World Journal of Nuclear Medicine

ORIGINAL ARTICLE
Year
: 2021  |  Volume : 20  |  Issue : 3  |  Page : 273--280

Alterations of regional cerebral glucose metabolism using18F-fluorodeoxyglucose positron-emission tomography/computed tomography and electroencephalography analysis during mindfulness breathing in Anapanasati meditation: A preliminary analysis


Chanisa Chotipanich1, Supatporn Tepmongkol2, Yodchanan Wongsawat3, Attapon Jantarato1,  
1 National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
2 Department of Radiology, Division of Nuclear Medicine, Faculty of Medicine, Chulalongkorn University Biomedical Imaging Group, Chulalongkorn University, Bangkok, Thailand
3 Department of Biomedical Engineering, Mahidol University, Nakhon Pathom, Thailand

Correspondence Address:
Prof. Chanisa Chotipanich
National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, 906, Kamphaeng Phet 6 Rd., Talat Bang Khen, Lak Si, Bangkok - 10210
Thailand

Abstract

Anapanasati is a core meditation of a breath-centered practice in the Buddhist Theravada tradition, which may have some neurological mechanism effects on the brain. To gain insight into the neurological mechanisms involved in Anapanasati meditation, we measured the alterations of regional cerebral glucose metabolism during Anapanasati meditation using positron-emission tomography/computed tomography (PET/CT) and electroencephalography (EEG) analysis. This prospective study was conducted in six right-handed volunteer participants (two men, four women; aged: 32–67 years) who underwent18F-fluorodeoxyglucose (18F-FDG) PET/CT scans to compare the alterations of regional cerebral glucose metabolism during normal consciousness and Anapanasati meditation states. Spectral EEG analysis was performed throughout the investigations. Statistical parametric mapping was used for the18F-FDG PET/CT image analyses. The visual analysis demonstrated moderate-to-marked increased metabolism in posterior cingulate cortex in all six patients, while mild-to-moderate increased uptake in the whole frontal lobe was also observed in four patients and precuneus in four patients. Meanwhile, the semiquantitative analysis yielded an increase of regional cerebral glucose metabolism in the right mid-to-posterior cingulate gyrus (P < 0.000), with visible alpha waves on the frontal of the EEG findings. Our semiquantitative analysis showed a significantly increased metabolism only in the posterior cingulate cortex, but visually, there was also an increased metabolism in the whole frontal lobe in most of the patients correlating with EEG findings.



How to cite this article:
Chotipanich C, Tepmongkol S, Wongsawat Y, Jantarato A. Alterations of regional cerebral glucose metabolism using18F-fluorodeoxyglucose positron-emission tomography/computed tomography and electroencephalography analysis during mindfulness breathing in Anapanasati meditation: A preliminary analysis.World J Nucl Med 2021;20:273-280


How to cite this URL:
Chotipanich C, Tepmongkol S, Wongsawat Y, Jantarato A. Alterations of regional cerebral glucose metabolism using18F-fluorodeoxyglucose positron-emission tomography/computed tomography and electroencephalography analysis during mindfulness breathing in Anapanasati meditation: A preliminary analysis. World J Nucl Med [serial online] 2021 [cited 2021 Oct 21 ];20:273-280
Available from: http://www.wjnm.org/text.asp?2021/20/3/273/299274


Full Text

 Introduction



The mindfulness of breathing, or Anapanasati meditation, is one of the most common forms of meditation in Theravada Buddhism, with the breath-centered practice that practitioners continually focus on the sensations of their own breathing. Meditation has been shown to be useful for improving mental health and brain function.[1] A number of studies have also demonstrated that the effects of meditation are related to complex neuronal mechanisms.[2]

Neuroimaging techniques including functional magnetic resonance imaging and positron-emission tomography (PET) have been applied to study the brain function of people in meditative states.[3],[4] However, the study to understand neurological mechanism effects on the body and brain during Anapanasati meditation practice remains lacking and limited. Thus, we aimed to compare the alterations of regional cerebral glucose metabolism during normal consciousness and mindful breathing of Anapanasati meditation states, using PET/computed tomography (PET/CT) and electroencephalography (EEG) analysis.

 Materials and Methods



This study was approved by the Human Research Ethics Committee of our institute on March 23, 2010. The project code was 012/2552. Before the study, written informed consent was obtained from all participants for participation in the study of data for research and educational purposes.

Participants

Six right-handed volunteers (two men, four women; aged: 31–67 years; median age: 50.5 years), with experience in Anapanasati meditation ranging from 1 month to 50 years (median 0.54 years), participated in the study. No participants had a history of psychological or neurological diseases or use of psychotropic drugs.

Procedures

All participants underwent a resting-state 18F-fluorodeoxyglucose (18F-FDG) PET/CT scan of normal consciousness within 2 weeks before the performed scan during Anapanasati meditation. On the day of Anapanasati meditation study, each participant had an intravenous catheter placed in the antecubital vein before starting Anapanasati meditation, while EEG was continuously recorded. They were not interrupted during the meditation. The participants sat with both eyes closed in a quiet room without covering their ears and meditated the Anapanasati meditation, focusing on mindful awareness of breathing while inhaling and exhaling. Once effective meditation, as described in the EEG section, was detected by EEG software, 18F-FDG was immediately injected via the intravenous catheter. Then, the participants continued their awareness of breathing for 30 min to allow brain uptake of the18F-FDG before the PET/CT scan. This was in accordance with the reference from EANM procedure guidelines for PET brain imaging, 18F-FDG, version 2, which recommended the uptake phase at least 20 min.[5]

On the day of normal consciousness, all of them underwent the same procedure during their performing of Anapanasati meditation. They were only asked to sit with both eyes closed while the18F-FDG was injected.

18F-fluorodeoxyglucose imaging procedure

All participants fasted for 6 h before being scanned using a Siemens/Biograph 16 scanner in three-dimensional mode. Imaging was then performed 30 min after intravenous injection of 5 MBq/kg18F-FDG during normal consciousness and mindfulness of breathing in Anapanasati meditation. The level of plasma glucose was determined prior to the18F-FDG PET/CT study. The plasma glucose level of < 200 mg/dl was considered as acceptable for all patients. Image acquisition was performed for 10 min per bed position, matrix size = 256 × 256, zoom = 1, and a Gaussian filter of full-width at half-maximum (FWHM) =2.0. Image reconstruction was performed using the ordered subset expectation maximization (OSEM) with four iterations and eight subsets.

Electroencephalography

EEGs were recorded during normal consciousness and Anapanasati meditation with a BIOSEMI™ ActiveTwo 32-channel EEG recording system, equipped with Ag/AgCl active electrodes. A sampling rate of 1024 Hz was applied together with LabVIEW software (LabVIEW 2015, National Instruments Corporation, Austin, Texas, USA) developed in-house to detect meditative states in the brain in real time. For this real-time quantitative evaluation, effective meditation should occur when the following condition was satisfied three times:

(PSDF3+PSDF4+PSDFp1+PSDFp2)>0.7 (PSDP03+PSDP04+PSD03+PSD04),[1] Where PSDi denotes the sum of the Welch power spectral density[6] of frequency between 8 and 13 Hz from channel i according to the 10–20 system of electrode placement.[7] The threshold of 0.7 was arbitrarily selected to enable early detection of effective meditation.

The idea of this equation can be explained by the assumption that the brain would focus on some specific concentrations during effective meditation. The subjects of every recorded EEG channels were likely to produce low frequencies (deactivation, 8–13 Hz) in the cortex area. Therefore, the spectrums of the lower frequency band tended to be increased in all channels. Naturally, at the normal state, the low-frequency EEG would not efficiently be observed in the frontal area. Consequently, the increasing of lower frequency spectrums in the frontal area compared with the parietal and the occipital areas was used as the index.

Data and Statistical analysis

PET imaging data processing and analysis was conducted using Statistical Parametric Mapping version 2 (SPM2, Wellcome Department of Cognitive Neurology, University College, London), running on MATLAB 6.5.1 (MathWorks, Inc., Sherborn, MA, USA). Images in DICOM format were converted to analyze format using MRIcro (www.mricro.com) and transferred to SPM2. Data were then standardized to the Montreal Neurological Institute (MNI) atlas, using a 12-parameter affine transformation, followed by trilinear interpolation. The resulting voxel dimensions were 2 mm × 2 mm × 2 mm. The standardized data were smoothed with a Gaussian filter of a FWHM of 16 mm to increase the signal-to-noise ratio and to blur individual variations in the gyral anatomy. The two brain states within the same person (normal consciousness and Anapanasati meditation) were normalized for whole-brain count and compared using paired t-test. Areas showing statistically significant differences were identified at the voxel level with a height threshold of corrected P < 0.05 and a cluster size larger than 32 voxels (voxel extent threshold, kE). The anatomical location from the resulting MNI coordinates was identified using the MNI2Tal and Talairach Daemon database (http://ric.uthscsa.edu/projects/talairachdaemon.html).

The imaging data were also analyzed by MIM neuroanalysis software (MIM Software Inc., 25800 Science Park Drive-Suite 180, Cleveland, Ohio, 44122, USA), including a cluster subtraction workflow (P = 0.05) of FDG metabolism difference between normal consciousness and Anapanasati meditation. This analysis applied the Chulabhorn Hospital normal neuro-database for the comparison of FDG metabolisms.

The visual assessment was separately interpreted by two experienced nuclear physicians in multiplanar images, using the Syngovia Dicom viewer software (Siemens Healthineers, Munich, Germany).

 Results



Patient characteristics are shown in [Table 1].{Table 1}

18F-fluorodeoxyglucose positron-emission tomography/computed tomography

Visual analysis demonstrated moderate-to-marked increased metabolism in the posterior cingulate cortex in all six patients and mild-to-moderate increased uptake in the whole frontal lobe in four patients and in precuneus in four patients on the meditation PET image. The results of the visual analysis were compared during the meditation and normal consciousness in each individual participant, as shown in [Table 2] and [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], respectively.{Table 2}{Figure 1}{Figure 2}{Figure 3}{Figure 4}{Figure 5}{Figure 6}

Statistical parametric mapping analysis indicated that glucose consumption during Anapanasati meditation was significantly higher than the state of normal consciousness in the right mid-to-posterior cingulate gyrus (P < 0.000 uncorrected for multiple comparisons). In addition, we observed an increased uptake in the left superior frontal gyrus, with no statistically significant difference from the state of normal consciousness.

MIMneuro software gave similar results, with higher activity observed in the mid-to-posterior cingulate gyrus during Anapanasati meditation. The results are shown in [Figure 7], [Figure 8], [Figure 9].{Figure 7}{Figure 8}{Figure 9}

Electroencephalography

The normal pattern of consciousness which naturally occurred in every individual and the sample pattern of concentration during Anapanasati meditation from the group of participants are shown in [Figure 10] and [Figure 11], while the timing of detected pattern of concentration during meditation by the proposed index is demonstrated in [Table 3]. The index was selected according to the fundamental of the EEG pattern. To further analyze the recorded multichannel EEG signals, time-domain EEGs, we applied the standardized low-resolution brain electromagnetic tomography (sLORETA) source localization[8] and topographical brain maps of the EEG signals before and during effective meditation, with a modified explanation. Furthermore, the records during the normal consciousness and the sample pattern of concentration during the meditation from the group of participants are represented in [Figure 10] and [Figure 11], with the normal alpha activity pattern during the normal consciousness [Figure 10]a and the low-frequency alpha activity in the occipital and parietal regions [Figure 11]a (rows A1, A30, A4, and A27 in the frontal channels Fp1, Fp2, F3, and F4, respectively; A14, A18, A15, and A17 in the parietal and occipital channels PO3, PO4, O1, and O2, respectively); A14, A18, A15, and A17 in the parietal and occipital channels PO3, PO4, O1, and O2, respectively).{Figure 10}{Figure 11}{Table 3}

In contrast, the sample of concentration patterns during meditation from participants is illustrated in [Figure 11]. In addition to the parietal and occipital regions, the alpha activity during effective meditation (detected at 26 min, 56 s) was also clearly observed in the frontal regions. The alpha activity led to high-amplitude EEGs, which are visualized in [Figure 10]c and [Figure 11]c as topographical brain maps (high amplitudes in red and low amplitudes in blue). To further analyze the differences in EEG between the two brain states, we examined the neural activity in the brain by taking the inverse of the 32-channel EEG using sLORETA. [Figure 11]b shows the neural activity in the frontal areas during effective meditation but absent during the normal consciousness state [Figure 10]b.

 Discussion



Different meditation techniques may have different effects on the brain.[9],[10] Directive meditation appears to be related to increased brain activity, while nondirective meditation is associated with decreased brain activity.[11] A previous 18F-FDG PET/CT study demonstrated alterations in regional metabolism after prolonged meditation practice for 8 weeks.[12] Body/mind-relaxation meditation could affect the brain activity in the prefrontal cortex[13] and yoga yielded the effects to the cerebellum, right temporal, right inferior frontal, left superior frontal, left associative visual, and right posterior cingulate cortices (PCCs).[14]

Our study is the first report of alterations in regional cerebral glucose metabolism and EEG during Anapanasati meditation. The increased glucose metabolism in the right mid-to-posterior cingulate gyrus was statistically significant at the voxel level when not corrected for multiple comparisons. Meanwhile, we found a nonsignificant increase in the left superior frontal gyrus. EEG analysis also indicated the frontal area alpha activity only during the meditation. Following the visual assessment in each individual, we found the hypermetabolism area during the meditation at posterior cingulate gyrus, compatible to the semiquantitative analysis. Meanwhile, the hypermetabolism was also identified at frontal, precuneus, or cuneus in some participants but not statistically significant in the semiquantitative analysis. This could be likely due to the limitation of our quantitative analysis, such as the selection of suboptimal brain area for signal intensity normalization, conversion of each individual brain to the MNI space template due to variation of individual brain morphology, adjustment of imaging smoothing parameters, statistical setting for voxel-wise comparison or variation from anatomical mapping with MNI2Tal, and Talairach Daemon database for identification of regional brain.[15],[16]

Our findings were compatible to those of Newberg et al., which used single-photon emission computed tomography (SPECT) to demonstrate the increased cerebral blood flow in the right posterior cingulate gyrus and left superior frontal regions of meditators.[14] Our results were also consistent with Khalsa et al., using SPECT to examine the alterations in brain physiology during the chanting meditation called Kirtan Kriya. The study reported the increased regional cerebral blood flow in the posterior cingulate gyrus.[17] Meanwhile, Herzog et al. reported that yoga meditation led to the increased cerebral glucose metabolism.[18]

Initially, the PCC is involved in very complex pathways, and several studies have reported its involvement in meditation practice. For instance, Brewer et al. reported the increased functional connectivity between the ventral PCC and the frontoparietal control network in expert meditators.[19] Additional support for the role of PCC in meditation was demonstrated in Manuello et al., with the increased posterior cingulate gyrus connectivity with the default mode network in novices who practiced mindfulness or meditation and the decreased connectivity in expert practitioners.[20]

Importantly, the stage of concentration or the optimal/successful meditation as defined in Buddhist Anapanasati meditation depends on each individual's mindfulness, not the different brain functions in a wide range of ages. As well, meditation in Buddhism mainly relies on the state of mind during each session of meditation. In the meantime, it was unable to define expert and novice practitioners in our study due to no single standardized parameter for measurement, such as the amount of time for meditation in practice to differentiate the level of expertise in meditation.

The increase in glucose metabolism in the right mid-to-posterior cingulate gyrus and a potentially increased metabolism in the left superior frontal gyrus in our study may be explained as follows. The increased activity in the posterior cingulate gyrus was likely because the participants reached a meditative level of compassion with joys and happiness.[21] The posterior cingulate gyrus is known to be activated during happiness.[22] Moreover, Brodmann area 9 (superior frontal gyrus) and the posterior cingulate gyrus can play a very crucial role in memory function during the Anapanasati meditation.[23] Ultimately, the increase in brain activity could be resulted from the required memory for consciousness while practising Anapanasati meditation.

Concerning the EEG analysis, we used the software developed in-house to calculate a proposed real-time index for early meditation. Based on EEG knowledge,[7] the alpha activity (8–13 Hz) increases with the reduced sensory perception and the sensory perception seems to decrease during effective meditation. The location of alpha activity during meditation differs from that during normal consciousness state, in which the alpha activity is only observed in the occipital and parietal areas but also in the frontal areas.

Our EEG findings indicated that effective meditation was associated with an increased alpha signal in the frontal lobe. This specific EEG signal was due to the chemical changes that resulted from the neuron activation. Various reports demonstrated that the alpha waves increase during meditation. For example, Lagopoulos et al. revealed that the nondirective meditation techniques could alter the theta and alpha EEG patterns significantly more than the regular relaxation.[24] Similarly, a review by Lee et al. reported that several types of meditation are related to the higher global oscillatory activity among experienced meditators than beginners. The increase in frontal lobe alpha activity is also correlated with the length of meditation training.[25] Moreover, Huang and Lo also reported more alpha waves in the frontal regions during mindfulness meditation. Based on this evidence, it is interesting that the meditation practice generates these alpha waves, which are believed to relieve stress, anxiety, and pain.[26]

Valente et al. and Kuschinsky[27],[28] described the strong correlation between local metabolism, blood flow, and EEG, activating brain function in specific functions. With activation in any brain areas, neurons would increase glucose utilization, leading to the increased cerebral blood flow and later glucose metabolism. Then, EEG signals can be linked to the alterations in glucose metabolism. Interestingly, our results showed that the increased alpha EEG activity was in the frontal lobe, with the significantly increased FDG metabolism in the posterior cingulate. It is assumed that the surface EEG cannot be measured by the occurrence of neural activity below the upper layers of the brain due to the voltage fields which fell off the square of the distance from the source.[29]

Our study was limited by the small number of subjects. This was due to the fact that the meditation in Buddhism is not just a common term of concentration. In particular, the levels of meditation cannot be truly showed off by any individuals. Actually, meditation is an internal and natural manner of each meditator toward truthful knowledge and true enlightenment. Hence, very few volunteers would rather participate, while many others feel quite awkward to join in our study. However, our results were statistically significant though a preliminary study.

Despite these limitations, our findings suggested that the state of Anapanasati meditation could lead to both the increased metabolism in the right mid-to-posterior cingulate gyrus and the increased frontal alpha waves. Thus, Anapanasati meditation practice may be related to the stage of meditative concentration of happiness and peacefulness, with the access concentration. Most importantly, Anapanasati meditation likely activates the PCC circuitry involved in self-control, mood stabilization, and happiness, leading to the well-being and improved health.

 Conclusion



This study is the first report describing the alterations of regional cerebral glucose metabolism and EEG during Anapanasati meditation. Our semiquantitative analysis showed a significantly increased metabolism only in the posterior cingulate cortex, but visually, there was also an increased metabolism in the whole frontal lobe in most of the patients correlating with EEG findings.

Acknowledgments

The authors would particularly like to extend our special thanks to Bhikkhu Piyalak Panyavaro from Wat Nyanavesakavan for the Anapanasati meditation teaching and practice, as well as the acquired-knowledge and technical supports during the intervention phase of the study. We would also like to acknowledge the help of Savittree Suratako and Wantana Juiklom in routine PET/CT imaging. English editing provided by Mrs. Sunattee Kessung was also appreciated. In addition, we thank Adam Phillips, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

Financial support and sponsorship

This study was financially supported Chulabhorn Hospital, Chulabhorn Royal Academy.

Conflicts of interest

There are no conflicts of interest.

References

1Innes KE, Selfe TK. Meditation as a therapeutic intervention for adults at risk for Alzheimer's disease – Potential benefits and underlying mechanisms. Front Psychiatry 2014;5:40.
2Zeidan F, Martucci KT, Kraft RA, McHaffie JG, Coghill RC. Neural correlates of mindfulness meditation-related anxiety relief. Soc Cogn Affect Neurosci 2014;9:751-9.
3Tomasino B, Fabbro F. Editorial: Neuroimaging and neuropsychology of meditation states. Front Psychol 2015;6:1757.
4Boccia M, Piccardi L, Guariglia P. The meditative mind: A comprehensive meta-analysis of MRI studies. Biomed Res Int.2015. doi: 01.1155/2015/419808.
5Varrone A, Asenbaum S, Vander Borght T, Booij J, Nobili F, Någren K, et al. EANM procedure guidelines for PET brain imaging using [18F] FDG, version 2. Eur J Nucl Med Mol Imaging 2009;36:2103-10.
6Stoica P, Moses R. Spectral Analysis of Signals. New Jersey: Prentice Hall; 2005.
7Nunez P, Srinivasan R. Electric fields of the brain: The neurophysics of EEG. New York: Oxford University Press; 2005.
8Pascual-Marqui RD. Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details. Methods Find Exp Clin Pharmacol 2002;24 Suppl D: 5-12.
9Sharma H. Meditation: Process and effects. Ayu 2015;36:233-7.
10Weitzman PD, Danson MJ. Citrate synthase. Curr Top Cell Regul 1976;10:161-204.
11Xu J, Vik A, Groote IR, Lagopoulos J, Holen A, Ellingsen O, et al. Nondirective meditation activates default mode network and areas associated with memory retrieval and emotional processing. Front Hum Neurosci 2014;8:86.
12Pomykala KL, Silverman DH, Geist CL, Voege P, Siddarth P, Nazarian N, et al. A pilot study of the effects of meditation on regional brain metabolism in distressed dementia caregivers. Aging health 2012;8:509-16.
13Chen F, Lv X, Fang J, Yu S, Sui J, Fan L, et al. The effect of body-mind relaxation meditation induction on major depressive disorder: A resting-state fMRI study. J Affect Disord 2015;183:75-82.
14Newberg A, Alavi A, Baime M, Pourdehnad M, Santanna J, d'Aquili E. The measurement of regional cerebral blood flow during the complex cognitive task of meditation: A preliminary SPECT study. Psychiatry Res 2001;106:113-22.
15Sarikaya I, Sarikaya A, Elgazzar AH. Current Status of 18F-FDG PET brain imaging in patients with dementia. J Nucl Med Technol 2018;46:362-7.
16Dukart J, Mueller K, Horstmann A, Vogt B, Frisch S, Barthel H, et al. Differential effects of global and cerebellar normalization on detection and differentiation of dementia in FDG-PET studies. Neuroimage 2010;49:1490-5.
17Khalsa DS, Amen D, Hanks C, Money N, Newberg A. Cerebral blood flow changes during chanting meditation. Nucl Med Commun 2009;30:956-61.
18Herzog H, Lele VR, Kuwert T, Langen KJ, Rota Kops E, Feinendegen LE. Changed pattern of regional glucose metabolism during yoga meditative relaxation. Neuropsychobiology 1990;23:182-7.
19Brewer JA, Worhunsky PD, Gray JR, Tang YY, Weber J, Kober H. Meditation experience is associated with differences in default mode network activity and connectivity. Proc Natl Acad Sci U S A 2011;108:20254-9.
20Manuello J, Vercelli U, Nani A, Costa T, Cauda F. Mindfulness meditation and consciousness: An integrative neuroscientific perspective. Conscious Cogn 2016;40:67-78.
21Deo G, Kumar IR, Srinivasan TM, Kushwah KK. Cumulative effect of short-term and long-term meditation practice in men and women on psychophysiological parameters of electrophotonic imaging: A cross-sectional study. J Complement Integr Med 2016;13:73-82.
22Cheng W, Rolls ET, Qiu J, Xie X, Wei D, Huang CC, et al. Increased functional connectivity of the posterior cingulate cortex with the lateral orbitofrontal cortex in depression. Transl Psychiatry 2018;8:90.
23Yee LT, Roe K, Courtney SM. Selective involvement of superior frontal cortex during working memory for shapes. J Neurophysiol 2010;103:557-63.
24Lagopoulos J, Xu J, Rasmussen I, Vik A, Malhi GS, Eliassen CF, et al. Increased theta and alpha EEG activity during nondirective meditation. J Altern Complement Med 2009;15:1187-92.
25Lee DJ, Kulubya E, Goldin P, Goodarzi A, Girgis F. Review of the Neural Oscillations Underlying Meditation. Front Neurosci 2018;12:178.
26Huang HY, Lo PC. EEG dynamics of experienced Zen meditation practitioners probed by complexity index and spectral measure. J Med Eng Technol 2009;33:314-21.
27Valente S, Ringwood J, Mangourova V, Lowry J. Investigation of Events in the EEG Signal Correlated with Changes in Both Oxygen and Glucose in the Brain”. In: IET Irish Signals and Systems Conference (ISSC 2012); 2012. p. 1-6.
28Kuschinsky W. Is the EEG correlated with the brain metabolism and cerebral blood flow? In: Zschocke S, Speckmann EJ, editors. Basic Mechanisms of the EEG. Birkhäuser, Boston, MA: Brain Dynamics; 1993.
29Rao RP. Brain-Computer Interfacing. New York: Cambridge University Press; 2013. p. 337.