Barriers to overlapping complex and general spine surgery at a tertiary academic hospital.

OBJECTIVE: Policy concern and debate surround the concept of overlapping spine surgery. Overlapping surgery specifically refers to nonessential portions of the case or noncutting time overlap. This differs from concurrent surgery, in which critical portions of the procedure overlap. Here the authors explore the barriers for safe and efficient overlapping surgery in academic spinal deformity practice. METHODS: Over a 24-month period, cases of spinal deformity, degenerative cases, anterior cervical discectomy and fusions (ACDFs), and laminectomy were reviewed for duration in operating room (OR) prior to surgery, duration of cutting time, duration in OR after surgery, turnover duration, and time delay from initial start time. Standard degenerative cases were referenced as 1-2 ACDFs as well as 1- to 2-level laminectomy surgery. The blocks of time between two consecutive cutting periods were investigated to determine the feasibility of overlapping an additional surgery. Specifically, the authors compared the blocks of time that include the postsurgery period, the turnover period, and the presurgery period to cutting periods. RESULTS: One hundred twenty-six complex spinal deformity procedures and 85 degenerative cases (including 49 ACDFs and 36 laminectomies) from one center and one neurosurgeon were reviewed. These procedures were performed between September 2019 and December 2021 with a 3-month gap in military deployment. On average, the procedure's duration for cases of deformity was 236.5 minutes, for cases of ACDFs it was 84 minutes, and for cases of laminectomies it was 105.5 minutes. The block of noncutting time while the patient was in the OR showed no difference from the surgical cut time. The turnover time between cases was 52.35 minutes. Of 100 cases scheduled as the first case of the day, 94 had a delay to the OR averaging 18.2 minutes. CONCLUSIONS: The data in this study indicate that estimates for pre- and postsurgical times alone are not sufficient to allow for overlapping surgery. The average cut-time duration of ACDF was 84 minutes; the average presurgical time for deformity was 68 minutes. This highlights the critical analysis for further examination of optimal scheduling, on-time first start, turnover periods, and the orchestration of all members of the providing team to optimize the cutting time for safe and consistent implementation of overlapping spine surgery.

Subthalamic nucleus deep brain stimulation driven by primary motor cortex γ2 activity in parkinsonian monkeys.

In parkinsonism, subthalamic nucleus (STN) electrical deep brain stimulation (DBS) improves symptoms, but may be associated with side effects. Adaptive DBS (aDBS), which enables modulation of stimulation, may limit side effects, but limited information is available about clinical effectiveness and efficaciousness. We developed a brain-machine interface for aDBS, which enables modulation of stimulation parameters of STN-DBS in response to γ2 band activity (80-200 Hz) of local field potentials (LFPs) recorded from the primary motor cortex (M1), and tested its effectiveness in parkinsonian monkeys. We trained two monkeys to perform an upper limb reaching task and rendered them parkinsonian with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Bipolar intracortical recording electrodes were implanted in the M1, and a recording chamber was attached to access the STN. In aDBS, the M1 LFPs were recorded, filtered into the γ2 band, and discretized into logic pulses by a window discriminator, and the pulses were used to modulate the interval and amplitude of DBS pulses. In constant DBS (cDBS), constant stimulus intervals and amplitudes were used. Reaction and movement times during the task were measured and compared between aDBS and cDBS. The M1-γ2 activities were increased before and during movements in parkinsonian monkeys and these activities modulated the aDBS pulse interval, amplitude, and dispersion. With aDBS and cDBS, reaction and movement times were significantly decreased in comparison to DBS-OFF. The electric charge delivered was lower with aDBS than cDBS. M1-γ2 aDBS in parkinsonian monkeys resulted in clinical benefits that did not exceed those from cDBS. However, M1-γ2 aDBS achieved this magnitude of benefit for only two thirds of the charge delivered by cDBS. In conclusion, M1-γ2 aDBS is an effective therapeutic approach which requires a lower electrical charge delivery than cDBS for comparable clinical benefits.

Spectrum dependency to rate and spike timing in neuronal spike trains.

BACKGROUND: Spike trains are series of interspike intervals in a specific order that can be characterized by their probability distributions and order in time which refer to the concepts of rate and spike timing features. Periodic structure in the spike train can be reflected in oscillatory activities. Thus, there is a direct link between oscillator activities and the spike train. The proposed methods are to investigate the dependency of emerging oscillatory activities to the rate and the spike timing features. METHOD: First, the circular statistics methods were compared to Fast Fourier Transform for best estimation of spectra. Second, two statistical tests were introduced to help make decisions regarding the dependency of spectrum, or individual frequencies, onto rate and spike timing. Third, the methodology is applied to in-vivo recordings of basal ganglia neurons in mouse, primate, and human. Finally, this novel framework is shown to allow the investigation of subsets of spikes contributing to individual oscillators. RESULTS: Use of circular statistical methods, in comparison to FFT, minimizes spectral leakage. Using virtual spike trains, the Rate versus Timing Dependency Spectrum Test (or RTDs-Test) permits identifying spectral spike trains solely dependent on the rate feature from those that are also dependent on the spike timing feature. Similarly, the Rate versus Timing Dependency Frequency Test (or RTDf-Test), allows to identify individual oscillators with partial dependency on spike timing. Dependency on spike timing was found for all in-vivo recordings but only in few frequencies. The mapping in frequency and time of dependencies showed a dynamical process that may be organizing the basal ganglia function. CONCLUSIONS: The methodology may improve our understanding of the emergence of oscillatory activities and, possibly, the relation between oscillatory activities and circuitry functions.

Challenges for future theories of Parkinson pathophysiology.

Current theories on the basal ganglia-thalamic-cortical circuitry address the phenomena of hypokinesia and hyperkinesia. In this Perspective, we question whether the current models can address the orchestration of the motor units which is the common final pathway of the motor system. We conclude that the current theories do not to address this orchestration in health and disease. One alternative approach worthy of consideration is nonmonotonic nonlinear dynamics that contrast with a fundamentally linear or monotonic nonlinear approach that are presumed by current theories of basal ganglia-thalamic-cortical system. The purpose here is to make the case that current theories do presuppose a linear or monotonic nonlinear perspective which will be demonstrated as failing to adequately explicate the complex orchestration of motor unit activities in normal movement and in movement disorders. The notion of nonlinear dynamics is not new to neurophysiology; however, it is argued that it is new to the concepts of the physiology and pathophysiology of the basal ganglia-thalamic-cortical system. Providing a wholesale reconceptualization of the basal ganglia-thalamic-cortical system is beyond the scope of this effort. Rather, the contribution of the essay is convincing that there is a need to reconceptualize theories as nonlinear dynamical systems and there are metaphors and analogies from nonlinear science that can be productive in the reconsideration.

Physical Plasticity of the Brain and Deep Brain Stimulation Lead: Evolution in the First Post-operative Week.

Background: Deep brain stimulation (DBS) is a therapy for movement disorders and psychiatric conditions. In the peri-operative period, brain shift occurs as the consequence of events related to the brain surgery which results in post-operative lead deformation. Objective: To quantify post-operative 3-dimensional DBS lead deformation after implantation. Methods: In 13 patients who had DBS lead implantation, we performed preoperative magnetic resonance imaging (MRI), preoperative computed tomography (CT) scans after placement of fiducial markers, and post-operative CT scans immediately, 24-48 h, and 7 days after implantation. The MRI scans were used to define brain orientation and merged with CT scans. Lead deviation was determined relative to a theoretical linear lead path defined by the skull entry and target lead tip points. Results: In the sagittal plane, we distinguished an initial period after surgery (<48 h) characterized by a deviation of the lead toward the rostral direction and a late period (over 1 week) characterized by a lead deviation toward the caudal direction. In the coronal plane, there was higher probability of lead deviation in the lateral than medial direction. During 7 days after implantation, there was net movement of the center of the lead anteriorly, and the half of the lead close to the entry point moved medially. These deviations appeared normative since all patients included in this study had benefits from DBS therapy with total power of charged comparable to those described in literature. Conclusion: DBS lead deviation occurs during 7 days after implantation. The range of deviation described in this study was not associated to adverse clinical effects and may be considered normative. Future multicenter studies would be helpful to define guide lines on DBS lead deformation and its contribution to clinical outcome.

Parkinsonism Differently Affects the Single Neuronal Activity in the Primary and Supplementary Motor Areas in Monkeys: An Investigation in Linear and Nonlinear Domains.

The changes in neuronal firing activity in the primary motor cortex (M1) and supplementary motor area (SMA) were compared in monkeys rendered parkinsonian by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The neuronal dynamic was characterized using mathematical tools defined in different frameworks (rate, oscillations or complex patterns). Then, and for each cortical area, multivariate and discriminate analyses were further performed on these features to identify those important to differentiate between the normal and the pathological neuronal activity. Our results show a different order in the importance of the features to discriminate the pathological state in each cortical area which suggests that the M1 and the SMA exhibit dissimilarities in their neuronal alterations induced by parkinsonism. Our findings highlight the need for multiple mathematical frameworks to best characterize the pathological neuronal activity related to parkinsonism. Future translational studies are warranted to investigate the causal relationships between cortical region-specificities, dominant pathological hallmarks and symptoms.

Local field potential dynamics in the primate cortex in relation to parkinsonism reveled by machine learning: A comparison between the primary motor cortex and the supplementary area.

The present study compares the cortical local field potentials (LFPs) in the primary motor cortex (M1) and the supplementary motor area (SMA) of non-human primates rendered Parkinsonian with administration of dopaminergic neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The dynamic of the LFPs was investigated under several mathematical frameworks and machine learning was used to discriminate the recordings based on these features between healthy, parkinsonian with off-medication and parkinsonian with on-medication states. The importance of each feature in the discrimination process was further investigated. The dynamic of the LFPs in M1 and SMA was affected regarding its variability (time domain analysis), oscillatory activities (frequency domain analysis) and complex patterns (non-linear domain analysis). Machine learning algorithms achieved accuracy near 0.90 for comparisons between conditions. The TreeBagger algorithm provided best accuracy. The relative importance of these features differed with the cortical location, condition and treatment. Overall, the most important features included beta oscillation, fractal dimension, gamma oscillation, entropy and asymmetry of amplitude fluctuation. The importance of features in discriminating between normal and pathological states, and on- or off-medication states depends on the pair-comparison and it is region-specific. These findings are discussed regarding the refinement of current models for movement disorders and the development of on-demand therapies.

Computed tomographic method to quantify electrode lead deformation and subdural gap after lead implantation for deep brain stimulation.

BACKGROUND: Deep brain stimulation is an effective treatment for movement disorders and psychiatric conditions. Intra-operative and post-operative events can result in brain tissue deformation (i.e. subdural gaps) which may cause lead deformation and its displacement from optimal target. We developed a method to quantify postoperative lead deformation and we present two DBS cases to illustrate the phenomena of lead deformation resulting from the development of subdural gaps. NEW METHOD: We present a semi-automatic computational algorithm using Computed Tomography scanning with reconstruction to determine lead curvature relative to a theoretical straight lead between the skull entry site and lead tip. Subdural gap was quantified from the CT scan. RESULTS: In 2 patients who had leads implanted, analysis of CT scans was completed within 5 min each. The maximum deviation of the observed lead from the theoretical linear path was 1.1 and 2.6 mm, and the subdural gap was 5.5 and 9.6 mL, respectively. COMPARISON WITH EXISTING METHOD(S): This is the first method allowing a comprehensive characterization of the lead deformation in situ. CONCLUSIONS: The computational algorithms provide a simple, semiautomatic method to characterize in situ lead curvature related to brain tissue deformation after lead placement.

Complex Dynamics in the Basal Ganglia: Health and Disease Beyond the Motor System.

The rate and oscillatory hypotheses are the two main current frameworks of basal ganglia pathophysiology. Both hypotheses have emerged from research on movement disorders sharing similar conceptualizations. These pathological conditions are classified either as hypokinetic or hyperkinetic, and the electrophysiological hallmarks of basal ganglia dysfunction are categorized as prokinetic or antikinetic. Although nonmotor symptoms, including neurobehavioral symptoms, are a key manifestation of basal ganglia dysfunction, they are uncommonly accounted for in these models. In patients with Parkinson's disease, the broad spectrum of motor symptoms and neurobehavioral symptoms challenges the concept that basal ganglia disorders can be classified into two categories. The profile of symptoms of basal ganglia dysfunction is best characterized by a breakdown of information processing, accompanied at an electrophysiological level by complex alterations of spiking activity from basal ganglia neurons. The authors argue that the dynamics of the basal ganglia circuit cannot be fully characterized by linear properties such as the firing rate or oscillatory activity. In fact, the neuronal spiking stream of the basal ganglia circuit is irregular but has temporal structure. In this context, entropy was introduced as a measure of probabilistic irregularity in the temporal organization of neuronal activity of the basal ganglia, giving place to the entropy hypothesis of basal ganglia pathology. Obtaining a quantitative characterization of irregularity of spike trains from basal ganglia neurons is key to elaborating a new framework of basal ganglia pathophysiology.

Parkinsonian Balance Deficits Quantified Using a Game Industry Board and a Specific Battery of Four Paradigms.

This study describes a cost-effective screening protocol for parkinsonism based on combined objective and subjective monitoring of balance function. Objective evaluation of balance function was performed using a game industry balance board and an automated analyses of the dynamic of the center of pressure in time, frequency, and non-linear domains collected during short series of stand up tests with different modalities and severity of sensorial deprivation. The subjective measurement of balance function was performed using the Dizziness Handicap Inventory questionnaire. Principal component analyses on both objective and subjective measurements of balance function allowed to obtained a specificity and selectivity for parkinsonian patients (vs. healthy subjects) of 0.67 and 0.71 respectively. The findings are discussed regarding the relevance of cost-effective balance-based screening system as strategy to meet the needs of broader and earlier screening for parkinsonism in communities with limited access to healthcare.

Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.

The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.

An entropy-based model for basal ganglia dysfunctions in movement disorders.

During this last decade, nonlinear analyses have been used to characterize the irregularity that exists in the neuronal data stream of the basal ganglia. In comparison to linear parameters for disparity (i.e., rate, standard deviation, and oscillatory activities), nonlinear analyses focus on complex patterns that are composed of groups of interspike intervals with matching lengths but not necessarily contiguous in the data stream. In light of recent animal and clinical studies, we present a review and commentary on the basal ganglia neuronal entropy in the context of movement disorders.

Non-linear dynamics in parkinsonism.

Over the last 30 years, the functions (and dysfunctions) of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the "rate hypothesis" and the "oscillatory hypothesis." In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively. More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e., parkinsonism, dyskinesia, healthy control) and are responsive to treatments (i.e., l-DOPA, deep brain stimulation). A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series) is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG), muscular activities (EMG), or kinetic of motor symptoms (tremor, gait) of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity, and hypokinesia.

The aging striatal dopamine function.

Movement disorders are prevalent in the elderly and may have both central and peripheral origins. Age-related parkinsonism often results in movement disorders identical to some of the cardinal symptoms of typical Parkinson's disease (TPD). Nevertheless, there may be limited similarity in the underlying dysfunction of the sensory-motor circuitry since these two conditions exhibit different changes in the nigro-striatal pathway. In this short review, we highlight some of the key distinctions between aging and TPD regarding striatal dopaminergic activity and discuss them in the context of therapeutic strategies to alleviate motor decline in the elderly.

Nonlinear temporal organization of neuronal discharge in the basal ganglia of Parkinson's disease patients.

Previous electrophysiological studies of the basal ganglia in Parkinson's disease (PD) patients have utilized linear analyses in time-or-frequency-domains to characterize neuronal discharge patterns. However, these measures do not fully describe the non-linear features of discharge rates and oscillatory activities of basal ganglia neurons. In this original research, we investigate whether non-linear temporal organizations exist in the inter-spike interval series of neurons recorded in the globus pallidus or the subthalamic nucleus in PD patients undergoing surgery for the implantation of deep brain stimulating electrodes. Our data indicate that in approximately 80% of globus pallidus and subthalamic neurons, the raw inter-spike interval sequences have lower entropy values than those observed after shuffling of the original series. This is the first report establishing non-linear temporal organization as a common feature of neuronal discharge in the basal ganglia of PD patients.

Nonlinear temporal organization of neuronal discharge in the basal ganglia of Parkinson's disease patients.

Previous electrophysiological studies of the basal ganglia in Parkinson's disease (PD) patients have utilized linear analyses in time-or-frequency domains to characterize neuronal discharge patterns. However, these measures do not fully describe the non-linear features of discharge rates and oscillatory activities of basal ganglia neurons. In this original research, we investigate whether non-linear temporal organizations exist in the inter-spike interval series of neurons recorded in the globus pallidus or the subthalamic nucleus in PD patients undergoing surgery for the implantation of deep brain stimulating electrodes. Our data indicate that in approximately 80% of globus pallidus and subthalamic neurons, the raw inter-spike interval sequences have lower entropy values than those observed after shuffling of the original series. This is the first report establishing non-linear temporal organization as a common feature of neuronal discharge in the basal ganglia of PD patients.

A non-invasive technique to monitor wakefulness during electrophysiologic recording experiments in primates.

Although the state of wakefulness has an impact on many physiological parameters, this variable is seldom controlled for in in vivo experiments, because the existing techniques to identify periods of wakefulness are laborious and difficult to implement. We here report on a simple non-invasive technique to achieve this goal, using the analysis of video material, collected along with the electrophysiologic data, to analyze eyelid movements. The technique was applied to recordings in non-human primates, and allowed us to automatically identify periods during which the subject has its eyes open. A comparison with frontal electroencephalographic records confirmed that such periods corresponded to wakefulness.