Universitätsspital Zürich Klinik für Ohren-, Nasen-, Hals- und ...
Transcript of Universitätsspital Zürich Klinik für Ohren-, Nasen-, Hals- und ...
Universitätsspital Zürich
Klinik für Ohren-, Nasen-, Hals- und Gesichtschirurgie
Direktor: Prof. Dr. med. Alexander Huber
Betreuung der Masterarbeit: Dr. med. Colette Hemsley
Leitung der Masterarbeit: Prof. Dr. med. Tobias Kleinjung
Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha connectivity
MASTERARBEIT
zur Erlangung des akademischen Grades
Master of Medicine (M Med) der Medizinischen Fakultät der Universität Zürich
vorgelegt von
Fabian Kraxner
Matrikelnummer: 10-752-640
2016
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Inhaltsverzeichnis
1 Begleittext zur Masterarbeit ............................................................................. 4
2 Publikation ......................................................................................................... 8
2.0 Abstract .................................................................................................................................. 8
2.1 Introduction ............................................................................................................................ 9
2.2 Methods ...............................................................................................................................10
2.2.1 Participants ...............................................................................................................10
2.2.2 Room ........................................................................................................................11
2.2.3 Design .......................................................................................................................11
2.2.4 Materials ...................................................................................................................11
2.2.4.1 Questionnaires ...........................................................................................11
2.2.4.2 Short Questionnaire....................................................................................11
2.2.4.3 Audiometry .................................................................................................11
2.2.5 EEG Recordings .......................................................................................................11
2.2.6 Procedure .................................................................................................................11
2.2.7 Data Analysis ............................................................................................................12
2.2.7.1 Questionnaires ...........................................................................................12
2.2.7.2 EEG Data ...................................................................................................12
2.2.7.2.1 Preprocessing ...........................................................................12
2.2.7.2.2 Global Average and Topographical Power Analysis.................12
2.2.7.2.3 Source-localized Current Density Analysis ...............................12
2.2.7.2.4 Functional Connectivity .............................................................13
2.3 Results .................................................................................................................................13
2.3.1 Audiometry ................................................................................................................13
2.3.2 Short Questionnaire ..................................................................................................13
2.3.3 EEG Data ..................................................................................................................14
2.3.3.1 Power Analysis ...........................................................................................14
2.3.3.2 Source-localized Current Density Analysis ................................................14
2.3.3.3 Source-localized Connectivity Analysis ......................................................15
2.4 Discussion ............................................................................................................................15
2.4.1 Psychometry .............................................................................................................15
2.4.2 EEG ..........................................................................................................................16
2.4.2.1 Power Analysis ...........................................................................................16
2.4.2.2 Source-localized Connectivity Analysis ......................................................17
2.4.3 Limitations .................................................................................................................17
2.4.4 Conclusion ................................................................................................................18
2.4.5 Future Directions.......................................................................................................18
2.5 References ...........................................................................................................................18
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2.6 Appendix ..............................................................................................................................25
2.6.1 List of Figures ...........................................................................................................25
2.6.2 List of Tables .............................................................................................................26
2.6.3 Supplemental Tables ................................................................................................27
3 Lebenslauf ....................................................................................................... 28
4 Ethikhinweis .................................................................................................... 29
5 Erklärung ......................................................................................................... 30
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Begleittext zur Masterarbeit
Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha
connectivity
Zusammenfassung
Tinnitus beschreibt das subjektive Hören eines Geräusches, meist ein Rauschen oder Sausen,
ohne Vorliegen einer objektivierbaren Tonquelle. In unserer klinischen Studie wurden 45
Tinnituspatienten aus der ORL Klinik des Universitätsspitals Zürich (USZ) eingeschlossen. Von
ihnen wurde mittels Elektroenzephalogramm (EEG) die Gehirnaktivität unter 2
Versuchsbedingungen gemessen; zunächst im passiven Ruhezustand (RZ), danach unter
aktiver Konzentration auf ihren Tinnitus (AK). Verschiedene Fragebögen vor, während und nach
den 2 Sequenzen ermöglichten die Erhebung psychometrischer Daten.
Letztere zeigten, dass signifikante Unterschiede zwischen den beiden Bedingungen vorliegen,
hinweisend auf eine erhöhte Präsenz und Leiden unter aktiver Tinnitusperzeption. Ebenso
veränderte sich das EEG zwischen den beiden Bedingungen. Die α-Wellenkonnektivität
zwischen dem anterioren Cingulum und dem primären Hörkortex ist nämlich erhöht. Überdies
treten -, - sowie ϑ-Wellen gehäuft auf, während sich die δ-Wellenstärke erniedrigt darstellt.
Hintergrund/Fragestellung
Tinnitus ist von nicht zu unterschätzender volksgesundheitlicher Relevanz. Beispielsweise liegt
die Lebenszeitprävalenz in der US-Population bei 35%. Ca. 10% haben regelmässigen oder
kontinuierlichen Tinnitus und 1-2% leiden schwer darunter mit allenfalls zusätzlichen
Komorbiditäten.
In dieser empirischen Studie wurden 2 Versuchssituationen innerhalb einer Patientengruppe
verglichen, RZ vs. AK. Dabei wollen wir wissen, welche neurophysiologischen Unterschiede wo
im EEG auftraten und wie diese zu interpretieren sind. Nebst diesen objektiven Daten
erwünschen wir uns mittels den Fragebögen Auskunft über den subjektiven Belastungszustand
des Patienten. Im Besonderen interessieren uns die Veränderungen von diesem zwischen den
beiden Messbedingungen.
Material und Methoden
Die eingeschlossenen 45 Patienten (11 Frauen, 34 Männer; Ethik-Nr.: ZH-2012-0324) befinden
sich alle in Behandlung in der ORL-Klinik am USZ wegen manifestem Tinnitus und nehmen auf
freiwilliger Basis an dieser klinisch-empirischen Querschnittsstudie teil. Es wurde darauf
geachtet, dass Verschiedenheiten in Altersgruppen, Geschlecht, sozioökonomischem Status
und Bildungsniveau bestanden. Überdies durften die Teilnehmer keinen Koffeinkonsum
mindestens in den letzten 4 Stunden vor der Messung getätigt haben. Ebenfalls lagen
audiometrische Voruntersuchungen bei allen Probanden vor. Der gegebenenfalls
tinnitusbedingte Hörverlust war nicht signifikant unterschiedlich zwischen den beiden Ohren
(p<0.878).
Als Messort diente der schallisolierte, fensterlose Audiometrieraum, in welchem ein besonders
geräuscharmes Umfeld vorherrschte. Diese unübliche Stille erlaubte ein ideales Setting für das
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Ruhe-EEG. Gleichwohl ermöglicht es dem Patienten sich optimal und ablenkungslos auf den
Tinnitus zu konzentrieren, sobald dies gewünscht wird.
Die EEG-Messungen wurden mit einem 64 Kanal EEG System (Brainamp DC Brain Products,
2013) durchgeführt, stets zuerst im RZ, dann unter AK. Während der technischen Vorbereitung
des Probanden wurde explizit darauf geachtet, Messartefakte zu minimieren. Die Impedanz für
jede Elektrode lag unter 5 Ω. Der Teilnehmer sollte Kiefer-, Mund-, Schluck-, Kopf- sowie
Augenbewegungen vermeiden. Deshalb fixiert dieser einen auf seiner Augenhöhe platzierten
Punkt während der EEG-Messung. Des Weiteren wurde das Thema Tinnitus erst bei den
Instruktionen zur AK angesprochen. Die Erniedrigung der Raumhelligkeit sowie der
standardisierter Übergang vom RZ zur AK mittels folgender Instruktion „Bitte hören Sie nun auf Ihren Tinnitus“ zielten ebenso auf eine Fehlerquellenreduktion ab.
Die erhobenen EEG-Daten wurden mit entsprechenden Programmen von Artefakten wie z.B.
Augenblinzen, Bewegungen jeglicher Art oder Schlucken gesäubert und in einem zweiten
Schritt ausgewertet. Genaueres hierzu ist der Originalpublikation zu entnehmen.
Resultate
Erwartungsgemäss wiesen die Fragebögen auf einen signifikanten Unterschied (p<0.001)
zwischen RZ und AK hin in allen geprüften Modalitäten. Hierbei wurden ein vermehrtes
Tinnitusleiden mit erhöhter Geräuschlautstärke sowie eine verstärkte Beeinträchtigung bei
verminderter Ignorierbarkeit des Tinnitus festgestellt.
Die EEG-Daten, analysiert mit einer Fast Fourier Transformation, zeigten eine global alterierte
Wellenintensität im Rahmen einer verminderten δ- sowie erhöhten ϑ-, - und - Wellenpräsenz
in AK verglichen zum RZ. In den lokalisationsberücksichtigenden Analysen ist hervorzuheben,
dass eine erhöhte α-Wellenkonnektivität zwischen dem subgenualen anterioren Cingulum
(sgACC) links und dem linken primären auditorischen Kortex / Heschl’sche Querwindungen / Gyri temporalis transversi (GTT) eruierbar ist.
Diskussion
Nach bald 20 Jahren neurowissenschaftlicher Forschung bleibt Tinnitus ein schlecht erklärbares
Phänomen ohne kurative Heilmethode.
Die genannten psychometrischen Modalitäten des Tinnitus korrelieren mit einem erhöhten
Niveau an Depressionen sowie Ängsten. Die verstärkte α-Wellenkonnektivität unter AK
zwischen dem sgACC und den GTT kann mittels 2 Theorien erklärt werden.
Eine spezifische, umstrittene Theorie aus der Fachliteratur (Rauschecker et al., 2010) inkludiert
diese zwei kortikalen Strukturen zu einem sogenannten „Geräusch-Annullierungssystem“. Bei einem gewissen Anteil der Patienten funktioniert dieses durch serotinerge Strukturen vermittelte
Konstrukt, primär aus subcallosalen Bereichen hervorgehend. Diese können ihr störendes
Ohrgeräusch somit mehr oder weniger unwillentlich ausblenden. Der andere Teil hingegen hat
damit Schwierigkeiten.
Der Mechanismus erklärt zudem, weswegen erniedrigte hormonelle Serotoninaktivität oft nebst
störender Tinnitusperzeption auch mit depressiver Symptomatik und Schlaflosigkeit als
Komorbidität einhergeht. Spielt doch in der Regulation von letzteren beiden ebenfalls Serotonin
eine zentrale Rolle.
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Die erste Theorie geht davon aus, dass eben gerade die bewusste Tinnituswahrnehmung in der
AK-Phase dies verursacht. Die zweite Theorie erklärt sich die festgestellte Alteration unter AK
als nun willentlicher Versuch der Tinnitusgeräuschannullierung im beschriebenen System.
Konklusion
Zum ersten Mal konnte gezeigt werden, dass aktive beziehungsweise wissentliche
Tinnituswahrnehmung die elektrische Hirnaktivität im EEG verändert. Subgenuales anteriores
Cingulum und primäre auditive Hörrinde werden dabei vornehmlich linksseitig aktiviert und
bilden ein aktives Netzwerk. Sie stehen dadurch im Verdacht, die heimtückische
Tinnituswahrnehmung zu beeinflussen beziehungsweise gar zu unterhalten.
Mit der Unterscheidung zwischen RZ und AK wird auch das bis anhin häufig gebrauchte
Paradigma der alleinigen EEG-Ruhemessung bei Tinnitus in Frage gestellt. Dieses ist zu
schlecht kontrolliert und liefert folglich verzerrte Daten. Zukünftiges Studiendesign muss diesen
Umstand berücksichtigen, indem man beispielsweise versucht, den Teilnehmer vor und
während der Ruhemessung abzulenken oder geeignet zu instruieren.
Des Weiteren zeigt diese Arbeit auf, wie methodisch wichtig multimodale Integration ist, welche
neuroanatomische, neurophysiologische und neuromodifizierende Ansätze berücksichtigt. Das
effektive, funktionelle Netzwerk hieraus kennzeichnet den Grundpfeiler von zukünftiger
Forschung und neuromodulatorischer Therapie.
Weitere Studien sollten ein longitudinales klinisches Studiendesign anstreben. Denn
insbesondere im Hinblick auf neuroplastische Veränderungen über die Zeit liegen keine
relevanten Forschungsdaten vor. Nichtsdestotrotz ist Tinnitus eine Erkrankung, welche sich
häufig über einen längeren Zeitrahmen hartnäckig manifestiert und im Allgemeinen die
individuellen Verläufe sowie der Leidensdruck sich sehr verschieden ausgestalten können.
Eigenleistung
Meine Hauptaufgabe war es, die artefaktarme Messung der Hirnaktivität mittels der gängigen
Elektroenzepahlographie (EEG) sowie die adäquate Durchführung der Fragebögen zum
momentanen subjektiven Befindenszustand für 45 Patienten eigenständig zu tätigen. Nebst der
sorgfältigen Patienteninstruktion sowie der präzisen Technikbedienung nach standardisiertem
Schema war ebenso meine kritische, objektive und sachkundige Interpretation aller erhobenen
Daten und Parametern während und nach dem Experiment von grosser Bedeutung.
Schlussendlich galt es im Rahmen der Datenprozessierung, die erhobenen Aufzeichnungen
korrekt in das EDV-System einzupflegen.
Die fehlerarme EEG-Messung erforderte genaue Kenntnisse der äusseren Kopfanatomie.
Durch die korrekte Vermessung des Kopfes anhand anatomischer Punkte wie beispielsweise
der Protuberantia occipitalis externa konnte die passende EEG-Messkappe korrekt positioniert
und das Messergebnis verbessert werden. Jede der 64 Elektroden erhielt somit einen
vordefinierten, reproduzierbaren örtlichen Bezugspunkt am Kopfschädel. Die anschliessende
Messung für die bekannten zwei Versuchsbedingungen (RZ, dann AK) durfte standardisiert erst
bei genügend starkem Messsignal, festgelegter tiefer Impedanz (< 5 Ω) über allen Elektroden
sowie glaubhafter Ausräumung aller Verständnisfragen beim Probanden gestartet werden.
Die Patientenakquisition sowie Kontaktierung und Aufbietung gehörten ebenso zu meinem
Aufgabenbereich wie die Terminkoordination sowie die Patientenvor- und Nachbereitung. Die
regelmässige Teilnahme an Meetings bezüglich dem Projektverlauf sowie die initiale
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thematische Einarbeitung mittels der einschlägigen Fachliteratur stellen eine
Selbstverständlichkeit dar.
Des Weiteren partizipierte ich an der kritischen Gegenlektüre der Publikation sowie an deren
Verbesserung innerhalb des Forschungsteams. Dadurch geschah gleichzeitig ein wertvoller
Wissensaustausch im Rahmen gemeinsamer Diskussionen, wodurch mir die weiteren
Gruppenmitglieder Ihren entsprechenden Arbeitsanteil detailliert erläuterten. Bezüglich der
Publikation trug ich die erstinstanzliche inhaltliche Hauptverantwortung für die Abschnitte 2.2.1
bis inklusive 2.2.6.
10. Februar 2016 – Fabian Kraxner
Active listening to tinnitus is related to enhanced EEG highfrequency activity and alpha connectivity
Patrick Neff1,2,3, Fabian Kraxner4, Colette Hemsley4, SteffiWeidt5, Martin Meyer1,2,6, and Tobias
Kleinjung4
1Neuroplasticity and Learning in the Healthy Aging Brain (HAB LAB), Institute of Psychology,
University of Zurich, Switzerland2University Research Priority Programm ‘Dynamics of Healthy Aging’, University of Zurich,
Switzerland3Institute for Computer Music and Sound Technology (ICST), University of Arts Zurich, Switzerland
4Department of Otorhinolaryngology, University of Zurich, Switzerland5Department of Psychiatry and Psychotherapy and Interdisciplinary Tinnitus Clinic, University Hospital
of Zurich, Switzerland6Cognitive Psychology Unit (CPU), University of Klagenfurt, Austria
Tinnitus is primarily manifest as an audible sound with no external source. Decisive consensus
exists that it is somehow related to central or peripheral hearing loss and related maladaptive
plasticity throughout the brain. A considerable amount of neuroscientific studies was con-
ducted in respect to tinnitus applying anatomic (magnetic resonance imaging (MRI)), func-
tional MRI (fMRI) as well as electroencephalography (EEG), and neurostimulation (mostly
(rhythmic) transcranial magnetic stimulation ((r)TMS) methods. Most of these studies imple-
ment group contrasts paradigms with healthy controls. To that end, resting state recordings are
most commonly performed in EEG studies.
No former study aimed at comparing different (auditory) perceptual modes in engaging to the
tinnitus percept in these ubiquitous EEG resting state paradigms. Therefore, the difference
between "resting state" (RS) and "active listening" to tinnitus (AL) was investigated with both
psychometric and neurophysiological instruments analyzing EEG power and connectivity.
A sample of 45 participants looking for help at the otolaryngology department of the University
Hospital of Zurich (USZ) was recruited. The short questionnaire used after both conditions pro-
duced significant differences in all assessed items (tinnitus distress, loudness, annoyance, ig-
norability, p < 0.05) pointing to an increased presence and distress during AL. Related to that,
insights could be gained into activated intra-cortical functional tinnitus networks during AL,
mainly increased EEG alpha connectivity between (subgenual) anterior cingulate (ACC) and
auditory cortices. Furthermore, EEG beta and gamma power were focally increased in frontal
and medial regions, whereas theta and delta power only showed trends of differences between
the conditions. These EEG power changes during AL reflect the well-established pattern of
altered high-frequency band activity (i.e., beta and gamma) in tinnitus sufferers compared to
healthy controls.
In conclusion, it is assumed that the established EEG resting state research paradigm in the tin-
nitus field may be partly confounded by aspects of (involuntary) perceptual modes or attention
to the tinnitus. Future studies should consider or integrate these insights, especially in regards
to individual treatment settings and protocols.
2 PATRICK NEFF,
FABIAN KRAXNER,
COLETTE HEMSLEY,
STEFFI WEIDT,
MARTIN MEYER,
TOBIAS KLEINJUNG
1 Introduction
The phenomenon of a ringing, whistling, sizzling, hum-
ming, hissing, buzzing, whooshing, roaring, fizzing, crack-
ling, cricketing, knocking, or pulsing sound in the ear or else-
where is known and reported since archaic and antique times
(Steiner, 2012). Predominately, tinnitus is defined as "the
perception of sound(s) in the absence of an external sound
source" (Eggermont & Roberts, 2004; Erlandsson & Dau-
man, 2013).
Haunted by this phantom auditory perception are no less
than 35 percent of the general (US) population any time dur-
ing their life (Jastreboff, 1990). 10-15 percent report their
tinnitus percept as frequent or continuous whereas about 1-2
percent suffer heavily from it (Langguth, Kreuzer, Kleinjung,
& De Ridder, 2013).
The percept itself, in most cases, manifests as a (sine)
tone or high-pitched noise around 6-8 kHz (Eggermont &
Roberts, 2004) perceived mostly in bilateral ears or with a
slight preference to one side (Lockwood, Salvi, & Burkard,
2002). Loudness and pitch are therefore the main perceptual
parameters of interest alongside maskability and residual in-
hibition (Henry & Meikle, 2000).
Usually, tinnitus is caused by either objective (Egger-
mont & Roberts, 2004; Mazurek, Olze, Haupt, & Szczepek,
2010; Schaette & Kempter, 2006) or hidden hearing loss
(Adjamian, Sereda, Zobay, Hall, & Palmer, 2012; Schaette
& McAlpine, 2011; Nathan Weisz, Hartmann, Dohrmann,
Schlee, & Norena, 2006; Xiong et al., 2013). It is speculated
that related loss of cochlear hair cells (outer hair cells (OHC)
as well as inner hair cells (IHC)) leads to maladaptive plas-
ticity throughout the auditory pathway and brain (Jastreboff,
1990), which then generates the percept in a putative similar
manner than phantom limb or general phantom (pain) per-
ception following sensory deafferentation (De Ridder, Elgoy-
hen, Romo, & Langguth, 2011). Up to this day, there is no
clearly established pathogenesis and -physiology model nor
an effective, understood cure - yet, it can be clearly stated that
both the inner ear (certainly involved in ’pathogenesis’) and
the brain (as the location of awareness and central nervous
system plasticity) are key contributors to tinnitus. With evi-
dence accumulated in tinnitus-related research up to this day,
a clear involvement of the brain has been clearly established
(Adjamian, Sereda, & Hall, 2009; De Ridder, Elgoyhen, et
al., 2011; De Ridder et al., 2013; Eggermont & Roberts,
2004; Jastreboff, 1990; Vanneste & De Ridder, 2012b).
Unfortunately, there is no simple ’switch’ to turn off the
tantalizing sound as is obvious from previous considerations
and clinical experience (Hesse, 2013). There are though
promising insights derived from the last years of research,
which clearly identify three approaches as the most promis-
ing (Langguth et al., 2013): First, an adaption of classi-
cal psychological (cognitive) therapy (Cima et al., 2012).
Secondly, auditive or musical retraining be it either with
tailor-made notched music training (Okamoto, Stracke, Stoll,
& Pantev, 2010; Pantev, Okamoto, & Teismann, 2012)
or acoustic coordinated reset neuromodulation (Adamchic,
Toth, Hauptmann, & Tass, 2014; Tass, Adamchic, Freund,
Stackelberg, & Hauptmann, 2012). Within the third group of
promising treatment approaches, namely neuromodulation,
is neurofeedback (NFB) usually applying EEG (Dohrmann,
Elbert, Schlee, & Weisz, 2007; Hartmann, Lorenz, Müller,
Langguth, & Weisz, 2014; Schenk, Lamm, Gundel, & Lad-
wig, 2005) or in some cases fMRI (Haller, Birbaumer, &
Veit, 2010, 2013). EEG NFB seems to be especially promis-
ing, as other non-invasive neuromodulatory approaches, like
(repetitive) transcranial magnetic stimulation ((r)TMS), e.g.,
(Burger et al., 2011; Müller, Lorenz, Langguth, Weisz, &
Mouraux, 2013; Plewnia et al., 2012; Vanneste & De Ridder,
2012c), failed to prove efficiency or an actual mechanism of
induced neuroplastic change, e.g. (Nathan Weisz, Lüchinger,
Thut, & Müller, 2014). For reviews the reader is referred to
Langguth et al. (2012) and Vanneste and De Ridder (2012a).
Regarding the aim and scope of the study it is considered
unnecessary to cover all involved pathologic and neurophys-
iological mechanism beyond the scope of the applied meth-
ods. For that reason, any basic research involving animals,
surgery, local and global pharmacological interventions and
mere audiology are skipped or referenced to respective com-
prehensive reviews - at this point ideally to the still valid and
highly influential review by Eggermont and Roberts (2004).
Former MEG/EEG studies comparing tinnitus sufferers
with healthy controls identified decreased global as well as
temporal alpha band power (Moazami-Goudarzi, Michels,
Weisz, & Jeanmonod, 2010; Schlee et al., 2014; N. Weisz,
2005) and increased delta band power (Adjamian et al., 2012;
Moazami-Goudarzi et al., 2010; N. Weisz, 2005). The study
of (Moazami-Goudarzi et al., 2010) furthermore showed an
increase in theta band power. Regarding the gamma band,
several studies showed an increase in gamma power (ana-
lyzed frequencies ranging from 35- 90 Hz) (Ashton et al.,
2007; Lorenz, Müller, Schlee, Hartmann, & Weisz, 2009;
van der Loo, Elsa et al., 2009; Weisz et al., 2007) ’Idle’
alpha desynchronization (Nathan Weisz, Hartmann, Müller,
& Obleser, 2011) seems related to increased spontaneous
synchronization in higher bands like gamma as shown in
a respective negative correlation between these two bands
(Lorenz et al., 2009). Reduced alpha therefore is either pre-
requisite to develop tinnitus or the consequence of the patho-
logical hypersynchronization in lower and higher bands. In-
creased synchronization in lower bands (i.e., delta and party
theta) is theorized to be related to activity of deafferenti-
ated neurons (R. R. Llinás, Ribary, Jeanmonod, Kronberg,
& Mitra, 1999) and thus typical of a lesion-induced deaf-
ferentiation pathology like tinnitus. The role of the gamma
band remains unclear as recent work of (Sedley et al., 2012)
proposes that gamma functions as an active attempt of tin-
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 3
nitus inhibition mediated by local circuits. Nevertheless,
gamma band is still widely accepted to reflect active percep-
tion and/or memory binding processes in tinnitus sufferers.
As not only the participant’s characteristics differ but of
more severity the recording (MEG vs. EEG, number of mag-
netic detectors and electrodes) and analysis methods (e.g.
different source localization methods) the results of these
studies must be interpreted carefully and a unified method-
ological framework should be established (Adjamian, 2014).
Recent advancements in MEG/EEG analysis methods
as well as increased interest in cortical network analyses
spawned respective connectivity analyses of putative tinni-
tus networks in the brain. Schlee, Hartmann, Langguth, and
Weisz (2009) showed decreased global phase coupling in the
alpha band whereas the phase coupling in the gamma band
was increased. Regarding cortical interregional connectiv-
ity, these alpha phase coupling reductions were generally ob-
served between tentative tinnitus network hubs including bi-
lateral frontal, temporal, parietal as well as anterior and pos-
terior cingulate cortices. Again, within the same network the
gamma connections were reduced which in turn was nega-
tively correlated with the alpha network. Furthermore, the
altered connectivity in these bands aggravated with tinni-
tus duration and the auditory cortex became gradually dis-
patched from the tinnitus network. The latter finding was a
major step towards the understanding of neuroplasticity over
the time course of the tinnitus suffering and finally lead to
the construction of a global brain model of tinnitus (Schlee,
Lorenz, et al., 2011; Schlee, Mueller, et al., 2009) which in
short describes the transition of tinnitus from a focal, lesion-
induced, auditory-temporal phenomenon to a wide-spread
global brain network. For a comprehensive overview of cur-
rent theorized tinnitus networks the reader is referred to re-
spective review papers (De Ridder, Elgoyhen, et al., 2011;
Schlee, Lorenz, et al., 2011; Vanneste, Joos, De Ridder, &
Koenig, 2012).
The study at hand is generally aiming at further explo-
ration of tinnitus within actual sufferer’s perceptual and at-
tentional modes. This goal is approached by applying a, in
that form, novel approach to EEG resting state study design
in tinnitus research by contrasting auditory engagement to
tinnitus, ’active listening’ (AL), to a passive standard ’rest-
ing state’ (RS) condition. Andersson et al. (2006) applied
a related design in a positron emission tomography (PET)
study and showed decreased activity of the auditory cortices
during distraction compared to a resting state condition. In
line with this finding we hypothesize that the auditory cor-
tex is less activated in the RS condition compared to AL. In a
further related design Adjamian et al. (2012) found decreased
delta activity in the right auditory cortex while tinnitus was
masked.
Beyond that, the approach can also be seen as a conceptual
transfer of the traditional group comparison approach be-
tween tinnitus sufferers and healthy controls into the ’within
subject’ domain of the tinnitus population. Thus, we hypoth-
esize that respective tinnitus-specific alterations in the delta,
theta, alpha, beta and gamma band become observable be-
tween the conditions.
Generally, it is assumed, that the different perceptual
modes may elucidate global and focal altered EEG power
as well as connectivities within the cortical tinnitus network.
Related to the nature of the task general neurophysiological
correlates of attention and perceptual mode engagement are
expected on a large-scale network level (Doesburg, Green,
McDonald, & Ward, 2012; Mathewson et al., 2014; Varela,
Lachaux, Rodriguez, & Martinerie, 2001) and especially
task-specific decreases in alpha power (Jensen & Mazaheri,
2010; Klimesch, Sauseng, & Hanslmayr, 2007; Mathew-
son et al., 2014; Pfurtscheller & da Silva, 1999). Concern-
ing tinnitus-specific alterations, an involvement of accessi-
ble (i.e., through EEG) brain regions, primarily (primary)
auditory cortices as well as medial limbic structures is ex-
pected throughout all planned subanalyses (e.g., (De Ridder,
Vanneste, Marco Congedo, & Koenig, 2011; Rauschecker,
Leaver, & Mühlau, 2010; Vanneste, Plazier, der Loo, Elsa
van, et al., 2010).
2 Methods
2.1 Participants
The study comprises tinnitus patients of the University
Hospital of Zürich (USZ), which partook in a psychomet-
ric study including an online survey. In the EEG analysis at
hand 45 participants (11/34 female/male) with high fidelity
EEG recordings were chosen resulting in a heterogeneous
and representative sample of tinnitus sufferers.
An overview with all relevant characteristics for this study
can be found in Table 1.
Table 1
Participant Characteristics
4 participants have a right-lateralized tinnitus, 5 a left-
lateralized, 11 a "central", 10 with a preference to the right
side, 9 with a preference to the left side, 5 diffusely inside
the head, and 1 participant in some other place. With most
of participants experiencing tinnitus in both "ears" or with a
preference to one side the sample is again representative of
the tinnitus population (Lockwood et al., 2002).
In respect to tinnitus pitch, only the completely-assessed,
categorical data is reported where 16 participants indicate a
4 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
"very high frequency", 20 a "high frequency", 8 a "middle
frequency", and 1 a "low frequency".
No secondary exclusions were performed based on medi-
cation (e.g., antidepressants or relaxants (7 cases)), or other
features (e.g., handedness (one left-hander)) as no indica-
tions or concerns related to tinnitus or the actual recording
procedure were identified.
2.2 Room
The room itself is a faraday cage as well as decoupled
from the rest of the building preventing concussions. It is
protected against every outside noise and has, at quiet, an
environmental noise level of about 27dBL or 35dBA. This
unusually quiet surrounding not only delivers an ideal setting
for the resting state EEG recording in not producing any au-
ditory stimuli possibly triggering neuronal activity, it further-
more enables the participant to focus on his tinnitus percept,
especially in the condition where active listening (AL) to the
tinnitus is demanded. An other acoustic feature of the room
is its well-balanced reverberation properties as the walls ab-
sorb most of the produced noises while not giving the im-
pression of a complete anechoic environment, which could
lead to auditory hallucinations or even tinnitus (Del Bo et al.,
2008; Heller & Bergman, 1953; Mason & Brady, 2009).
2.3 Design
In the first condition, patients were undergoing a standard-
ized vigilance-controlled EEG recording (RS) whereas, after
a break including a short questionnaire of tinnitus character-
istics, they were instructed to actively listen to their tinnitus
(AL) in the second condition.
This approach renders the study into a distinct method-
ological chimera mostly eliciting traits of standard resting
state EEG measurements with traits of a task-related design
as participants are asked to engage into a steady perceptual
mode.
2.4 Materials
2.4.1 Questionnaires. The questionnaires analyzed in
the course of the EEG study at hand are the Tinnitus Ques-
tionnaire (TQ) (G. Goebel & W. Hiller, 1994), Tinnitus
Handicap Inventory (THI) (Newman, Jacobson, & Spitzer,
1996), and "Tinnitus Beeinträchtigungsfragebogen" (TBF)
(Greimel, Leibetseder, Unterrainer, Biesinger, & Albegger,
2000) for tinnitus-related suffering, Beck Depression Inven-
tory (BDI) (Beck, Ward, Mendelson, Mock, & Erbaugh,
1961) and Beck Anxiety Inventory (BAI) (Beck, Epstein,
Brown, & Steer, 1988) for possibly comorbid affective dis-
orders, short forms of Symptom Check List (SCL) (Dero-
gatis, 1977) and Health Questionnaire ("Gesundheitsfrage-
bogen") (SF) (Bullinger & Kirchberger, 1998) for general
mental respectively physical health, and finally a short form
of WHO Quality of Life (WHOQOL-BREF) (WHOQoL
Group, 1998) to assess general well-being aspects of life. All
of these questionnaires are advocated as standards in tinnitus-
related studies (Landgrebe et al., 2012, 2010; Zeman, Koller,
Schecklmann, Langguth, & Landgrebe, 2012).
2.4.2 Short Questionnaire. The intention behind the
use of the Short Questionnaire (SQ) was to obtain a psy-
chometric confirmation of an increased tinnitus presence in-
cluding loudness and related distress in the second condi-
tion (AL). For this purpose, a selection of questions out of
the online survey and a previous EEG study (Meyer, Luethi,
Neff, Langer, & Büchi, 2014) was adapted. The first and
main question assessed the general tinnitus distress level on
5-point likert scale. Following that, the loudness, the annoy-
ance and the ignorability was assessed on a 10-point likert
scale each.
2.4.3 Audiometry. Standard audiometry was per-
formed by well-trained otolaryngologists binaurally starting
at 125 Hz pure tone presentation (in 5dB steps) in octaves
up to 8 kHz (i.e., 125, 250, 500, 1000, 2000, 4000, 6000,
and 8000 Hz). The measurement was taken in the course of
the patient’s diagnosis and assessment following standards
issued by the American Medical Association (AMA).
2.5 EEG Recordings
The EEG data was collected using a BrainAmp DC ampli-
fier system in combination with a 64 active channel EasyCap
electrode cap (BrainProducts, 2013), corresponding to the
established 10/5 electrode position system (Jurcak, Tsuzuki,
& Dan, 2007; Oostenveld & Praamstra, 2001), using the Fcz
electrode as the online reference. Impedances were kept be-
low 5 kOhm (mean, SD), sampling frequency was set to 1000
Hz. Recordings were performed in direct current (DC) mode
and hardware low-pass filtered with a cutoff frequency of 125
Hz with a slope of 12dB/Octave.
2.6 Procedure
All clinical, audiometric and demographical data were
gathered precursively during clinical consultations at the oto-
laryngology department of the USZ. The patients volunteer-
ing for the EEG recordings where then instructed to re-
frain from caffeine consumption at least 8 hours prior to the
recording session to prevent a confounding effect on the EEG
signal (Landolt et al., 2004), as neural oscillations in the theta
frequency band are hypothesized to be prominent in tinni-
tus pathophysiology (e.g., (De Ridder, van der Loo, Elsa,
et al., 2011; Moazami-Goudarzi et al., 2010; Nathan Weisz,
Moratti, Meinzer, Dohrmann, & Elbert, 2005)).
After being introduced to the aim and scope of the study
as well as signing the informed consent form, the participants
filled in the online survey at a desk in quiet while the record-
ing setting was prepared. Upon completion of the question-
naire they were seated in a comfortable chair in the mid-
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 5
dle of the room facing a wall with an asterisk as a fixation
point. Participants were informed about different EEG arti-
facts and asked to sit upright, relaxed and avoid unnecessary
movements especially with critical body parts (i.e., eyes, jaw,
head) whenever possible.
For the actual EEG recording lights were dimmed to a
medium level 1. The participants were instructed to simply
follow the vocal instruction played back by Presentation soft-
ware (Neurobehavioral Systems, 2013) and fixate the aster-
isk in the eyes open (EO) condition. A neutral, female voice
requested the participants to open or close their eyes respec-
tively via computer speakers followed by a low-pitched bell
sound. Total recording length was 8 minutes for each con-
dition yielding eight 40 seconds eyes closed (EC) segments
and eight 20 seconds EO segments per condition.
After the recording of the first condition, participants were
asked to fill in the SQ resulting in a little break where the the
room was again lightened to a normal level. For the second
condition, participants were orally instructed to actively lis-
ten to their tinnitus (in german: "Bitte hören Sie nun auf ihren
Tinnitus") and apart from this stick to the instructions of the
first condition (i.e., sit comfortable and upright, avoid unnec-
essary movements etc.). At the end of the second condition
the participants filled in a further exemplar of the SQ.
2.7 Data Analysis
2.7.1 Questionnaires. For statistical analyses of the
questionnaire and audiometry data, SPSS software (version
22) was used.
The 4 items of the SQ were compared using two-tailed
paired t-statistics. Furthermore, to estimate the effect size,
adequacy of sample size, and true significance Cohen’s d
(Cohen, 2013) was calculated using a published formula
suited for paired t-tests (Morris & DeShon, 2002). To con-
trol for multiple comparisons, the bonferroni method was ap-
plied.
2.7.2 EEG Data.
2.7.2.1 Preprocessing. Preprocessing of the EEG data
was performed with BrainVision Analyzer 2 (BrainProducts,
2013). The data was bandpass filtered with Butterworth zero
phase filters between 0.1 Hz and 100 Hz with a slope at the
low cutoff of 24 dB/octave and a slope at the high cutoff of 48
dB/octave. As the alternating current hum had only minimal
influence on the EEG signal, a 2nd order band rejection filter
with a central frequency of 50 Hz and a bandwidth of 1 Hz
was sufficient to eliminate the electrical interference. Bad
channels were excluded following standardized criteria (i.e.,
noise, drift or low activity).
As a next step, an independent component analysis (ICA)
was run with the whole data applying the restricted Infomax
(Gradient) algorithm with classic sphering in 512 iterations.
Resulting components indicative of eye blinks and move-
ments, some indefinite noise sources and very few pulse ar-
tifact components were removed of the data with the subse-
quent inverse ICA procedure. Next, excluded channels were
(re-)interpolated using the spline-type topographical interpo-
lation algorithm, which, simply put, estimates the signal of
a channel based on the activity of neighboring channels. An
average reference (channel) was calculated and applied in-
cluding the implicit reference channel of the actual recording
(i.e, Fcz), which on its part was reused increasing the amount
of analyzable ’active’ channels to 65. After segmenting the
data to the EC (sub-)conditions, always discarding the first
3 seconds due to excessive artifacts caused by the transition
from EO to EC, 8 segments with 37 seconds of EC recordings
each where extracted and further subdivided into 2-second
segments respectively.
The last step in the EEG preprocessing pipeline was the
semi-automatic rejection of remaining artifacts following
standardized criteria. In average, the artifact rejection pro-
cedure yielded 129 segments (SD=14.4) per participant and
conditions in the case of 2-second segments. The amount of
valid segments did not statistically differ between conditions
(t=-0.996, p=0.339 (two-tailed)).
2.7.2.2 Global Average and Topographical Power
Analysis. Eeglab (Delorme & Makeig, 2004) was invoked
to calculate neural activity differences between the condi-
tions on a global and scalp level. First a power spectrum
contrast averaged over all electrodes was calculated. Sec-
ond, topographical maps were produced depicting activation
of frequency bands of interest. The results of the topograph-
ical analysis were corrected for multiple comparisons using
the bonferoni method.
2.7.2.3 Source-localized Current Density Analysis.
SLORETA (Pascual-Marqui, 2007a; R. D. Pascual-Marqui,
2002) was used to source-localize electric potentials to possi-
ble intracortical generators. Technical details to both power-
and connectivity analyses implemented in the sLORETA
software suite can be found in the respective sources (R. D.
Pascual-Marqui, 2002; R. D. Pascual-Marqui et al., 2011).
The volume conductor model (of the brain) behind the
sLORETA algorithm is described in (Fuchs, Kastner, Wag-
ner, Hawes, & Ebersole, 2002) and the integrated proper
electrode position system in (Jurcak et al., 2007). Be-
sides being the most established source-localization algo-
rithm throughout EEG neurophysiology (Greenblatt, Os-
sadtchi, & Pflieger, 2005; Yao & Dewald, 2005), sLORETA
is also widely used in tinnitus-related EEG studies (e.g.,
(Adamchic et al., 2014; Joos, Vanneste, & De Ridder, 2012;
Song, De Ridder, Nathan Weisz, et al., 2013; van der Loo, E.,
Congedo, Vanneste, De Heyning, P. Van, & De Ridder, 2011;
Vanneste, M. Congedo, & De Ridder, 2013; Vanneste, De
Ridder, & Baumert, 2013; Vanneste et al., 2014; Vanneste,
Plazier, der Loo, Elsa van, et al., 2010; Vanneste, Song, &
1The standard room lighting was deemed too glaring for the
study.
6 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
De Ridder, 2013; Vanneste, Van de Heyning, Paul, & De
Ridder, 2011)).
The two conditions were compared using sLORETA in the
frequency domain (i.e., FFT current density analysis) with
paired tests yielding a differential activity map created by sta-
tistical non-parametric methods (Nichols & Holmes, 2002)
and corrected for multiple comparisons using a permutation
based approach with 5000 iterations.
2.7.2.4 Functional Connectivity. To be able to instan-
tiate connectivity calculations within in the brain, regions of
interest (ROI) had to be defined establishing the nodes of a
putative functional network as derived from previous litera-
ture or actual hypotheses.
A set of ROIs was selected from literature and own reason-
ings about a core tinnitus network as well as a putative noise-
canceling system e.g. (Leaver et al., 2011; Rauschecker et
al., 2010; Schlee, Hartmann, et al., 2009; Song, De Ridder,
Schlee, Van de Heyning, Paul, & Vanneste, 2013; Song, De
Ridder, Nathan Weisz, et al., 2013; Song, Vanneste, Schlee,
Van de Heyning, Paul, & De Ridder, 2013; Vanneste, M.
Congedo, & De Ridder, 2013; Vanneste et al., 2014). No-
tably, the selection of ROIs is not trivial as the locations and
number of selected ROIs influences the obtained results im-
mensely. The choice of ROIs was therefore limited to regions
conjectured in the hypotheses as well as established regions
in previous literature, most prominently frontal, temporal,
anterior and posterior cingulate, and parietal cortical regions
(Schlee, Hartmann, et al., 2009). Furthermore, a parahip-
pocampal ROI was added as of risen interest in recent studies
and models (Vanneste & De Ridder, 2012b). Centroid voxels
in the respective Brodmann areas (BA) were chosen instead
of averaged activity of whole BAs to circumvent ’spillover’
effects between neighboring ROIs.
The respective coordinates and more precise structural
definitions and localizations are referenced in the supplement
(see Supplement: Table 3).
With the ROIs defined, lagged and instantaneous coher-
ence between the nodes can be calculated (Pascual-Marqui,
2007b).
Following network terminology, the brain is a highly in-
terconnected network where brain areas (or underlying sub-
structures like cortical columns or other assemblies of neu-
rons) can be defined as ’nodes’ within a ’network’ and
functional connections between them as ’edges’ within this
network. Classically, these networks were theorized and
probed by means of (scalp) EEG activity phase synchroniza-
tion over multiple frequency bands (Doesburg et al., 2012;
Sauseng & Klimesch, 2008; Varela et al., 2001). In intracor-
tical ROIs, measures of phase synchronization are disturbed
by nonphysiological factors arising from volume conduc-
tion and general low spatial resolution (Bruder et al., 2012).
sLORETA software suite offers a handy toolbox applying a
refined technique (i.e., Hermitian covariance matrices) re-
Figure 1. Mean Audiogram of Participants with Standard
Deviations
moving these confounding factors best-possibly (Pascual-
Marqui, 2007b). The measure of dependence applied in the
sLORETA connectivity toolbox are basically able to calcu-
late all ROIs jointly based on activity in all ROIs estimated
with eLORETA (Pascual-Marqui, 2007a). In also not being
sensitive to propagation lag or energy loss of the signal, the
method is able to cover large-scale synchronous network ac-
tivation within respective frequency bands. Based on these
principles, lagged phase connectivity was calculated using
the connectivity toolbox in sLORETA.
3 Results
3.1 Audiometry
Mean hearing loss was 19.63 dB (SD=15.1) for the right
ear and 19.86 dB (SD=13.73) for the left ear respectively
(n=41). 11 out of the 41 participants with audiometry sur-
passed the clinical threshold for hearing loss of 20 dB re-
duced hearing capacity in at least one frequency and ear,
resulting in 11 participants with mild hearing loss. With
hearing loss levels within the range of 40 and 70 dB, an-
other 4 participants displayed moderate and one participant
severe hearing loss (80+ dB in most frequencies). Hearing
levels did not significantly differ between the ears (t=-0.154,
p<0.878). Figure 1 illustrates the hearing levels for both ears
in a standard audiogram.
3.2 Short Questionnaire
The conditions significantly differed in ratings of tinnitus
distress, loudness, annoyance, and ignorability (p<0.001, ex-
cept loudness: p<0.01, corrected for multiple comparisons
with bonferoni method) displaying higher scores in the AL
condition. Furthermore, Cohen’s d above 0.5 indicate mid-
size effect sizes and confirm the adequacy of the sample size
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 7
Table 2
Paired Differences T-Test and Cohen’s D of Short Question-
naires Scores
(again with the exception of loudness: d=0.442) (Cohen,
2013) (Table 2). The mean difference in loudness is less
pronounced in contrast to the mean differences of the other
assessed tinnitus aspects.
3.3 EEG Data
3.3.1 Power Analysis. The global average power
analysis for both conditions (i.e., averaged over all recording
electrodes) is plotted in Figure 2. Interestingly, there is no
significant difference between the conditions (p(min)=1.043,
bonferoni corrected, at 4 Hz), also not in the alpha band (peak
around 10 Hz).
Figure 2. Spectral Power Plot Averaged over All Electrodes
for Both Conditions
The topographical analysis of the frequency spectrum pro-
duced two single significant maxima of activation in two
frequency bands (p<0.05 with bonferoni correction, Figure
3). At 22 Hz (Panel A) the observed increase in activity
in AL is most prominent over slight left-lateralized fronto-
medial electrodes (pink dot indicating maximum, t=-4,183,
p=0.009). Further increased activity in this band (statistical
trends) was observed over left temporal and parietal scalp
positions. Panel B shows increased activity in the 41 Hz
frequency band over slight left-lateralized posterior central
regions (t=-4,009, p=0.015).
Figure 3. Topographical Maps of Significant Differences be-
tween Conditions
3.3.2 Source-localized Current Density Analysis.
First, the results of the power analysis (i.e., current density in
mA/mm3) comparison between the two study conditions are
reported. All reported results (i.e., t-values) in this section
and the next section (i.e., connectivity analysis) are corrected
for multiple comparisons applying Statistical non Parametric
Mapping (SnPM) producing "bullet-proof" results (Nichols
& Holmes, 2002; R. D. Pascual-Marqui, 2002).
In contrast to RS, the AL condition exhibits lower alpha 1
activity in left BA3 with the peak voxel in postcentral gyrus
(-55 -15 50) (Figure 4). The finding is significant (t=-1.40,
p<0.05) and the cluster extents to middle frontal gyrus (e.g.,
-45 0 55).
3.3.3 Source-localized Connectivity Analysis. First,
Increased alpha 2 (10-12 Hz) connectivity was found be-
tween left sgACC and left auditory cortices in AL (Figure
5). The projection (not implying any directionality) from the
sgACC to the transverse temporal gyrus (TTG, core primary
auditory cortex, -45 -30 10) was more pronounced (t=3.26,
p<0.1, p-extreme (pe)=0.065) compared to the connection to
the STG (-55 -25 5, t=3.11, p<0.1).
Figure 5. Increased Alpha 2 Connectivity between Left
sgACC and Left Auditory Core Cortices during AL
8 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY,, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
Figure 4. Decreased Alpha 2 Activity in Left Paracentral Figure 6. Increased Alpha 1 Connectivity between Bilateral
Regions during AL
sgACC and Right PCC during AL
Second, bilateral subgenual regions show increased con-
nectivity in the alpha 1 band with PCC (5 -45 25) dur-
ing AL (Figure 6). The ipsilateral connection is more
pronounced (t=5.11, p<0.01, pe=0.002), as also reflected
in a darker magenta tone, than the contralateral projection
(t=4.20, p<0.05).
4 Discussion
After 20 years of respective neuroscientific research, tin-
nitus remains a poorly understood phenomenon affecting 5-
10 percent of the population in Western civilization, 1-2 per-
cent gravely with intricate comorbidities, related distress,
and no cure in sight (Langguth et al., 2013). Yet, with grow-
ing evidence derived from various studies, separable cortical,
thalamo-cortical, and cortico-limbic (sub-)networks at inter-
play contributing to the heterogeneous symptom and related
suffering arise (De Ridder et al., 2013; Vanneste & De Rid-
der, 2012b).
In this study, the focus was set on the constant tinnitus per-
cept in comparing different perceptual modes in resting state
EEG, namely actively listen (AL), and ’normal’ resting state
(RS) being the ’inattentive’ mode. EEG power and connec-
tivity analyses were performed to discover possible under-
pinnings of functional networks contributing to the tinnitus
sensation.
Differential neurophysiological signatures, in combina-
tion with supporting psychometric differences, came as no
surprise in both perceptual modes and implications for the
widely adapted EEG resting state paradigm in tinnitus re-
search can be derived from the data at hand.
4.1 Psychometry
Alongside the considerations of the last section, re-
sults from various tinnitus-related as well as general health
and well-being questionnaires were also comparable to for-
mer studies, as most importantly TQ scores (Mean=38,
SD=13.14) are in the same range as in various other studies
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 9
with tinnitus patients ((40.93)(Joos et al., 2012), (40.2)(van
der Loo, E. et al., 2011), and (42)(Schecklmann et al., 2013))
contributing to a solid markedness of the tinnitus symp-
tom in the sample. This is particularly evident, as partici-
pants scored, relatively to the TQ and its subscales, equally
high in the SQ questions, assessing core distress (Mean=2.4,
SD=0.86, range=1-5), annoyance (Mean=4.51, SD=2.52,
range=1-10), ignorability (Mean=5.8, SD=3.27, range=1-
10), and finally tinnitus loudness (Mean=5.96, SD=2.38,
range=1-10) after the RS condition. Herewith the basis for a
successful psychometric backdrop is set enhancing the plau-
sibility of measured differences in EEG ’resting state’ be-
tween conditions (Table 2), as all 4 tinnitus-related dimen-
sions of the SQ elicited higher scores after AL (Al>RS:
distress (t=4.582, p<0.001), loudness (t=2.937, p<0.05),
annoyance (t=4.474, p<0.001), and ignorability (t=5.199,
p<0.0001)).
On the other hand, it was not possible to further ana-
lyze different profiles of differences in SQ with the obtained
results contributing to a marked dichotomy between tinni-
tus distress (measured by distress and annoyance) and tin-
nitus presence (measured by loudness and partly by ignora-
biltity) (Meyer et al., 2014). Respective analyses of variance
(ANOVA) contrasting extreme groups of differences in SQ
did not yield any significant results in both sensor-based and
source-localized activity and connectivity (data not shown).
4.2 EEG
4.2.1 Power Analyses. As hypothesized before, the
two conditions used in the EEG paradigm could possibly be
regarded as a between-subjects design (i.e., patients vs. con-
trols) adapted to a within-subject design (i.e., the two condi-
tions corresponding to normal resting ("controls") and active
engaging in listening to tinnitus ("patients")). Therefore, a
comparison to (older) studies applying a between-subject de-
sign (Adjamian et al., 2012; Ashton et al., 2007; Moazami-
Goudarzi et al., 2010; Weisz et al., 2007) is of particular in-
terest.
The delta band activities are in all mentioned studies in-
creased in tinnitus patients. This finding is not replicated
following the introduced logic as in AL there was a decrease
(statistical trend) in delta both in average whole-scalp power
(Figure 2) as well as in focal left temporal 4 Hz band on the
scalp topography (data not shown). A further explanation
could be a ’tinnitus independent’ alteration in lower band
powers possibly accounting for the attentional shift in per-
ceptual engaging (Jensen & Mazaheri, 2010; Klimesch et al.,
2007; Mathewson et al., 2014), as alterations in the puta-
tively involved alpha band could influence concurrent lower
frequency activities.
Surprisingly there was no significant alteration in al-
pha band activity observed on the sensor level but source-
localized decreased alpha 1 activity (8-10 Hz, peak MNI: -
55 -15 50) could be observed in left lateral paracentral re-
gions including part of the middle frontal gyrus. This could
possibly reflect findings in previous group comparison stud-
ies of temporal decreases in alpha power of tinnitus patients
(Moazami-Goudarzi et al., 2010; Schlee et al., 2014; Weisz
et al., 2007) or intracortical reduction of alpha power induced
by residual inhibition at similar sites (W. Sedley et al., 2015).
Neither convincingly congruent with tinnitus literature as
well as with basics of (event-related) alpha (de-) synchro-
nization (Jensen & Mazaheri, 2010; Klimesch et al., 2007;
Mathewson et al., 2014; Pfurtscheller & da Silva, 1999) these
results are puzzling. Nevertheless it can be clearly stated that
the absence of any significant difference in alpha power on
the sensor level between the conditions (Figure 2 and 3) fur-
ther reinforces the widely observed global and temporal al-
pha reduction in tinnitus patients compared to healthy con-
trols as there is no observable difference in alpha activity be-
tween AL and RS.
A further overlap with previous work is conceivable as
the beta band most prominently represented by the 22 Hz
frequency (Panel A Figure 3) shows a similar spatial dis-
tribution as in Moazami-Goudarzi et al. (2010) where in-
creases in beta band power (18-25 Hz) agglomerate over
mid-frontal regions with a peak in (slightly left-lateralized)
central frontal regions. Again, it is difficult to disentangle
auditory-perceptual aspects of tinnitus presence from tinni-
tus distress related activity changes. Yet, looking at our pre-
vious study (Meyer et al., 2014) it could be assumed that
this enhanced beta activity is related to the higher distress
in the AL conditions (previous study beta range: 20-25 Hz).
Location-wise it could be speculated that the increased beta
activity is possibly originating from ventromedial/cingulate
(e.g., (Vanneste et al., 2014)) or insular/auditory regions
(e.g., (Moazami-Goudarzi et al., 2010)). Unfortunately,
the source-localization using sLORETA at the 22 Hz fre-
quency did not yield significant results. A clear increase
in gamma activity in AL around 41 Hz was also observed
in previous studies but rather in overall gamma frequency
band power (approximately between 40 and 80 Hz) (Ashton
et al., 2007; Moazami-Goudarzi et al., 2010; Weisz et al.,
2007). Location-wise the congruence is not that clear as lat-
eral patches (see Panel B, Figure 3) in the data at hand are
only weakly pronounced and the hot spot is located (slightly
left-lateralized) over parieto-occipital electrodes. Again, re-
spective source-localization of the 41 Hz gamma increase on
the sensor level was not possible. Nevertheless, it is assumed,
that the local maximum over posterior electrodes is possibly
indicative of enhanced gamma band activity in posterior cin-
gulate and parietal (including precuneus) regions.
In conclusion, we tentatively attribute the enhanced high
frequency band activity to the larger presence and distress
indicated by the SQ: Increased frontal beta activity is pos-
sibly related to increased distress whereas increased poste-
10 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
rior gamma activity is possibly related to increased pres-
ence as especially posterior cingulate regions are theorized in
tinnitus-specific memory-related (probably memory updat-
ing and forming) processes (Vanneste & De Ridder, 2012b).
Generally, the increased high frequency activity here could
partly explain the heterogeneous findings in former studies.
4.2.2 Source-localized Connectivity Analysis. First,
a major finding is the increased connectivity of the upper al-
pha band (alpha 2) between left sgACC and left (primary) au-
ditory cortices, which speaks heavily in favor of a proposed
"noise-cancellation" system (De Ridder et al., 2013; Leaver
et al., 2011, 2012; Rauschecker et al., 2010) linking the pu-
tative "noise-gate" in and around sgACC with the prime site
of auditory perception or activity (i.e., primary auditory cor-
tices). If this finding in this study holds true, it can be rea-
soned that the increased alpha connectivity may be indica-
tive of an ongoing attempt of noise-, or ’tinnitus’-canceling.
As alpha activity is also widely brought into connection with
inhibitory processes in auditory perception (e.g., (Jensen &
Mazaheri, 2010; Klimesch et al., 2007)), this general ob-
servations may further corroborate the "noise-cancellation"
hypothesis. On the other hand, contrasting the above in-
hibitory function of this connectivity, the increase could also
just merely reflect a heightened percept of tinnitus increasing
its auditory ’presence’. Beyond that, a pronounced prefer-
ence of the left hemisphere is observable in this putative core
tinnitus network, which is a distinct pattern emerging of the
data at hand and previous work both in tinnitus as well as in
general auditory phenomena (e.g., (Geven, Kleine, Willem-
sen, & van Dijk, 2014)).
Secondly, a similar pattern is discernible in the increased
connectivity between bilateral sub- and pregenual areas with
posterior (cingulate cortical) regions. The latter regions are
brought into connection with tinnitus distress and memory
in alpha 2 band (Vanneste, Plazier, der Loo, Elsa van, et
al., 2010), possibly related to the results at hand, but more
prominently with "tonal" features of the percept in higher
frequency bands (i.e., beta and gamma bands) (Vanneste,
Plazier, van der Loo, Elsa, Van de Heyning, Paul, & De Rid-
der, 2010). The results of this subanalysis are therefore inter-
preted in a similar way as in the last section, linking increased
connectivity to "noise-gate" and "perceptual" (here: "tonal")
networks.
Finally, though tendentiously spun in contrast to other
connectivity subanalyses and in the case of the alpha 2 band
possibly elusive (see limitations section and Schlee et al.
(2014)), the general increased connectivities between frontal
and posterior regions in the case of the alpha 2 band still are
in range of any proposed tinnitus network frameworks espe-
cially the seminal data of Schlee, Hartmann, et al. (2009).
4.3 Limitations
Sample size is always an issue as the amount of partici-
pants in the study at hand is certainly above general averages
in basic research psychological studies but tendentially be-
low the average of EEG resting state studies in the context of
tinnitus (e.g., (Vanneste, M. Congedo, & De Ridder, 2013)).
For future studies or the continuation of the project - espe-
cially aiming at more distinct tinnitus subgrouping - larger
case numbers and/or more specific sampling strategies are
deemed extremely useful. Nevertheless, sample size is obvi-
ously superior to the previous study (Meyer et al., 2014) as
the results are more robust, clear-cut and imbued with more
statistical power (i.e., correctable for multiple comparisons
in whole-brain/-head voxel-/electrode-wise analyses).
Methods like cluster analysis in (Schecklmann et al.,
2012) or (group) blind source separation analysis (BSS)
(Marco Congedo, John, De Ridder, Prichep, & Isen-
hart, 2010; De Ridder, Vanneste, Marco Congedo, &
Koenig, 2011) are of special interest as they possibly reveal
new insights into cortical mechanisms of tinnitus applying
assumption- and hypothesis-free data-driven algorithms.
As worked out in previous work by Weisz et al. (2007) at-
tributing it specifically to a ’pathological’ tinnitus activation
pattern, slow waves and related periods of high frequency ac-
tivities were observed during preprocessing of EEG data but
interpreted as ’normal’ activation below the threshold of pos-
sible drowsiness effects. In future re-analysis of the data or
new studies, special attention should be directed to this phe-
nomenon as it may be highly indicative of thalamo-cortical
networks (De Ridder, van der Loo, Elsa, et al., 2011; R. R.
Llinás et al., 1999; R. Llinás, Urbano, Leznik, Ramírez, &
van Marle, Hein J.F., 2005).
Temporal integrity of tinnitus-related or general resting
state EEG signals is a considerable issue as averaged excerpts
(i.e. segments) over the whole time course of the recording
are usually the basis for respective statistical analysis. Future
analyses of the data should take this limitation into consid-
eration. It may though not be that confounding within tin-
nitus sufferers as, for example, alpha activity seems to elicit
less variability than in controls (Schlee et al., 2014). Never-
theless, another finding in the same study identifies tinnitus
duration as a possible cause of this decrease in variation.
Network-related interregional coupling is only looked at
in single, identical frequency bands (e.g., in alpha 2 connec-
tivity) whereas previous literature in other research fields is
highly indicative of cross-frequency coupling in large-scale
assemblies (Doesburg et al., 2012; Varela et al., 2001), also
in tinnitus (e.g., (De Ridder, van der Loo, Elsa, et al., 2011)).
In the actual version of the sLORETA software suite, this
feature is still missing.
Related to that, extending insights of long-known EEG
coherence connectivity measures, is the graph-theory driven
network analysis, which has not been conducted in the con-
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 11
text of tinnitus using (source-localized) EEG nodes. It is ex-
pected, that this would further validate and possibly extend
the insights derived from previous (i.e., coherence-based)
connectivity results (Langer, von Bastian, Claudia C., Wirz,
Oberauer, & Jäncke, 2013; Stam, 2004) or possibly in com-
bination with fMRI (Mantini, Perrucci, M. G., Del Gratta,
Romani, G. L., & Corbetta, 2007).
The distribution of tinnitus characteristics in the sample
at hand are typical for the respective population and com-
parable to other studies. Nevertheless, in the spirit of further
subgrouping tinnitus types as propagated by the European re-
search initiative TINNET (http://tinnet.tinnitusresearch.net/)
distinct contrasts of these characteristics should also be
probed within the paradigm at hand. Most critically, tinnitus
lateralization may limit the extent of the interpretation as the
task in this study is auditive in nature. Yet, tinnitus-related
as wells as general auditory phenomena with their respective
activity tend to be left-lateralized (Geven et al., 2014), which
is in line with our data.
A last point is aimed towards a ’realistic’ transfer of basic
research insights to therapeutic settings of neuromodulatory
applications as individual EEG profiles of tinnitus make it
difficult to derive concrete neuromodulatory treatment proto-
cols. This concern can be further extended to more general
incongruencies within band-power EEG research related to
the tinnitus percept or suffering. Applying this reasoning,
a putative re-interpretation of the gamma frequency from a
perceptive correlate of tinnitus to a possible inhibitory mech-
anism should be taken seriously (Sedley & Cunningham,
2013; Sedley et al., 2012).
4.4 Conclusion
The study at hand produces novel insights into tinnitus
perception mechanisms as it could be clearly shown that en-
gaging in listening to tinnitus activates a functional network
between subgenual and auditory areas (including auditory
memory) possibly indicative of the malicious tinnitus per-
cept or an active attempt of its inhibition. Additionally, fo-
cal maxima of increased high frequency activity (beta and
gamma) could be observed on the sensor level as well as a
left-lateralized decrease of alpha power in source space. In-
sights gained from these results could be of use in reinter-
preting previous studies applying the established EEG/MEG
resting state approach as differential alterations of activity
and connectivity in well-known tinnitus could be confounded
by the perceptual mode/attentional state towards tinnitus in
the recording settings. Furthermore, these insights could sen-
sitize future EEG resting state studies in tinnitus. Ideally, the
paradigm at hand should be used or at least controlled for
(e.g., by distractors (Andersson et al., 2006)) in these studies.
4.5 Future Directions
Further classifications of distinct tinnitus patients sub-
groups are mandatory to understand and treat the tangled web
of different tinnitus manifestations or comorbidities. Consid-
erable effort has already been taken to that effect (De Rid-
der, Vanneste, Marco Congedo, & Koenig, 2011; Wolfgang
Hiller & Gerhard Goebel, 2007; Landgrebe et al., 2010;
Schecklmann et al., 2012; Schlee, Kleinjung, et al., 2011;
Vanneste et al., 2012).
Method-wise, multimodal integration combining differ-
ent available neuroanatomic and -physiological as well as
neuromodulatory approaches seems very promising (e.g.,
(Bruder et al., 2012; Halchenko, Hanson, & Pearlmutter,
2005)). Networks, either broadly conceived or narrowly
studied through graph theory, establish themselves as the new
research method paradigm (shift).
Longitudinal data is completely missing but would, in-
terleaved with the above methodological advances, certainly
shatter decisive light on neuroplastic changes related to tinni-
tus after its onset or more generally over the whole life span.
More classical, in contrast, are calls for larger sam-
ples and standardized operation procedures of psycho-
metric, clinical, and especially neurophysiological assess-
ments. Applying these recommendations in constructing
large international databases with afore-mentioned assessed
data, this strategy is already deployed in initiatives like
TRI (Landgrebe et al., 2010) and its spring-off TINNET
(http://tinnet.tinnitusresearch.net/).
As a switch or wonderous cure for tinnitus is still missing,
the propositions in this section and the data of the study at
hand, may contribute to better treatment or symptom alle-
viation in the spirit of translational science. The approach
of EEG resting state diagnostic assessment in combination
with psychometric and clinical efforts, could ease the devel-
opment of individual NFB protocols applying neuro-guided
multi-frequency and -localization (network) trainings.
Interpreting the overall impression of the data in this study
as well as a general trend in the (neuro-)scientific community,
functional networks mark a promising future, not only in re-
search, but most certainly also in neuromodulatory therapy.
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18 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
5 Appendix
List of Figures
1 Mean Audiogram of Participants with Stan-
dard Deviations . . . . . . . . . . . . . . . . 6
2 Spectral Power Plot Averaged over All Elec-
trodes for Both Conditions . . . . . . . . . . 7
3 Topographical Maps of Significant Differ-
ences between Conditions . . . . . . . . . . . 7
4 Decreased Alpha 2 Activity in Left Paracen-
tral Regions during AL . . . . . . . . . . . . 8
5 Increased Alpha 2 Connectivity between
Left sgACC and Left Auditory Core Cortices
during AL . . . . . . . . . . . . . . . . . . . 8
6 Increased Alpha 1 Connectivity between Bi-
lateral sgACC and Right PCC during AL . . . 8
ACTIVE LISTENING TO TINNITUS IS RELATED TO ENHANCED EEG HIGH FREQUENCY ACTIVITY AND ALPHA CONNECTIVITY 19
List of Tables
1 Participant Characteristics . . . . . . . . . . 3
2 Paired Differences T-Test and Cohen’s D of
Short Questionnaires Scores . . . . . . . . . 7
3 13 Bilateral ROIs of sLORETA Connectivity
Analysis . . . . . . . . . . . . . . . . . . . . 20
20 PATRICK NEFF, FABIAN KRAXNER, COLETTE HEMSLEY, STEFFI WEIDT, MARTIN MEYER, TOBIAS KLEINJUNG
5.1 Supplemental Tables
Table 3
13 Bilateral ROIs of sLORETA Connectivity Analysis
28
3. Lebenslauf
Name Kraxner
Vorname Fabian Herbert
Geschlecht männlich
Geburtsdatum 10.02.1992
Bürgerort Lengnau AG
Staatsangehörigkeit Schweiz und Österreich
Ausbildung 08/1998 – 07/2004 Primarschule Basadingen
08/2004 – 07/2006 Sekundarschule Diessenhofen
08/2006 – 07/2010 Kantonsschule Schaffhausen
07/2010 – heute Universität Zürich, Humanmedizin
29
4. Ethikhinweis
Hiermit bestätige ich, dass die obige klinische Studie der kantonalen Ethikkommission des Kantons Zürich zur Bewilligung vorgelegt wurde und die Überprüfung positiv ausfiel. Die entsprechende Ethik-Nummer lautet ZH-2012-0324.
Fabian Kraxner
30
5. Erklärung
Masterarbeit
Ich erkläre ausdrücklich, dass es sich bei der von mir im Rahmen des Studiengangs Master Humanmedizin UZH eingereichten schriftlichen Arbeit mit dem Titel „Active listening to tinnitus is related to enhanced electroencephalography high frequency activity and alpha connectivity“ um eine von mir selbst und ohne unerlaubte Beihilfe sowie in eigenen Worten verfasste Masterarbeit* handelt.
Ich bestätige überdies, dass die Arbeit als Ganzes oder in Teilen weder bereits einmal zur Abgeltung anderer Studienleistungen an der Universität Zürich oder an einer anderen Universität oder Ausbildungseinrichtung eingereicht worden ist.
Verwendung von Quellen
Ich erkläre ausdrücklich, dass ich sämtliche in der oben genannten Arbeit enthaltenen Bezüge auf fremde Quellen (einschliesslich Tabellen, Grafiken u. Ä.) als solche kenntlich gemacht habe. Insbesondere bestätige ich, dass ich ausnahmslos und nach bestem Wissen sowohl bei wörtlich übernommenen Aussagen (Zitaten) als auch bei in eigenen Worten wiedergegebenen Aussagen anderer Autorinnen oder Autoren (Paraphrasen) die Urheberschaft angegeben habe.
Sanktionen
Ich nehme zur Kenntnis, dass Arbeiten, welche die Grundsätze der Selbstständigkeitserklärung verletzen – insbesondere solche, die Zitate oder Paraphrasen ohne Herkunftsangaben enthalten –, als Plagiat betrachtet werden und die entsprechenden rechtlichen und disziplinarischen Konsequenzen nach sich ziehen können (gemäss §§ 7ff der Disziplinarordnung der Universität Zürich sowie §§ 51ff der Rahmenverordnung für das Studium in den Bachelor- und Master-Studiengängen an der Medizinischen Fakultät der Universität Zürich)
Ich bestätige mit meiner Unterschrift die Richtigkeit dieser Angaben.
Datum: 10. Februar 2016
Name: Kraxner Vorname: Fabian
Unterschrift:………………………………………..
* Falls die Masterarbeit eine Publikation enthält, bei der ich Erst- oder Koautor/-in bin, wird meine eigene Arbeitsleistung im Begleittext detailliert und strukturiert beschrieben.