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Synaesthesia lost and found: Two cases of person- and music-colour synaesthesia.

Synaesthesia is a developmental condition involving cross-communication between sensory modalities or substreams whereby an inducer (e.g. a sound) automatically evokes a concurrent percept in another modality (e.g. a colour). Whether this condition arises due to atypical structural connectivity (e.g., between normally unconnected cortical areas) or altered neurochemistry remains a central question. We report the exceptional cases of two synaesthetes - subjects AB and CD - both of whom experience coloured auras around individuals, as well as coloured perceptions in response to music. Both subjects have, in recent years, suffered a complete loss or reduction of their synaesthetic experiences, one (AB) through successive head traumas, including a lightning strike, followed by a number of medications, and the other (CD) while taking anxiolytic medications. Using semi-structured interviews and data from the Synaesthesia Battery and a colourpicker task, we characterise the phenomenological characteristics of their pre-loss synaesthesia, as well as the subsequent restoration of each subject's synaesthetic experiences (in the months post-trauma for AB, and after cessation of medication for CD). Even after years of suppression, the patterns of associations were highly consistent with those experienced pre-injury. The phenomenological experience of synaesthesia can, thus, like most conscious experiences, be modulated by pharmacologically diverse medications or head injury. However, the underlying neural substrates mediating specific synaesthetic pairings appear remarkably \"hard-wired\" and can persist over very long periods even under conditions that alter or completely suppress the conscious synaesthetic experience itself.

Neuroscience

The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing.\n\nTechnical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested.

Neuroscience

Selective activation of ganglion cells without axon bundles using epiretinal electrical stimulation

Epiretinal prostheses for treating blindness activate axon bundles, causing large, arc-shaped visual percepts that limit the quality of artificial vision. Improving the function of epiretinal prostheses therefore requires understanding and avoiding axon bundle activation. This paper introduces a method to detect axon bundle activation based on its electrical signature, and uses the method to test whether epiretinal stimulation can directly elicit spikes in individual retinal ganglion cells without activating nearby axon bundles. Combined electrical stimulation and recording from isolated primate retina were performed using a custom multi-electrode system (512 electrodes, 10 {micro}m diameter, 60 {micro}m pitch). Axon bundle signals were identified by their bi-directional propagation, speed, and increasing amplitude as a function of stimulation current. The threshold for bundle activation varied across electrodes and retinas, and was in the same range as the threshold for activating retinal ganglion cells near their somas. In the peripheral retina, 45% of electrodes that activated individual ganglion cells (17% of all electrodes) did so without activating bundles. This permitted selective activation of 21% of recorded ganglion cells (7% of all ganglion cells) over the array. In the central retina, 75% of electrodes that activated individual ganglion cells (16% of all electrodes) did so without activating bundles. The ability to selectively activate a subset of retinal ganglion cells without axon bundles suggests a possible novel architecture for future epiretinal prostheses.\n\nNew & NoteworthyLarge-scale multi-electrode recording and stimulation were used to test how selectively retinal ganglion cells can be electrically activated without activating axon bundles. A novel method was developed to identify axon activation based on its unique electrical signature, and used to find that a subset of ganglion cells can be activated at single-cell, single-spike resolution without producing bundle activity, in peripheral and central retina. These findings have implications for the development of advanced retinal prostheses.

Neuroscience

Functional consequences of pre- and postsynaptic expression of synaptic plasticity

Growing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this evidence and methods used to determine expression loci. Next, we discuss functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts 1) more reliable receptive fields and sensory perception, 2) rapid recovery of forgotten information (memory savings) and 3) reduced response latencies, compared to a model with postsynaptic expression only. Finally we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations.

Neuroscience

Neuroplasticity of language in left-hemisphere stroke: evidence linking subsecond electrophysiology and structural connections

Our understanding of neuroplasticity following stroke is predominantly based on neuroimaging measures that cannot address the subsecond neurodynamics of impaired language processing. We combined behavioral and electrophysiological measures and structural-connectivity estimates to characterize neuroplasticity underlying successful compensation of language abilities after left-hemispheric stroke. We recorded the electroencephalogram from patients with stroke lesions to the left temporal lobe and matched controls during context-driven word retrieval. Participants heard lead-in sentences that either constrained the final word (\"He locked the door with the\") or not (\"She walked in here with the\"). The last word was shown as a picture to be named. We conducted individual-participant analyses and focused on oscillatory power as a subsecond indicator of a brain region's functional neurophysiological computations. All participants named pictures faster following constrained than unconstrained sentences, except for two patients, who had extensive damage to the left temporal lobe. Left-lateralized alpha-beta oscillatory power decreased in controls pre-picture presentation for constrained relative to unconstrained contexts. In patients, the alpha-beta power decreases were observed with the same time course as in controls but were lateralized to the intact right hemisphere. The right lateralization depended on the probability of white-matter connections between the bilateral temporal lobes. The two patients who performed poorly behaviorally showed no alpha-beta power decreases. Our findings suggest that incorporating direct measures of neural activity into investigations of neuroplasticity can provide important neural markers to help predict language recovery, assess the progress of neurorehabilitation, and delineate targets for therapeutic neuromodulation.

Neuroscience

Homeostasis of columnar synchronization during cortical map formation

Synchronous spontaneous activity is critical for circuit development. A key open question is to what degree is this synchronization models adult activity or is specifically tuned for circuit development. To address this we used multi-electrode array recordings of spontaneous activity in non-anesthetized neonatal mice to quantify firing rates, synchronization, binary spike-vectors and population-coupling of single-units throughout the period of map formation. Consistent with the first hypothesis, adult-like network interactions are established during the period of retinal waves, before the onset of vision and normal inhibition, and are largely conserved throughout juvenile ages. Significant differences from mature properties were limited to initial topographic map formation, when synchronization was lower than expected by chance, suggesting active decoupling in early networks. These findings suggest that developmental activity models adult synchronization, and that there is remarkable homeostasis of network properties throughout development, despite massive changes in the drive and circuit basis of cortical activity.

Neuroscience

State-dependent modulation of functional connectivity in early blind individuals

Resting-state functional connectivity (RSFC) studies have highlighted how visual experience influences the brains functional architecture. Reduced RSFC coupling between occipital (visual) and temporal (auditory) regions has been reliably observed in early blind individuals (EB) at rest. In contrast, task-dependent activation studies have repeatedly demonstrated enhanced co-activation and connectivity of occipital and temporal regions during auditory processing in EB. To investigate this apparent discrepancy, the functional coupling between temporal and occipital networks at rest was directly compared to that of an auditory task in both EB and sighted controls (SC). Functional brain clusters shared across groups and cognitive states (rest and auditory task) were defined. In EBs, we observed higher occipito-temporal correlations in activity during the task than at rest. The reverse pattern was observed in SC. We also observed higher temporal variability of occipito-temporal RSFC in EB suggesting that occipital regions in this population may play a role of multiple demand system. Our study reveals how the connectivity profile of sighted and early blind people is differentially influenced by their cognitive state, bridging the gap between previous task-dependent and RSFC studies. Our results also highlight how inferring group-differences in functional brain architecture solely based on resting-state acquisition has to be considered with caution.\n\nHighlightsO_LIOccipito-temporal functional connectivity is modified by cognitive states.\nC_LIO_LIThis modulation is different in blind and sighted individuals.\nC_LIO_LIBlind participants have higher occipito-temporal temporal variability at rest.\nC_LIO_LIThe group difference in variability at rest explains the differences in modulation.\nC_LIO_LIInferring group differences with resting-state data should be subject to caution.\nC_LI

Neuroscience

Bursting deep dorsal horn neurons: the pharmacological target for the anti-spastic effects of Zolmitriptan?

In a recent publication, Thaweerattanasinp and colleagues employed an in vitro preparation and electrophysiology to investigate firing properties of deep dorsal horn neurons following spinal cord injury during NMDA or zolmitriptan application. Deep dorsal horn neurons were classified into bursting, simple or tonic, with bursting neurons showing NMDA and zolmitriptan sensitivity. Here, we discuss the findings in a methodological framework and propose future experiments of importance for translating the results into a physiological setting.

Neuroscience

Dynamic Brain Connectivity Patterns in Conscious and Unconscious Brain

Brain functional connectivity undergoes dynamic changes from the awake to unconscious states. However, how the dynamics of functional connectivity patterns are linked to consciousness at the behavioral level remains elusive. Here we acquired resting-state functional magnetic resonance imaging (rsfMRI) data during wakefulness and graded levels of consciousness in rats. Data were analyzed using a dynamic approach combining the sliding-window method and k-means clustering. Our results demonstrate that whole-brain networks contain several quasi-stable patterns that dynamically recurred from the awake state into anesthetized states. Remarkably, two brain connectivity states with distinct spatial similarity to the structure of anatomical connectivity were strongly biased toward high and low consciousness levels, respectively. These results provide compelling neuroimaging evidence linking the dynamics of whole-brain functional connectivity patterns and states of consciousness at the behavioral level.\n\nConflict of interestnone.

Neuroscience

Deriving robust biomarkers from multi-site resting-state data: An Autism-based example

Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such biomarkers is challenging for complex multi-faceted neuropathologies, such as autism spectrum disorders. Large multi-site datasets increase sample sizes to compensate for this complexity, at the cost of uncontrolled heterogeneity. This heterogeneity raises new challenges, akin to those face in realistic diagnostic applications. Here, we demonstrate the feasibility of inter-site classification of neuropsychiatric status, with an application to the Autism Brain Imaging Data Exchange (ABIDE) database, a large (N=871) multi-site autism dataset. For this purpose, we investigate pipelines that extract the most predictive biomarkers from the data. These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas. Connectomes are then compared across participants to learn patterns of connectivity that differentiate typical controls from individuals with autism. We predict this neuropsychiatric status for participants from the same acquisition sites or different, unseen, ones. Good choices of methods for the various steps of the pipeline lead to 67% prediction accuracy on the full ABIDE data, which is significantly better than previously reported results. We perform extensive validation on multiple subsets of the data defined by different inclusion criteria. These enables detailed analysis of the factors contributing to successful connectome-based prediction. First, prediction accuracy improves as we include more subjects, up to the maximum amount of subjects available. Second, the definition of functional brain areas is of paramount importance for biomarker discovery: brain areas extracted from large R-fMRI datasets outperform reference atlases in the classification tasks.

Neuroscience

The tubulin repertoire of C. elegans sensory neurons and its context dependent role in process outgrowth

Microtubules contribute to many cellular processes, including transport, signaling, and chromosome separation during cell division (Kapitein and Hoogenraad, 2015). They are comprised of {beta}-tubulin heterodimers arranged into linear protofilaments and assembled into tubes. Eukaryotes express multiple tubulin isoforms (Gogonea et al., 1999), and there has been a longstanding debate as to whether the isoforms are redundant or perform specialized roles as part of a tubulin code (Fulton and Simpson, 1976). Here, we use the well-characterized touch receptor neurons (TRNs) of Caenorhabditis elegans to investigate this question, through genetic dissection of process outgrowth both in vivo and in vitro. With single-cell RNA-seq, we compare transcription profiles for TRNs with those of two other sensory neurons, and present evidence that each sensory neuron expresses a distinct palette of tubulin genes. In the TRNs, we analyze process outgrowth and show that four tubulins (tba-1, tba-2, tbb-1, and tbb-2) function partially or fully redundantly, while two others (mec-7 and mec-12) perform specialized, context-dependent roles. Our findings support a model in which sensory neurons express overlapping subsets of tubulin genes whose functional redundancy varies between cell types and in vivo and in vitro contexts.\n\nHighlight SummaryMicrotubules contribute to key cellular processes and are composed of {beta}-tubulin heterodimers. Neurons in C. elegans express cell type-specific isoforms in addition to a shared repertoire and rely on tubulins for neurite outgrowth. Isoform function varies between in vivo and in vitro contexts.\n\nAbbreviations\n\nConflict of InterestThe authors declare no conflicting financial interests.

Neuroscience

Cortical dynamics of saccade-target selection during free-viewing of natural scenes

Natural visual behaviour entails explorative eye movements, saccades, that bring different parts of a visual scene into the central vision. The neural processes guiding the selection of saccade targets are still largely unknown. Therefore, in this study, we tracked with magnetoencephalography (MEG) cortical dynamics of viewers who were freely exploring novel natural scenes. Overall, the viewers were largely consistent in their gaze behaviour, especially if the scene contained any persons. We took a fresh approach to relate the eye-gaze data to the MEG signals by characterizing dynamic cortical representations by means of representational distance matrices. Specifically, we compared the representational distances between the stimuli in the evoked MEG responses with predictions based (1) on the low-level visual similarity of the stimuli (as visually more similar stimuli evoke more similar responses in early visual areas) and (2) on the eye-gaze data. At 50-75 ms after the scene onset, the similarity of the occipital MEG patterns correlated with the low-level visual similarity of the scenes, and already at 75-100 ms the visual features attracting the first saccades predicted the similarity of the right parieto-occipital MEG responses. Thereafter, at 100-125 ms, the landing positions of the upcoming saccades explained MEG responses. These results indicate that MEG signals contain signatures of the rapid processing of natural visual scenes as well as of the initiation of the first saccades, with the processing of the saccade target preceding the processing of the landing position of the upcoming saccade.\n\nSIGNIFICANCE STATEMENTHumans naturally make eye movements to bring different parts of a visual scene to the fovea where our visual acuity is the best. Tracking of eye gaze can reveal how we make inferences about the content of a scene by looking at different objects, or which visual cues automatically attract our attention and gaze. The brain dynamics governing natural gaze behaviour is still largely unknown. Here we suggest a novel approach to relate eye-tracking results with brain activity, as measured with magnetoencephalography (MEG), and demonstrate signatures of natural gaze behaviour in the MEG data already before the eye movements occur.

Neuroscience

Transformation of head-direction signal into spatial code

Head direction (HD), boundary vector, grid and place cells in the entorhinal-hippocampal system form the brains navigational system that allows to identify the animals current location. How the functions of these specialized neuron types are acquired and how their computations relate to each other remain to be understood. Firing patterns of HD neurons are influenced by the ambulatory constraints imposed upon the animal by the boundaries of the explored environment. In the post-subiculum, the main cortical stage of HD signal processing, the amount of spatial information is increased compared to their driving thalamic inputs by the combination of the HD signal with other sensory modalities. In addition, HD signal directly reach the hippocampus, likely conveyed from the thalamus. These findings demonstrate how the HD and other sensory information can be transduced into a spatial code in parallel, distributed pathways.

Neuroscience

Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding

Monitoring and updating temporal predictions are critical abilities for adaptive behavior. Here, we investigated whether neural oscillations are related to violation and updating of temporal predictions. Human participants performed an experiment in which they had to generate a target at an expected time point, by pressing a button while taking into account a variable delay between the act and the stimulus occurrence. Our behavioral results showed that participants quickly adapted their temporal predictions in face of an error. Concurrent electrophysiological (EEG) data showed that temporal errors elicited markers that are classically related to error coding. Furthermore, intertrial phase coherence of frontal theta oscillations was modulated by error magnitude, possibly indexing the degree of surprise. Finally, we found that delta phase at stimulus onset was correlated with future behavioral adjustments. Together, our findings suggest that low frequency oscillations play a key role in monitoring and in updating temporal predictions.

Neuroscience

Heterozygous mutation to Chd8 causes macrocephaly and widespread alteration of neurodevelopmental transcriptional networks in mouse

The chromatin remodeling gene CHD8 represents a central node in early neurodevelopmental gene networks implicated in autism. We examined the impact of heterozygous germline Chd8 mutation on neurodevelopment in mice. Network analysis of neurodevelopmental gene expression revealed subtle yet strongly significant widespread transcriptional changes in Chd8+/- mice across autism-relevant networks from neurogenesis to synapse function. Chd8+/- expression signatures included enrichment of RNA processing genes and a Chd8-regulated module featuring altered transcription of chromatin remodeling, splicing, and cell cycle genes. Chd8+/- mice exhibited increased proliferation during brain development and neonatal increase in cortical length and volume. Structural MRI confirmed regional brain volume increase in adult Chd8+/- mice, consistent with clinical macrocephaly. Adult Chd8+/- mice displayed normal social interactions, and repetitive behaviors were not evident. Our results show that Chd8+/- mice exhibit neurodevelopmental changes paralleling CHD8+/- humans and show that Chd8 is a global genomic regulator of pathways disrupted in neurodevelopmental disorders.

Neuroscience

Language-selective brain regions track linguistic input more closely than domain-general regions

Language comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by non-linguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this \"Multiple Demand (MD)\" network scales with comprehension difficulty, but also with cognitive effort across a wide range of non-linguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Critically, given that each network is sensitive to some linguistic features, prior research has assumed - implicitly or explicitly - that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time-courses in each network across different people listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks.\n\nSignificance StatementLanguage comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized \"core language network\", whereas domain-general mechanisms are implemented in the bilateral \"Multiple Demand (MD)\" network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking.

Neuroscience

A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI.

Accelerated functional Magnetic Resonance Imaging (fMRI) with multiband sequences is now relatively widespread. These sequences can be used to dramatically reduce the repetition time (TR) and produce a time-series sampled at a higher temporal resolution. We tested the effects of higher temporal resolutions for fMRI on statistical outcome measures in a comprehensive manner on two different MRI scanner platforms. Experiment 1 tested a range of acceleration factors (1-6) against a standard EPI sequence on a single composite task that maps a number of basic sensory, motor, and cognitive networks. Experiment 2 compared the standard sequence with acceleration factors of 2 and 3 on both resting-state and two task paradigms (an N-back task, and faces/places task), with a number of different analysis approaches. Results from experiment 1 showed modest but relatively inconsistent effects of the higher sampling rate on statistical outcome measures. Experiment 2 showed strong benefits of the multiband sequences on results derived from resting-state data, but more varied effects on results from the task paradigms. Notably, the multiband sequences were superior when Multi-Voxel Pattern Analysis was used to interrogate the faces/places data, but showed less benefit in conventional General Linear Model analyses of the same data. In general, ROI-derived measures of statistical effects benefitted relatively little from higher sampling resolution, with decrements even seen in one task (N-back). Across both experiments, results from the two scanner platforms were broadly comparable. The statistical benefits of high temporal resolution fMRI with multiband sequences may therefore depend on a number of factors, including the nature of the investigation (resting-state vs. task-based), the experimental design, the particular statistical outcome measure, and the type of analysis used. Higher sampling rates in fMRI are not a panacea, and it is recommended that researchers use multiband acquisition sequences conservatively.

Neuroscience

Neural correlates of early sound encoding and their relationship to speech in noise perception

Speech-in-noise (SIN) perception is a complex cognitive skill that affects social, vocational, and educational activities. Poor SIN ability particularly affects young and elderly populations, yet varies considerably even among healthy young adults with normal hearing. Although SIN skills are known to be influenced by top-down processes that can selectively enhance lower-level sound representations, the complementary role and of feed-forward mechanisms and their relationship to musical training is poorly understood. Using a paradigm that eliminates the main top-down factors that have been implicated in SIN performance, we aimed to better understand how robust encoding of periodicity in the auditory system (as measured by the frequency-following response) contributes to SIN perception. Using magnetoencephalograpy, we found that the strength of encoding at the fundamental frequency in the brainstem, thalamus, and cortex is correlated with SIN accuracy, as was the amplitude of the slower cortical P2 wave, and these enhancements were related to the extent and timing of musicianship. These results are consistent with the hypothesis that basic feed-forward sound encoding affects SIN perception by providing better information to later processing stages, and that modifying this process may be one mechanism through which musical training might enhance the auditory networks that subserve both musical and language functions.\n\nHighlights- Enhancements in periodic sound encoding are correlated with speech-in-noise ability\n- This effect is observed in the absence of contextual cues and task demands\n- Better encoding is observed throughout the auditory system and is right-lateralized\n- Stronger encoding is related to stronger subsequent secondary auditory cortex activity\n- Musicianship is related to both speech-in-noise perception and enhanced MEG signals

Neuroscience