Auditory mismatch impairments are characterized by core neural dysfunctions in schizophrenia

Major theories on the neural basis of schizophrenic core symptoms highlight aberrant salience network activity (insula and anterior cingulate cortex), prefrontal hypoactivation, sensory processing deficits as well as an impaired connectivity between temporal and prefrontal cortices. The mismatch negativity is a potential biomarker of schizophrenia and its reduction might be a consequence of each of these mechanisms. In contrast to the previous electroencephalographic studies, functional magnetic resonance imaging may disentangle the involved brain networks at high spatial resolution and determine contributions from localized brain responses and functional connectivity to the schizophrenic impairments. Twenty-four patients and 24 matched control subjects underwent functional magnetic resonance imaging during an optimized auditory mismatch task. Haemodynamic responses and functional connectivity were compared between groups. These data sets further entered a diagnostic classification analysis to assess impairments on the individual patient level. In the control group, mismatch responses were detected in the auditory cortex, prefrontal cortex and the salience network (insula and anterior cingulate cortex). Furthermore, mismatch processing was associated with a deactivation of the visual system and the dorsal attention network indicating a shift of resources from the visual to the auditory domain. The patients exhibited reduced activation in all of the respective systems (right auditory cortex, prefrontal cortex, and the salience network) as well as reduced deactivation of the visual system and the dorsal attention network. Group differences were most prominent in the anterior cingulate cortex and adjacent prefrontal areas. The latter regions also exhibited a reduced functional connectivity with the auditory cortex in the patients. In the classification analysis, haemodynamic responses yielded a maximal accuracy of 83% based on four features; functional connectivity data performed similarly or worse for up to about 10 features. However, connectivity data yielded a better performance when including more than 10 features yielding up to 90% accuracy. Among others, the most discriminating features represented functional connections between the auditory cortex and the anterior cingulate cortex as well as adjacent prefrontal areas. Auditory mismatch impairments incorporate major neural dysfunctions in schizophrenia. Our data suggest synergistic effects of sensory processing deficits, aberrant salience attribution, prefrontal hypoactivation as well as a disrupted connectivity between temporal and prefrontal cortices. These deficits are associated with subsequent disturbances in modality-specific resource allocation. Capturing different schizophrenic core dysfunctions, functional magnetic resonance imaging during this optimized mismatch paradigm reveals processing impairments on the individual patient level, rendering it a potential biomarker of schizophrenia.

Spatio-temporal coupling of the electric and hemodynamic brain responses in humans

Roberto Martuzzi

Our comprehension of human brain functions and their dynamics has been dramatically improved by recent developments in non-invasive imaging techniques. These methods can be divided into two different categories, according to the nature of the measured signal: hemodynamic techniques, such as functional magnetic resonance imaging (fMRI) and positiron emission tomography (PET), and electromagnetic techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG). These two categories are have complementary characteristics: hemodynamic techniques have a good spatial resolution (on a millimeter spatial scale) but have a poor temporal resolution, which is inherently limited by the rate changes in blood flow and oxygenation. Electromagnetic techniques have sub-millisecond temporal resolution but have a poor spatial resolution, since the analysis of intracranial generators requires the solution of an underdetermined inverse problem (i.e. there are infinite solutions that can explain equally well the same scalp-recorded distribution). The complementarity of the characteristics of these two families of methods allowed researchers to suppose that the understanding of spatio-temporal brain dynamics can be drastically improved by their combination (so-called multimodal imaging). Unfortunately some caveats hinder such combination. First, the nature of neurovascular coupling is still poorly understood. Second, analytical methods for multimodal imaging are largely in their infancy. The first part of this thesis focuses on the analysis of the temporal characteristics of the blood oxygenation level dependent (BOLD) signal and on how they are modulated by stimulus conditions. To analyze the BOLD dynamics, a novel method for synchronizing stimulus delivery and volume acquisition was developed. This method allows for estimating the BOLD signal with a high temporal resolution (in this thesis up to 125 ms) and for studying how the temporal characteristics (in this thesis mainly the BOLD peak latency and slope) are modulated by stimulus conditions (with an approach similar to that used in the analysis of the EEG evoked potentials). We applied this novel technique to a simple reaction time task to lateralized visual stimuli (the so-called Poffenberger paradigm) as well as to a multisensory auditory-visual reaction time task. In the first study (the Poffenberger paradigm) the analysis of BOLD dynamics supported the theory of a bilateral visuo-motor pathway even in the case of a visual stimulus ipsilateral to the responding hand. In the second study, (the auditory-visual multisensory reaction-time task), the analysis showed auditory-visual interactions within both primary auditory and visual cortices that could not be otherwise revealed by traditional fMRI analysis methods since it does not involve changes in signal amplitude. The second part of this thesis focuses on the comparison of the statistical results obtained by the analyses of fMRI and of the intracranial local field potentials (LFPs), estimated by the ELECTRA inverse solution. We first developed a new method for the analysis of EEG data. This method is based on the statistical comparison of the spectral characteristics of the estimated intracranial LFPs of the pre- and post- stimulus onset periods. Each single trial is analyzed independently, without including an averaging step, so that the information carried by high frequencies is preserved. We also propose a new metric, called resemblance, to investigate the relationship between fMRI and the estimated intracranial LFPs. Single-trial analysis and the resemblance metric were applied in an experiment involving separate EEG and fMRI acquisitions during the same passive visual stimulation protocol. This experiment revealed that only a limited set of LFP frequencies shows a spatial correlation with fMRI. This set of frequencies changes across brain areas, such that progression from lower to higher cortical levels of visual processing incorporates at each step new frequencies. In conclusion, in this thesis we show that the estimation and the analysis of the BOLD time course can give an important contribution to better understanding brain functions and brain organization. To fully understand the meaning of changes in BOLD dynamics, we need a better knowledge of the neuro-vascular coupling. To do that, we introduced a new method for evaluating the relationship between EEG and fMRI across frequencies and anatomical regions.

EPFL2006

Noise in brain activity engenders perception and influences discrimination sensitivity

Fosco Bernasconi, Athina Tzovara

Behavioral and brain responses to identical stimuli can vary with experimental and task parameters, including the context of stimulus presentation or attention. More surprisingly, computational models suggest that noise-related random fluctuations in brain responses to stimuli would alone be sufficient to engender perceptual differences between physically identical stimuli. In two experiments combining psychophysics and EEG in healthy humans, we investigated brain mechanisms whereby identical stimuli are (erroneously) perceived as different (higher vs lower in pitch or longer vs shorter in duration) in the absence of any change in the experimental context. Even though, as expected, participants' percepts to identical stimuli varied randomly, a classification algorithm based on a mixture of Gaussians model (GMM) showed that there was sufficient information in single-trial EEG to reliably predict participants' judgments of the stimulus dimension. By contrasting electrical neuroimaging analyses of auditory evoked potentials (AEPs) to the identical stimuli as a function of participants' percepts, we identified the precise timing and neural correlates (strength vs topographic modulations) as well as intracranial sources of these erroneous perceptions. In both experiments, AEP differences first occurred ~100 ms after stimulus onset and were the result of topographic modulations following from changes in the configuration of active brain networks. Source estimations localized the origin of variations in perceived pitch of identical stimuli within right temporal and left frontal areas and of variations in perceived duration within right temporoparietal areas. We discuss our results in terms of providing neurophysiologic evidence for the contribution of random fluctuations in brain activity to conscious perception.

Society for Neuroscience2011

Spatio-temporal coupling of the electric and hemodynamic brain responses in humans

Roberto Martuzzi

EPFL2006