Research Topics

A few examples of research conducted in the BBL are described below. For more details please visit the website of each research group or check on PubMed!


Vision and face recognition

The recognition of faces and perception of facial information such as expression or gaze direction is among the most sophisticated visual skills of humans and plays a major role in social interactions. Face perception is mediated by a widely distributed brain network of regions in the visual occipital cortex, but also in the temporal and frontal lobe. We investigate the specific function of each of these regions using functional MRI (red) and evoked potentials (EEG), as well as the architecture of the white-matter fibers that connect these different regions together using diffusion tensor MRI with tractography (blue). Our work is the first to combine fMRI with DTI methodology to delineate both functional and structural organization of the human face recognition system, and contributes to better understand the cerebral bases of face recognition impairments (e.g. prosopagnosia) that are caused by focal lesions (stroke) or developmental disorders (autism). - Vuilleumier, Gschwind, Sander, Van de Ville.

Face network

Hypnosis and consciousness

Hypnosis provides a unique window on complex aspects of consciousness and subjective components of sensory and affective experiences. Hypnosis is a striking phenomenon that can powerfully modulate the subjective appraisal of many sensory or motor experiences such as pain perception, hallucination, paralysis. But its cerebral substrates remain poorly known. Our research uses hypnosis as a tool to modify conscious state and behavior, and aims at understanding the neural bases of its effects in therapeutical applications. Our current work focuses on (1) the role of executive control, (2) motivation, (3) mechanisms of induced analgesia, and (4) stress reduction during hypnosis. By using imaging techniques like fMRI and EEG, we have shown that hypnosis can induce specific changes in the patterns of brain activity: for example motor brain areas become controlled by regions involved in memory and mental imagery when people are paralyzed under hypnosis (red); but this is not seen in those who aren't hypnotized but pretend their hand is paralyzed (green). Thsi participants ellicit a normal control of motor areas by premotor planning regions. - Cojan, Vuilleumier, Forster, Cheseaux.



Sleep disorders (or deprivations) are frequently associated with cognitive and affective symptoms, and patients with emotion disorders often present sleep disturbances. Sleep is involved in the regulation of stress (ex: nightmares in patients with post-traumatic-stress-disorder), and emotional memories are altered by sleep deprivation. Thus, both clinical and neurobiological findings converge to suggest close interactions between sleep and emotion regulation. However, the brain mechanisms underlying such effects in humans remain largely unknown. We investigate the effects of normal and modified sleep on cognition and emotional processing in healthy subjects, as well as patients with severe disorders in sleep control (narcolepsy). We combine measures of brain activity using fMRI when subjects performed various tasks in different conditions and after pharmacological manipulations. Our subjects are invited to sleep in the lab under polysomnography, for a nap or for all the night and we measured the relation between changes in behaviour and brain activity during or after a period of sleep. The comparison between subjects who sleep normally and those with altered sleep patterns allows us to highlight the impact of sleep on cognition and emotional regulation. Our research was the first to reveal a major impact of the neuropeptide orexin/hypocretin (a substance produced in hypothalamus, regulating both wake-sleep states and motivation) on emotional circuits in amygdala (involved in fear and anxiety) and in striatum (involved in reward and addiction). - Schwartz, Sterpenich, Igloi, Perrig.



Emotion and music

Music can induce intense and complex emotions, beyond basic categories of affect typically studied in psychology and neuroscience such as fear, anger, or happiness. Music can also evoke feelings of wonder, nostalgia, tenderness, or even transcendence. Many psychologists and philosophers have argued that these emotions do not correspond to the basic affect categories, but rather include a distinct class of so-called “non-utilitarian” or aesthetic emotions. Our research aims at elucidating the neural circuits involved in these “special” kinds of emotions by recording brain activity while participants listen to musical pieces selected to evoke such emotions. We also record concomitant changes in physiological states such as respiration, heart rate, and skin conductance reactivity. Our work has begun to identify a complex affective space of emotion dimensions associated with music. We could show that, at the brain level, these dimensions are partly shared with those of non-musical emotions, including activations of pleasure centers (in striatum and ventral tegmental area), but also combined in unique ways with a concomitant recruitment of other brain circuits that are involved in action (motor cortex), memory (hippocampus), and self-reflective processes (ventromedial prefrontal cortex, VMPFC). Our results thus suggest that the distinct activation profiles evoked by each musical emotion in these circuits may determine their distinctive richness and flavor. In addition, other ongoing studies investigate the neural plasticity induced by musical expertise in professional musicians, and the behavioral correlates of motor execution and coordination during performance with efficient emotion inductions. - Trost, Vuilleumier, Grandjean, Scherer, James.


Emotion and odors

Our project is funded by, and carried out in collaboration with, a world-leading fragrance producer (Firmenich SA). Our goal is to develop a new measurement methodology to study the emotional effects of odours. The effect of emotions produced by odours are studied as (more or less conscious) feelings that integrate cognitive, physiological, motivational and expressive effects, which also consider a major role for individual and cultural differences. We combine behavioral experiments to identify the semantic space describing emotions elicited by olfactory stimuli, together with thermography measures allowing us to record changes in skin temperatures and facial muscle activity with high temporal resolution, as well as neuroimaging measures with fMRI and EEG thanks to a dedicated olfactometer allowing a precise delivery of odor molecules directly to the nose of participants. - Sander, Delplanque, Vuilleumier, Grandjean, Jarlier, Pichon, Coppin.


Decoding emotions and voice prosody

Brain activations patterns can be analyzed not only by measuring the degree of increases or decreases in specific regions, but also by determining the distribution of activity within or across cortical areas. By employing classification methods (such as support vector machine (SVM)) to analyze multi-voxel patterns of activity recorded by high-resolution fMRI, we have shown that it is possible to decode the emotion expressed by voices from neural activity observed in auditory cortex. Distinct patterns were found to be evoked by five different vocal emotions (anger, sadness, neutral, relief, joy), and this pattern could be successfully used to recognize the emotions perceived by human volunteers in the fMRI scanner. Similarly, we have shown that perceived emotions can be decoded from medial prefrontal cortex (MPFC) across different sensory modalities: in other words, the pattern of neural activity recorded in response to facial expressions could be used to recognize the category of emotion perceived from voices or gestures, suggesting that MPFC represent affective information at a supramodal level. - Vuilleumier, Peelen, Ethofer, Grandjean, Fruehholz.



Alzheimer's Disease

Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by deficits in episodic memory at the earliest stages. Individuals with Mild Cognitive Impairment (MCI) are at high risk of developing AD. MCI is defined as isolated memory impairment, without problems with daily activities. However, not all MCI patients develop AD; some remain stable over time, improve, or progress to another dementia. Because treatments for AD focus on slowing the progression of the disease, an early diagnosis is essential. Structural neuroimaging techniques may help the diagnosis, but are often not sensitive enough to detect AD at this early stage. We propose functional MRI as a tool to provide a quantitative measure of the risk to develop AD in MCI patients. We have developped a new fMRI paradigm that probes different components of memory function, allowing us to distinguish elderly people with and without MCI, and subsequently identify those at risk of a true Alzheimer dementia. Assal, Schwartz, Vuilleumier, van der Meulen.


Stroke and spatial neglect syndrome

Cerebrovascular diseases are a major cause of death and handicap. Focal brain lesions due to stroke can cause severe deficits and still often represent a challenge for rehabilitation. We use functional MRI combined with structural and diffusion imaging, as well as neuropsychological behavioral tests, to uncover the impact of stroke on cognitive and affective functioning. In particular, we investigate the neural mechanisms of unilateral spatial neglect (USN), a common disorder following focal right hemisphere damage, which is characterized by a failure to perceive and orient towards stimuli located on the left side of space. These deficits are not attributable to primary sensory or motor loss, but involve a neuropsychological disturbance in the representation of space. By using fMRI and EEG in stroke patients, we have shown that these symptoms reflect functional anomalies in anatomically intact sensory areas due to the loss of top-down modulation by spatial processes in frontal and parietal areas, which are damaged by the stroke. By using statistical lesion mapping techniques, we also showed that different distributions of lesions cause different disturbances in spatial behavior and awareness, suggesting that the neglect syndrome reflects a combination of deficits affecting different cognitive components. In addition, our fMRI and EEG results have revealed that intact occipital areas can still show residual activation to visual stimuli despite brain damage and lack of conscious perception, leading to new research looking at appropriate therapeutic interventions that might restore normal activity in these areas. Functional neuroimaging techniques can thus provide precious clues on the mechanisms underlying handicap and recovery after stroke. Vuilleumier, Saj, Verdon, Vocat


Multiple sclerosis

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system that commonly leads to inflammatory and atrophic brain pathology, often causing motor and sensory impairment but also cognitive and emotional disturbances. However, the frequency, quality, and mechanisms of cognitive and emotional problems are still poorly understood. In addition, although early treatment is important to reduce the progression of inflammatory damage, early diagnosis is often not possible by conventional MRI techniques that identify only structural and large inflammatory lesions. To improve the detection of brain dysfunction induced by demyelination, our research combines new MRI techniques based on diffusion tensor imaging (DTI) to assess disconnection within white-matter pathways, and functional MRI to assess impaired network connectivity in sensorimotor and cognitive-affective tasks.


We have also developped new measures of functional connectivity between brain regions allowing us to detect anomalies at early stages of disease using advanced statistical classification methods based on pattern recognition approaches. Vuilleumier, Gschwind, Van de Ville, Richiardi.

MS connect

Depression and psychiatric disorders

Recent functional MRI research has shown that depression and mood disorders are associated with disturbances in the activation of brain areas implicated in emotion regulation and cognitive control. Our results demonstrate that non-medicated patients with a first episode of unipolar major depression (compared to controls) have a reduced ability to filter irrelevant information due to a loss of functional connectivity between fronto-parietal networks (involved in cognitive control) and visual cortices (involved in perception). In addition, increased attentional demands produce a suppression of abnormal hyperactivity in subgenual-cingulate/ventromedial prefrontal regions, the latter being a major functional marker of major depression. These results reveals the neural substrates of attention deficits in major depression, and clarify how neural networks implicated in mood regulation influence executive control and perceptual processes. Ongoing studies investigate the effect of meditation training on emotion regulation in depression and the neural substrates of subjective loss of control over thoughts (e.g. ruminations, tachypsychism) in mood disorders. Desseilles, Schwartz, Bondolfi, Aubry, Bertschy, Vuilleumier, Piguet, Rey.



Brain Decoding Based on Functional-Connectivity Measures

Resting state
Resting state

Multivariate pattern analysis has become a key approach to perform "brain reading" from fMRI acquisitions; i.e., predict the subject's brain state from the imaging data. We showed that it is possible to correctly decode brain states using the brain's connectivity profile. This new methodology can not only be applied to better understand functional integration during cognitive tasks, but also to explore early modification of connectivity for various neurological disorders - Van De Ville and Richiardi (MIPLAB), Eryilmaz, Schwartz and Vuilleumier (LABNIC).

Scale-Free Dynamics of EEG Microstates

We investigate the temporal organization of global brain states; i.e., EEG microstates. Given the surprising fact that the fast changes (100ms) of the four EEG microstates can be linked to the slow fMRI BOLD oscillations (10s) of large-scale resting-state networks (as measured using simultaneous EEG-fMRI recordings), we postulate that the EEG microstate dynamics are scale-free. Indeed, using the wavelet leaders framework for fractal analysis, we show that the process observed is stochastically the same at timescales between 256ms and 16s. This finding is intriguing, since EEG microstates are considered as the "atoms of thought" and thus spontaneous brain activity is organized in an unpredictable (non-stationary) but well defined way. Scale-free dynamics are reminiscent for systems at critical state; i.e., they maintain the ability to quickly reorganize - Van De Ville (MIPLAB), Britz and Michel (EEG FBM Lab).


EEG source localization

Source Localization
Source Localization
We propose a new theoretical framework that leads to a non-iterative technique for EEG source imaging. We designate our method as analytic sensing, since the key contribution is to apply analytic sensors (functions with vanishing Laplacian in some domain) that sense the influence of the source distribution in a specific region. Our approach can be applied for multi-pole or multi-dipole source models, bringing together several attractive features: (1) the non-linear (dipole positions) and linear (dipolar moments) estimation steps are decoupled; (2) the non-linear estimation is direct (non-iterative) and fast; (3) no forward model is needed, while the scalp surface can be non-spherical; (4) the method can be spatially selective to only incorporate the influence of sources in a desired region-of-interest - Van De Ville and Kandaswamy (MIPLAB), Blu (CUHK, Hong Kong), Michel and Spinelli (EEG FBM Lab).