Impairment in predictive processes during auditory mismatch negativity in ScZ: evidence from event-related fields

Patients with schizophrenia (ScZ) show pronounced dysfunctions in auditory perception but the underlying mechanisms as well as the localization of the deficit remain unclear. To examine these questions, the current study examined whether alterations in the neuromagnetic mismatch negativity (MMNm) in ScZ-patients could involve an impairment in sensory predictions in local sensory and higher auditory areas. Using a whole-head MEG-approach, we investigated the MMNm as well as P300m and N100m amplitudes during a hierarchical auditory novelty paradigm in 16 medicated ScZ-patients and 16 controls. In addition, responses to omitted sounds were investigated, allowing for a critical test of the predictive coding hypothesis. Source-localization was performed to identify the generators of the MMNm, omission responses as well as the P300m. Clinical symptoms were examined with the positive and negative syndrome scale. Event-related fields (ERFs) to standard sounds were intact in ScZ-patients. However, the ScZ-group showed a reduction in the amplitude of the MMNm during both local (within trials) and global (across trials) conditions as well as an absent P300m at the global level. Importantly, responses to sound omissions were reduced in ScZ-patients which overlapped both in latency and generators with the MMNm sources. Thus, our data suggest that auditory dysfunctions in ScZ involve impaired predictive processes that involve deficits in both automatic and conscious detection of auditory regularities

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (⁠R1⁠), effective transverse relaxation rate (⁠R2∗⁠), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (⁠R2∗ at 3T, R1 at 7T), endothelial cells (⁠R1 and MTsat at 3T), microglia (⁠R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes and oligodendrocyte precursor cells (⁠R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types

Predictive coding over the lifespan: Increased reliance on perceptual priors in older adults-a magnetoencephalography and dynamic causal modelling study

Aging is accompanied by unisensory decline. To compensate for this, two complementary strategies are potentially relied upon increasingly: first, older adults integrate more information from different sensory organs. Second, according to the predictive coding (PC) model, we form “templates” (internal models or “priors”) of the environment through our experiences. It is through increased life experience that older adults may rely more on these templates compared to younger adults. Multisensory integration and predictive coding would be effective strategies for the perception of near-threshold stimuli, which may however come at the cost of integrating irrelevant information. Both strategies can be studied in multisensory illusions because these require the integration of different sensory information, as well as an internal model of the world that can take precedence over sensory input. Here, we elicited a classic multisensory illusion, the sound-induced flash illusion, in younger (mean: 27 years, N = 25) and older (mean: 67 years, N = 28) adult participants while recording the magnetoencephalogram. Older adults perceived more illusions than younger adults. Older adults had increased pre-stimulus beta-band activity compared to younger adults as predicted by microcircuit theories of predictive coding, which suggest priors and predictions are linked to beta-band activity. Transfer entropy analysis and dynamic causal modeling of pre-stimulus magnetoencephalography data revealed a stronger illusion-related modulation of cross-modal connectivity from auditory to visual cortices in older compared to younger adults. We interpret this as the neural correlate of increased reliance on a cross-modal predictive template in older adults leading to the illusory percept

Is Computed-Tomography-Based Body Composition a Reliable Predictor of Chemotherapy-Related Toxicity in Pancreatic Cancer Patients?

BACKGROUND Malnutrition, loss of weight and of skeletal muscle mass are frequent in pancreatic cancer patients, a majority of which will undergo chemotherapy over the course of their disease. Available data suggest a negative prognostic role of these changes in body composition on disease outcomes; however, it is unclear whether tolerance to chemotherapeutic treatment is similarly and/or negatively affected. We aimed to explore this association by retrospectively assessing changes in body composition and chemotherapy-related toxicity in a cohort of advanced pancreatic cancer patients. METHODS Body composition was evaluated through clinical parameters and through radiological assessment of muscle mass, skeletal muscle area, skeletal muscle index and skeletal muscle density; and an assessment of fat distribution by subcutaneous adipose tissue and visceral adipose tissue. We performed descriptive statistics, pre/post chemotherapy comparisons and uni- and multivariate analyses to assess the relation between changes in body composition and toxicity. RESULTS Toxicity risk increased with an increase of skeletal muscle index (OR: 1.03) and body mass index (OR: 1.07), whereas it decreased with an increase in skeletal muscle density (OR: 0.96). Multivariate analyses confirmed a reduction in the risk of toxicity only with an increase in skeletal muscle density (OR: 0.96). CONCLUSIONS This study suggests that the retrospective analysis of changes in body composition is unlikely to be useful to predict toxicity to gemcitabine-nab-paclitaxel

Inferring laminar origins of MEG signals with optically pumped magnetometers (OPMs): a simulation study

We explore the potential of optically-pumped magnetometers (OPMs) to infer the laminar origins of neural activity non-invasively. OPM sensors can be positioned closer to the scalp than conventional cryogenic MEG sensors, opening an avenue to higher spatial resolution when combined with high-precision forward modelling. By simulating the forward model projection of single dipole sources onto OPM sensor arrays with varying sensor densities and measurement axes, and employing sparse source reconstruction approaches, we find that laminar inference with OPM arrays is possible at relatively low sensor counts at moderate to high signal-to-noise ratios (SNR). We observe improvements in laminar inference with increasing spatial sampling densities and number of measurement axes. Surprisingly, moving sensors closer to the scalp is less advantageous than anticipated - and even detrimental at high SNRs. Biases towards both the superficial and deep surfaces at very low SNRs and a notable bias towards the deep surface when combining empirical Bayesian beamformer (EBB) source reconstruction with a whole-brain analysis pose further challenges. Adequate SNR through appropriate trial numbers and shielding, as well as precise co-registration, is crucial for reliable laminar inference with OPMs

Advances in MEG methods and their applications to investigate auditory perception

Das verbindende Ziel meiner Doktorarbeit war die Weiterentwicklung von statistischen und methodischen Ansätzen in der Analyse von Magnetenzephalographie- Daten und die Anwendung dieser Ansätze in Studien zur Hörwahrnehmung beim Menschen. Magnetenzephalographie (MEG) ist eine nicht-invasive Meßmethode, die die Änderungen der magnetischen Felder, welche durch die synchronisierte neuronale Erregung von Pyramidenzellen in der Hirnrinde hervorgerufen werden, mit einer hohen zeitlichen Auflösung außerhalb des Kopfes aufzeichnet. In einem allgemeinen Einführungskapitel werden zunächst die Grundlagen der Magnetenzephalographie dargestellt und der physiologische Ursprung der gemessenen elektromagnetischen Signale beschrieben. Um die kortikalen Stromquellen, die den außerhalb des Kopfes gemessenen Feldern zugrunde liegen, schätzen zu können, werden sogenannte Vorwärtsmodelle benötigt, die beschreiben wie sich die Ströme einzelner kortikaler Quellen auf die an den Sensoren gemessenen Magnetfelder auswirken. Das inverse Problem, die Schätzung der kortikalen Quellen anhand der Topographie der gemessenen Magnetfelder, ist jedoch selbst wenn das Vorwärtsmodell bekannt ist nicht eindeutig lösbar. Es müssen daher bei der Rekonstruktion der kortikalen Quellströme zusätzliche Vorannahmen über die Eigenschaften der neuronalen Quellen getroffen werden. Die räumliche Genauigkeit der Quellenlokalisierung bei MEG-Studien ist dabei geringer als bei der funktionellen Magnetresonanztomographie...Magnetoencephalography (MEG) measures neural activity non-invasively and at an excellent temporal resolution. Since its invention (Cohen, 1968, 1972), MEG has proven a most valuable tool in neurocognitive (Salmelin et al., 1994) and clinical research (Stufflebeam et al., 2009; Van ’t Ent et al., 2003). MEG is able to measure rapid changes in electrophysiological neural signals related to sensory and cognitive processes. The magnetic fields measured outside the head by MEG directly reflect the cortical currents generated by the synchronised activity of thousands of neuronal sources. This distinguishes MEG from functional magnetic resonance imaging (fMRI), where measurements are only indirectly related to electrophysiological activity through neurovascular coupling..

Predictive coding over the lifespan: Increased reliance on perceptual priors in older adults: A magnetoencephalography and dynamic causal modelling study

Aging is accompanied by unisensory decline; but to compensate for this, two complementary strategies are potentially relied upon increasingly: first, older adults integrate more information from different sensory organs. Second, according to predictive coding (PC) we form ‘templates’ (internal models or ‘priors’) of the environment through our experiences. It is through increased life experience that older adults may rely more on these templates compared to younger adults. Multisensory integration and predictive coding would be effective strategies for the perception of near-threshold stimuli, but they come at the cost of integrating irrelevant information. Their role can be studied in multisensory illusions because these require the integration of different sensory information, as well as an internal model of the world that can take precedence over sensory input. Here, we elicited a classic multisensory illusion, the sound-induced flash illusion, in younger (mean: 27 yrs) and older (mean: 67 yrs) adult participants while recording the magnetoencephalogram. Older adults perceived more illusions than younger adults. Older adults had increased pre-stimulus beta(β)-band activity compared to younger adults as predicted by microcircuit theories of predictive coding, which suggest priors and predictions are linked to β-band activity. In line with our hypothesis, transfer entropy analysis and dynamic causal models of pre-stimulus MEG data revealed a stronger illusion-related modulation of cross-modal connectivity from auditory to visual cortices in older compared to younger adults. We interpret this as the neural correlate of increased reliance on a cross-modal predictive template in older adults that is leading to the illusory percept

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (equation ImEquation1), effective transverse relaxation rate (equation ImEquation2), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (equation ImEquation3 at 3T, equation ImEquation4 at 7T), endothelial cells (equation ImEquation5 and MTsat at 3T), microglia (equation ImEquation6 and MTsat at 3T, equation ImEquation7 at 7T), and oligodendrocytes and oligodendrocyte precursor cells (equation ImEquation8 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2∗), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2∗ at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types