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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2015

Resting state MEG oscillations show long-range temporal correlations of phase synchrony that break down during finger-tapping

The capacity of the human brain to interpret and respond to multiple temporal scales in its surroundings suggests that its internal interactions must also be able to operate over a broad temporal range. In this paper, we utilise a recently introduced method for characterising the rate of change of the phase difference between MEG signals and use it to study the temporal structure of the phase interactions between MEG recordings from the left and right motor cortices during rest and during a finger-tapping task. We use the Hilbert transform to estimate moment-to-moment fluctuations of the phase difference between signals. After confirming the presence of scale-invariance we estimate the Hurst exponent using detrended fluctuation analysis (DFA). An exponent of >0.5 is indicative of long-range temporal correlations (LRTCs) in the signal. We find that LRTCs are present in the / and {beta} frequency bands of resting state MEG data. We demonstrate that finger movement disrupts LRTCs correlations, producing a phase relationship with a structure similar to that of Gaussian white noise. The results are validated by applying the same analysis to data with Gaussian white noise phase difference, recordings from an empty scanner and phase-shuffled time series. We interpret the findings through comparison of the results with those we obtained from an earlier study during which we adopted this method to characterise phase relationships within a Kuramoto model of oscillators in its sub-critical, critical and super-critical synchronisation states. We find that the resting state MEG from left and right motor cortices shows moment-to-moment fluctuations of phase difference with a similar temporal structure to that of a system of Kuramoto oscillators just prior to its critical level of coupling, and that finger tapping moves the system away from this pre-critical state towards a more random state.

Neuroscience↗

bioRxiv2015

Intrinsic coupling modes reveal the functional architecture of cortico-tectal networks

In the absence of sensory stimulation or motor output, the brain exhibits complex spatiotemporal patterns of intrinsically generated neural activity. However, little is known about how such patterns of activity are correlated between cortical and subcortical brain areas. Here, we investigate the large-scale correlation structure of ongoing cortical and superior colliculus (SC) activity across multiple spatial and temporal scales. Cortico-tectal interaction was characterized by correlated fluctuations in the amplitude of delta, spindle, low gamma and high frequency oscillations (> 100 Hz). Of these identified coupling modes, topographical patterns of high frequency coupling were the most consistent with anatomical connectivity, and reflected synchronized spiking in cortico-tectal networks. Ongoing high frequency cortico-tectal coupling was temporally governed by the phase of slow cortical oscillations. Collectively, our findings show that cortico-tectal networks can be resolved through the correlation structure of ongoing neural activity, and demonstrate the rich information conveyed by high frequency electrocorticographic signals.

Neuroscience↗

bioRxiv2015

Large-scale cortical synchronization promotes multisensory processing: An EEG study of visual-tactile pattern matching

The integration of sensory signals from different modalities requires flexible interaction of remote brain areas. One candidate mechanism to establish communication in the brain is transient synchronization of oscillatory neural signals. Although there is abundant evidence for the involvement of cortical oscillations in brain functions based on the analysis of local power, assessment of the phase dynamics among spatially distributed neuronal populations and their relevance for behavior is still sparse. In the present study, we investigated the interaction between remote brain areas by analyzing high-density electroencephalogram (EEG) data obtained from human participants engaged in a visuotactile pattern matching task. We deployed an approach for purely data-driven clustering of neuronal phase coupling in source space, which allowed imaging of large-scale functional networks in space, time and frequency without defining a priori constraints. Based on the phase coupling results, we further explored how brain areas interacted across frequencies by computing phase-amplitude coupling. Several networks of interacting sources were identified with our approach, synchronizing their activity within and across the theta (~5 Hz), alpha (~10 Hz), and beta (~ 20 Hz) frequency bands and involving multiple brain areas that have previously been associated with attention and motor control. We demonstrate the functional relevance of these networks by showing that phase delays - in contrast to spectral power - were predictive of task performance. The data-driven analysis approach employed in the current study allowed an unbiased examination of functional brain networks based on EEG source level connectivity data. Showcased for multisensory processing, our results provide evidence that large-scale neuronal coupling is vital to long-range communication in the human brain and relevant for the behavioral outcome in a cognitive task.

Neuroscience↗

bioRxiv2015

Generators and connectivity of the early auditory evoked gamma band response.

BackgroundHigh frequency oscillations in the gamma range are known to be involved in early stages of auditory information processing in terms of synchronization of brain regions, e.g., in cognitive functions. It has been shown using EEG source localisation, as well as simultaneously recorded EEG-fMRI, that the auditory evoked gamma-band response (aeGBR) is modulated by attention. In addition to auditory cortex activity a dorsal anterior cingulate cortex (dACC) generator could be involved. In the present study we investigated aeGBR magnetic fields using magnetoencephalography (MEG). We aimed to localize the aeGBR sources and its connectivity features in relation to mental effort.\n\nMethodsWe investigated the aeGBR magnetic fields in 13 healthy participants using a 275-channel CTF-MEG system. The experimental paradigms were two auditory choice reaction tasks with different difficulties and demands for mental effort. We performed source localization with eLORETA and calculated the aeGBR lagged phase synchronization between bilateral auditory cortices and frontal midline structures.\n\nResultsThe eLORETA analysis revealed sources of the aeGBR within bilateral auditory cortices and in frontal midline structures of the brain including the dACC. Compared to the control condition the dACC source activity was found to be significantly stronger during the performance of the cognitively demanding task. Moreover, this task involved a significantly stronger functional connectivity between auditory cortices and dACC.\n\nConclusionIn accordance with previous EEG and EEG-fMRI investigations, our study confirms an aeGBR generator in the dACC by means of MEG and suggests its involvement in the effortful processing of auditory stimuli.

Neuroscience↗

bioRxiv2015

Modulating pathological oscillations by rhythmic non-invasive brain stimulation – a therapeutic concept?

A large amount of studies of the last decades revealed an association between human behaviour and oscillatory activity in the human brain. Alike, abnormalities of oscillatory activity were related with pathological behaviour in many neuropsychiatric disorders, such as in Parkinsons disease (PD) or in schizophrenia (SCZ). As a therapeutic tool, non-invasive brain stimulation (NIBS) has demonstrated the potential to improve behavioural performance in patients suffering from neuropsychiatric disorders. Since evidence accumulates that NIBS might be able to modulate oscillatory activity and related behaviour in a scientific setting, this review focuses on discussing potential interventional strategies to target abnormalities in oscillatory activity in neuropsychiatric disorders. In particular, we will review oscillatory changes described in patients after stroke, with PD or suffering from SCZ. Potential ways of targeting interventionally the underlying pathological oscillations to improve related pathological behaviour will be further discussed.

Neuroscience↗

bioRxiv2015

PREDICTABILITY OF AUTISM, SCHIZOPHRENIC AND OBSESSIVE SPECTRA DIAGNOSIS. TOWARD A DAMAGE NETWORK APPROACH

Schizophrenia, obsessive-compulsive and autistic disorders are traditionally considered as three separate psychiatric conditions each with specific symptoms and pattern of brain alterations. This view can be challenged since these three conditions have the same neurobiological origin, stemming from a common root of a unique neurodevelopmental tree.\n\nThe aim of this meta-analytic study was to determine, from a neuroimaging perspective, whether i) white matter and gray matter alterations are specific for the three different spectrum disorders, and the nosographical differentiation of three spectra is supported by different patterns of brain alterations. ii) it might be possible to define new spectra starting from specific brain damage. iii) it is possible to detect a \"brain damage network\" (a connecting link between the damaged areas that relates areas constantly involved in the disorder).\n\nThree main findings emerged from our meta-analysis: O_LIThe three psychiatric spectra do not appear to have their own specific damage.\nC_LIO_LIIt is possible to define two new damage clusters. The first includes substantial parts of the salience network, and the second is more closely linked to the auditory-visual, auditory and visual somatic areas.\nC_LIO_LIIt is possible to define a \"Damage Network\" and to infer a hierarchy of brain substrates in the pattern of propagation of the damage.\nC_LI\n\nThese results suggest the presence of a common pattern of damage in the three pathologies plus a series of variable alterations that, rather than support the sub-division into three spectra, highlight a two-cluster parcellation with an input-output and more cognitive clusters.

Neuroscience↗

bioRxiv2015

A literature-based meta-analysis of brain-wide electrophysiological diversity

For decades, neurophysiologists have characterized the biophysical properties of a rich diversity of neuron types. However, identifying common features and computational roles shared across neuron types is made more difficult by inconsistent conventions for collecting and reporting biophysical data. Here, we leverage NeuroElectro, a literature-based database of electrophysiological properties (www.neuroelectro.org), to better understand neuronal diversity - both within and across neuron types - and the confounding influences of methodological variability. We show that experimental conditions (e.g., electrode types, recording temperatures, or animal age) can explain a substantial degree of the literature-reported biophysical variability observed within a neuron type. Critically, accounting for experimental metadata enables massive cross-study data normalization and reveals that electrophysiological data are far more reproducible across labs than previously appreciated. Using this normalized dataset, we find that neuron types throughout the brain cluster by biophysical properties into 6-9 super-classes. These classes include intuitive clusters, such as fast-spiking basket cells, as well as previously unrecognized clusters, including a novel class of cortical and olfactory bulb interneurons that exhibit persistent activity at theta-band frequencies.

Neuroscience↗

bioRxiv2015

Transdermal neuromodulation of noradrenergic activity suppresses psychophysiological and biochemical stress responses in humans

We engineered a transdermal neuromodulation approach that targets peripheral (cranial and spinal) nerves and utilizes their afferent pathways as signaling conduits to influence brain function. We investigated the effects of this transdermal electrical neurosignaling (TEN) method on sympathetic physiology in human volunteers under different experimental conditions. In all cases, the TEN involved delivering high-frequency pulsed electrical currents to ophthalmic and maxillary divisions of the right trigeminal nerve (V1/V2) and cervical spinal nerve afferents (C2/C3). Under resting conditions when subjects were not challenged or presented with environmental stimuli, TEN significantly suppressed basal sympathetic tone compared to sham as indicated by functional infrared thermography of facial temperatures. In a different experiment conducted under similar resting conditions, subjects treated with TEN reported significantly lower levels of tension and anxiety on the Profile of Mood States scale compared to sham. In a third experiment when subjects were experimentally stressed by a classical fear conditioning paradigm and a series of time-constrained cognitive tasks, TEN produced a significant suppression of heart rate variability, galvanic skin conductance, and salivary -amylase levels compared to sham. Collectively these observations demonstrate TEN can dampen basal sympathetic tone and attenuate sympathetic activity in response to acute stress induction. Our physiological and biochemical observations are consistent with the hypothesis that TEN modulates noradrenergic signaling to suppress sympathetic activity. We conclude that dampening sympathetic activity in such a manner represents a promising approach to managing daily stress.

Neuroscience↗

bioRxiv2015

Decoding of human hand actions to handle missing limbs in Neuroprosthetics

The only way we can interact with the world is through movements, and our primary interactions are via the hands, thus any loss of hand function has immediate impact on our quality of life. However, to date it has not been systematically assessed how coordination in the hands joints affects every day actions. This is important for two fundamental reasons. Firstly, to understand the representations and computations underlying motor control \"in-the-wild\" situations, and secondly to develop smarter controllers for prosthetic hands that have the same functionality as natural limbs. In this work we exploit the correlation structure of our hand and finger movements in daily-life. The novelty of our idea is that instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. We asked seven subjects to interact in 17 daily-life situations, and quantified behaviour in a principled manner using CyberGlove body sensor networks that, after accurate calibration, track all major joints of the hand. Our key findings are: 1. We confirmed that hand control in daily-life tasks is very low-dimensional, with four to five dimensions being sufficient to explain 80-90% of the variability in the natural movement data. 2. We established a universally applicable measure of manipulative complexity that allowed us to measure and compare limb movements across tasks. We used Bayesian latent variable models to model the low-dimensional structure of finger joint angles in natural actions. 3. This allowed us to build a naive classifier that within the first 1000ms of action initiation (from a flat hand start configuration) predicted which of the 17 actions was going to be executed - enabling us to reliably predict the action intention from very short-time-scale initial data, further revealing the foreseeable nature of hand movements for control of neuroprosthetics and tele operation purposes. 4. Using the Expectation-Maximization algorithm on our latent variable model permitted us to reconstruct with high accuracy (<5{degrees}-6{degrees} MAE) the movement trajectory of missing fingers by simply tracking the remaining fingers. Overall, our results suggest the hypothesis that specific hand actions are orchestrated by the brain in such a way that in the natural tasks of daily-life there is sufficient redundancy and predictability to be directly exploitable for neuroprosthetics.

Neuroscience↗

bioRxiv2015

Can rodents conceive hyperbolic spaces?

The grid cells discovered in the rodent medial entorhinal cortex have been proposed to provide a metric for Euclidean space, possibly even hardwired in the embryo. Yet one class of models describing the formation of grid unit selectivity is entirely based on developmental self-organization, and as such it predicts that the metric it expresses should reflect the environment to which the animal has adapted. We show that, according to self-organizing models, if raised in a non-Euclidean hyperbolic cage rats should be able to form hyperbolic grids. For a given range of grid spacing relative to the radius of negative curvature of the hyperbolic surface, such grids are predicted to appear as multi-peaked firing maps, in which each peak has seven neighbours instead of the Euclidean six, a prediction that can be tested in experiments. We thus demonstrate that a useful universal neuronal metric, in the sense of a multi-scale ruler and compass that remain unaltered when changing environments, can be extended to other than the standard Euclidean plane.\n\nAbbreviation

Neuroscience↗

bioRxiv2015

Spike sorting for large, dense electrode arrays

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes will in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. There currently exists no practical solution to this problem of \"spike sorting\" for large, dense electrode arrays. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from rat cortex, demonstrating error rates as low as 5%.

Neuroscience↗

bioRxiv2015

The brain of the beholder: honouring individual representational idiosyncrasies

In the early days of neuroimaging, brain function was investigated by averaging across voxels within a region, stimuli within a category and individuals within a group. These three forms of averaging discard important neuroscientific information. Recent studies have explored analyses that combine the evidence in better-motivated ways. Multivariate pattern analyses enable researchers to reveal representations in distributed population codes, honouring the unique information contributed by different voxels (or neurons). Condition-rich designs more richly sample the stimulus space and can treat each stimulus as a unique entity. Finally, each individuals brain is unique and recent studies have found ways to model and analyse the interindividual representational variability. Here we review our fields journey towards more sophisticated analyses that honour these important idiosyncrasies of brain representations. We describe an emerging framework for investigating individually unique pattern representations of particular stimuli in the brain. The framework models stimuli, responses and individuals multivariately and relates representations by means of representational dissimilarity matrices. Important components are computational models and multivariate descriptions of brain and behavioural responses. These recent developments promise a new paradigm for studying the individually unique brain at unprecedented levels of representational detail.

Neuroscience↗

bioRxiv2015

Restoration of Sp4 in forebrain GABAergic neurons rescues hypersensitivity to ketamine in Sp4 hypomorphic mice

Ketamine produces schizophrenia-like behavioral phenotypes in healthy people. Prolonged ketamine effects and exacerbation of symptoms were observed in schizophrenia patients after administration of ketamine. More recently, ketamine has been used as a potent antidepressant to treat patients with major depression. The genes and neurons that regulate behavioral responses to ketamine, however, remain poorly understood. Our previous studies found that Sp4 hypomorphic mice displayed several behavioral phenotypes relevant to psychiatric disorders, consistent with human SP4 gene associations with schizophrenia, bipolar, and major depression. Among those behavioral phenotypes, hypersensitivity to ketamine-induced hyperlocomotion has been observed in Sp4 hypomorphic mice. Here, we report differential genetic restoration of Sp4 expression in forebrain excitatory neurons or GABAergic neurons in Sp4 hypomorphic mice and the effects of these restorations on different behavioral phenotypes. Restoration of Sp4 in forebrain excitatory neurons did not rescue deficient sensorimotor gating, fear learning, or ketamine-induced hyperlocomotion. Restoration of Sp4 in forebrain GABAergic neurons, however, rescued ketamine-induced hyperlocomotion, but did not rescue deficient sensorimotor gating or fear learning. Our studies suggest that the Sp4 gene in forebrain GABAergic neurons plays an essential role in regulating some behavioral responses to ketamine.

Neuroscience↗

bioRxiv2015

A matter of attention: Crossmodal congruence enhances and impairs performance in a novel trimodal matching paradigm

A novel crossmodal matching paradigm including vision, audition, and somatosensation was developed in order to investigate the interaction between attention and crossmodal congruence in multisensory integration. To that end, all three modalities were stimulated concurrently while a bimodal focus was defined blockwise. Congruence between stimulus intensity changes in the attended modalities had to be evaluated. We found that crossmodal congruence improved performance if both, the attended modalities and the task-irrelevant distractor were congruent. If the attended modalities were incongruent, the distractor impaired performance due to its congruence relation to one of the attended modalities. Between attentional conditions, magnitudes of crossmodal enhancement or impairment differed. Largest crossmodal effects were seen in visual-tactile matching, intermediate effects for audio-visual and smallest effects for audio-tactile matching. We conclude that differences in crossmodal matching likely reflect characteristics of multisensory neural network architecture. We discuss our results with respect to the timing of perceptual processing and state hypotheses for future physiological studies. Finally, etiological questions are addressed.

Neuroscience↗

bioRxiv2015

Complexity of dendritic SER increases at enlarging synapses during LTP

Smooth endoplasmic reticulum (SER) forms a membranous network that extends throughout neurons. SER regulates intracellular calcium and the posttranslational modification and trafficking of membrane and proteins. As the structure of dendritic SER shifts from a tubular to a more complex, branched form, the movement of membrane cargo slows and delivery to nearby spines increases. Here we discovered changes in the structural complexity of SER that have important functional implications during long-term potentiation (LTP) in adult rat hippocampus. By 2 hours after the induction of LTP with theta-burst stimulation, synapse enlargement was greatest on spines that contained SER. More spines had an elaborate spine apparatus than a simple tubule of SER. The SER in dendritic shafts became more complex beneath spines with both polyribosomes and SER, and less complex along aspiny dendritic regions. The findings suggest that local changes in dendritic SER support enhanced growth of specific synapses during LTP.

Neuroscience↗

bioRxiv2015

Different Coupling Modes Mediate Cortical Cross-Frequency Interactions

Cross-frequency coupling (CFC) has been suggested to constitute a highly flexible mechanism for cortical information gating and processing, giving rise to conscious perception and various higher cognitive functions in humans. In particular, it might provide an elegant tool for information integration across several spatiotemporal scales within nested or coupled neuronal networks. However, it is currently unknown whether low frequency (theta/alpha) or high frequency gamma oscillations orchestrate cross-frequency interactions, raising the question of who is master and who is slave. While correlative evidence suggested that at least two distinct CFC modes exist, namely phase-amplitude-coupling (PAC) and amplitude-envelope-correlations (AEC), it is currently unknown whether they subserve distinct cortical functions. Novel non-invasive brain stimulation tools, such as transcranial alternating current stimulation (tACS), now provide the unique opportunity to selectively entrain the low or high frequency component and study subsequent effects on CFC. Here, we demonstrate the differential modulation of CFC during selective entrainment of alpha or gamma oscillations. Our results reveal that entrainment of the low frequency component increased PAC, where gamma power became preferentially locked to the trough of the alpha oscillation, while gamma-band entrainment reduced alpha power through enhanced AECs. These results provide causal evidence for the functional role of coupled alpha and gamma oscillations for visual processing.

Neuroscience↗

bioRxiv2015

Hippocampal Spine Head Sizes are Highly Precise

Hippocampal synaptic activity is probabilistic and because synaptic plasticity depends on its history, the amount of information that can be stored at a synapse is limited. The strong correlation between the size and efficacy of a synapse allowed us to estimate the precision of synaptic plasticity. In an electron microscopic reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites which would have shared histories of presynaptic and postsynaptic activity. The postsynaptic spine heads, but not the spine necks, of these pairs were nearly identical in size. The precision is much greater than previous estimates and requires postsynaptic averaging over a time window many seconds to minutes in duration depending on the rate of input spikes and probability of release.\n\nOne Sentence SummarySpine heads on the same dendrite that receive input from the same axon are the same size.

Neuroscience↗

bioRxiv2015

Intersubject information mapping: revealing canonical representations of complex natural stimuli.

Real-world time-continuous stimuli such as video promise greater naturalism for studies of brain function. However, modeling the stimulus variation is challenging and introduces a bias in favor of particular descriptive dimensions. Alternatively, we can look for brain regions whose signal is correlated between subjects, essentially using one subject to model another. Intersubject correlation mapping (ICM) allows us to find brain regions driven in a canonical manner across subjects by a complex natural stimulus. However, it requires a direct voxel-to-voxel match between the spatiotemporal activity patterns and is thus only sensitive to common activations sufficiently extended to match up in Talairach space (or in an alternative, e.g. cortical-surface-based, common brain space). Here we introduce the more general approach of intersubject information mapping (IIM). For each brain region, IIM determines how much information is shared between the subjects' local spatiotemporal activity patterns. We estimate the intersubject mutual information using canonical correlation analysis applied to voxels within a spherical searchlight centered on each voxel in turn. The intersubject information estimate is invariant to linear transforms including spatial rearrangement of the voxels within the searchlight. This invariance to local encoding will be crucial in exploring fine-grained brain representations, which cannot be matched up in a common space and, more fundamentally, might be unique to each individual - like fingerprints. IIM yields a continuous brain map, which reflects intersubject information in fine-grained patterns. Performed on data from functional magnetic resonance imaging (fMRI) of subjects viewing the same television show, IIM and ICM both highlighted sensory representations, including primary visual and auditory cortices. However, IIM revealed additional regions in higher association cortices, namely temporal pole and orbitofrontal cortex. These regions appear to encode the same information across subjects in their fine-grained patterns, although their spatial-average activation was not significantly correlated between subjects.

Neuroscience↗