Electrophysiological Classification Research Articles

Nodopathy: clinic, diagnosis, treatment. Clinical description

AIM: Evaluation of the significance and possibilities of laboratory-instrumental diagnostic methods in establishing the diagnosis and selection of targeted therapy in patients with nodopathies.
 MATERIALS AND METHODS: System analysis of data from foreign and domestic literature with the presentation of a clinical case.
 RESULTS: Polyneuropathies are classified as demyelinating or axonal based on electrophysiological studies. However, in 2015, in addition to axonal and demyelinating neuropathies, it was proposed to distinguish a separate pathophysiological group — nodopathies. The pathogenesis of nodopathies may differ depending on the type of ion channels involved in the process, but always leads to a loss of excitability of the axon membrane; in the nodal region the membrane becomes inexcitable. Such neuropathies are characterized by transient conduction blocks followed by the development of axonal degeneration. Typical examples of nodopathies are acute motor axonal neuropathy, as well as multifocal motor neuropathy. Current pathophysiological understanding of specialized nodal regions (nodes of Ranvier) and associated axoglial proteins is growing. Hypotheses have been put forward about their role in the pathogenesis of immune-mediated attack on the peripheral myelinated axon. Recently, high titers of antibodies directed against a number of key adhesion molecules have been identified in both acute and chronic inflammatory neuropathies. These facts add to the differences in differential diagnosis between axonal and demyelinating peripheral neuropathies. New disease classification schemes based on seropositivity, improved electrophysiological and ultrasound classification, and identification of putative underlying pathological targets and mechanisms are being rapidly developed.
 CONCLUSION: Using our clinical example, we demonstrated the capabilities of laboratory and instrumental diagnostic methods in establishing a diagnosis in a patient with one of the forms of nodopathies — multifocal motor neuropathy.

AĞIR KARPAL TÜNEL SENDROMU İÇİN RİSK FAKTÖRLERİNİN İNCELENMESİ - EV HANIMLIĞI BİR RİSK Mİ?

Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy. In this study, risk factors of severe CTS were examined. This study was conducted on 227 patients diagnosed with CTS in EMG laboratuary. The criteria of American Academy of Electrodiagnostic Medicine was used as the diagnosis for CTS. All patients were examined for bilateral median and ulnar motor and sensory peak latency, amplitude and conduction velocities. The patients were classified into 4 groups electrophysiologically; Normal, Light, Medium, Severe. Electrophysiological classification was compared with the identified risk factors. The mean age of the patients was 51.04±13.37 (min=18-max=83). Severe CTS cases in both hands were higher in housewives. Housewifery increased the risk of severe CTS in the right and left hand by 2.74 and 2.23 times, respectively. In addition, obesity increased the risk of severe CTS in the right and left hand by 5.10-4.40, presence of lateral epicondylitis was 2.73-4.19 and medial epicondylitis was 4.39-4.93, respectively. Hand dominancy was increased the risk of severe CTS by 6.88 times for the left hand and 1.15 times for the right hand. Otherwise in multivariate analyse of left hand results, obesity increase the risk of severe CTS by 3.34, left hand dominancy 7.83 times, chronic disease 2.62 times, and for the right hand being a housewife increases the risk by 2.14, obesity 4.68 times and medial epicondylitis 6.40 times. This study put forth that being a housewife, obesity, dominant hand, presence of lateral or medial epicondylitis are the risk factors of severe CTS.

Association Between A-Waves and Outcome in Pediatric Guillain-Barré Syndrome.

IntroductionTo examine the importance of abundant A-waves in electrophysiological classification and prognosis of pediatric Guillain-Barré Syndrome (GBS).MethodsA single-center and retrospective study enrolling 65 children-patients, aged 16 years and younger, with clinically diagnosed GBS between 2013 to 2020. Hughes grade was used to assess functional disability at nadir, 1 month, and 6 months after symptom onset. Patients were divided into 2 groups according to the presence of abundant A-waves. Clinical features and prognosis between the 2 groups were compared.ResultsThe distal motor latency of the median nerve in patients with GBS with A-waves (9.18 ms) was more prolonged than that of patients with GBS without A-waves (4.1 ms). An electrophysiological variant of these two groups was also statistically different (p = 0.006). The short-term prognosis of patients with AIDP with A-waves was worse than patients with AIDP without A-waves (χ2 = 5.022, p = 0.025), and univariable logistic regression analysis showed statistically significant (OR: 5.844, 95% CI 1.118–30.553; p = 0.036).ConclusionA-waves were strongly associated with demyelination and poor short-term prognosis of AIDP in children. We proposed an electrophysiological marker for early prediction of outcome in the AIDP subtype of GBS, applicable for clinical practice and future treatment administration.

Eczematous skin reaction after intravenous immunoglobulin therapy in axonal Guillain-Barré syndrome

Background: Intravenous immunoglobulin (IVIG) treatment in Guillain-Barré syndrome (GBS) is relatively easy to administer and safe due to infrequent, non-severe side effects. Adverse effects can include skin reactions, the causes of which have not been fully elucidated. In this study, we investigated skin reactions following IVIG treatment for acute inflammatory neuropathy. We examined the relationship between the clinical results in the neuropathy and the clinical profile of skin reactions. Methods: We retrospectively analyzed patients with skin reactions that developed after IVIG treatment in acute immune-mediated or inflammatory neuropathy [GBS or Miller Fisher syndrome (MFS)] based on the dermatologic evaluation. Results: Ninety-six patients with acute inflammatory neuropathy were treated with IVIG during the study period. Thirteen cases (13.5%), with age at onset ranging from 22–69 years (mean, 50.3 years), developed skin reactions after IVIG treatment. The features accompanying skin reactions were hand eczema, including pompholyx (9/13, 82%), generalized eczematous eruption (2/13, 15.4%), and contact dermatitis, including folliculitis. The electrophysiological classification of 11 patients with classical GBS showed that nine patients (81.8 %) had axonal neuropathy, and one (9.1 %) had acute inflammatory demyelinating polyradiculoneuropathy. Conclusions: Eczematous skin reactions or pompholyx are the most common skin reactions following IVIG treatment in axonal GBS. These reactions were relatively minor and recovered well. Although adverse skin reactions to IVIG were usually benign and the precise mechanism of this cutaneous eruption remains unknown, its occurrence within days of IVIG treatment can be managed effectively if recognized by neurologists.

Hierarchical Classification of Event-Related Potentials for the Recognition of Gender Differences in the Attention Task.

Research on the functioning of human cognition has been a crucial problem studied for years. Electroencephalography (EEG) classification methods may serve as a precious tool for understanding the temporal dynamics of human brain activity, and the purpose of such an approach is to increase the statistical power of the differences between conditions that are too weak to be detected using standard EEG methods. Following that line of research, in this paper, we focus on recognizing gender differences in the functioning of the human brain in the attention task. For that purpose, we gathered, analyzed, and finally classified event-related potentials (ERPs). We propose a hierarchical approach, in which the electrophysiological signal preprocessing is combined with the classification method, enriched with a segmentation step, which creates a full line of electrophysiological signal classification during an attention task. This approach allowed us to detect differences between men and women in the P3 waveform, an ERP component related to attention, which were not observed using standard ERP analysis. The results provide evidence for the high effectiveness of the proposed method, which outperformed a traditional statistical analysis approach. This is a step towards understanding neuronal differences between men’s and women’s brains during cognition, aiming to reduce the misdiagnosis and adverse side effects in underrepresented women groups in health and biomedical research.

Correlation Nerve Conduction Studies with Findings of the Ultrasound of the Median Nerve in Patients with Carpal Tunnel Syndrome

Background: Ultrasonography is a diagnostic resource that serves as a complement in the evaluation of patients with carpal tunnel syndrome. The correlation of ultrasonography findings with nerve conduction studies can serve to classify new phenotypes and to evaluate therapeutic responses. Objectives: To determine the diagnostic sensitivity of ultrasound, the correlation between the diameter of the nerve (CSA) against the motor and sensitive latencies, and the capacity to differentiate the mild, moderate and severe degrees of the electrophysiological classification of carpal tunnel syndrome. Methods: A cross-sectional study with prospective data collection was carried out. An ultrasonography system with a 15 MHz transducer was used. Nerve conduction studies of the median nerve were performed with conventional techniques. Data from the most symptomatic hand were used. Determination of the correlations of nerve diameter with motor and sensitive latencies of the median nerve was performed in four age groups: <40(n=11), 40-54 (n=47), 55-70 (n=42) y >70(n=27). Results : A total of 127 patients were evaluated (average age = 58.2 years: minimum = 26; maximum = 85; SD = 13.4); 109 (85.8%) were female patients. According to the electrophysiological classification, 40 (31.5%) were mild ; 60 (47.2%) were moderate ; and 27 (21.3%) were severe . Significant differences in the area of the median nerve were found between the electrophysiological types (mild, moderate and severe; p = 0.000). The diagnostic sensitivity of ultrasonography differed for each age group. In general, the diagnostic sensitivity was high in patients with severe cases and low for mild cases. The capacity for ultrasonography to classify the degrees of electrophysiological severity was different for each age group. For patients above 70 years and in the age group of 40 to 54 years, the CSA did not differentiate the electrophysiologically moderate cases from the severe ones. Conclusions: There is a well-defined and significant correlation between nerve conduction studies and median nerve diameter in patients with Carpal Tunnel Syndrome. However, it shows that the exclusive use of the ultrasonographic measurement of the cross-sectional area through the inlet of the carpal tunnel would not be enough to confirm or rule out an entrapment of the median nerve through the carpal tunnel, nor to predict in every case their electrophysiological severity.

Unclassified subtype of Guillain-Barré syndrome is associated with quick recovery

Electrophysiological classification of Guillain-Barré syndrome (GBS) is important for predicting its clinical course. However, few reports discuss GBS patients who do not fit into the acute inflammatory demyelinating polyneuropathy (AIDP) or acute motor axonal neuropathy (AMAN) classifications of GBS. Therefore, the present study focused on the features of unclassified types of GBS and compared these to AIDP and AMAN.

Unclassified subtype of Guillain-Barré syndrome is associated with quick recovery

Electrophysiological classification of Guillain-Barré syndrome (GBS) is important for predicting its clinical course; however, few reports discuss GBS patients who do not conform to the acute inflammatory demyelinating polyneuropathy (AIDP) or acute motor axonal neuropathy (AMAN) classifications. Therefore, the present study assessed the features of unclassified types of GBS and compared them to those of AIDP and AMAN. We compared clinical symptoms, nerve conduction, and laboratory data among patients with AIDP, AMAN, and unclassified subtypes of GBS, according to criteria developed by Rajabally, Hadden, and Ho. According to the Rajabally criteria, the F wave frequency in the upper and lower extremities was higher in the unclassified subgroup than in the AIDP and AMAN subgroups; however, according to the Hadden and Ho criteria, the F wave frequency in only the lower extremities was higher in the unclassified subgroup than in the other subgroups. The unclassified subgroup showed better prognosis using the Rajabally criteria. Classification with the Rajabally criteria is useful for predicting prognosis and determining treatment in patients with GBS. Moreover, unclassified patients exhibit the quickest recovery.

Electrophysiological properties of maxillary trigeminal Aβ-afferent neurons of rats.

Aβ-afferents in maxillary or V2 trigeminal ganglion (TG) neurons are somatosensory neurons that may be involved in both non-nociceptive and nociceptive functions in orofacial regions. However, electrophysiological properties of these V2 trigeminal Aβ-afferent neurons have not been well characterized so far. Here, we used rat ex vivo trigeminal nerve preparations and applied patch-clamp recordings to large-sized V2 TG neurons to characterize their electrophysiological properties. All the cells recorded had afferent conduction velocities in the range of Aβ-afferent conduction speeds. However, these V2 trigeminal Aβ-afferent neurons displayed different action potential (AP) properties. APs showed fast kinetics in some cells but slow kinetics with shoulders in repolarization phases in other cells. Based on the derivatives of voltages in AP repolarization with time (dV/dt), we classified V2 trigeminal Aβ-afferent neurons into four types: type I, type II, type IIIa and type IIIb. Type I V2 trigeminal Aβ-afferent neurons had the largest dV/dt of repolarization, the fastest AP conduction velocities, the shortest AP and afterhyperpolarization (AHP) durations, and the highest AP success rates. In contrast, type IIIb V2 trigeminal Aβ-afferent neurons had the smallest dV/dt of AP repolarization, the slowest AP conduction velocities, the longest AP and AHP durations, and the lowest AP success rates. The type IIIb cells also had significantly lower voltage-activated K+ currents. For type II and type IIIa V2 trigeminal Aβ-afferent neurons, AP parameters were in the range between those of type I and type IIIb V2 trigeminal Aβ-afferent neurons. Our electrophysiological classification of V2 trigeminal Aβ-afferent neurons may be useful in future to study their non-nociceptive and nociceptive functions in orofacial regions.

Transparent Electrophysiological Muscle Classification From EMG Signals Using Fuzzy-Based Multiple Instance Learning.

Although a well-established body of literature has examined electrophysiological muscle classification methods and systems, ways to enhance their transparency is still an important challenge and requires further study. In this work, a transparent semi-supervised electrophysiological muscle classification system which uses needle-detected EMG signals to classify muscles as normal, myopathic, or neurogenic is proposed. The electrophysiological muscle classification (EMC) problem is naturally formulated using multiple instance learning (MIL) and needs an adaptation of standard supervised classifiers for the purpose of training and evaluating bags of instances. Here, a novel MIL-based EMC system in which the muscle classifier uses predictions based on motor unit potentials (MUPs) to infer muscle labels is described. This system uses morphological, stability, near fiber and spectral MUP features. Quantitative results obtained from applying the proposed transparent system to four electrophysiologically different groups of muscles, composed of proximal and distal hand and leg muscles, resulted in an average classification accuracy of 95.85%. The findings show the superior and stable performance of the proposed EMC system compared to previous works using other supervised, semi-supervised and unsupervised methods.

Atrial Flutter: up-to-date Problem Evaluation with Clinical Positions

The review provides current ideas about the etiology and prevalence of atrial flutter (AF), mechanism and substrate of arrhythmogenesis, and principles of clinical and electrophysiological classification of this arrhythmia. Methods for conservative and surgical treatments of AF, including their comparative aspect, are described in detail. The review presented recent data on efficacy and potential risks of different approaches to reversing the arrhythmia. The authors indicated a need for early diagnosis and strict control of the sinus rhythm in AF, which would help a successful intervention not only to completely cure the existing arrhythmia but also to prevent other heart rhythm disorders, primarily atrial fibrillation.

The Association between Causes and Electrophysiology in Myoclonus

Objective: We aimed to identify the possible causes of myoclonus and related electrophysiological features in a cohort of young patients. Patients and Methods: We performed a retrospective analysis of all clinical and electrophysiological recordings of patients who had myoclonus and were under 60 years between 2005 and 2018. The clinical data included age at examination, gender, age at onset, and main neurological or systemic findings, underlying cause and electrophysiological features constituted surface electromyogram, long-loop reflexes, electroencephalography, and somatosensory-evoked potentials. Results: In the study period, we identified 155 patients with myoclonus. Myoclonus was most commonly related with epilepsy and movement disorders. Myoclonus with epilepsy was the leading cause between 10 and 30 years, whereas myoclonus with movement disorders was more common after 30 years. In our country, SSPE was an important cause of myoclonus under the 20 years of age. We identified cortico-subcortical subtype followed by cortical, cortical reflex, subcortical-basal ganglia, subcortical-brainstem and propriospinal subtypes, and correlated these subtypes with relevant disorders. Conclusion: The electrophysiological classification provides anatomical subtyping, which is favorable in diagnosing certain cases such as brainstem and propriospinal myoclonus. Certain characteristics such as reflex nature of myoclonus and accompanying features narrow the list of differentials and help in making the diagnosis.

Tremoroton, a new free online platform for tremor analysis

ObjectiveThe electrophysiological classification of tremors can be a key element in the diagnosis and can facilitate treatment of a patient with tremor; however, the ability to conduct electrophysiological studies of tremor is not widely available. The purpose of this study was to develop and validate a free online platform for tremor analysis. MethodsAn online platform for tremor analysis was developed using “R” language; called “Tremoroton”. For validation, we compared the frequency estimation of the tremor obtained with Tremoroton compared with a commercially available software in a cohort of 20 patients (10 with essential tremor and 10 with Parkinson diagnosis), comparing the activity recorded on the accelerometer, extensor carpi radialis and flexor carpi radialis EMG. An intraclass correlation coefficient was used for the comparison. ResultsThe final version of tremoroton is now online. It allows reading up to 6 channels, and will do time, frequency, time-frequency analysis and calculate coherence. We demonstrated a high correlation in frequency measurements (0.97 (0.945–0.984, 95% IC) for the accelerometers, 0.98 (0.977–0.994, 95% IC) for the extensor carpi radialis EMG, and 0.99 (0.987–0.997, 95% IC) for the flexor carpi radialis EMG) when compared to a commercial software. ConclusionWe were able to develop and validate a free online platform for tremor analysis. SignificanceMaking this tool available should help expanding tremor analysis techniques from research to the clinical setting.

Electrophysiological Assessment and Classification of Motor Pathway Function in Patients With Spinal Dural Arteriovenous Fistula.

The diagnosis of spinal dural arteriovenous fistula (SDAVF) is difficult and often delayed because clinical features are often nonspecific. We assessed the motor function electrophysiologically in patients with SDAVF. Motor-evoked potentials after transcranial magnetic stimulation and compound muscle action potentials and F-waves after electrical stimulation in the ulnar and tibial nerves were measured from the abductor hallucis (AH) muscles in 14 patients with SDAVF (SDAVF group), 12 patients with compressive thoracic myelopathy (CTM group), and 16 normal subjects (control group). The peripheral conduction time determined from abductor hallucis muscles (PCT-AH) and the central motor conduction time determined from abductor hallucis muscles (CMCT-AH) were calculated. According to the neurological findings, patients in the SDAVF group were classified to upper motor neuron (UMN) sign and lower motor neuron (LMN) sign categories. CMCT-AH in the SDAVF and CMT groups were significantly longer than those in the control group. PCT-AH in the SDAVF group was significantly longer than that in the control and CMT groups. Twelve patients in the SDAVF group showed abnormal CMCT-AH and/or PCT-AH. Abnormal CMCT-AH and PCT-AH were detected in five cases that exhibited UMN sign and/or LMN sign. Three cases with abnormal CMCT-AH and normal PCT-AH exhibited UMN sign. LMN sign without UMN sign was observed in four cases with abnormal PCT-AH and normal CMCT-AH. Our study revealed abnormalities in the corticospinal tract and/or lower motor neurons, and classified the patients with SDAVF into three types: the UMN type, LMN type, and mixed type.

Electrophysiological Muscle Classification Using Multiple Instance Learning and Unsupervised Time and Spectral Domain Analysis.

Electrophysiological muscle classification (EMC) is a crucial step in the diagnosis of neuromuscular disorders. Existing quantitative techniques are not sufficiently robust and accurate to be reliably clinically used. Here, EMC is modeled as a multiple instance learning (MIL) problem and a system to infer unsupervised motor unit potential (MUP) labels and create supervised muscle classifications is presented. The system has five main steps: MUP representation using morphological, stability, and near fiber parameters as well as spectral features extracted from wavelet coefficients; MUP feature selection using unsupervised Laplacian scores; MUP clustering using neighborhood distance entropy consistency to find representations of MUP normality and abnormality; muscle representation by embedding its MUP cluster associations in a feature vector; and muscle classification using support vector machines or random forests. The evaluation data consist of 63, 83, 93, and 84 sets of MUPs recorded in deltoid, vastus medialis, first dorsal interosseous, and tibialis anterior muscles, respectively. The proposed system discovered representations of normal, myopathic, and neurogenic MUPs for each specific muscle type and resulted in an average classification accuracy of 98%, which is higher than in previous works. Modeling EMC as an instance of the MIL solves the traditional problem of characterizing MUPs without full supervision. Furthermore, finding representations of MUP normality and abnormality using morphological, stability, near fiber, and spectral features improve muscle classification. The proposed method is able to characterize MUPs with respect to disease categories, with no a priori information.

P2-03. An electrophysiological severity classification system for diabetic polyneuropathy and small fiber dysfunction

We reported an electrophysiological severity classification for diabetic polyneuropathy (DPN) using a nerve conduction study (NCS). This new classification system combines of the amplitude and velocity of NCS and classifies DPN into five stages. Stage 0 is the mildest stage, while Stage IV is the most severe. Here, we clarified the association of this classification system with small fiber abnormalities. We measured intra-epidermal nerve fiber densities (IENFD) and pain threshold using intra-epidermal electrical stimulation (IES) to evaluate the function of small fibers. We recruited 65 patients with diabetes, and performed NCS, skin biopsy and pain threshold using IES. The mean IENFD observed in the skin biopsies were 8.27 n/mm in Stage 0, 7.79 n/mm in Stage I, 4.49 n/mm in Stage II, 2.85 n/mm in Stage III, and 0 n/mm in Stage IV. The mean pain thresholds were 0.05 mA in Stage 0, 0.11 mA in Stage I, 0.08 mA in Stage II, 0.27 mA in Stage III, and 0.59 mA in Stage IV. In summary, the abnormalities of IENFD and pain threshold correlated with electrophysiological severity. The present results indicate that the large fiber dysfunction in DPN progresses in parallel with the small fiber abnormalities.

Reliability of neuroconduction studies in carpal tunnel syndrome

To determine the reliability of neuroconduction studies by comparing two observers and detecting minimum changes when diagnosing carpal tunnel syndrome. Sixty-nine patients referred for electrophysiological study due to suspected carpal tunnel syndrome were studied. The patients underwent two examinations, performed by two evaluators, on two different days. Sensory and motor latencies of the median and ulnar nerves were evaluated; all were classified as negative, incipient, mild, moderate, severe or extreme. Relative interval variation, intraclass correlation coefficient, kappa index, limit of agreement and minimum detectable change were estimated. The relative variation of motor nerve latency of the median nerve was -6.8% to 15.9%, with intraclass correlation coefficient of 0.98 for the difference of median-ulnar nerve latency. The minimum detected change was 0.4ms, while the relative interval variation of sensory latency of the median nerve was -5.0% to 11%, with intraclass correlation coefficient of 0.95 for difference with the ulnar nerve. The minimum detectable change was 0.2ms. Electrophysiological classification agreed in 93% of the cases, with a kappa index of 0.89. Sensory and motor latencies of the median nerve, as well as the difference between them and the ulnar nerve, are reliable measures. The minimum detectable change obtained in our study helps clinicians to establish whether changes in latencies in consecutive or post-treatment studies are significant.

Blink reflex role in algorithmic genetic testing of inherited polyneuropathies.

In severely affected inherited polyneuropathy patients, primary demyelination can be difficult to determine by routine extremity limb nerve conduction studies (NCS). Blink reflexes may help classify severe polyneuropathies as either axonal or demyelinating. However, blink reflex studies have not been studied systematically in any genetically confirmed cohort. Patients with a genetic diagnosis who had undergone blink reflex testing and extremity NCS were identified retrospectively. Blink reflex R1 latency, extremity NCS, and severity were compared. We identified 26 demyelinating and 23 axonal, genetically confirmed cases, including 20 with PMP22 duplications. In 12 (25%), the ulnar CMAP amplitude was ≤0.5 mV making electrophysiological classification difficult. However, the R1-latency cutoff of >13 ms (demyelinating) robustly classified all patients regardless of severity. We show that blink reflex studies are reliable for identification of inherited demyelinating polyneuropathy regardless of severity and can facilitate algorithmic decisions in genetic testing. Muscle Nerve 55: 316-322, 2017.

43. The quest for optimal electrodiagnosis of Guillain–Barre’ syndrome subtypes: criteria sets versus a linear discriminant analysis model

Up to 38% of Guillain-Barré syndrome (GBS) patients change electrophysiological classification after serial recordings. Aim of this study is to compare at the first electrodiagnostic test the predictivity of final diagnosis of three diagnostic criteria sets versus a regularized form of linear discriminant analysis (LDA) model. In 98 GBS patients with serial conduction studies in three motor and sensory nerves 24 electrophysiological variables were analyzed. Final diagnosis, established by serial studies and result of anti-ganglioside antibodies testing, revealed 54 demyelinating and 44 axonal GBS. We applied a sparse LDA method which is a technique for partitioning a vector of parameters (predictors) into one of the two classes (demyelinating or axonal) based on a linear projection learned from the 98 labeled patients. The evaluation of the discriminant power of sparse LDA is based on the leave one out cross validation procedure. We also employed the electrodiagnostic criteria sets developed by Hadden et al. (1998), by Rajabally et al. (2015) and by us. The overall misclassification error rate of sparse LDA at first test is 14% with a sensitivity for demyelinating GBS of 87% and a specificity of 84%. Distal motor latency, duration of distal motor potentials, proximal/distal motor amplitude ratio and sensory nerve action potential amplitude play a prominent role for the appropriate classification of patients. The overall misclassification error rates with the electrodiagnostic criteria are: 45% for Hadden’s, 43% for Rajabally’s and 26% for ours. Conclusions: (1) the model based on sparse LDA performs much better than the “a priori” established criteria sets; (2) the criteria set we developed, including the analysis of duration of distal motor potentials and of sensory nerve action potential amplitude, performs better than the other two; (3) only serial studies were able to demonstrate reversible conduction failure in motor and sensory fibers.

EP 63. Spectral analysis and visualization of multi-unit activity in subthalamic nucleus in Parkinson’s as a tool for automated electrophysiological classification of basal ganglia structures during deep brain stimulation procedures

Introduction In deep brain stimulation (DBS) of the subthalamic nucleus (STN) intraoperative microelectrode recordings (MER) are a well-established method for electrophysiological stereotactic target identification. Despite the main electrophysiological properties of STN are already well described ( [Cagnan et al., 2011] , [Seifried et al., 2012] ), mapping of STN rely on visual and acoustic inspection of raw recordings of MER trajectories. In this study we analyzed spectral decomposition and spike train patterns retrospectively of MER in STN-DBS to proposing a simple and reliable electrophysiological classification system. Secondly we suggest visualization techniques to present electrophysiological results in a user-friendly way. Patients and methods We analyzed MER in 7 patients with bilateral STN-DBS including 26 MER trajectories retrospectively. All recordings were carried out on multiple trajectories 10 mm prior and 4–5 mm below MR-tomographic STN target along planed DBS lead trajectory. Data was recorded intraoperative by Medtronic Leadpoint system using sharp microTargeting electrodes (FHC, USA). Offline Multi-Unit activity analysis was realized with Fieldtrip-Toolbox and Matlab, Mathworks. Statistical analysis of power spectral density, noise level and spike interstimulus interval were obtained through non-parametric student’s t-test. In purpose of visualization we integrated the stereotactic surgical plan to the electrophysiological results. Results Spectral density analysis showed a strong increase in frequency bands of 300–1000 Hz within STN borders. Spike train patterns within STN were heterogeneously and differed in firing rate and interstimulus interval to the key anatomical structures, thalamus and substantia nigra. Conclusion Through combination of spectral density analysis and spike train analysis we propose a simple and reliable MER signal classification method, which can be used for automated electrophysiological mapping of STN. Three-dimensional visualization of mapping results can provide help for decision of final DBS electrode implantation site.