Where in the brain do internally generated and externally presented visual information interact?

Conscious experiences normally result from the flow of external input into our sensory systems. However, we can also create conscious percepts independently of sensory stimulation. These internally generated percepts are referred to as mental images, and they have many similarities with real visual percepts. Consequently, mental imagery is often referred to as "seeing in the mind's eye". While the neural basis of imagery has been widely studied, the interaction between internal and external sources of visual information has received little interest. Here we examined this question by using fMRI to record brain activity of healthy human volunteers while they were performing visual imagery that was distracted with a concurrent presentation of a visual stimulus. Multivariate pattern analysis (MVPA) was used to identify the brain basis of this interaction. Visual imagery was reflected in several brain areas in ventral temporal, lateral occipitotemporal, and posterior frontal cortices, with a left-hemisphere dominance. The key finding was that imagery content representations in the left lateral occipitotemporal cortex were disrupted when a visual distractor was presented during imagery. Our results thus demonstrate that the representations of internal and external visual information interact in brain areas associated with the encoding of visual objects and shapes.

Reproducibility of importance extraction methods in neural network based fMRI classification.

Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have proved useful in functional magnetic resonance imaging (fMRI) studies, there are concerns regarding extraction, reproducibility and visualization of brain regions that contribute most significantly to the classification. We addressed these issues using an fMRI classification scheme based on neural networks and compared a set of methods for extraction of category-related voxel importances in three simulated and two empirical datasets. The simulation data revealed that the proposed scheme successfully detects spatially distributed and overlapping activation patterns upon successful classification. Application of the proposed classification scheme to two previously published empirical fMRI datasets revealed robust importance maps that extensively overlap with univariate maps but also provide complementary information. Our results demonstrate increased statistical power of importance maps compared to univariate approaches for both detection of overlapping patterns and patterns with weak univariate information.

Proteomic Profiling in the Brain of CLN1 Disease Model Reveals Affected Functional Modules.

Neuronal ceroid lipofuscinoses (NCL) are the most commonly inherited progressive encephalopathies of childhood. Pathologically, they are characterized by endolysosomal storage with different ultrastructural features and biochemical compositions. The molecular mechanisms causing progressive neurodegeneration and common molecular pathways linking expression of different NCL genes are largely unknown. We analyzed proteome alterations in the brains of a mouse model of human infantile CLN1 disease-palmitoyl-protein thioesterase 1 (Ppt1) gene knockout and its wild-type age-matched counterpart at different stages: pre-symptomatic, symptomatic and advanced. For this purpose, we utilized a combination of laser capture microdissection-based quantitative liquid chromatography tandem mass spectrometry (MS) and matrix-assisted laser desorption/ionization time-of-flight MS imaging to quantify/visualize the changes in protein expression in disease-affected brain thalamus and cerebral cortex tissue slices, respectively. Proteomic profiling of the pre-symptomatic stage thalamus revealed alterations mostly in metabolic processes and inhibition of various neuronal functions, i.e., neuritogenesis. Down-regulation in dynamics associated with growth of plasma projections and cellular protrusions was further corroborated by findings from RNA sequencing of CLN1 patients' fibroblasts. Changes detected at the symptomatic stage included: mitochondrial functions, synaptic vesicle transport, myelin proteome and signaling cascades, such as RhoA signaling. Considerable dysregulation of processes related to mitochondrial cell death, RhoA/Huntington's disease signaling and myelin sheath breakdown were observed at the advanced stage of the disease. The identified changes in protein levels were further substantiated by bioinformatics and network approaches, immunohistochemistry on brain tissues and literature knowledge, thus identifying various functional modules affected in the CLN1 childhood encephalopathy.

Discrete Neural Signatures of Basic Emotions.

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience.

MALDI-imaging mass spectrometry on tissues.

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF)-profiling and imaging mass spectrometry (MSI) are promising technologies for measuring hundreds of different molecules directly on tissues. For instance, small molecules, drugs and their metabolites, endogenous lipids, carbohydrates and complex peptides/proteins can be measured at the same time. In the most advanced instruments, it is achieved without significant disruption of sample integrity. MSI is a unique approach for assessing the spatial distribution of molecules using graphical multidimensional maps of their constituent analytes, which may for instance be correlated with histopathological alterations in patient tissues. MALDI-TOF-MSI technology has been implemented in hospitals of several countries, where it is routinely used for quick pathogen(s) identification, a task formerly accomplished by laborious and expensive DNA/RNA-based PCR (polymerase chain reaction) screening.In this chapter, we describe how MSI is performed, what is required from the researcher, the instrument vendors and finally what can be achieved with MSI. We restrict our descriptions only to MALDI-MSI although several other MS techniques of ionization can easily be linked to MSI.

Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks.

Speech provides a powerful means for sharing emotions. Here we implement novel intersubject phase synchronization and whole-brain dynamic connectivity measures to show that networks of brain areas become synchronized across participants who are listening to emotional episodes in spoken narratives. Twenty participants' hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI) while they listened to 45-s narratives describing unpleasant, neutral, and pleasant events spoken in neutral voice. After scanning, participants listened to the narratives again and rated continuously their feelings of pleasantness-unpleasantness (valence) and of arousal-calmness. Instantaneous intersubject phase synchronization (ISPS) measures were computed to derive both multi-subject voxel-wise similarity measures of hemodynamic activity and inter-area functional dynamic connectivity (seed-based phase synchronization, SBPS). Valence and arousal time series were subsequently used to predict the ISPS and SBPS time series. High arousal was associated with increased ISPS in the auditory cortices and in Broca's area, and negative valence was associated with enhanced ISPS in the thalamus, anterior cingulate, lateral prefrontal, and orbitofrontal cortices. Negative valence affected functional connectivity of fronto-parietal, limbic (insula, cingulum) and fronto-opercular circuitries, and positive arousal affected the connectivity of the striatum, amygdala, thalamus, cerebellum, and dorsal frontal cortex. Positive valence and negative arousal had markedly smaller effects. We propose that high arousal synchronizes the listeners' sound-processing and speech-comprehension networks, whereas negative valence synchronizes circuitries supporting emotional and self-referential processing.

Imaging mass spectrometry: a new tool for kidney disease investigations.

Matrix-assisted laser desorption ionization (MALDI)-profiling and imaging mass spectrometry are promising technologies for measuring hundreds of different molecules directly on tissues. For instance, small molecules, drugs and their metabolites, endogenous lipids, carbohydrates and complex peptides/proteins can be measured at the same time without significant disruption of sample integrity. In this review, the potential of MALDI-profiling/imaging technologies in disease proteomics, drug action and studies of cellular processes in the context of kidney tissue is described. Spatial and sequence information obtained in tissue MALDI-profiling/imaging studies can be correlated with other mass spectrometry-based techniques, auxiliary imaging technologies and routine (immuno) histochemical staining.