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Sven Haller

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12 papers

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YNICL Journal 2026 Journal Article

Altered parietal multisensory integration in chronic tinnitus during closed-loop real-time fMRI auditory downregulation

Nicolas Gninenko
Pascal Senn
Sven Haller
Dimitri Van De Ville

Chronic subjective tinnitus is the most common form of tinnitus and refers to an internal persistent phantom auditory perception. Evidence from neuroimaging studies has established tinnitus and its associated distress as a brain network disorder, with multiple brain regions displaying dysregulated activity or connectivity extending way beyond the auditory pathway. Hyperactivity in the auditory cortex has been associated with perceived tinnitus loudness, and somatosensory-auditory interactions have recently been involved in promising treatment avenues through their disruption using non-invasive or bimodal neuromodulation techniques, albeit with low mechanistic evidence. In this study, we evaluated the neural effects of prolonged downregulation of bilateral auditory cortex activity mediated by real-time fMRI neurofeedback in individuals with moderate to severe (Tinnitus Handicap Inventory [THI] scores ≥ 48) chronic tinnitus. Twenty-one participants (aged 49 ± 11.4 years old, 16 males, 5 females) completed 15 fMRI neurofeedback sessions over 3-4 months each, as part of a randomized clinical trial (ClinicalTrials.gov: NCT05737888) comparing neurofeedback interventions over the current standard of care, cognitive behavioral therapy (CBT). We performed whole-brain general linear modeling analyses to delineate regulated brain areas, accounting for age, gender, and THI scores at baseline. Task-modulated functional connectivity analyses were carried out using psychophysiological interactions to unveil associated connectivity patterns emerging during cognitively demanding tinnitus defocalization. Most participants succeeded at reducing the average activity of their auditory cortex throughout the training. Whole brain analyses additionally revealed a strong downregulation of parietal operculum 3 (OP3), a region previously reported to be activated in the right hemisphere during experimentally induced transient phantom percepts. In accordance with the hypothesis that OP3 may mediate the integration of multisensory inputs in tinnitus, we have shown that both left and right auditory cortices decrease their connectivity with OP3 during closed-loop auditory downregulation. Moreover, we observed a reduced connectivity of bilateral OP3 with a functional multisensory integration network that was previously found to be engaged by the primary and secondary auditory cortices during audio-tactile integration. These findings support the hypothesis of OP3 having a key role in multisensory integration stemming from altered somatosensory-auditory crosstalk in chronic tinnitus. Targeted neuromodulation to desynchronize the connectivity between OP3 and the auditory cortex could further inform our understanding of the mechanisms behind recent successful bimodal interventions for reducing tinnitus.

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YNICL Journal 2022 Journal Article

The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow

Luigi Lorenzini
Silvia Ingala
Alle Meije Wink
Joost P.A. Kuijer
Viktor Wottschel
Mathijs Dijsselhof
Carole H. Sudre
Sven Haller

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.

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YNIMG Journal 2021 Journal Article

Predictors of real-time fMRI neurofeedback performance and improvement – A machine learning mega-analysis

Amelie Haugg
Fabian M. Renz
Andrew A. Nicholson
Cindy Lor
Sebastian J. Götzendorfer
Ronald Sladky
Stavros Skouras
Amalia McDonald

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

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YNICL Journal 2021 Journal Article

Tau aggregation and increased neuroinflammation in athletes after sports-related concussions and in traumatic brain injury patients – A PET/MR study

Niklas Marklund
Fredrik Vedung
Mark Lubberink
Yelverton Tegner
Jakob Johansson
Kaj Blennow
Henrik Zetterberg
Markus Fahlström

Traumatic brain injury (TBI) and repeated sports-related concussions (rSRCs) are associated with an increased risk for neurodegeneration. Autopsy findings of selected cohorts of long-term TBI survivors and rSRC athletes reveal increased tau aggregation and a persistent neuroinflammation. To assess in vivo tau aggregation and neuroinflammation in young adult TBI and rSRC cohorts, we evaluated 9 healthy controls (mean age 26 ± 5 years; 4 males, 5 females), 12 symptomatic athletes (26 ± 7 years; 6 males, 6 females) attaining ≥3 previous SRCs, and 6 moderate-to severe TBI patients (27 ± 7 years; 4 males, 2 females) in a combined positron emission tomography (PET)/magnetic resonance (MR) scanner ≥6 months post-injury. Dual PET tracers, [18F]THK5317 for tau aggregation and [11C]PK11195 for neuroinflammation/microglial activation, were investigated on the same day. The Repeated Battery Assessment of Neurological Status (RBANS) scores, used for cognitive evaluation, were lower in both the rSRC and TBI groups (p < 0. 05). Neurofilament-light (NF-L) levels were increased in plasma and cerebrospinal fluid (CSF; p < 0. 05), and serum tau levels lower, in TBI although not in rSRC. In rSRC athletes, PET imaging showed increased neuroinflammation in the hippocampus and tau aggregation in the corpus callosum. In TBI patients, tau aggregation was observed in thalami, temporal white matter and midbrain; widespread neuroinflammation was found e. g. in temporal white matter, hippocampus and corpus callosum. In mixed-sex cohorts of young adult athletes with persistent post-concussion symptoms and in TBI patients, increased tau aggregation and neuroinflammation are observed at ≥6 months post-injury using PET. Studies with extended clinical follow-up, biomarker examinations and renewed PET imaging are needed to evaluate whether these findings progress to a neurodegenerative disorder or if spontaneous resolution is possible.

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YNIMG Journal 2020 Journal Article

Higher availability of α4β2 nicotinic receptors (nAChRs) in dorsal ACC is linked to more efficient interference control

Swann Pichon
Valentina Garibotto
Michael Wissmeyer
Yann Seimbille
Lia Antico
Osman Ratib
Patrik Vuilleumier
Sven Haller

Nicotinic acetylcholine receptors (nAChRs) are widely distributed in the human brain and play an important role in the neuromodulation of brain networks implicated in attentional processes. Previous work in humans showed that heteromeric α4β2 nAChRs are abundant in the cingulo-insular network underlying attentional control. It has been proposed that cholinergic neuromodulation by α4β2 nAChRs is involved in attentional control during demanding tasks, when additional resources are needed to minimize interference from task-irrelevant stimuli and focus on task-relevant stimuli. Here we investigate the link between the availability of α4β2 nAChRs in the cingulo-insular network and behavioral measures of interference control using two versions of the Stroop paradigm, a task known to recruit cingulo-insular areas. We used a previously published PET dataset acquired in 24 non-smoking male subjects in the context of a larger study which investigated the brain distribution of nAChRs in two clinical groups using 2-[(18)F]F-A-85380 PET. We found that higher availability of α4β2 nAChRs in the dorsal anterior cingulate cortex (ACC) predicted better interference control independently of group and age. In line with animal models, our results support the view that the availability of α4β2 nAChRs in the dorsal ACC is linked with more efficient attentional control.

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YNICL Journal 2019 Journal Article

A study of neural activity and functional connectivity within the olfactory brain network in Parkinson's disease

Charalampos Georgiopoulos
Suzanne T. Witt
Sven Haller
Nil Dizdar
Helene Zachrisson
Maria Engström
Elna-Marie Larsson

Olfactory dysfunction is an early manifestation of Parkinson's disease (PD). The present study aimed to illustrate potential differences between PD patients and healthy controls in terms of neural activity and functional connectivity within the olfactory brain network. Twenty PD patients and twenty healthy controls were examined with olfactory fMRI and resting-state fMRI. Data analysis of olfactory fMRI included data-driven tensorial independent component (ICA) and task-driven general linear model (GLM) analyses. Data analysis of resting-state fMRI included probabilistic ICA based on temporal concatenation and functional connectivity analysis within the olfactory network. ICA of olfactory fMRI identified an olfactory network consisting of the posterior piriform cortex, insula, right orbitofrontal cortex and thalamus. Recruitment of this network was less significant for PD patients. GLM analysis revealed significantly lower activity in the insula bilaterally and the right orbitofrontal cortex in PD compared to healthy controls but no significant differences in the olfactory cortex itself. Analysis of resting-state fMRI did not reveal any differences in the functional connectivity within the olfactory, default mode, salience or central executive networks between the two groups. In conclusion, olfactory dysfunction in PD is associated with less significant recruitment of the olfactory brain network. ICA could demonstrate differences in both the olfactory cortex and its main projections, compared to GLM that revealed differences only on the latter. Resting-state fMRI did not reveal any significant differences in functional connectivity within the olfactory, default mode, salience and central executive networks in this cohort.

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YNICL Journal 2017 Journal Article

Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI - A pilot study

Kirsten Emmert
Rotem Kopel
Yury Koush
Raphael Maire
Pascal Senn
Dimitri Van De Ville
Sven Haller

The emerging technique of real-time fMRI neurofeedback trains individuals to regulate their own brain activity via feedback from an fMRI measure of neural activity. Optimum feedback presentation has yet to be determined, particularly when working with clinical populations. To this end, we compared continuous against intermittent feedback in subjects with tinnitus. Fourteen participants with tinnitus completed the whole experiment consisting of nine runs (3 runs × 3 days). Prior to the neurofeedback, the target region was localized within the auditory cortex using auditory stimulation (1 kHz tone pulsating at 6 Hz) in an ON-OFF block design. During neurofeedback runs, participants received either continuous (n = 7, age 46.84 ± 12.01, Tinnitus Functional Index (TFI) 49.43 ± 15.70) or intermittent feedback (only after the regulation block) (n = 7, age 47.42 ± 12.39, TFI 49.82 ± 20.28). Participants were asked to decrease auditory cortex activity that was presented to them by a moving bar. In the first and the last session, participants also underwent arterial spin labeling (ASL) and resting-state fMRI imaging. We assessed tinnitus severity using the TFI questionnaire before all sessions, directly after all sessions and six weeks after all sessions. We then compared neuroimaging results from neurofeedback using a general linear model (GLM) and region-of-interest analysis as well as behavior measures employing a repeated-measures ANOVA. In addition, we looked at the seed-based connectivity of the auditory cortex using resting-state data and the cerebral blood flow using ASL data. GLM group analysis revealed that a considerable part of the target region within the auditory cortex was significantly deactivated during neurofeedback. When comparing continuous and intermittent feedback groups, the continuous group showed a stronger deactivation of parts of the target region, specifically the secondary auditory cortex. This result was confirmed in the region-of-interest analysis that showed a significant down-regulation effect for the continuous but not the intermittent group. Additionally, continuous feedback led to a slightly stronger effect over time while intermittent feedback showed best results in the first session. Behaviorally, there was no significant effect on the total TFI score, though on a descriptive level TFI scores tended to decrease after all sessions and in the six weeks follow up in the continuous group. Seed-based connectivity with a fixed-effects analysis revealed that functional connectivity increased over sessions in the posterior cingulate cortex, premotor area and part of the insula when looking at all patients while cerebral blood flow did not change significantly over time. Overall, these results show that continuous feedback is suitable for long-term neurofeedback experiments while intermittent feedback presentation promises good results for single session experiments when using the auditory cortex as a target region. In particular, the down-regulation effect is more pronounced in the secondary auditory cortex, which might be more susceptible to voluntary modulation in comparison to a primary sensory region.

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YNICL Journal 2016 Journal Article

Discriminating among degenerative parkinsonisms using advanced 123I-ioflupane SPECT analyses

Simon Badoud
Dimitri Van De Ville
Nicolas Nicastro
Valentina Garibotto
Pierre R. Burkhard
Sven Haller

123I-ioflupane single photon emission computed tomography (SPECT) is a sensitive and well established imaging tool in Parkinson's disease (PD) and atypical parkinsonian syndromes (APS), yet a discrimination between PD and APS has been considered inconsistent at least based on visual inspection or simple region of interest analyses. We here reappraise this issue by applying advanced image analysis techniques to separate PD from the various APS. This study included 392 consecutive patients with degenerative parkinsonism undergoing 123I-ioflupane SPECT at our institution over the last decade: 306 PD, 24 multiple system atrophy (MSA), 32 progressive supranuclear palsy (PSP) and 30 corticobasal degeneration (CBD) patients. Data analysis included voxel-wise univariate statistical parametric mapping and multivariate pattern recognition using linear discriminant classifiers. MSA and PSP showed less ioflupane uptake in the head of caudate nucleus relative to PD and CBD, yet there was no difference between MSA and PSP. CBD had higher uptake in both putamen relative to PD, MSA and PSP. Classification was significant for PD versus APS (AUC 0. 69, p<0. 05) and between APS subtypes (MSA vs CBD AUC 0. 80, p<0. 05; MSA vs PSP AUC 0. 69 p<0. 05; CBD vs PSP AUC 0. 69 p<0. 05). Both striatal and extra-striatal regions contain classification information, yet the combination of both regions does not significantly improve classification accuracy. PD, MSA, PSP and CBD have distinct patterns of dopaminergic depletion on 123I-ioflupane SPECT. The high specificity of 84–90% for PD versus APS indicates that the classifier is particularly useful for confirming APS cases.

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YNIMG Journal 2016 Journal Article

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

Kirsten Emmert
Rotem Kopel
James Sulzer
Annette B. Brühl
Brian D. Berman
David E.J. Linden
Silvina G. Horovitz
Markus Breimhorst

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i. e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

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YNICL Journal 2016 Journal Article

Prediction of long-term memory scores in MCI based on resting-state fMRI

Djalel-Eddine Meskaldji
Maria Giulia Preti
Thomas AW Bolton
Marie-Louise Montandon
Cristelle Rodriguez
Stephan Morgenthaler
Panteleimon Giannakopoulos
Sven Haller

Resting-state functional MRI (rs-fMRI) opens a window on large-scale organization of brain function. However, establishing relationships between resting-state brain activity and cognitive or clinical scores is still a difficult task, in particular in terms of prediction as would be meaningful for clinical applications such as early diagnosis of Alzheimer's disease. In this work, we employed partial least square regression under cross-validation scheme to predict episodic memory performance from functional connectivity (FC) patterns in a set of fifty-five MCI subjects for whom rs-fMRI acquisition and neuropsychological evaluation was carried out. We show that a newly introduced FC measure capturing the moments of anti-correlation between brain areas, discordance, contains key information to predict long-term memory scores in MCI patients, and performs better than standard measures of correlation to do so. Our results highlighted that stronger discordance within default mode network (DMN) areas, as well as across DMN, attentional and limbic networks, favor episodic memory performance in MCI.

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YNIMG Journal 2013 Journal Article

Dynamic reconfiguration of human brain functional networks through neurofeedback

Sven Haller
Rotem Kopel
Permi Jhooti
Tanja Haas
Frank Scharnowski
Karl-Olof Lovblad
Klaus Scheffler
Dimitri Van De Ville

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e. g. , learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity.

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YNIMG Journal 2012 Journal Article

Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks

Dimitri Van De Ville
Permi Jhooti
Tanja Haas
Rotem Kopel
Karl-Olof Lovblad
Klaus Scheffler
Sven Haller

The default mode (DM) network is a major large-scale cerebral network that can be identified with functional magnetic resonance imaging (fMRI) during resting state. Most studies consider functional connectivity networks as stationary phenomena. Consequently, the transient behavior of the DM network and its subnetworks is still largely unexplored. Most functional connectivity fMRI studies assess the steady state of resting without any task. To specifically investigate the recovery of the DM network during the transition from activation to rest, we implemented a cognitively demanding real-time fMRI neurofeedback task that targeted down-regulation of the primary auditory cortex. Each of twelve healthy subjects performed 16 block-design fMRI runs (4 runs per day repeated on 4days) resulting 192 runs in total. The analysis included data-driven independent component analysis (ICA) and high-resolution latency estimation between the four components that corresponded to subnetworks of the DM network. These different subnetworks reemerged after regulation with an average time lag or 3. 3s and a time lag of 4. 4s between the first and fourth components; i. e. , the DM recovery first shifts from anterior to posterior, and then gradually focuses on the ventral part of the posterior cingulate cortex, which is known to be implicated in internally directed cognition. In addition, we found less reactivation in the early anterior subnetwork as regulation strength increased, but more reactivation with larger regulation for the late subnetwork that encompassed the ventral PCC. This finding confirms that the level of task engagement influences inversely the subsequent recovery of regions related to attention compared to those related to internally directed cognition.

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