemistry and stereology. RESULTS: All monkeys in the MPTP group developed severe clinical and behavioral impairment (mean clinical scores = 21-34; n = 11). By contrast, the MPTP-NIr group developed much less clinical and behavioral impairment (n = 9); some monkeys developed moderate clinical signs (mean scores = 11-15; n = 3), whereas the majority--quite remarkably--developed few clinical signs (mean scores = 1-6; n = 6). The monkeys that developed moderate clinical signs had hematic fluid in their optical fibers at postmortem, presumably limiting NIr exposure and overall clinical improvement. NIr was not toxic to brain tissue and offered neuroprotection to dopaminergic cells and their terminations against MPTP insult, particularly in animals that developed few clinical signs. INTERPRETATION: Our findings indicate NIr to be an effective therapeutic agent in a primate model of the disease and create the template for translation into clinical trials.

Intracranial application of near-infrared light in a hemi-parkinsonian rat model: the impact on behavior and cell survival.

OBJECT The authors of this study used a newly developed intracranial optical fiber device to deliver near-infrared light (NIr) to the midbrain of 6-hydroxydopamine (6-OHDA)-lesioned rats, a model of Parkinson's disease. The authors explored whether NIr had any impact on apomorphine-induced turning behavior and whether it was neuroprotective. METHODS Two NIr powers (333 nW and 0.16 mW), modes of delivery (pulse and continuous), and total doses (634 mJ and 304 J) were tested, together with the feasibility of a midbrain implant site, one considered for later use in primates. Following a striatal 6-OHDA injection, the NIr optical fiber device was implanted surgically into the midline midbrain area of Wistar rats. Animals were tested for apomorphine-induced rotations, and then, 23 days later, their brains were aldehyde fixed for routine immunohistochemical analysis. RESULTS The results showed that there was no evidence of tissue toxicity by NIr in the midbrain. After 6-OHDA lesion, regardless of mode of delivery or total dose, NIr reduced apomorphine-induced rotations at the stronger, but not at the weaker, power. The authors found that neuroprotection, as assessed by tyrosine hydroxylase expression in midbrain dopaminergic cells, could account for some, but not all, of the observed behavioral improvements; the groups that were associated with fewer rotations did not all necessarily have a greater number of surviving cells. There may have been other "symptomatic" elements contributing to behavioral improvements in these rats. CONCLUSIONS In summary, when delivered at the appropriate power, delivery mode, and dosage, NIr treatment provided both improved behavior and neuroprotection in 6-OHDA-lesioned rats.

810nm near-infrared light offers neuroprotection and improves locomotor activity in MPTP-treated mice.

We explored whether 810nm near-infrared light (NIr) offered neuroprotection and/or improvement in locomotor activity in an acute 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mouse model of Parkinson's disease. Mice received MPTP and 810nm NIr treatments, or not, and were tested for locomotive activity in an open-field test. Thereafter, brains were aldehyde-fixed and processed for tyrosine hydroxylase immunohistochemistry. Our results showed that MPTP-treated mice that were irradiated with 810nm NIr had both greater locomotor activity (∼40%) and number of dopaminergic cells (∼20%) than those that were not. In summary, 810nm (as with 670nm) NIr offered neuroprotection and improved locomotor activity in MPTP-treated mice.

CLINATEC® BCI platform based on the ECoG-recording implant WIMAGINE® and the innovative signal-processing: preclinical results.

The goal of the CLINATEC® Brain Computer Interface (BCI) Project is to improve tetraplegic subjects' quality of life by allowing them to interact with their environment through the control of effectors, such as an exoskeleton. The BCI platform is based on a wireless 64-channel ElectroCorticoGram (ECoG) recording implant WIMAGINE®, designed for long-term clinical application, and a BCI software environment associated to a 4-limb exoskeleton EMY (Enhancing MobilitY). Innovative ECoG signal decoding algorithms will allow the control of the exoskeleton by the subject's brain activity. Currently, the whole BCI platform was tested in real-time in preclinical experiments carried out in nonhuman primates. In these experiments, the exoskeleton arm was controlled by means of the decoded neuronal activity.

Deep brain stimulation: BCI at large, where are we going to?

UNLABELLED: Brain-computer interfaces (BCIs) include stimulators, infusion devices, and neuroprostheses. They all belong to functional neurosurgery. Deep brain stimulators (DBS) are widely used for therapy and are in need of innovative evolutions. Robotized exoskeletons require BCIs able to drive up to 26 degrees of freedom (DoF). We report the nanomicrotechnology development of prototypes for new 3D DBS and for motor neuroprostheses. For this complex project, all compounds have been designed and are being tested. Experiments were performed in rats and primates for proof of concepts and development of the electroencephalogram (EEG) recognition algorithm. METHODS: Various devices have been designed. (A) In human, a programmable multiplexer connecting five tetrapolar (20 contacts) electrodes to one DBS channel has been designed and implanted bilaterally into STN in two Parkinsonian patients. (B) A 50-mm diameter titanium implant, telepowered, including a radioset, emitting ECoG data recorded by a 64-electrode array using an application-specific integrated circuit, is being designed to be implanted in a 50-mm trephine opening. Data received by the radioreceiver are processed through an original wavelet-based Iterative N-way Partial Least Square algorithm (INPLS, CEA patent). Animals, implanted with ECoG recording electrodes, had to press a lever to obtain a reward. The brain signature associated to the lever press (LP) was detected online by ECoG processing using INPLS. This detection allowed triggering the food dispenser. RESULTS: (A) The 3D multiplexer allowed tailoring the electrical field to the STN. The multiplication of the contacts affected the battery life and suggested different implantation schemes. (B) The components of the human implantable cortical BCI are being tested for reliability and toxicology to meet criteria for chronicle implantation in 2012. (C) In rats, the algorithm INPLS could detect the cortical signature with an accuracy of about 80% of LPs on the electrodes with the best correlation coefficient (located over the cerebellar cortex), 1% of the algorithm decisions were false positives. We aim to pilot effectors with DoF up to 3 in monkeys. CONCLUSION: We have designed multielectrodes wireless implants to open the way for BCI ECoG-driven effectors. These technologies are also used to develop new generations of brain stimulators, either cortical or for deep targets. This chapter is aimed at illustrating that BCIs are actually the daily background of DBS, that the evolution of the method involves a growing multiplicity of targets and indications, that new technologies make possible and simpler than before to design innovative solutions to improve DBS methodology, and that the coming out of BCI-driven neuroprostheses for compensation of motor and sensory deficits is a natural evolution of functional neurosurgery.

Iterative N-way partial least squares for a binary self-paced brain-computer interface in freely moving animals.

In this paper a tensor-based approach is developed for calibration of binary self-paced brain-computer interface (BCI) systems. In order to form the feature tensor, electrocorticograms, recorded during behavioral experiments in freely moving animals (rats), were mapped to the spatial-temporal-frequency space using the continuous wavelet transformation. An N-way partial least squares (NPLS) method is applied for tensor factorization and the prediction of a movement intention depending on neuronal activity. To cope with the huge feature tensor dimension, an iterative NPLS (INPLS) algorithm is proposed. Computational experiments demonstrated the good accuracy and robustness of INPLS. The algorithm does not depend on any prior neurophysiological knowledge and allows fully automatic system calibration and extraction of the BCI-related features. Based on the analysis of time intervals preceding the BCI events, the calibration procedure constructs a predictive model of control. The BCI system was validated by experiments in freely moving animals under conditions close to those in a natural environment.

Dual-level afferent control of growth hormone-releasing hormone (GHRH) neurons in GHRH-green fluorescent protein transgenic mice.

The organization of the peptidergic neurons of the hypothalamic arcuate nucleus is not fully understood. These include growth hormone-releasing hormone (GHRH) neurons involved in growth and metabolism. We studied identified GHRH neurons of GHRH-green fluorescent protein transgenic mice using patch-clamp methods and focused on gender differences, which govern the physiological patterns of GHRH release. Both the spontaneous firing rates and the intrinsic properties of GHRH neurons were similar in males and females, although higher glutamatergic currents were noticed in females. Surprisingly, marked gender differences in GHRH neuronal activity were observed in response to the muscarinic agonist carbachol (CCh). In females, CCh enhanced action potential firing in all GHRH neurons. In males, CCh enhanced action potential firing in two-thirds of GHRH neurons, whereas it decreased firing in the remainders. M1 agonist McN-A343 (10 microM) mimicked, and M1 antagonist pirenzepine (3 microM) blocked the effects of CCh. In both genders, CCh did not change the intrinsic properties of GHRH neurons, although it strongly increased the frequency of glutamatergic currents, in the presence or absence of tetrodotoxin. In males only, CCh enhanced the frequency of GABAergic currents, and this modulation was antagonized by tetrodotoxin. Thus, the muscarinic regulation involved differential control of afferent inputs at short and long distances in male and female mice. The dual-level control could be a mechanism whereby the selective modulation of the GHRH system (short-distance control) is adjusted to the integrated regulation of arcuate nucleus activity (long-distance control).