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Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources may spatially extend (known as source leakage) into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large‐scale cortical networks. In this technical report, we develop a novel denoising approach for suppressing the leakage of interference source activity into the activity representing a brain region of interest. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We apply this denoising approach to reconstruct simulated evoked response topographies to deep brain stimulation (DBS) in a phantom recording. We highlight the advantages of our approach compared to the benchmark—spatiotemporal signal space separation—and show that it can more accurately reveal brain stimulation‐evoked response topographies. Finally, we apply our method to MEG recordings from a single patient with Parkinson's disease, to reveal early cortical‐evoked responses to DBS of the subthalamic nucleus. [ABSTRACT FROM AUTHOR]

Exaggerated local field potential bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus of patients with Parkinson's disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the subthalamic nucleus local field potential in Parkinson's disease, and that together these different states predict motor impairment with high fidelity. Local field potentials were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the subthalamic nucleus. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. Local field potentials were analysed using hidden Markov modelling to identify transient spectral states with frequencies under 40 Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional local field potential states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all local field potential states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients' hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the subthalamic nucleus local field potential have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how local field potential feedback can be made more informative in closed-loop deep brain stimulation systems. [ABSTRACT FROM AUTHOR]

Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) are related conditions that are associated with cholinergic system dysfunction. Dysfunction of the nucleus basalis of Meynert (NBM), a basal forebrain structure that provides the dominant source of cortical cholinergic innervation, has been implicated in the pathogenesis of both PDD and DLB. Here we leverage the temporal resolution of magnetoencephalography with the spatial resolution of MRI tractography to explore the intersection of functional and structural connectivity of the NBM in a unique cohort of PDD and DLB patients undergoing deep brain stimulation of this structure. We observe that NBM-cortical structural and functional connectivity correlate within spatially and spectrally segregated networks including: (i) a beta band network to supplementary motor area, where activity in this region was found to drive activity in the NBM; (ii) a delta/theta band network to medial temporal lobe structures encompassing the parahippocampal gyrus; and (iii) a delta/theta band network to visual areas including lingual gyrus. These findings reveal functional networks of the NBM that are likely to subserve important roles in motor control, memory and visual function, respectively. Furthermore, they motivate future studies aimed at disentangling network contribution to disease phenotype. [ABSTRACT FROM AUTHOR]

Dementia with Lewy bodies (DLB) is the second most common form of dementia. Current symptomatic treatment with medications remains inadequate. Deep brain stimulation of the nucleus basalis of Meynert (NBM DBS) has been proposed as a potential new treatment option in dementias. To assess the safety and tolerability of low frequency (20 Hz) NBM DBS in DLB patients and explore its potential effects on both clinical symptoms and functional connectivity in underlying cognitive networks. We conducted an exploratory randomised, double-blind, crossover trial of NBM DBS in six DLB patients recruited from two UK neuroscience centres. Patients were aged between 50 and 80 years, had mild-moderate dementia symptoms and were living with a carer-informant. Patients underwent image guided stereotactic implantation of bilateral DBS electrodes with the deepest contacts positioned in the Ch4i subsector of NBM. Patients were subsequently assigned to receive either active or sham stimulation for six weeks, followed by a two week washout period, then the opposite condition for six weeks. Safety and tolerability of both the surgery and stimulation were systematically evaluated throughout. Exploratory outcomes included the difference in scores on standardised measurements of cognitive, psychiatric and motor symptoms between the active and sham stimulation conditions, as well as differences in functional connectivity in discrete cognitive networks on resting state fMRI. Surgery and stimulation were well tolerated by all six patients (five male, mean age 71.33 years). One serious adverse event occurred: one patient developed antibiotic-associated colitis, prolonging his hospital stay by two weeks. No consistent improvements were observed in exploratory clinical outcome measures, but the severity of neuropsychiatric symptoms reduced with NBM DBS in 3/5 patients. Active stimulation was associated with functional connectivity changes in both the default mode network and the frontoparietal network. Low frequency NBM DBS can be safely conducted in DLB patients. This should encourage further exploration of the possible effects of stimulation on neuropsychiatric symptoms and corresponding changes in functional connectivity in cognitive networks. NCT02263937. • Novel therapeutic strategies for dementia are urgently needed. • Deep brain stimulation of the nucleus basalis of Meynert has been proposed. • This intervention was well tolerated in patients with dementia with Lewy bodies. • It may impact upon neuropsychiatric symptoms. • Stimulation possibly induced functional connectivity changes in cognitive networks. [ABSTRACT FROM AUTHOR]

Background Deep Brain Stimulation (DBS) is an effective treatment for several neurological and psychiatric disorders. In order to gain insights into the therapeutic mechanisms of DBS and to advance future therapies a better understanding of the effects of DBS on large-scale brain networks is required. New method In this paper, we describe an experimental protocol and analysis pipeline for simultaneously performing DBS and intracranial local field potential (LFP) recordings at a target brain region during concurrent magnetoencephalography (MEG) measurement. Firstly we describe a phantom setup that allowed us to precisely characterise the MEG artefacts that occurred during DBS at clinical settings. Results Using the phantom recordings we demonstrate that with MEG beamforming it is possible to recover oscillatory activity synchronised to a reference channel, despite the presence of high amplitude artefacts evoked by DBS. Finally, we highlight the applicability of these methods by illustrating in a single patient with Parkinson's disease (PD), that changes in cortical-subthalamic nucleus coupling can be induced by DBS. Comparison with existing approaches To our knowledge this paper provides the first technical description of a recording and analysis pipeline for combining simultaneous cortical recordings using MEG, with intracranial LFP recordings of a target brain nucleus during DBS. [ABSTRACT FROM AUTHOR]

Movement is accompanied by changes in the degree to which neurons in corticobasal ganglia loops synchronize their activity within discrete frequency ranges. Although two principal frequencybands--beta (15-30 Hz) andgamma(60 -90Hz)--have been implicated in motor control, the precise functional correlates of their activities remain unclear. Local field potential (LFP) recordings in humans with Parkinson's disease undergoing surgery for deep brain stimulation to the subthalamic nucleus (STN) indicate that spectral changes both anticipate movement and occur perimovement. The extent to which such changes are modulated by cognitive factors involved in making a correct response seems critical in characterizing the functional associations of these oscillations. Accordingly, by recording LFP activity from the STN in parkinsonian patients, we demonstrate that perimovement beta and gamma reactivity is modulated by task complexity in a dopamine-dependent manner, despite the dynamics of the movement remaining unchanged. In contrast, spectral changes occurring in anticipation of future movement were limited to the beta band and, although modulated by dopaminergic therapy, were not modulated by task complexity. Our findings suggest two dopamine-dependent processes indexed by spectral changes in the STN: (1) an anticipatory activity reflected in the beta band that signals the likelihood of future action but does not proactively change with the cognitive demands of the potential response, and (2) perimovement activity that involves reciprocal beta and gamma band changes and is not exclusively related to explicit motor processing. Rather perimovement activity can also vary with, and may reflect, the cognitive complexity of the task. [ABSTRACT FROM AUTHOR]

Oscillatory activity in the beta frequency band has been shown to be modulated during the preparation and execution of voluntary movements at both cortical and subcortical levels. The exaggeration of beta activity in the basal ganglia of patients with Parkinson's disease has heightened interest in this phenomenon. However, the precise function, if any, subserved by modulations in beta activity remains unclear. Here we test the hypothesis that beta reactivity can be dissociated from processing of specific actions and can index the salience of cues with respect to future behavior in a way that might help prospectively prioritize resources. To this end we used an experimental paradigm designed to dissociate salient warning cues from processing of specific motor or cognitive actions. We recorded local field potential activity from the subthalamic nucleus of humans undergoing functional neurosurgery for the treatment of Parkinson's disease, while the same patients were on or off the dopamine prodrug levodopa. In this way we demonstrate that beta reactivity is indeed dependent on the salience of cues with respect to future motor and cognitive action and is promoted by dopamine. The loss of normal beta encoding of saliency may underlie some of the motor and cognitive features of basal ganglia disorders such as Parkinson's disease. [ABSTRACT FROM AUTHOR]

The article discusses the central targets, signaling mechanisms and role of leptin and the control of body weight in the pathogenesis of obesity. Leptin is a hormone which detects fat mass in part of a negative feedback loop that maintains a set point for body fat stores. The hormone is capable of modifying synaptic links between neurons. It seems that leptin-responsive neurons establish rather complex mechanisms of controlling their own sensitivity to leptin.

We describe two unusual cases; both patients wish to continue using the Gynefix® despite experiencing difficulty with the device. In case A, the marker string of the Gynefix® perforated the full thickness of the cervix and was visualized on the left lateral aspect of the cervix. Three months later the string had moved again and could no longer be visualized, but an ultrasound scan confirmed fundal implantation of the device. Case B demonstrates repeated late expulsion and failure of implantation of Gynefix®. Appropriateness of ultrasound with reference to measurement of the distance SS (between the peritoneal surface of the uterine fundus and the first copper sleeve of the Gynefix®), failure of implantation and problems with the new Gynefix® introducer are discussed. [ABSTRACT FROM AUTHOR]

Both scalp and intracranial electroencephalograms (EEGs) are of great importance for diagnosing brain disorders. However, the scalp EEG (sEEG) is attenuated by the skull and contaminated with artifacts. At the same time, intracranial EEG (iEEG) is almost free of artifacts and can capture all brain activities without any attenuation due to being close to the brain sources. In this study, the aim is to enhance the performance of sEEG by mapping the sEEG to the iEEG. To do so, we here develop a deep neural network using a generative adversarial network to estimate the sEEG from the iEEG. The proposed method is applied to sEEG and iEEG recorded simultaneously from epileptics to detect interictal epileptiform discharges (IEDs). The proposed method detects IEDs with 76% accuracy outperforming the state-of-the-art methods. Furthermore, it is at least twelve times less complex than the compared methods.

Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field., (Copyright © 2023 Chien-Hung Yeh et al.)

Exaggerated local field potential bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus of patients with Parkinson's disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the subthalamic nucleus local field potential in Parkinson's disease, and that together these different states predict motor impairment with high fidelity. Local field potentials were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the subthalamic nucleus. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. Local field potentials were analysed using hidden Markov modelling to identify transient spectral states with frequencies under 40 Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional local field potential states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all local field potential states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients' hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the subthalamic nucleus local field potential have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how local field potential feedback can be made more informative in closed-loop deep brain stimulation systems., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)