Potentially Pathological Alpha-Pattern as a Variant of Vigilance EEG in Drug-Resistant Epilepsy

Cover Page


As a result of pathomorphosis affecting the mechanisms of electrical activity generation interictal EEG may show reduced epileptiform changes whereas clinically apparent epileptic seizures may be present. In these cases patterns of dominant alpha activity are sometimes recorded on the scalp. In this study variations of alpha activity in patients with refractory epilepsy are classified. A group of 50 refractory epilepsy patients aged between 20 and 55 years who were submitted to Polenov Russian Scientific Research Institute of Neurosurgery in 2014-2017 was included in this study. They underwent scalp EEG as a part of their presurgical assessment. In 12 cases patterns of potentially pathological alpha activity were observed. Three variations of alpha-patterns were described: 1) alpha-rhythm with decreased regional diversity and a marked synchronization in temporal areas; 2) alpha-rhythm with reduced epileptiform complexes integrated into the spindles, 3) decelerated non-rhythmic alpha activity distorted by the higher frequency components. Distinguished varieties of potentially pathological alpha-activity according to their order here represent gradual functional decline of normal thalamo-cortical interaction. Considering clinical manifestation of drug-resistant epilepsy with frequent seizures in these patients, reported varieties of alpha activity can not be interpreted as Landolt’s syndrome (forced normalization of EEG). Invasive electrocorticographic monitoring demonstrated that bursts of sharpened polyphasic waves coinciding with alpha-rhythm on scalp EEG are consistent with epileptic discharges on the brain cortex surface. This allows to think of these components as correlates of epileptic activity. Therefore, on a number of occasions in patients with epilepsy a dissonance between clinical signs and electroencephalographic patterns recorded during restful wakefulness may be observed, when epileptiform components are absent or reduced to nonspecific complexes.


Presently, elucidating epilepsy pathogenesis and improvement of its diagnostics and treatment are among the most significant challenges in neurology [7]. Epilepsy is a relatively widespread condition, with a worldwide incidence rate of 5–10 per 1000 people. In the Russian Federation, the estimated incidence of epilepsy is 1.2–7.2 per 1000 people [1]. Since the disease is often diagnosed late, it results in the development of drug-resistant epilepsy observed in 20%–30% of all cases.

For many years, electroencephalography (EEG) remains the leading diagnostic method for patients with epilepsy [3, 6, 7], as a majority of patients experiencing regular epileptic seizures exhibit epileptiform activity on EEG. However, up to 30% of patients suffering from epileptic seizures and receiving antiepileptic therapy have only alpha activity with no epileptiform patterns on EEG during passive wakefulness [6]. This can be partially explained by changes in bioelectric activity with the involvement of critical thalamic mechanisms of alpha rhythms’ generation [2, 12] as well as deformation and reduction of epileptiform changes, primarily induced by antiepileptic therapy. While the detection of pronounced alpha spindles on EEG indicates well-established adaptive mechanisms for upward and downward regulation, their disappearance demonstrates impaired sensorimotor integration [4]. Nonetheless, alpha range potentials on EEG do not always indicate well-being as they can be detected, for example, in a coma [16, 17]. The detection of alpha activity without epileptiform patterns on EEG significantly reduces the probability of diagnosing epilepsy, assessing its dynamics, and choosing a correct treatment regimen. Recent studies investigating alpha activity in patients with epilepsy have revealed only a reduction of variability in the frequency of the basic rhythm in these patients [15]. However, despite the apparent role of thalamocortical interactions in spreading epileptic discharges in experimental and mathematical models [2, 9, 20], its pathophysiological aspects are poorly understood to establish unambiguous relationships [21]. The characteristics of the alpha rhythm and its evolution are currently investigated in the normal EEG and non-epileptic pathological EEG using novel sophisticated methods of data processing [10, 19, 22]. A detailed analysis of alpha activity in patients with epilepsy receiving antiepileptic drugs (AEDs) will probably enhance the predictive value of EEG for these patients [11].

This study aimed to assess and systematize EEG patterns with a prevalence of alpha activity in patients with drug-resistant epilepsy.

Material and methods

We analyzed the results of comprehensive clinical, neurophysiological, and neuroimaging examination of 50 patients with drug-resistant epilepsy aged between 20 and 55 years. Patients were examined and treated at the Clinic of the Polenov Russian Neurosurgical Institute during 2014–2017. The inclusion criteria in this study were as follows: (1) have focal drug-resistant epilepsy according to the International League Against Epilepsy (ILAE) criteria (treatment with two or more modern AEDs for more than 2 years); and (2) have stable rhythmic alpha activity on EEG during passive wakefulness.

Neurophysiological examination included conventional EEG with functional tests and long-term video-EEG monitoring during wakefulness and sleep. The surface EEG was recorded in standard leads using monopolar and bipolar montage with electrode locations according to the International 10–20 System.

In this study, 12 patients underwent long-term invasive neurophysiological monitoring to verify the location of the epileptic focus. Electrocorticography (ECoG) was recorded using subdural electrodes in a bipolar montage; the electrodes were introduced through the burr holes. In addition, conventional EEG was recorded in parallel with ECoG to assess the distribution of bioelectric activity. The amplifier’s bandwidth was 0.5–70 Hz in both variants.

Furthermore, neurophysiological examinations were performed using two diagnostic systems, “Mitsar-EEG-201” and “Mitsar-EEG-202.”


All study participants have had epilepsy for a long time (3–29 years). The age at the disease onset varied between 1 and 51 years. The antiepileptic therapy included at least two modern AEDs, and plasma concentration of the drugs was within the therapeutic reference ranges. Thus, all patients fulfilled the ILAE criteria for drug-resistant epilepsy.

In this study, 22 of 50 patients had concordant clinical, neuroimaging, and neurophysiological findings. In addition, 10 patients exhibited a high index of stable regional epileptic activity along with alpha activity registered by EEG. In 12 patients, both conventional EEG and video-EEG monitoring during passive wakefulness demonstrated only stable alpha activity without any epileptic patterns. Bilateral epileptiform activity was registered in 26 patients using the surface EEG. Furthermore, 14 patients required two or three additional procedures of long-term video-EEG monitoring with a mean duration of 5.5 ± 2.2 h to verify the location of the epileptic area. In 13 patients, the sensitivity of video-EEG monitoring was insufficient to identify the location of the epileptic focus; these patients additionally underwent invasive monitoring of the brain bioelectrical activity.

Thus, conditionally pathological alpha activity on EEG was observed in 12 of 50 patients with drug-resistant epilepsy (Table 1). Of these, 8 patients developed epileptic seizures in childhood at the age of 3–16 years.


Table 1. The characteristics of patients with predominant alpha activity on EEG during wakefulness

Таблица 1. Характеристика группы пациентов с доминирующей альфа-активностью на ЭЭГ бодрствования


Gender/ age

Age at disease onset

Disease duration

Type of seizures







Partial sensory; complex: dialeptic, automotor

Moderate encephalopathy of mixed origin

Carbamazepine, Sodium Valproate, Phenytoin





Partial: sensorimotor, vegetative; automotor

Hippocampal asymmetry (L > R), FCD

Perampanel, Carbamazepine





Partial: sensory, vegetative; automotor

Pilocytic astrocytoma in the right lateral ventricle

Sodium Valproate, Levetiracetam





Partial: vegetative sensory, motor; complex: dialeptic, automotor; SGS

Right hippocampal sclerosis, heterotopia at the left lateral ventricle, cystic atrophy of the right frontal lobe

Sodium Valproate, Carbamazepine





Complex partial vegetovisceral: dialeptic, automotor; SGS

Right hippocampal cyst, external hydrocephalus substitution

Sodium Valproate, Oxcarbazepine





Partial psychosensory; complex automotor; SGS

Right hippocampal sclerosis

Sodium Valproate, Oxcarbazepine, Lacosamide, Levetiracetam





Partial, psychomotor, SGS

Right hippocampal sclerosis, heterotopia

Sodium Valproate, Levetiracetam





Partial: vegetative, psychomotor; GS complex automotor

Moderate mixed hydrocephalus

Sodium Valproate, Lacosamide, Levetiracetam





Partial, vegetovisceral; GS

No pathological changes

Lacosamide, Levetiracetam





Complex focal seizures with motor and ambulatory automatisms, rare GS

Bilateral subependymal heterotopia of the gray matter

Sodium Valproate, Levetiracetam, Oxcarbazepine





Serial focal motor seizures, aura

No pathological changes

Zonisamide, Lacosamide





Complex focal seizures

No pathological changes

Carbamazepine, Lacosamide, Levetiracetam

Abbreviations: AEDs, antiepileptic drugs; SGS, secondarily generalized seizures; GS, generalized seizures; MRI, magnetic resonance imaging; FCD, focal cortical dysplasia


Table 1 shows that we failed to find significant correlations between the clinical manifestations, neuroimaging findings, and the type of EEG changes. However, we observed some deviations from the normal alpha activity during passive wakefulness.

The detected alpha activity differed from the standard alpha activity during passive wakefulness. We identified the following three main variants of conditionally pathological alpha activity (Figures 1–3):

  1. alpha rhythm with reduced zonal differences and pronounced synchronization in the temporal areas;
  2. alpha rhythm with reduced epileptiform elements within the spindles; and
  3. slow non-rhythmic alpha activity distorted by high-frequency oscillations (sharpened waves).

Figure 2 shows a pattern of the background activity with well-modulated alpha rhythm. Regional high-amplitude sharpened oscillations are registered in the structure of alpha spindles. Usually, such findings are considered as a nonspecific pathological activity. Figure 3 shows weakly modulated sharpened alpha rhythm characterized by unstable frequency (8–11 Hz) and medium amplitude (up to 60–70 μV). Alpha activity prevailed in the central and temporoparietal leads. Asynchronous sharpened transients originating primarily from posteriotemporal areas were occasionally registered on EEG.



Fig. 1. Alpha rhythm with reduced zonal differences and pronounced synchronization in the temporal areas in a 36-year-old male patient with drug-resistant epilepsy



Fig. 2. Alpha rhythm with reduced epileptiform elements within the spindles in a 28-year-old female patient with drug-resistant epilepsy



Fig. 3. Slow alpha activity distorted by rare high-frequency oscillations (sharpened waves) in a 38-year-old male patient with drug-resistant epilepsy


We described a clinical case of symptomatic temporal lobe epilepsy in a 40-year-old female patient with complex focal seizures to complete the classification of EEG patterns. The first seizure occurred at the age of 29 during delivery; she lost consciousness and developed motor automatisms (scratching movements of the hands and leg extension) with subsequent postictal confusion. After delivery, seizures continued with a frequency of 10–15 every month. The patient received several AEDs, including valproates, topiramate, trileptal, and vimpat; however, treatment regimens were changed several times because of ineffectiveness. Until hospitalization, the patient had 1–2 serial (4–5 per day) seizures per month with a duration of 2–3 min. Her treatment regimen included levetiracetam and lamotrigine. While video-EEG monitoring demonstrated two foci of pathological activity (sharpened waves) in the right and left temporoparietal areas, MRI brain scans revealed focal changes with possible vascular origin. In addition, we detected hippocampal asymmetry (D < S). Positron emission tomography/computed tomography (PET/CT) scanning revealed signs of glucose hypometabolism in the cortex of the right temporal lobe, primarily in the temporal pole and in the temporoparietal area of the left hemisphere. Owing to the partial concordance of clinical, neuroimaging, and neurophysiological findings, the patient underwent invasive monitoring to verify the location of the epileptic focus. Accordingly, subdural strip electrodes were placed bilaterally over the temporal lobes, and a dominant focus of epileptic activity (with activity index of 50%–60%) was detected in the right temporal lobe.

Hence, video-EEG monitoring with sleep deprivation did not allow identification of the exact location of a dominant epileptic focus. The pattern of the background activity included the alpha rhythm with abnormal zonal distribution, and diphasic and triphasic sharpened waves were occasionally detected.

Furthermore, we performed long-term invasive monitoring of the cortical bioelectric activity to verify the location of the epileptic focus. Strip electrodes were introduced through the burr holes and placed on the cortical surface of the temporal lobes in the right and left hemisphere under general anesthesia. After 2 days, we performed co-registration of the surface EEG and ECoG. The invasive monitoring revealed that diphasic and triphasic sharpened waves in the alpha rhythm coincided with epileptic discharges in the cortex (Figure 4). Our results suggested that sharp polyphasic waves in the structure of alpha spindles correlate with epileptic discharges in the cortex.



Fig. 4. Reduced cortical epileptiform activity on the surface EEG: results of invasive monitoring. Surface EEG signals were registered from the leads Fp1, Fp2, T3, T4, O1, and O2. Leads D and S correspond to corticographic strip electrodes in the right and left hemisphere, respectively. The Bio1 lead–ECG


Finally, we detected an epileptic focus in the right temporal area. The patient underwent surgical removal of two-thirds of the temporal lobe, amygdala, and anterior hippocampus under electrophysiological control. The patient was examined after 1 year of surgery. Although no seizures occurred during this time, the patient had several episodes of aura. Video-EEG monitoring demonstrates steady alpha rhythm with no signs of focal or diffuse epileptiform activity.


We believe that the described variants of conditionally pathological alpha activity (in order of their appearance in the text) reflect gradually increasing dysfunction in thalamocortical interactions [2, 16].

The detected changes in the alpha rhythm do not necessarily indicate typical epileptiform activity. However, if a patient presents epileptic seizures with no response to therapy, these EEG changes can be considered conditionally pathological.

The presence of sharpened waves within normal or distorted alpha rhythm is probably explained by the reduction (incomplete conduction) of epileptiform activity from the cortex to the scalp surface because of the signal scattering in the dielectric structures of the skull and integumentary tissues [8]. Cortical epileptiform discharges are detected on the scalp only when they reach specific amplitude [3, 6, 7, 18]. In this description of alpha activity patterns, the focus should be on the relatively high frequency of EEG alpha patterns in patients diagnosed with epilepsy, especially in those with drug-resistant forms and frequent seizures. In this case, the clinical manifestations hinder the interpretation of the alpha pattern as a sign of Landolt syndrome (syndrome of forced normalization).

A hypersynchronous sharpened alpha rhythm has already been described as an equivalent of cortical epileptiform discharges [5]. These oscillations are similar to typical epileptiform discharges (sharp waves) when registered directly in the cortex. Some researchers consider sharpened theta/alpha activity with an average frequency of 9.5 Hz and increasing amplitude as one of the EEG patterns typical of the seizure beginning [14]. However, such EEG patterns are currently described as nonspecific pathological changes or lowered seizure threshold in most cases. Limited studies emphasize the importance of high-frequency oscillations in the alpha rhythm for detecting epileptogenic areas in the cortex [13].

Thus, patients with epilepsy often have discordance between the clinical manifestations and EEG findings during passive wakefulness. Perhaps, epileptiform discharges could be completely absent or reduced to nonspecific complexes in the structure of the basic rhythm.


  1. Twelve of 50 patients with drug-resistant epilepsy had conditionally pathological alpha activity on EEG. Of these, eight developed epileptic seizures in childhood at the age of 3–16 years.
  2. We described three main variants of conditionally pathological alpha activity as follows: (1) alpha rhythm with reduced zonal differences and pronounced synchronization in the temporal areas; (2) alpha rhythm with reduced epileptiform elements within the spindles; and (3) slow non-rhythmic alpha activity distorted by high-frequency oscillations (sharpened waves).
  3. The described variants of conditionally pathological alpha activity reflect gradually developing dysfunction in thalamocortical interactions. The detected changes in the alpha rhythm do not necessarily indicate typical epileptiform activity. However, if a patient has epileptic seizures with no response to therapy, these EEG changes can be considered conditionally pathological.

Aleksandr A. Chukhlovin

Author for correspondence.
Russian Polenov Research Neurosurgical Institute
Russian Federation, Saint Petersburg

MD, PhD, Laboratory of Neurophysiological Monitoring

Mikhail V. Aleksandrov

Russian Polenov Research Neurosurgical Institute
Russian Federation, Saint Petersburg

MD, PhD, Dr Med Sci, Professor, Deputy Director, Scientific Research Department of Clinical Neurophysiology and Epileptology

Sergey A. Lytaev

St Petersburg State Pediatric Medical University, Ministry of Healthcare of the Russian Federation
Russian Federation, Saint Petersburg

MD, PhD, Dr Med Sci, Professor, Head, Department of Human Physiology

Vugar R. Kasumov

Russian Polenov Research Neurosurgical Institute
Russian Federation, Saint Petersburg

MD, PhD, Dr Med Sci, Senior researcher, Department of reconstructive-regenerative and functional surgery of injuries and diseases of the central and peripheral nervous system

Marina E. Pavlovskaya

Russian Polenov Research Neurosurgical Institute
Russian Federation, Saint Petersburg

Doctor of functional diagnostics, Epileptological center

Nastasia B. Arkhipova

Federal Almazov North-West Medical Research Center
Russian Federation, Saint Petersburg

Postgraduate Student, Department of Neurosurgery

  • Авакян Г.Н. Современная эпилептология. Проблемы и решения // Эпилепсия и пароксизмальные состояния. – 2014. – № 4. – С. 16–24. [Avakjan GN. Issues of modern epileptology. Epilepsija i paroksizmal'nye sostojanija. 2015;(4):16-21. (In Russ.)]
  • Александров М.В. Механизмы генерации биоэлектрической активности головного мозга: альфа-тета континуум // Вестник клинической нейрофизиологии. – 2016. – № 2. – С. 4–9. [Aleksandrov MV. The mechanisms of the brain bioelectric activity generation: alpha-theta continuum. Vestnik klinicheskoj nejrofiziologii. 2016;(2):4-9. (In Russ.)]
  • Александров М.В., Чухловин А.А., Павловская М.Е., и др. Электроэнцефалографические признаки детерминантного очага при многоочаговой эпилепсии // Материалы конференции «Эпилептология в системе нейронаук». – СПб., 2015. – С. 38–39. [Aleksandrov MV, Chuhlovin AA, Pavlovskaya ME, et al. Electroencephalographic attributes of dominant focus in multifocal epilepsy. In: “Epileptologija v sisteme nejronauk” (conference proceedings) Saint Petersburg; 2015. P. 38-9. (In Russ.)]
  • Базанова О.М. Современная интерпретация альфа-активности ЭЭГ // Международный неврологический журнал. – 2011. – № 8. – С. 96–104. [Bazanova OM. Modern interpretation of alpha activity on EEG. Mezhdunarodnyj nevrologicheskij zhurnal. 2011;(8):96-104. (In Russ.)]
  • Зенков Л.Р., Ронкин М.А. Функциональная диагностика нервных болезней. – М.: Медицина, 1982. [Zenkov LR, Ronkin MA. Functional diagnostics in neuropathology. Moscow: Medicina; 1982. (In Russ.)]
  • Общая электроэнцефалография. – СПб.: Информационно-издательский учебно-научный центр «Стратегия будущего», 2017. [General ectroen cephalography. Saint Petersburg: Informacionno-izdatel'skij uchebno-nauch nyj centr “Strategija budushhego”, 2017. (In Russ.)]
  • Современная эпилептология: проблемы и решения. – М.: ООО «Буки-Веди», 2015. [Modern epileptology: challenges and solutions. Moscow: Buki-Vedi; 2015. (In Russ.)]
  • Amzica F, Lopes da Silva FH. Cellular substrates of brain rhythms. Niedermeyer’s Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. 2011;6:33-63.
  • Da Silva FL, et al. Epilepsies as dynamical diseases of brain systems: basic models of the transition between normal and epileptic activity. Epilepsia. 2003; 12:72-83. doi: 10.1111/j.0013-9580.2003.12005.x.
  • Eidelman-Rothman M, Levy J, Feldman R. Alpha oscillations and their impairment in affective and post-traumatic stress disorders. Neuroscience & Biobehav. Reviews. 2016;68:794-815. doi: 10.1016/j.neubiorev.2016.07.005.
  • Grau-López L, et al. Importance of neuropsychological and clinical features to predict seizure control in medically treated patients with mesial temporal epilepsy and hippocampal sclerosis. Epilepsy & Beha vior. 2017;69:121-5. doi: 10.1016/j.yebeh.2017.01.009.
  • Hughes SW, Crunelli V. Thalamic mechanisms of EEG alpha rhythms and their pathological implications. The Neuroscientist. 2005;4:357-72. doi: 10.1177/ 1073858405277450.
  • Ibrahim GM, et al. Dynamic modulation of epileptic high frequency oscillations by the phase of slower cortical rhythms. Experimental Neurology. 2014;251:30-8. doi: 10.1016/j.expneurol.2013.10.019.
  • Lagarde S, et al. Seizure-onset patterns in focal cortical dysplasia and neurodevelopmental tumors: Relationship with surgical prognosis and neuropathologic subtypes. Epilepsia. 2016;9:1426-35. doi: 10.1111/epi.13464.
  • Larsson PG, Kostov H. Lower frequency variability in the alpha activity in EEG among patients with epilepsy. Clinical Neurophysiology. 2005;11:2701-6. doi: 10.1016/ j.clinph.2005.07.019.
  • Lytaev S, Aleksandrov M, Vasilyev S, Arutunyan A. The Predictability of Pharm-EEG in Patients with Long Unconscious Status. Lecture Notes in Computer Scien ce. Foundation of Augmented Cognition. V. 8534. Heidelberg, New York, Dordrecht, London: Springer; 2014. P. 288-95. doi: 10.1007/978-3-319-07527-3_27.
  • Niedermeyer E. Alpha rhythms as physiological and abnormal phenomena. Int J Psychophysiol. 1997;(1):31-49. doi: 10.1016/S0167-8760(97)00754-X.
  • Petroff OA, Spencer DD, Goncharova II, Zaveri HP. A comparison of the power spectral density of scalp EEG and subjacent electrocorticograms. Clin Neurophysiol. 2016;127(2):1108-12. doi: 10.1016/j.clinph.2015.08.004.
  • Schwabedal JTC, et al. Alpha-wave frequency characteristics in health and insomnia during sleep. J Sleep Res. 2016;25:278-86. doi: 10.1111/jsr.12372.
  • Sherman D, et al. Detection of nonlinear interactions of EEG alpha waves in the brain by a new coherence measure and its application to epilepsy and anti-epileptic drug therapy. Int J Neural Systems. 2011;(2):115-26. doi: 10.1142/S0129065711002754.
  • Sitnikova E. Thalamo-cortical mechanisms of sleep spindles and spike-wave discharges in rat model of absence epilepsy (a review). Epilepsy Res. 2010;(1):17-26. doi: 10.1016/j.eplepsyres.2009.09.005.
  • horpe SG, Cannon EN, Fox NA. Spectral and source structural development of mu and alpha rhythms from infancy through adulthood. Clin Neurophysiol. 2016;(1):254-69. doi: 10.1016/j.clinph.2015.03.004.

Supplementary files

There are no supplementary files to display.


Abstract - 109

PDF (Russian) - 115

PDF (English) - 0

Copyright (c) 2017 Chukhlovin A.A., Aleksandrov M.V., Lytaev S.A., Kasumov V.R., Pavlovskaya M.E., Arkhipova N.B.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.