Ilknur Telkes Ergun

Interests

Teaching

• biomedical signal processing• neural engineering

Research

• Investigate neural pathways responsible for chronic pain and identify signatures for objective pain assessment.• Develop computational tools for clinical applications such as brain/spinal mapping, target localization, data visualization • Enhance real-time and neural data analysis to improve the precision of therapeutic interventions (e.g., SCS, DBS).• Integrate machine learning and multimodality approach for personalized neuromodulation therapies, adapting treatment to individual patient responses.

Courses

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Scholarly Contributions

Journals/Publications

• Andrade, F. S., Ornelas, J., Park, J., Engstrom, G., Shih, R. D., Ahn, H., & Telkes, I. (2024). Multimodal Biomedical Signal Acquisition Setup to Assess Chronic Pain in Older Adults With Alzheimer's Disease. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. doi:10.1109/EMBC53108.2024.10782487
• Berwal, D., Quintero, A., Telkes, I., DiMarzio, M., Harland, T., Paniccioli, S., Dalfino, J., Iyassu, Y., McLaughlin, B. L., & Pilitsis, J. G. (2024). Improved Selectivity in Eliciting Evoked Electromyography Responses With High-Resolution Spinal Cord Stimulation. Neurosurgery, 95(2), 322-329.
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  As spinal cord stimulation (SCS) offers a therapy for increasing numbers of patients with chronic pain and spinal cord injury, it becomes increasingly important to better understand its somatotopy. In this prospective study, we investigate whether high-resolution SCS (HR-SCS) offers improved selectivity assessed through elicitation of evoked electromyography (EMG) responses as compared with commercial paddle leads.
• Harland, T., Elliott, T., Telkes, I., & Pilitsis, J. G. (2024). Machine Learning in Pain Neuromodulation. Advances in experimental medicine and biology, 1462, 499-512.
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  This chapter highlights the intersection of pain neuromodulation and machine learning (ML), exploring current limitations in pain management and how ML techniques can address these challenges. Neuromodulation technologies, such as spinal cord stimulation (SCS), have emerged as promising interventions for chronic pain, but limitations such as patient selection have resulted in high rates of failure and costly removal of these devices. ML offers a powerful approach to augment pain management outcomes by leveraging predictive modeling for enhanced patient selection, adaptive algorithms for programming optimization, and identification of objective biomarkers for improved outcome assessment. This chapter discusses various ML applications in pain neuromodulation and how we can expect it to shape the future of the field. While ML holds great promise, challenges such as algorithm transparency, data quality, and generalizability must be addressed to fully realize its potential in revolutionizing pain management.
• Park, J., Tong, H., Kang, Y., Miao, H., Lin, L., Fox, R. S., Telkes, I., Martorella, G., & Ahn, H. (2024). Comparison of responders and nonresponders with knee osteoarthritis after transcranial direct current stimulation. Pain management, 14(9), 507-518.
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  The study compared responders and nonresponders to transcranial direct current stimulation (tDCS) regarding clinical pain outcomes in knee osteoarthritis (OA) patients.
• Quintero, A., Berwal, D., Telkes, I., DiMarzio, M., Harland, T., Morris, D. R., Paniccioli, S., Dalfino, J., Iyassu, Y., McLaughlin, B. L., & Pilitsis, J. G. (2024). Correlating Evoked Electromyography and Anatomic Factors During Spinal Cord Stimulation Implantation With Short-Term Outcomes. Neuromodulation : journal of the International Neuromodulation Society, 27(8), 1470-1478.
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  We examine ways intraoperative neuromonitoring during spinal cord stimulation (SCS) varies between a high-resolution investigational SCS (HR-SCS) paddle and a commercial paddle. Furthermore, the presence of evoked motor responses (eg, electromyography [EMG]) in painful regions during surgery is correlated to outcomes.
• Berwal, D., Telkes, I., Agarwal, S., Paniccioli, S., McCarthy, K., DiMarzio, M., McLaughlin, B., & Pilitsis, J. G. (2023). Investigation of the intraoperative cortical responses to spinal motor mapping in a patient with chronic pain. Journal of neurophysiology, 130(3), 768-774.
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  Intraoperative neurophysiological monitoring (IONM) in spinal cord stimulation (SCS) surgery for chronic pain is shown to provide effective guidance during device placement. Electromyography (EMG) is used to determine the laterality of the paddle. In some SCS cases, laterality cannot be obtained via EMG due to patient physiology. Electroencephalography (EEG) is already used in IONM to monitor cortical responses. Here, we show proof-of-concept of assessing the responses of epidurally evoked EMGs simultaneously with EEGs to determine laterality during IONM using a high-resolution (HR) SCS paddle. An 8-column HR-SCS paddle was acutely placed at T9-T10 interspace in patients with failed back surgery syndrome. EMG signals from 18 muscle groups were recorded simultaneously with 60-channel EEG signals at various stimulation amplitudes (0-10 mA). Particular attention was paid to regions associated with pain including the somatosensory cortex (S1), prefrontal cortex (PFC), and motor cortex (M1). When left and right lateral contacts were stimulated at low amplitudes (1-2 mA), significant changes were seen in θ, α, and β powers in the contralateral PFC but not in M1 or S1. There was a significant correlation between M1 and contralateral contacts in α power. At higher currents (7-8 mA), right-sided contacts resulted in α power change. We found significant differences in α, θ, and β powers in PFC for contralateral stimulation of the lateral SCS contacts at low amplitudes and in α power at higher amplitudes. The changes in PFC suggest the potential of EEG for understanding a cortical mechanism of action of SCS and provide insight into the pathophysiology of chronic pain. Here, we present proof of concept of assessing the responses of epidurally evoked electromyography simultaneously with scalp electroencephalography to determine whether both laterality and insights into pain mechanisms can be elucidated. With stimulation, significant changes were seen in θ, α, and β band power in the contralateral prefrontal cortex and in α power in the motor cortex. We provide insight into the mechanism of action of SCS in preventing pain in this patient.
• Hani Abdullah, U. E., Kelly, S., Ricker, A., Nabage, M., Khazen, O., Telkes, I., DiMarzio, M., Wilson, C., & Pilitsis, J. G. (2023). Perceptions of pain in aging females undergoing spinal cord stimulation. Pain management, 13(12), 701-708.
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  Effects of age and sex on chronic pain outcomes following spinal cord stimulation (SCS) have not yet been assessed. We retrospectively reviewed 1 year outcomes from a database of patients receiving thoracic SCS. Subjects were divided into four cohorts: pre-menopausal and post-menopausal females, and aged-matched males. Improvement using the numerical rating scale, Oswestry Disability Index (ODI), Beck's Depression Inventory (BDI), McGill Pain Questionnaire and Pain Catastrophizing Scale (PCS) was assessed. Older females were notably different from males and females under 60 as they had greater improvements in ODI, BDI and PCS. Further, females ≥60 had greater improvement in PCS compared with males ≥60. Our findings suggest greater improvement with 1 year SCS treatment in post-menopausal females, compared with age-matched males.
• Ozturk, M., Hernandez-Pavon, J. C., Kent, A., Pons, J. L., Telkes, I., & Tarakad, A. (2023). Editorial: Peripheral stimulation: neuromodulation of the central nervous system through existing pathways. Frontiers in neuroscience, 17, 1285474.
• Hadanny, A., Harland, T. A., Khazen, O., DiMarzio, M., Telkes, I., & Pilitsis, J. G. (2022). In Reply: Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation. Neurosurgery, 91(2), e68-e70.
• Hadanny, A., Harland, T., Khazen, O., DiMarzio, M., Marchese, A., Telkes, I., Sukul, V., & Pilitsis, J. G. (2022). Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation. Neurosurgery, 90(5), 523-532.
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  Despite spinal cord stimulation's (SCS) proven efficacy, failure rates are high with no clear understanding of which patients benefit long term. Currently, patient selection for SCS is based on the subjective experience of the implanting physician.
• Telkes, I., Hadanny, A., DiMarzio, M., Chitnis, G., Paniccioli, S., O'Connor, K., Grey, R., McCarthy, K., Khazen, O., McLaughlin, B., & Pilitsis, J. G. (2022). High-Resolution Spinal Motor Mapping Using Thoracic Spinal Cord Stimulation in Patients With Chronic Pain. Neurosurgery, 91(3), 459-469.
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  High-resolution spinal cord stimulation (HR-SCS) paddle can stimulate medial-dorsal columns and extend stimulation coverage to the laterally positioned spinal targets.
• DiMarzio, M., Madhavan, R., Hancu, I., Fiveland, E., Prusik, J., Joel, S., Gillogly, M., Telkes, I., Staudt, M. D., Durphy, J., Shin, D., & Pilitsis, J. G. (2021). Use of Functional MRI to Assess Effects of Deep Brain Stimulation Frequency Changes on Brain Activation in Parkinson Disease. Neurosurgery, 88(2), 356-365.
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  Models have been developed for predicting ideal contact and amplitude for subthalamic nucleus (STN) deep brain stimulation (DBS) for Parkinson disease (PD). Pulse-width is generally varied to modulate the size of the energy field produced. Effects of varying frequency in humans have not been systematically evaluated.
• Jiang, F., Elahi, B., Saxena, M., Telkes, I., DiMarzio, M., Pilitsis, J. G., & Golestanirad, L. (2021). Patient-specific modeling of the volume of tissue activated (VTA) is associated with clinical outcome of DBS in patients with an obsessive-compulsive disorder. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 5889-5892.
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  Deep brain stimulation (DBS) promises to treat an increasing number of neurological and psychiatric disorders. DBS outcome is directly a factor of optimal targeting of the relevant brain structures. Computational models can help to interpret a patient's outcome by predicting the volume of tissue activated (VTA) around DBS electrode contacts. Here we report results of a preliminary study of DBS in two patients with obsessive-compulsive disorder and show that VTA predictions, which are based on patient-specific volume conductor models, correlate with clinical outcome. Our results suggest that patient specific VTA calculation can help inform device programing to maximize therapeutic effects and minimize side effects.Clinical Relevance- Patient-specific modeling of the volume of activated tissue can predict clinical outcomes and thus, can help to optimize DBS device programing to maximize therapeutic effects.
• Staudt, M. D., Telkes, I., & Pilitsis, J. G. (2021). Editorial. Achieving optimal outcomes with deep brain stimulation for posttraumatic stress disorder. Journal of neurosurgery, 134(6), 1711-1713.
• Telkes, I., Behal, A., Hadanny, A., Olmsted, Z. T., Chitnis, G., McLaughlin, B., & Pilitsis, J. G. (2021). Rapid Visualization Tool for Intraoperative Dorsal Column Mapping Triggered by Spinal Cord Stimulation in Chronic Pain Patients. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 5760-5763.
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  Spinal cord stimulation (SCS) is a widely accepted effective treatment for managing chronic pain. SCS outcomes depend highly on accurate placement of SCS electrodes at the appropriate spine level for a desired pain relief. Intraoperative neurophysiological monitoring (IONM) under general anesthesia provides an objective real-time mapping of the dorsal columns, and has been shown to be a safe and effective tool. IONM applies stimulation to multiple electrode contacts at various intensities and monitors the triggered electromyography (EMG) responses in several muscle groups simultaneously. Therefore, it requires dynamic communication between neurosurgeon and neurophysiologist and continuous real-time annotations of the responses, which makes the procedure complex and experience-based. Here, we describe an automated data visualization tool that generates patient specific activity maps using intraoperatively collected signals. Responses were collected using a High-resolution (HR)-SCS lead with 8 columns of electrodes spanning the dorsal columns. Our JavaScript/Python based graphical user interface (GUI) provides a fast and robust visualization of EMG activity via denoising, feature extraction, normalization, and overlaying of the activity maps on body images in selected colormaps. In contrast to reviewing series of EMG signals, our user-friendly tool provides a rapid and robust analysis of stimulation effects on various muscle groups and direct comparison across subjects and/or stimulation settings. Future work includes expanding analytics capabilities and operating room implementation as a real-time processing tool that can be used in conjunction with the current IONM techniques.
• DiMarzio, M., Madhavan, R., Joel, S., Hancu, I., Fiveland, E., Prusik, J., Gillogly, M., Rashid, T., MacDonell, J., Ashe, J., Telkes, I., Feustel, P., Staudt, M. D., Shin, D. S., Durphy, J., Hwang, R., Hanspal, E., & Pilitsis, J. G. (2020). Use of Functional Magnetic Resonance Imaging to Assess How Motor Phenotypes of Parkinson's Disease Respond to Deep Brain Stimulation. Neuromodulation : journal of the International Neuromodulation Society, 23(4), 515-524.
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  Deep brain stimulation (DBS) is a well-accepted treatment of Parkinson's disease (PD). Motor phenotypes include tremor-dominant (TD), akinesia-rigidity (AR), and postural instability gait disorder (PIGD). The mechanism of action in how DBS modulates motor symptom relief remains unknown.
• Ozturk, M., Telkes, I., Jimenez-Shahed, J., Viswanathan, A., Tarakad, A., Kumar, S., Sheth, S. A., & Ince, N. F. (2020). Randomized, Double-Blind Assessment of LFP Versus SUA Guidance in STN-DBS Lead Implantation: A Pilot Study. Frontiers in neuroscience, 14, 611.
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  The efficacy of deep brain stimulation (DBS) therapy in Parkinson's disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients' symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent. Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline. We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, = 3 STNs). The selected tracks were characterized by higher activity in beta (11-32 Hz) and high-frequency (200-400 Hz) bands ( < 0.01) of LFPs and stronger non-linear coupling between these bands ( < 0.05). Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.
• Telkes, I., Hancu, M., Paniccioli, S., Grey, R., Briotte, M., McCarthy, K., Raviv, N., & Pilitsis, J. G. (2020). Corrigendum to "Differences in EEG patterns between tonic and high frequency spinal cord stimulation in chronic pain patients" [Clin. Neurophysiol. 131(8) (2020) 1731-1740]. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 131(12), 2937.
• Telkes, I., Sabourin, S., Durphy, J., Adam, O., Sukul, V., Raviv, N., Staudt, M. D., & Pilitsis, J. G. (2020). Functional Use of Directional Local Field Potentials in the Subthalamic Nucleus Deep Brain Stimulation. Frontiers in human neuroscience, 14, 145.
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  Directional deep brain stimulation (DBS) technology aims to address the limitations, such as stimulation-induced side effects, by delivering selective, focal modulation via segmented contacts. However, DBS programming becomes more complex and time-consuming for clinical feasibility. Local field potentials (LFPs) might serve a functional role in guiding clinical programming.
• Telkes, L., Hancu, M., Paniccioli, S., Grey, R., Briotte, M., McCarthy, K., Raviv, N., & Pilitsis, J. G. (2020). Differences in EEG patterns between tonic and high frequency spinal cord stimulation in chronic pain patients. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 131(8), 1731-1740.
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  To investigate the differences in neural patterns between spinal cord stimulation (SCS) waveforms (60-Hz tonic vs 10-KHz high frequency stimulation, HFS) and their correlation to stimulation-induced pain relief.
• Telkes, I., Viswanathan, A., Jimenez-Shahed, J., Abosch, A., Ozturk, M., Gupte, A., Jankovic, J., & Ince, N. F. (2018). Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson's disease. Proceedings of the National Academy of Sciences of the United States of America, 115(36), E8567-E8576.
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  Although motor subtypes of Parkinson's disease (PD), such as tremor dominant (TD) and postural instability and gait difficulty (PIGD), have been defined based on symptoms since the mid-1990s, no underlying neural correlates of these clinical subtypes have yet been identified. Very limited data exist regarding the electrophysiological abnormalities within the subthalamic nucleus (STN) that likely accompany the symptom severity or the phenotype of PD. Here, we show that activity in subbands of local field potentials (LFPs) recorded with multiple microelectrodes from subterritories of STN provide distinguishing neurophysiological information about the motor subtypes of PD. We studied 24 patients with PD and found distinct patterns between TD ( = 13) and PIGD ( = 11) groups in high-frequency oscillations (HFOs) and their nonlinear interactions with beta band in the superior and inferior regions of the STN. Particularly, in the superior region of STN, the power of the slow HFO (sHFO) (200-260 Hz) and the coupling of its amplitude with beta-band phase were significantly stronger in the TD group. The inferior region of STN exhibited fast HFOs (fHFOs) (260-450 Hz), which have a significantly higher center frequency in the PIGD group. The cross-frequency coupling between fHFOs and beta band in the inferior region of STN was significantly stronger in the PIGD group. Our results indicate that the spatiospectral dynamics of STN-LFPs can be used as an objective method to distinguish these two motor subtypes of PD. These observations might lead to the development of sensing and stimulation strategies targeting the subterritories of STN for the personalization of deep-brain stimulation (DBS).
• Thompson, J. A., Tekriwal, A., Felsen, G., Ozturk, M., Telkes, I., Wu, J., Ince, N. F., & Abosch, A. (2018). Sleep patterns in Parkinson's disease: direct recordings from the subthalamic nucleus. Journal of neurology, neurosurgery, and psychiatry, 89(1), 95-104.
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  Sleep is a fundamental homeostatic process, and disorders of sleep can greatly affect quality of life. Parkinson's disease (PD) is highly comorbid for a spectrum of sleep disorders and deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been reported to improve sleep architecture in PD. We studied local field potential (LFP) recordings in PD subjects undergoing STN-DBS over the course of a full-night's sleep. We examined the changes in oscillatory activity recorded from STN between ultradian sleep states to determine whether sleep-stage dependent spectral patterns might reflect underlying dysfunction. For this study, PD (n=10) subjects were assessed with concurrent polysomnography and LFP recordings from the DBS electrodes, for an average of 7.5 hours in 'off' dopaminergic medication state. Across subjects, we found conserved spectral patterns among the canonical frequency bands (delta 0-3 Hz, theta 3-7 Hz, alpha 7-13 Hz, beta 13-30 Hz, gamma 30-90 Hz and high frequency 90-350 Hz) that were associated with specific sleep cycles: delta (0-3 Hz) activity during non-rapid eye movement (NREM) associated stages was greater than during Awake, whereas beta (13-30 Hz) activity during NREM states was lower than Awake and rapid eye movement (REM). In addition, all frequency bands were significantly different between NREM states and REM. However, each individual subject exhibited a unique mosaic of spectral interrelationships between frequency bands. Our work suggests that LFP recordings from human STN differentiate between sleep cycle states, and sleep-state specific spectral mosaics may provide insight into mechanisms underlying sleep pathophysiology.
• Jimenez-Shahed, J., Telkes, I., Viswanathan, A., & Ince, N. F. (2016). GPi Oscillatory Activity Differentiates Tics from the Resting State, Voluntary Movements, and the Unmedicated Parkinsonian State. Frontiers in neuroscience, 10, 436.
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  Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. In all PD patients, we noted excessive beta band activity (13-30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4-7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200-400 Hz) and gamma band (35-200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5-10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5-10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present.
• Telkes, I., Jimenez-Shahed, J., Viswanathan, A., Abosch, A., & Ince, N. F. (2016). Prediction of STN-DBS Electrode Implantation Track in Parkinson's Disease by Using Local Field Potentials. Frontiers in neuroscience, 10, 198.
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  Optimal electrophysiological placement of the DBS electrode may lead to better long term clinical outcomes. Inter-subject anatomical variability and limitations in stereotaxic neuroimaging increase the complexity of physiological mapping performed in the operating room. Microelectrode single unit neuronal recording remains the most common intraoperative mapping technique, but requires significant expertise and is fraught by potential technical difficulties including robust measurement of the signal. In contrast, local field potentials (LFPs), owing to their oscillatory and robust nature and being more correlated with the disease symptoms, can overcome these technical issues. Therefore, we hypothesized that multiple spectral features extracted from microelectrode-recorded LFPs could be used to automate the identification of the optimal track and the STN localization. In this regard, we recorded LFPs from microelectrodes in three tracks from 22 patients during DBS electrode implantation surgery at different depths and aimed to predict the track selected by the neurosurgeon based on the interpretation of single unit recordings. A least mean square (LMS) algorithm was used to de-correlate LFPs in each track, in order to remove common activity between channels and increase their spatial specificity. Subband power in the beta band (11-32 Hz) and high frequency range (200-450 Hz) were extracted from the de-correlated LFP data and used as features. A linear discriminant analysis (LDA) method was applied both for the localization of the dorsal border of STN and the prediction of the optimal track. By fusing the information from these low and high frequency bands, the dorsal border of STN was localized with a root mean square (RMS) error of 1.22 mm. The prediction accuracy for the optimal track was 80%. Individual beta band (11-32 Hz) and the range of high frequency oscillations (200-450 Hz) provided prediction accuracies of 72 and 68% respectively. The best prediction result obtained with monopolar LFP data was 68%. These results establish the initial evidence that LFPs can be strategically fused with computational intelligence in the operating room for STN localization and the selection of the track for chronic DBS electrode implantation.
• Telkes, I., Ince, N. F., Onaran, I., & Abosch, A. (2015). Spatio-spectral characterization of local field potentials in the subthalamic nucleus via multitrack microelectrode recordings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2015, 5561-4.
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  Deep brain stimulation of the subthalamic nucleus (STN) is a highly effective treatment for motor symptoms of Parkinson's disease. However, precise intraoperative localization of STN remains a procedural challenge. In the present study, local field potentials (LFPs) were recorded from three tracks during microelectrode recording-based (MER) targeting of STN, in five patients. The raw LFP data were preprocessed in original recording setup and then data quality was compared to data with common average derivation. The depth-frequency maps were generated according to preprocessing results for each patient and spectral characteristics of LFPs were explored at each depth across different tracks and different subjects. Spatio-spectral analysis of LFP was investigated to see whether LFP activity can be used for optimal track selection and STN border identification. Analysis show that monopolar derivation suffer from various artifacts and/or power line noise which makes the interpretation of target localization very difficult in most of the subjects. Unlikely, bipolar derivation helps to recover the neurological signals and investigation of signal characteristics. The frequency-vs-depth maps using a modified Welch periodogram with robust statistics, demonstrated that a median-based spectrum estimation approach eliminates outliers pretty well by preserving band-specific LFP activity. The results indicate that there is a clear oscillatory beta activity around 20 Hz in all subjects. 1/f normalization reveals the high frequency oscillations (HFOs) between 200-to-350 Hz in two subjects. It's noted that the optimal track selection is not consistent with the track having highest beta band oscillations in two out of five subjects. In conclusion, microelectrode-derived LFP recordings may provide an alternative approach to single unit activity (SUA)-based MER, for localizing the target STN borders during DBS surgery. Despite the small number of subjects, the present study adds to existing knowledge about LFP-based pathophysiology of PD and its target-based spectral activities.
• Telkes, I., Meloni, G., Sen, A., Shahed, J., Viswanathan, A., Abosch, A., & Ince, N. F. (2015). Intraoperative macroelectrode LFP recordings in Essential Tremor. 7th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 276-279. doi:doi: 10.1109/NER.2015.7146613
• Elibol-Can, B., Dursun, I., Telkes, I., Kilic, E., Canan, S., & Jakubowska-Dogru, E. (2014). Examination of age-dependent effects of fetal ethanol exposure on behavior, hippocampal cell counts, and doublecortin immunoreactivity in rats. Developmental neurobiology, 74(5), 498-513.
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  Ethanol is known as a potent teratogen having adverse effects on brain and behavior. However, some of the behavioral deficits caused by fetal alcohol exposure and well expressed in juveniles ameliorate with maturation may suggest some kind of functional recovery occurring during postnatal development. The aim of this study was to reexamine age-dependent behavioral impairments in fetal-alcohol rats and to investigate the changes in neurogenesis and gross morphology of the hippocampus during a protracted postnatal period searching for developmental deficits and/or delays that would correlate with behavioral impairments in juveniles and for potential compensatory processes responsible for their amelioration in adults. Ethanol was delivered to the pregnant dams by intragastric intubation throughout 7-21 gestation days at daily dose of 6 g/kg. Isocaloric intubation and intact control groups were included. Locomotor activity, anxiety, and spatial learning tasks were applied to juvenile and young-adult rats from all groups. Unbiased stereological estimates of hippocampal volumes, the total number of pyramidal and granular cells, and double cortin expressing neurons were carried out for postnatal days (PDs) PD1, PD10, PD30, and PD60. Alcohol insult during second trimester equivalent caused significant deficits in the spatial learning in juvenile rats; however, its effect on hippocampal morphology was limited to a marginally lower number of granular cells in dentate gyrus (DG) on PD30. Thus, initial behavioral deficits and the following functional recovery in fetal-alcohol subjects may be due to more subtle plastic changes within the hippocampal formation but also in other structures of the extended hippocampal circuit. Further investigation is required.
• Telkes, I., Ince, N. F., Onaran, I., & Abosch, A. (2014). Localization of subthalamic nucleus borders using macroelectrode local field potential recordings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2014, 2621-4.
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  Deep brain stimulation of the subthalamic nucleus (STN) is a highly effective treatment for motor symptoms of Parkinson's disease. However, precise intraoperative localization of STN remains a procedural challenge. In the present study, local field potentials (LFPs) were recorded from DBS macroelectrodes during trajectory to STN, in six patients. The frequency-vs-depth map of LFP activity was extracted and further analyzed within different sub-bands, to investigate whether LFP activity can be used for STN border identification. STN borders identified by LFPs were compared to border predictions by the neurosurgeon, based on microelectrode-derived, single-unit recordings (MER-SUA). The results demonstrate difference between MER-SUA and macroelectrode LFP recording with respect to the dorsal STN border of -1.00 ±0.84 mm and -0.42 ±1.07 mm in the beta and gamma frequency bands, respectively. For these sub-bands, RMS of these distances was found to be 1.26 mm and 1.06 mm, respectively. Analysis of other sub-bands did not allow for distinguishing the caudal border of STN. In conclusion, macroelectrode-derived LFP recordings may provide an alternative approach to MER-SUA, for localizing the target STN borders during DBS surgery.

Proceedings Publications

• Telkes, I., Hwang, R., Pilitsis, J., & Durphy, J. (2019). Directional Deep Brain Stimulation Lead Placement in A Patient with Severe Obsessive-Compulsive Disorder. In International Neuromodulation Society 14th World Congress, 12, e122-e124.
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  Published in Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation
• Telkes, I., Paniccioli, S., Grey, R., Briotte, M., McCarthy, K., & Pilitsis, J. (2019). Effect of Spinal Cord Stimulation on Intraoperatively Recorded EEG in Chronic Pain Patients. In The International Neuromodulation Society 14th World Congress, 12, e102-e103.
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  Published in Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation