Somatosensory Evoked Potentials Recorded Directly From Human Thalamus and Sm I Cortical Area

Celesia, Gastone G.

doi:10.1001/archneur.1979.00500430029003

Cited by 106 publications

(25 citation statements)

References 39 publications

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“…lb, e, f). These data were sim ilar to other authors' results but there are some controversial points [1][2][3][5][6][7][8]. We conclude that the thalamic first positive deflection must have been of medial lemniscal origin and the first negative wave was attributable to synaptic potentials of thalamic relay neurons [7].…”

Section: Results and Conclusionsupporting

confidence: 87%

“…No polarity reversal was observed in the recordings of the authors [2,4]. Peak major N had its highest amplitude under the precentral gy rus in 3 cases and only 1 patient showed higher amplitude under the postcentral gyrus.…”

Section: Results and Conclusionmentioning

confidence: 73%

“…Very few direct recordings have been carried out from the human cortex and subcortical structures on pa tients with chronic deep electrodes. Direct recordings from the thala mus [1][2][3][5][6][7][8] and the cortex [2,4] have been discussed but failed to provide definite results and conclusions.…”

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confidence: 99%

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The Spread of Somatosensory-Evoked Potentials Within the Nervous System

Sólyom¹,

Tóth²,

Holczinger³

et al. 1985

Stereotact Funct Neurosurg

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Four thalamic and cortical recordings were carried out in 5 patients. The thalamic-evoked potentials were typical and revealed a triphasic complex, but their latencies showed a relatively high Standard deviation. They could be divided into two groups according to their latencies, both of which had low SD. These data suggested that there could be two types of latency of thalamic SEP, because the 4 patients’ body sizes were very similar. More detailed surface, cortical and depth recordings are needed to resolve these questions.

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Section: Results and Conclusionsupporting

confidence: 87%

Section: Results and Conclusionmentioning

confidence: 73%

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The Spread of Somatosensory-Evoked Potentials Within the Nervous System

Sólyom¹,

Tóth²,

Holczinger³

et al. 1985

Stereotact Funct Neurosurg

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“…For this purpose, we recorded somatosen sory evoked potentials (SEPs) following stimulation of peripheral nerves. The recording data reflect an afferent input from the periphery, as also shown in the past by other workers [4,5,7,10]. We analyzed whether functional modalities of the afferent input could be differen tiated by the SEPs.…”

Section: Introductionmentioning

confidence: 71%

Somatosensory Evoked Potentials in the Ventrolateral Thalamus

Birk

Riescher²,

Strüppler³

et al. 1986

Stereotact Funct Neurosurg

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Within the target area (VL) used for the stereotactic treatment of parkinsonian tremor and spasmodic torticollis, electrical stimulation as well as recording of somatosensory evoked potential (SEP) was performed. The effects of stimulation in the target area are facilitation of muscle tone showing some degree of somatotopic distribution. The recorded SEPs indicate a projection of an afferent system (probably of muscle afferents) to the target area. We assume that the target area is a relay station involved in the control of muscle tone. The interruption of muscle afferents in combination with the correct somatotopic localization of the lesion is important for the therapeutic efficacy in parkinsonian tremor and spasmodic torticollis.

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“…They are also used for the identification of the sensory portion of the sensorimotor cortex (Celesia, 1979). SSEPs are also widely used for intraoperative neurophysiological monitoring (IONM) in surgeries for scoliosis (Pastorelli et al, 2011;Schwartz et al, 2007), pedicle-screw placement procedures (Jou et al, 2003) and spinal cord related surgical procedures (Dinner et al, 1986;McGarry et al, 1984;Nuwer et al, 1995;Deletis and Sala, 2008;Deletis, 2007).…”

Section: Intraoperative Neurophysiologic Monitoring (Ionm) Is An Intementioning

confidence: 99%

A Novel Signal Processing Method for Intraoperative Neurophysiological Monitoring in Spinal Surgeries

Vedala¹

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My mentor Dr. Malek Adjouadi has taught me a great deal in professional, personal and intellectual development. He has always had my best interest at heart and has provided me with every opportunity to grow. I am grateful for all the kindness and patience that he has shown me over the years. I would like to thank my gurus, Dr.Armando Barreto, Dr. Jean Andrian and Dr. Naphtalie Rishe, naming a few, whose trials to obtain an SSEP signal, which is excessive and introduces a significant delay to prevent potential neurological risks during surgery. The main objective of this dissertation is to develop a means to obtain the SSEP signal using a much reduced number of trials (20 trials or less) while still optimizing the effectiveness of the monitoring system. The preliminary research steps were to determine those characteristics that distinguish the SSEP with the ongoing brain activity. We first established that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded.A novel algorithm is subsequently developed using Chebyshev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasistationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised vii when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials.In this study, the analysis was performed on the data recorded in 29 patients who underwent surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp EEG. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm took on an average 4sec to extract an SSEP signal, as compared to conventional methods, which take up to several minutes.The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provided for a much improved and effective neurophysiological monitoring process.

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Somatosensory Evoked Potentials Recorded Directly From Human Thalamus and Sm I Cortical Area

Cited by 106 publications

References 39 publications

The Spread of Somatosensory-Evoked Potentials Within the Nervous System

The Spread of Somatosensory-Evoked Potentials Within the Nervous System

Somatosensory Evoked Potentials in the Ventrolateral Thalamus

A Novel Signal Processing Method for Intraoperative Neurophysiological Monitoring in Spinal Surgeries

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