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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.151969v1?rss=1

    Authors: Franca, A. S. C., Borgegius, N., Cohen, M.

    Abstract:
    Novelty detection is a core feature of behavioral adaptation, and involves cascades of neuronal responses, from initial evaluation of the stimulus to the encoding of new representations, resulting in the behavioral ability to respond to an unexpected input (Kafkas and Montaldi, 2018; van Kesteren et al., 2012). In the past decade, a new important novelty detection feature, beta2 (~20 to 30 Hz) oscillations, has been described in the hippocampus. However, the interactions between beta2 and the hippocampal network is unknown, as well as the role (or even the presence) of beta2 in other areas involved with novelty detection. We used behavioral tasks that modulate novelty in combination with multisite local field potential (LFP) recordings (acquired by custom-designed and self-made electrode arrays) targeting the CA1 region of the hippocampus, parietal cortex and mid-prefrontal cortex in mice, to describe the oscillatory dynamics among the regions involved with novelty detection processing. We found that transient beta2 power increases were observed only during interaction with novel contexts and objects, but not with familiar contexts and objects. Robust theta-gamma cross-frequency coupling was observed during exploration of novel environments. Surprisingly, bursts of beta2 power had strong coupling with the phase of delta-range oscillations. Finally, the parietal and mid-frontal cortices had strong coherence with the hippocampus in both theta and beta2 during novelty exploration. These results highlight the importance of beta2 oscillations in a larger hippocampal-cortical circuit, suggesting that beta2 is a mechanism for detecting and modulating behavioral adaptation to novelty.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.151605v1?rss=1

    Authors: Kossowsky, H., Farajian, M., Milstein, A., Nisky, I.

    Abstract:
    When interacting with objects, haptic information is used to create perception of the object stiffness and to regulate grip force. Studies have shown that introducing noise into sensory inputs can create uncertainty in those sensory channels, yet a method of creating haptic uncertainty without distorting the haptic information has yet to be discovered. Toward this end, we investigated the effect of between-probe haptic variability on stiffness perception and grip force control. In a stiffness discrimination task, we added different levels of between-probe haptic variability by changing the stiffness of the force fields between consecutive probes. Unlike the low and high variability levels, the medium level created perceptual haptic uncertainty. Additionally, we ascertained that participants calculated a weighted average of the different stiffness levels applied by a given force field. Examining participants' grip force showed that the modulation of the grip force with the load force decreased with repeated exposure to the force field, whereas no change in the baseline was observed. These results were observed in all the variability levels and suggest that between-probe variability created haptic uncertainty that affected the grip force control. Overall, the medium variability level can be effective in inducing uncertainty in both perception and action.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.151795v1?rss=1

    Authors: Roeth, K., Shao, S., Gjorgjieva, J.

    Abstract:
    Sensory organs transmit information to downstream brain circuits using a neural code comprised of spikes from multiple neurons. According to the prominent efficient coding framework, the properties of sensory populations have evolved to encode maximum information about stimuli given biophysical constraints. How information coding depends on the way sensory signals from multiple channels converge downstream is still unknown, especially in the presence of noise which corrupts the signal at different points along the pathway. Here, we calculated the optimal information transfer of a population of nonlinear neurons under two scenarios. First, a lumped-coding channel where the information from different inputs converges to a single channel, thus reducing the number of neurons. Second, an independent-coding channel when different inputs contribute independent information without convergence. In each case, we investigated information loss when the sensory signal was corrupted by two sources of noise. We determined critical noise levels at which the optimal number of distinct thresholds of individual neurons in the population changes. Comparing our system to classical physical systems, these changes correspond to first- or second-order phase transitions for the lumped- or the independent-coding channel, respectively. We relate our theoretical predictions to coding in a population of auditory nerve fibers recorded experimentally, and find signatures of efficient coding. Our results yield important insights into the diverse coding strategies used by neural populations to optimally integrate sensory stimuli in the presence of distinct sources of noise.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.151993v1?rss=1

    Authors: Saska, D., Pichler, P., Qian, C., Pegasiou, C., Buckley, C. L., Lagnado, L.

    Abstract:
    Selective Plane Illumination Microscopy (SPIM) is a fluorescence imaging technique that allows volumetric imaging at high spatio-temporal resolution to monitor neural activity in live organisms such as larval zebrafish. A major challenge in the construction of a custom SPIM microscope is the control and synchronization of the various hardware components. Here we present a control toolset, SPIM, built around the open-source MicroManager platform that has already been widely adopted for the control of microscopy hardware. Installation of SPIM is relatively straightforward, involving a single C++ executable and a Java-based extension to Micro-Manager. Imaging protocols are defined through the SPIM extension to Micro-Manager. The extension then synchronizes the camera shutter with the galvanometer mirrors to create a light-sheet that is scanned in the z-dimension, in synchrony with the imaging objective, to produce volumetric recordings. A key advantage of SPIM is that a series of calibration procedures optimizes acquisition for a given set-up making it relatively independent of the optical design of the microscope, or the hardware used to build it. Two laser illumination arms can be used while also allowing for the introduction of illumination masks. SPIM allows imaging of calcium activity throughout the brain of larval zebrafish at rates of 100 planes per second with single cell resolution as well as slower imaging to reconstruct cell populations, for example, in the cleared brains of mice.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.142554v1?rss=1

    Authors: Di Liberto, G., Nie, J., Yeaton, J., Khalighinejad, B., Shamma, S., Mesgarani, N.

    Abstract:
    Acquiring a new language requires a simultaneous and gradual learning of multiple levels of linguistic attributes. Here, we investigated how this process changes the neural encoding of natural speech by assessing the encoding of the linguistic feature hierarchy in second-language listeners. Electroencephalography (EEG) signals were recorded from native English and native Mandarin speakers with varied English proficiency as they listened to English stories. The neural encoding of acoustic, phonemic, phonotactic, and semantic features was measured in individual participants. We found a progressive convergence of linguistic feature representation in native and nonnative listeners with increased proficiency, which enabled accurate decoding of language proficiency. At the same time, we found distinct neural signatures in native and nonnative listeners that persisted even in the most proficient listeners. This detailed view advances our understanding of the cortical processing of linguistic information in second-language learners and provides an objective measure of language proficiency.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.14.151118v1?rss=1

    Authors: Arana, O. L. G., Palmer, H., Dannhauer, M., Hile, C., Liu, S., Hamdan, R., Brito, A., Cabeza, R., Davis, S. W., Peterchev, A. V., Sommer, M. A., Appelbaum, L.

    Abstract:
    Despite the widespread use of transcranial magnetic stimulation (TMS) in research and clinical care, the underlying mechanisms-of-actions that mediate modulatory effects remain poorly understood. To fill this gap, we studied dose-response functions of TMS for modulation of visual processing. Our approach combined electroencephalography (EEG) with application of single pulse TMS to visual cortex as participants performed a motion perception task. During participants' first visit, motion coherence thresholds, 64-channel visual evoked potentials (VEPs), and TMS resting motor thresholds (RMT) were measured. In second and third visits, single pulse TMS was delivered 30 ms before the onset of motion or at the onset latency of the N2 VEP component derived from the first session. TMS was delivered at 0%, 80%, 100%, or 120% of RMT over the site of N2 peak activity, or at 120% over vertex. Behavioral results demonstrated a significant main effect of TMS timing on accuracy, with better performance when TMS was applied at N2-Onset timing versus Pre-Onset, as well as a significant interaction, indicating that 80% intensity produced higher accuracy than other conditions. TMS effects on VEPs showed reduced amplitudes in the 80% Pre-Onset condition, an increase for the 120% N2-Onset condition, and monotonic amplitude scaling with stimulation intensity. The N2 component was not affected by TMS. These findings reveal dose-response relationships between intensity and timing of TMS on visual perception and electrophysiological brain activity, generally indicating greater facilitation at stimulation intensities below RMT.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.148114v1?rss=1

    Authors: Bos, H., Oswald, A.-M., Doiron, B.

    Abstract:
    Synaptic inhibition is the mechanistic backbone of a suite of cortical functions, not the least of which is maintaining overall network stability as well as modulating neuronal gain. Past cortical models have assumed simplified recurrent networks in which all inhibitory neurons are lumped into a single effective pool. In such models the mechanics of inhibitory stabilization and gain control are tightly linked in opposition to one another -- meaning high gain coincides with low stability and vice versa. This tethering of stability and response gain restricts the possible operative regimes of the network. However, it is now well known that cortical inhibition is very diverse, with molecularly distinguished cell classes having distinct positions within the cortical circuit. In this study, we analyze populations of spiking neuron models and associated mean-field theories capturing circuits with pyramidal neurons as well as parvalbumin (PV) and somatostatin (SOM) expressing interneurons. Our study outlines arguments for a division of labor within the full cortical circuit where PV interneurons are ideally positioned to stabilize network activity, whereas SOM interneurons serve to modulate pyramidal cell gain. This segregation of inhibitory function supports stable cortical dynamics over a large range of modulation states. Our study offers a blueprint for how to relate the circuit structure of cortical networks with diverse cell types to the underlying population dynamics and stimulus response.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.152173v1?rss=1

    Authors: Jepma, M., Schaaf, J. V., Visser, I., Huizenga, H.

    Abstract:
    Healthy adults flexibly adapt their learning strategies to ongoing changes in uncertainty, a key feature of adaptive behaviour. However, the developmental trajectory of this ability is yet unknown, as developmental studies have not incorporated trial-to-trial variation in uncertainty in their analyses or models. To address this issue, we compared adolescents' and adults' trial-to-trial dynamics of uncertainty, learning rate, and exploration in two tasks that assess learning in noisy but otherwise stable environments. In an estimation task--which provides direct indices of trial-specific learning rate--both age groups reduced their learning rate over time, as self-reported uncertainty decreased. Accordingly, the estimation data in both groups was better explained by a Bayesian model with dynamic learning rate (Kalman filter) than by conventional reinforcement-learning models. Furthermore, adolescents' learning rates asymptoted at a higher level, reflecting an over-weighting of the most recent outcome, and the estimated Kalman-filter parameters suggested that this was due to an overestimation of environmental volatility. In a choice task, both age groups became more likely to choose the higher-valued option over time, but this increase in choice accuracy was smaller in the adolescents. In contrast to the estimation task, we found no evidence for a Bayesian expectation-updating process in the choice task, suggesting that estimation and choice tasks engage different learning processes. However, our modeling results of the choice task suggested that both age groups reduced their degree of exploration over time, and that the adolescents explored overall more than the adults. Finally, age-related differences in exploration parameters from fits to the choice data were mediated by participants' volatility parameter from fits to the estimation data. Together, these results suggest that adolescents overestimate the rate of environmental change, resulting in elevated learning rates and increased exploration, which may help understand developmental changes in learning and decision-making.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.151811v1?rss=1

    Authors: Osako, Y., Ohnuki, T., Manabe, H., Sakurai, Y., Hirokawa, J.

    Abstract:
    During visual detection tasks, subjects sometimes fail to respond to identical visual stimuli even when the stimuli are registered on their retinas. It is widely assumed that variability in detection performance is attributed to the fidelity of the visual responses in visual cortical areas, which could be modulated by fluctuations of subjective internal states such as vigilance, attention, and reward experiences. However, it is not clear what neural ensembles represent such different internal states. Here, we utilized a behavioral task that differentiated distinct perceptual states to identical stimuli, and analyzed neuronal responses simultaneously recorded from both primary visual cortex (V1) and posterior parietal cortex (PPC) during the task. We found that population activity differed across choice types with the major contribution of non-sensory neurons, rather than visually-responsive neurons, in V1 as well as PPC. The distinct population-level activity in V1, but not PPC, was restricted within the stimulus presentation epoch, which was distinguished from pre-stimulus background activity and was supported by near-zero noise correlation. These results indicate a major contribution of non-sensory neurons in V1 for population-level computation that enables behavioral responses from visual information.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.150201v1?rss=1

    Authors: Beyreli, I., Karakahya, O., Cicek, A. E.

    Abstract:
    Autism Spectrum Disorder (ASD) and Intellectual Disability (ID) are comorbid neurodevelopmental disorders with complex genetic architectures. Despite large-scale sequencing studies only a fraction of the risk genes were identified for both. Here, we present a novel network-based gene risk prioritization algorithm named DeepND that performs cross-disorder analysis to improve prediction power by exploiting the comorbidity of ASD and ID via multitask learning. Our model leverages information from gene co-expression networks that model human brain development using graph convolutional neural networks and learns which spatio-temporal neurovelopmental windows are important for disorder etiologies. We show that our approach substantially improves the state-of-the-art prediction power in both single-disorder and cross-disorder settings. DeepND identifies mediodorsal thalamus and cerebral cortex brain region and infancy to childhood period as the highest neurodevelopmental risk window for both ASD and ID. We observe that both disorders are enriched in transcription regulators. Despite tight regulatory links in between ASD risk genes, such is lacking across ASD and ID risk genes or within ID risk genes. Finally, we investigate frequent ASD and ID associated copy number variation regions and confident false findings to suggest several novel susceptibility gene candidates. DeepND can be generalized to analyze any combinations of comorbid disorders and is released at http://github.com/ciceklab/deepnd.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.150342v1?rss=1

    Authors: Pellegrini, M., Zoghi, M., Jaberzadeh, S.

    Abstract:
    High variability between individuals (i.e. inter-individual variability) in response to transcranial direct current stimulation (tDCS) has become a commonly reported issue in the tDCS literature in recent years. Inherent genetic differences between individuals has been proposed as a contributing factor to observed response variability. This study investigated whether tDCS inter-individual variability was genetically mediated. A large sample-size of sixty-one healthy males received cathodal-tDCS (c-tDCS) and sham-tDCS, of the primary motor cortex at 1mA and 10-minutes via 6x4cm active and 7x5cm return electrodes. Corticospinal excitability (CSE) was assessed via twenty-five single-pulse transcranial magnetic stimulation motor evoked potentials (MEP). Intracortical inhibition (ICI) was assessed via twenty-five 3ms inter-stimulus interval (ISI) paired-pulse MEPs, known as short-interval intracortical inhibition (SICI). Intracortical facilitation (ICF) was assessed via twenty-five 10ms ISI paired-pulse MEPs. Gene variants encoding for excitatory and inhibitory neuroreceptors were determined via saliva samples. Pre-determined thresholds and statistical cluster analyses were used to subgroup individuals. Two distinct subgroups were identified, Responders reducing CSE following c-tDCS and Non-Responders showing no reduction or even increase in CSE. Differences in CSE between responders and non-responders following c-tDCS were not explained by changes in SICI or ICF. No significant relationships were reported between gene variants and inter-individual variability to c-tDCS suggesting the chosen gene variants did not influence the activity of the neuroreceptors involved in eliciting changes in CSE in responders following c-tDCS. In this largest c-tDCS study of its kind, novel insights were reported into the contribution genetic factors may play in observed inter-individual variability to c-tDCS.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.150029v1?rss=1

    Authors: Sonobe, Y., Aburas, J., Islam, P., Gendron, T. F., Brown, A. E. X., Roos, R. P., Kratsios, P.

    Abstract:
    A hexanucleotide repeat expansion GGGGCC in the noncoding region of C9orf72 is the most common cause of inherited amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Potentially toxic dipeptide repeats (DPRs) are synthesized from the GGGGCC sequence via repeat associated non-AUG (RAN) translation. We developed C. elegans models that express, either ubiquitously or exclusively in neurons, a transgene with 75 GGGGCC repeats flanked by intronic C9orf72 sequence. The worms generate DPRs (poly-glycine-alanine [poly-GA], poly-glycine-proline [poly-GP]) and display neurodegeneration, locomotor and lifespan defects. Mutation of a non-canonical translation-initiating codon (CUG) upstream of the repeats blocked poly-GA production and ameliorated disease, suggesting poly-GA is pathogenic. Importantly, eukaryotic translation initiation factor 2D (eif-2D/eIF2D) was necessary for RAN translation. Genetic removal of eif-2D increased lifespan in both C. elegans models. In vitro findings in human cells demonstrated a conserved role for eif-2D/eIF2D in RAN translation that could be exploited for ALS and FTD therapy.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.12.149484v1?rss=1

    Authors: Saito, K., Sun, H., Tierney, A. T.

    Abstract:
    In this brief report, we examined the test-retest reliability of our in-house explicit auditory processing measures in the context of 30 L1 and L2 English users. The participants took the same test battery which consisted of a total of four discrimination tasks (encoding acoustic details of formant, pitch, duration, and rise time) and two reproduction tasks (repeating novel melodic and rhythmic patterns) at Days 1 and 2. According to the results, the participants' initial and second test scores demonstrated medium-to-large associations (r = .562-.907). The results suggest that the tests can tap into various dimensions of individuals' auditory acuity and integration abilities.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.152108v1?rss=1

    Authors: Ezra, M., Garry, P., Rowland, M., Mitsis, G. D., Pattinson, K.

    Abstract:
    Aneurysmal subarachnoid haemorrhage (SAH) is a devastating subset of stroke. One of the major determinates of morbidity is the development of delayed cerebral ischemia (DCI). Disruption of the nitric oxide (NO) pathway and consequently the control of cerebral blood flow (CBF), known as cerebral autoregulation, is believed to play a role in its pathophysiology. Through the pharmacological manipulation of in vivo NO levels using an exogenous NO donor we sought to explore this relationship. Phase synchronisation index (PSI), an expression of the interdependence between CBF and arterial blood pressure (ABP) and thus cerebral autoregulation, was calculated before and during sodium nitrite administration in 10 high-grade SAH patients acutely post-rupture. In patients that did not develop DCI, there was a significant increase in PSI around 0.1 Hz during the administration of sodium nitrite (33%; p-value 0.006). In patients that developed DCI, PSI did not change significantly. Synchronisation between ABP and CBF at 0.1 Hz has been proposed as a mechanism by which organ perfusion is maintained, during periods of physiological stress. These findings suggest that functional NO depletion plays a role in impaired cerebral autoregulation during EBI, but the development of DCI may have a distinct pathophysiological aetiology.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.14.151258v1?rss=1

    Authors: Takeo, Y. H., Shuster, A., Jiang, L., Hu, M., Luginbuhl, D., Rulicke, T., Contreras, X., Hippenmeyer, S., Wagner, M., Ganguli, S., Luo, L.

    Abstract:
    The synaptotrophic hypothesis posits that synapse formation stabilizes dendritic branches, yet this hypothesis has not been causally tested in vivo in the mammalian brain. Presynaptic ligand cerebellin-1 (Cbln1) and postsynaptic receptor GluD2 mediate synaptogenesis between granule cells and Purkinje cells in the molecular layer of the cerebellar cortex. Here we show that sparse but not global knockout of GluD2 causes under-elaboration of Purkinje cell dendrites in the deep molecular layer and overelaboration in the superficial molecular layer. Developmental, overexpression, structure-function, and genetic epistasis analyses indicate that dendrite morphogenesis defects result from competitive synaptogenesis in a Cbln1/GluD2-dependent manner. A generative model of dendritic growth based on competitive synaptogenesis largely recapitulates GluD2 sparse and global knockout phenotypes. Our results support the synaptotrophic hypothesis at initial stages of dendrite development, suggest a second mode in which cumulative synapse formation inhibits further dendrite growth, and highlight the importance of competition in dendrite morphogenesis.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.15.148338v1?rss=1

    Authors: Calaim, N., Dehmelt, F. A., Goncalves, P. J., Machens, C. K.

    Abstract:
    The interactions of large groups of spiking neurons have been difficult to understand or visualise. Using simple geometric pictures, we here illustrate the spike-by-spike dynamics of networks based on efficient spike coding, and we highlight the conditions under which they can preserve their function against various perturbations. We show that their dynamics are confined to a small geometric object, a 'convex polytope', in an abstract error space. Changes in network parameters (such as number of neurons, dimensionality of the inputs, firing thresholds, synaptic weights, or transmission delays) can all be understood as deformations of this polytope. Using these insights, we show that the core functionality of these network models, just like their biological counterparts, is preserved as long as perturbations do not destroy the shape of the geometric object. We suggest that this single principle---efficient spike coding---may be key to understanding the robustness of neural systems at the circuit level.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.150060v1?rss=1

    Authors: Pompilus, M., Colon-Perez, L. M., Grudny, M. M., Febo, M.

    Abstract:
    Stimuli presented at short temporal delays before functional magnetic resonance imaging (fMRI) can have a robust impact on the organization of synchronous activity in resting state networks. This presents an opportunity to investigate how sensory, affective and cognitive stimuli alter functional connectivity in rodent models. Here, we assessed the effect of a familiar contextual stimulus presented 10 minutes prior to sedation for imaging on functional connectivity. A subset of animals were co-presented with an unfamiliar social stimulus in the same environment to further investigate the effect of familiarity on network topology. Female and male rats were imaged at 11.1 Tesla and graph theory analysis was applied to matrices generated from seed-based functional connectivity data sets with 144 nodes and 10,296 edge weights. Our results show an unconventional network topology in response to the familiar (context) but not the unfamiliar (social) stimulus. The familiar stimulus strongly reduced network strength, global efficiency, and altered the location of the highest eigenvector centrality nodes from cortex to the hypothalamus. Alterations were not widespread across topological properties, as we did not observe changes in modular organization, nodal cartographic assignments, assortative mixing, rich club organization, and network resilience. The results suggest that experiential factors, perhaps involving associative or episodic memory, can exert a dramatic effect on functional network strength and efficiency when presented at a short temporal delay before imaging.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.149658v1?rss=1

    Authors: Cropley, V., Tian, Y., Fernando, K., Mansour, S., Pantelis, C., Cocchi, L., Zalesky, A.

    Abstract:
    Background: This study aims to investigate whether dimensional constructs of psychopathology relate to advanced, attenuated or normal patterns of brain development, and to determine whether these constructs share common neurodevelopmental profiles. Methods: Psychiatric symptom ratings from 9312 youths (8-21 years) were parsed into 7 independent dimensions of clinical psychopathology representing conduct, anxiety, obsessive-compulsive, attention, depression, bipolar, and psychosis symptoms. Using a subset of this cohort with structural MRI (n=1313), a normative model of brain morphology was established and the model was then applied to predict the age of youth with clinical symptoms. We investigated whether the deviation of brain-predicted age from true chronological age, called the brain age gap, explained individual variation in each psychopathology dimension. Results: Individual variation in the brain age gap significantly associated with clinical dimensions representing psychosis (t=3.16, p=0.0016), obsessive-compulsive symptoms (t=2.5, p=0.01), and general psychopathology (t=4.08, p<0.0001). Greater symptom severity along these dimensions was associated with brain morphology that appeared older than expected for typically developing youth of the same age. Psychopathology dimensions clustered into two modules based on shared brain loci where putative accelerated neurodevelopment was most prominent. Patterns of morphological development were accelerated in frontal cortices for depression, psychosis and conduct symptoms (Module I), whereas acceleration was most evident in subcortex and insula for the remaining dimensions (Module II). Conclusions: Our findings suggest that advanced brain development, particularly in frontal cortex and subcortical nuclei, underpins clinical psychosis and obsessive-compulsive symptoms in youth. Psychopathology dimensions share common neural substrates, despite representing clinically independent symptom profiles.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.13.150151v1?rss=1

    Authors: Smith, W. C., Borba, C., Schwennicke, S., Kourakis, M. J.

    Abstract:
    Ciona larvae have two distinct visuomotor behaviors - a looming shadow response and negative phototaxis. These are mediated by separate neural pathways that initiate from different clusters of photoreceptors. We report that input from both pathways is processed to generate fold-change detection (FCD) outputs - making the behavioral outputs reflective of relative changes in input, not absolute input values. Visual inputs from both pathways project first to the posterior brain vesicle (pBV). We find that the pBV shares hallmarks with the vertebrate midbrain optic tectum, including its anatomy, connectivity, function and gene expression - despite previous speculation that Ciona lacks a midbrain. The connectivity and properties (excitatory or inhibitory) of pBV interneurons conform to known FCD circuits, but with different circuit architectures for the two pathways. The negative phototaxis circuit forms an incoherent feedforward loop that involves interconnecting cholinergic and GABAergic interneurons. The looming shadow circuit uses the same cholinergic and GABAergic interneurons, but with different synaptic inputs to create a nonlinear integral feedback loop. Consequently, the two FCD circuits generate different behavioral profiles, with the negative phototaxis circuit resulting in a power-function relationship of behavioral output versus fold-change, while in the dimming response this relationship is linear.

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  • Link to bioRxiv paper:
    http://biorxiv.org/cgi/content/short/2020.06.12.149203v1?rss=1

    Authors: Buser, N. J., Madan, C. R., Hanson, J.

    Abstract:
    On-going, large-scale neuroimaging initiatives have produced many MRI datasets with hundreds, even thousands, of individual participants and scans. These databases can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important factors. While volumetric quantification of brain structures can be completed by expert hand-tracing, automated segmentations are becoming the only truly tractable approach for particularly large datasets. Here, we assessed the spatial and numerical reliability for newly-deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer. In a sample of participants with repeated structural imaging scans (N=118), we found numerical reliability (as assessed by intraclass correlations) to be generally high, with 92% of the subregions having ICCs above 0.90 and the remainder still above 0.75. Spatial reliability was lower with only 11% of regions having Dice coefficients above 0.90, but 70% with Dice coefficients above 0.75. Of particular concern, three regions, the hippocampal fissure, the anterior amygdaloid area, and the paralaminar nucleus, had only moderate spatial reliability (0.50-0.75). We also examined correlations between spatial reliability and person-level factors (e.g., age, inter-scan interval, and difference in image quality). For these factors, interscan interval and image quality were related to variations in spatial reliability. Examined collectively, our work suggests strong numerical and spatial reliability for the majority of hippocampal and amygdala subdivisions; however, caution should be exercised for a few regions with more variable reliability.

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