Resting-state cross-frequency coupling networks in human electrophysiological recordings, bioRxiv, 2019-02-13
Neuronal oscillations underlie temporal coordination of neuronal processing and their synchronization enables neuronal communication across distributed brain areas to serve a variety of sensory, motor, and cognitive functions. The regulation and integration of neuronal processing between oscillating assemblies at distinct frequencies, and thereby the coordination of distinct computational functions, is thought to be achieved via cross-frequency coupling (CFC). Although many studies have observed CFC locally within a brain region during cognitive processing, the large-scale networks of CFC have remained largely uncharted. Critically, also the validity of prior CFC observations and the presence of true neuronal CFC has been recently questioned because non-sinusoidal or non-zero-mean waveforms that are commonplace in electrophysiological data cause filtering artefacts that lead to false positive CFC findings. We used a unique dataset of stereo-electroencephalography (SEEG) and source-reconstructed magnetoencephalography (MEG) data to chart whole-brain CFC networks from human resting-state brain dynamics. Using a novel graph theoretical method to distinguish true inter-areal CFC from potentially false positive CFC, we show that the resting state is characterized by two separable forms of true inter-areal CFC phase-amplitude coupling (PAC) and nm-cross-frequency phase synchrony (CFS). PAC and CFS large-scale networks coupled prefrontal, visual and sensorimotor cortices, but with opposing anatomical architectures. Crucially also directionalities between low- and high-frequency oscillations were opposite between CFS and PAC. We also found CFC to decay as a function of distance and to be stronger in the superficial than deep layers of the cortex. In conclusion, these results provide conclusive evidence for the presence of two forms of genuine inter-areal CFC and elucidate the large-scale organization of CFC resting-state networks.
biorxiv neuroscience 0-100-users 2019Predictive neural processing in adult zebrafish depends on shank3b, bioRxiv, 2019-02-12
Intelligent behavior requires a comparison between the predicted and the actual consequences of behavioral actions. According to the theory of predictive processing, this comparison relies on a neuronal error signal that reflects the mismatch between an internal prediction and sensory input. Inappropriate error signals may generate pathological experiences in neuropsychiatric conditions. To examine the processing of sensorimotor prediction errors across different telencephalic brain areas we optically measured neuronal activity in head-fixed, adult zebrafish in a virtual reality. Brief perturbations of visuomotor feedback triggered distinct changes in swimming behavior and different neuronal responses. Neuronal activity reflecting sensorimotor mismatch, rather than sensory input or motor output alone, was prominent throughout multiple forebrain areas. This activity preceded and predicted the transition in motor behavior. Error signals were altered in specific forebrain regions by a mutation in the autism-related gene shank3b. Predictive processing is therefore a widespread phenomenon that may contribute to disease phenotypes.
biorxiv neuroscience 0-100-users 2019THINGS A database of 1,854 object concepts and more than 26,000 naturalistic object images, bioRxiv, 2019-02-11
In recent years, the use of a large number of object concepts and naturalistic object images has been growing enormously in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually-curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of uncontrolled naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science.
biorxiv neuroscience 100-200-users 2019A neurodevelopmental origin of behavioral individuality, bioRxiv, 2019-02-06
The genome versus experience, or Nature versus Nurture, debate has dominated our understanding of individual behavioral variation. A third factor, namely variation in complex behavior potentially due to non-heritable developmental noise in brain development, has been largely ignored. Using the Drosophila vinegar fly we demonstrate a causal link between variation in brain wiring due to developmental noise, and behavioral individuality. A population of visual system neurons called DCNs shows non-heritable, inter-individual variation in rightleft wiring asymmetry, and control object orientation in freely walking flies. We show that DCN wiring asymmetry predicts individual object responses the greater the asymmetry, the better the individual orients. Silencing DCNs abolishes correlations between anatomy and behavior, while inducing visual asymmetry via monocular deprivation rescues object orientation in DCN-symmetric individuals.
biorxiv neuroscience 0-100-users 2019Revealing neural correlates of behavior without behavioral measurements, bioRxiv, 2019-02-06
Measuring neuronal tuning curves has been instrumental for many discoveries in neuroscience but requires a-priori assumptions regarding the identity of the encoded variables. We applied unsupervised learning to large-scale neuronal recordings in behaving mice from circuits involved in spatial cognition, and uncovered a highly-organized internal structure of ensemble activity patterns. This emergent structure allowed defining for each neuron an 'internal tuning-curve' that characterizes its activity relative to the network activity, rather than relative to any pre-defined external variable -revealing place-tuning in the hippocampus and head-direction tuning in the thalamus and postsubiculum, without relying on measurements of place or head-direction. Similar investigation in prefrontal cortex revealed schematic representations of distances and actions, and exposed a previously unknown variable, the 'trajectory-phase'. The structure of ensemble activity patterns was conserved across mice, allowing using one animal's data to decode another animal's behavior. Thus, the internal structure of neuronal activity itself enables reconstructing internal representations and discovering new behavioral variables hidden within a neural code.
biorxiv neuroscience 100-200-users 2019A primal role for balance in the development of coordinated locomotion, bioRxiv, 2019-02-02
Mature locomotion requires that animal nervous systems coordinate distinct groups of muscles. The pressures that guide the development of coordination are not well understood. We studied vertical locomotion in developing zebrafish to understand how and why coordination might emerge. We found that zebrafish used their pectoral fins and bodies synergistically to climb. As they developed, zebrafish came to coordinate their fins and bodies to climb with increasing postural stability. Fin-body synergies were absent in mutants without vestibular sensation, linking balance and coordination. Similarly, synergies were systematically altered following cerebellar lesions, identifying a neural substrate regulating fin-body coordination. Computational modeling illustrated how coordinated climbing could improve balance as zebrafish mature. Together these findings link the sense of balance to the maturation of coordinated locomotion. As they develop, zebrafish improve postural stability by optimizing fin-body coordination. We therefore propose that the need to balance drives the development of coordinated locomotion.
biorxiv neuroscience 100-200-users 2019