ResearchPad - neuroscience https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Gain of channel function and modified gating properties in TRPM3 mutants causing intellectual disability and epilepsy]]> https://www.researchpad.co/article/elastic_article_13328 Developmental and epileptic encephalopathies (DEE) are a heterogeneous group of disorders characterized by epilepsy with comorbid intellectual disability. Recently, two de novo heterozygous mutations in the gene encoding TRPM3, a calcium permeable ion channel, were identified as the cause of DEE in eight probands, but the functional consequences of the mutations remained elusive. Here we demonstrate that both mutations (V990M and P1090Q) have distinct effects on TRPM3 gating, including increased basal activity, higher sensitivity to stimulation by the endogenous neurosteroid pregnenolone sulfate (PS) and heat, and altered response to ligand modulation. Most strikingly, the V990M mutation affected the gating of the non-canonical pore of TRPM3, resulting in large inward cation currents via the voltage sensor domain in response to PS stimulation. Taken together, these data indicate that the two DEE mutations in TRPM3 result in a profound gain of channel function, which may lie at the basis of epileptic activity and neurodevelopmental symptoms in the patients.

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<![CDATA[Distinct spatiotemporal mechanisms underlie extra-classical receptive field modulation in macaque V1 microcircuits]]> https://www.researchpad.co/article/elastic_article_13324 Complex scene perception depends upon the interaction between signals from the classical receptive field (CRF) and the extra-classical receptive field (eCRF) in primary visual cortex (V1) neurons. Although much is known about V1 eCRF properties, we do not yet know how the underlying mechanisms map onto the cortical microcircuit. We probed the spatio-temporal dynamics of eCRF modulation using a reverse correlation paradigm, and found three principal eCRF mechanisms: tuned-facilitation, untuned-suppression, and tuned-suppression. Each mechanism had a distinct timing and spatial profile. Laminar analysis showed that the timing, orientation-tuning, and strength of eCRF mechanisms had distinct signatures within magnocellular and parvocellular processing streams in the V1 microcircuit. The existence of multiple eCRF mechanisms provides new insights into how V1 responds to spatial context. Modeling revealed that the differences in timing and scale of these mechanisms predicted distinct patterns of net modulation, reconciling many previous disparate physiological and psychophysical findings.

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<![CDATA[Light Up the Brain: The Application of Optogenetics in Cell-Type Specific Dissection of Mouse Brain Circuits]]> https://www.researchpad.co/article/elastic_article_13105 The exquisite intricacies of neural circuits are fundamental to an animal’s diverse and complex repertoire of sensory and motor functions. The ability to precisely map neural circuits and to selectively manipulate neural activity is critical to understanding brain function and has, therefore been a long-standing goal for neuroscientists. The recent development of optogenetic tools, combined with transgenic mouse lines, has endowed us with unprecedented spatiotemporal precision in circuit analysis. These advances greatly expand the scope of tractable experimental investigations. Here, in the first half of the review, we will present applications of optogenetics in identifying connectivity between different local neuronal cell types and of long-range projections with both in vitro and in vivo methods. We will then discuss how these tools can be used to reveal the functional roles of these cell-type specific connections in governing sensory information processing, and learning and memory in the visual cortex, somatosensory cortex, and motor cortex. Finally, we will discuss the prospect of new optogenetic tools and how their application can further advance modern neuroscience. In summary, this review serves as a primer to exemplify how optogenetics can be used in sophisticated modern circuit analyses at the levels of synapses, cells, network connectivity and behaviors.

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<![CDATA[Regeneration Through <i>in vivo</i> Cell Fate Reprogramming for Neural Repair]]> https://www.researchpad.co/article/elastic_article_13097 The adult mammalian central nervous system (CNS) has very limited regenerative capacity upon neural injuries or under degenerative conditions. In recent years, however, significant progress has been made on in vivo cell fate reprogramming for neural regeneration. Resident glial cells can be reprogrammed into neuronal progenitors and mature neurons in the CNS of adult mammals. In this review article, we briefly summarize the current knowledge on innate adult neurogenesis under pathological conditions and then focus on induced neurogenesis through cell fate reprogramming. We discuss how the reprogramming process can be regulated and raise critical issues requiring careful considerations to move the field forward. With emerging evidence, we envision that fate reprogramming-based regenerative medicine will have a great potential for treating neurological conditions such as brain injury, spinal cord injury (SCI), Alzheimer’s disease (AD), Parkinson’s disease (PD), and retinopathy.

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<![CDATA[Speech-Induced Suppression for Delayed Auditory Feedback in Adults Who Do and Do Not Stutter]]> https://www.researchpad.co/article/elastic_article_13085 Speech-induced suppression is the normal, relative amplitude reduction of the auditory evoked potential for self-, compared to externally-generated, auditory stimulation. It remains controversial as to whether adults who stutter exhibit expected auditory modulation during speech; some studies have reported a significant difference between stuttering and fluent groups in speech-induced suppression during speech movement planning, while others have not. We compared auditory evoked potentials (N1 component) for auditory feedback arising from one’s own voice (Speaking condition) with passive listening to a recording of one’s own voice (Listening condition) in 24 normally-fluent speakers and 16 adults who stutter under various delayed auditory feedback (DAF) time conditions (100 ms, 200 ms, 500 ms, and 1,000 ms). We presented the participant’s own voice with a delay, immediately after presenting it without a delay. Our working hypothesis was that the shorter the delay time, the more likely the delayed sound is perceived as self-generated. Therefore, shorter delay time conditions are proposed to result in relatively enhanced suppression of the auditory system. Results showed that in fluent speakers, the shorter the delay time, the more the auditory evoked potential in the Speaking condition tended to be suppressed. In the Listening condition, there was a larger evoked potential with shorter delay times. As a result, speech-induced suppression was only significant at the short delay time conditions of 100 and 200 ms. Adults who stutter did not show the opposing changes in the Speaking and Listening conditions seen in the fluent group. Although the evoked potential in the Listening condition tended to decrease as the delay time increased, that in the Speaking condition did not show a distinct trend, and there was a significant suppression only at 200 ms delay. For the 200 ms delay condition, speakers with more severe stuttering showed significantly greater speech-induced suppression than those with less severe stuttering. This preliminary study suggests our methods for investigating evoked potentials by presenting own voice with a delay may provide a clue as to the nature of auditory modulation in stuttering.

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<![CDATA[Linear Predictive Approaches Separate Field Potentials in Animal Model of Parkinson's Disease]]> https://www.researchpad.co/article/elastic_article_13076 Parkinson's disease (PD) causes impaired movement and cognition. PD can involve profound changes in cortical and subcortical brain activity as measured by electroencephalography or intracranial recordings of local field potentials (LFP). Such signals can adaptively guide deep-brain stimulation (DBS) as part of PD therapy. However, adaptive DBS requires the identification of triggers of neuronal activity dependent on real time monitoring and analysis. Current methods do not always identify PD-related signals and can entail delays. We test an alternative approach based on linear predictive coding (LPC), which fits autoregressive (AR) models to time-series data. Parameters of these AR models can be calculated by fast algorithms in real time. We compare LFPs from the striatum in an animal model of PD with dopamine depletion in the absence and presence of the dopamine precursor levodopa, which is used to treat motor symptoms of PD. We show that in dopamine-depleted mice a first order AR model characterized by a single LPC parameter obtained by LFP sampling at 1 kHz for just 1 min can distinguish between levodopa-treated and saline-treated mice and outperform current methods. This suggests that LPC may be useful in online analysis of neuronal signals to guide DBS in real time and could contribute to DBS-based treatment of PD.

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<![CDATA[Automated Home-Cage Testing as a Tool to Improve Reproducibility of Behavioral Research?]]> https://www.researchpad.co/article/elastic_article_13066 <![CDATA[Subthalamic Single Cell and Oscillatory Neural Dynamics of a Dyskinetic Medicated Patient With Parkinson's Disease]]> https://www.researchpad.co/article/elastic_article_13057 Single cell neuronal activity (SUA) and local field potentials (LFP) in the subthalamic nucleus (STN) of unmedicated Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery have been well-characterized during microelectrode recordings (MER). However, there is limited knowledge about the changes in the firing patterns and oscillations above and within the territories of STN after the intake of dopaminergic medication. Here, for the first time, we report the STN single cell and oscillatory neural dynamics in a medicated patient with idiopathic PD using intraoperative MER. We recorded LFP and SUA with microelectrodes at various depths during bilateral STN-DBS electrode implantation. We isolated 26 neurons in total and observed that tonic and irregular firing patterns of individual neurons predominated throughout the territories of STN. While burst-type firings have been well-characterized in the dorsal territories of STN in unmedicated patients, interestingly, this activity was not observed in our medicated subject. LFP recordings lacked the excessive beta (8–30 Hz) activity, characteristic of the unmedicated state and signal energy was mainly dominated by slow oscillations below 8 Hz. We observed sharp gamma oscillations between 70 and 90 Hz within and above the STN. Despite the presence of a broadband high frequency activity in 200–400 Hz range, no cross-frequency interaction in the form of phase-amplitude coupling was noted between low and high frequency oscillations of LFPs. While our results are in agreement with the previously reported LFP recordings from the DBS lead in medicated PD patients, the sharp gamma peak present throughout the depth recordings and the lack of bursting firings after levodopa intake have not been reported before. The lack of bursting in SUA, the lack of excessive beta activity and cross frequency coupling between HFOs and lower rhythms further validate the link between bursting firing regime of neurons and pathological oscillatory neural activity in PD-STN. Overall, these observations not only validate the existing literature on the PD electrophysiology in healthy/medicated animal models but also provide insights regarding the underlying electro-pathophysiology of levodopa-induced dyskinesias in PD patients through demonstration of multiscale relationships between single cell firings and field potentials.

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<![CDATA[Early Inflammatory Signatures Predict Subsequent Cognition in Long-Term Virally Suppressed Women With HIV]]> https://www.researchpad.co/article/elastic_article_13050 Immunologic function is an important determinant of cognition. Here we examined the contribution of early immune signatures to cognitive performance among HIV-infected, virally suppressed women (HIV+VS) and in HIV-uninfected (HIV-) women. Specifically, we measured serum inflammatory markers, developed combinatory immune signatures, and evaluated their associations with cognition. Forty-nine HIV+VS women in the Women’s Interagency HIV Study (WIHS) who achieved viral suppression shortly after effective antiretroviral therapy (ART) initiation, and 56 matched HIV− women were selected. Forty-two serum inflammatory markers were measured within 2 years of effective ART initiation for HIV+VS women, and at an initial timepoint for HIV− women. The same inflammatory markers were also measured approximately 1, 7, and 12 years later for all women. Of the 105 women with complete immune data, 83 (34 HIV+VS, 49 HIV−) also had cognitive data available 12 years later at ≥1 time points (median = 3.1). We searched for combinatory immune signatures by adapting a dynamic matrix factorization analytic method that builds upon Tucker decomposition followed by Ingenuity® Pathway Analysis to facilitate data interpretation. Seven combinatory immune signatures emerged based on the Frobenius residual. Three signatures were common between HIV+VS and HIV− women, while four signatures were unique. These inflammatory signatures predicted subsequent cognitive performance in both groups using mixed-effects modeling, but more domain-specific associations were significant in HIV+VS than HIV− women. Leukocyte influx into brain was a major contributor to cognitive function in HIV+VS women, while T cell exhaustion, inflammatory response indicative of depressive/psychiatric disorders, microglial activity, and cytokine signaling predicted both global and domain-specific performance for HIV− women. Our findings suggest that immune signatures may be useful diagnostic, prognostic, and immunotherapeutic targets predictive of subsequent cognitive performance. Importantly, they also provide insight into common and distinct inflammatory mechanisms underlying cognition in HIV− and HIV+VS women.

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<![CDATA[5-Hydroxytryptamine Receptors and Tardive Dyskinesia in Schizophrenia]]> https://www.researchpad.co/article/elastic_article_13017 Tardive dyskinesia (TD) is a common side effect of antipsychotic treatment. This movement disorder consists of orofacial and limb-truncal components. The present study is aimed at investigating the role of serotonin receptors (HTR) in modulating tardive dyskinesia by genotyping patients with schizophrenia.MethodsA set of 29 SNPs of genes of serotonin receptors HTR1A, HTR1B, HTR2A, HTR2C, HTR3A, HTR3B, and HTR6 was studied in a population of 449 Caucasians (226 females and 223 males) with verified clinical diagnosis of schizophrenia (according to ICD-10: F20). Five SNPs were excluded because of low minor allele frequency or for not passing the Hardy-Weinberg equilibrium test. Affinity of antipsychotics to 5-HT2 receptors was defined according to previous publications. Genotyping was carried out with SEQUENOM Mass Array Analyzer 4.ResultsStatistically significant associations of rs1928040 of HTR2A gene in groups of patients with orofacial type of TD and total diagnosis of TD was found for alleles, and a statistical trend for genotypes. Moreover, statistically significant associations were discovered in the female group for rs1801412 of HTR2C for alleles and genotypes. Excluding patients who used HTR2A, respectively, HTR2C antagonists changed little to the associations of HTR2A polymorphisms, but caused a major change of the magnitude of the association of HTR2C variants. Due to the low patient numbers, these sub-analyses did not have significant results.ConclusionWe found significant associations in rs1928040 of HTR2A and for rs1801412 of X-bound HTR2C in female patients. The associations were particularly related to the orofacial type of TD. Excluding patients using relevant antagonists particularly affected rs1801412, but not rs1928040-related associations. This suggest that rs1801412 is directly or indirectly linked to the functioning of HTR2C. Further study of variants of the HTR2C gene in a larger group of male patients who were not using HTR2C antagonists is necessary in order to verify a possible functional role of this receptor. ]]> <![CDATA[Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell]]> https://www.researchpad.co/article/elastic_article_13002 The perceptron learning algorithm and its multiple-layer extension, the backpropagation algorithm, are the foundations of the present-day machine learning revolution. However, these algorithms utilize a highly simplified mathematical abstraction of a neuron; it is not clear to what extent real biophysical neurons with morphologically-extended non-linear dendritic trees and conductance-based synapses can realize perceptron-like learning. Here we implemented the perceptron learning algorithm in a realistic biophysical model of a layer 5 cortical pyramidal cell with a full complement of non-linear dendritic channels. We tested this biophysical perceptron (BP) on a classification task, where it needed to correctly binarily classify 100, 1,000, or 2,000 patterns, and a generalization task, where it was required to discriminate between two “noisy” patterns. We show that the BP performs these tasks with an accuracy comparable to that of the original perceptron, though the classification capacity of the apical tuft is somewhat limited. We concluded that cortical pyramidal neurons can act as powerful classification devices.

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<![CDATA[Going the Extra (Synaptic) Mile: Excitotoxicity as the Road Toward Neurodegenerative Diseases]]> https://www.researchpad.co/article/elastic_article_12948 Excitotoxicity is a phenomenon that describes the toxic actions of excitatory neurotransmitters, primarily glutamate, where the exacerbated or prolonged activation of glutamate receptors starts a cascade of neurotoxicity that ultimately leads to the loss of neuronal function and cell death. In this process, the shift between normal physiological function and excitotoxicity is largely controlled by astrocytes since they can control the levels of glutamate on the synaptic cleft. This control is achieved through glutamate clearance from the synaptic cleft and its underlying recycling through the glutamate-glutamine cycle. The molecular mechanism that triggers excitotoxicity involves alterations in glutamate and calcium metabolism, dysfunction of glutamate transporters, and malfunction of glutamate receptors, particularly N-methyl-D-aspartic acid receptors (NMDAR). On the other hand, excitotoxicity can be regarded as a consequence of other cellular phenomena, such as mitochondrial dysfunction, physical neuronal damage, and oxidative stress. Regardless, it is known that the excessive activation of NMDAR results in the sustained influx of calcium into neurons and leads to several deleterious consequences, including mitochondrial dysfunction, reactive oxygen species (ROS) overproduction, impairment of calcium buffering, the release of pro-apoptotic factors, among others, that inevitably contribute to neuronal loss. A large body of evidence implicates NMDAR-mediated excitotoxicity as a central mechanism in the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), Alzheimer’s disease (AD), and epilepsy. In this review article, we explore different causes and consequences of excitotoxicity, discuss the involvement of NMDAR-mediated excitotoxicity and its downstream effects on several neurodegenerative disorders, and identify possible strategies to study new aspects of these diseases that may lead to the discovery of new therapeutic approaches. With the understanding that excitotoxicity is a common denominator in neurodegenerative diseases and other disorders, a new perspective on therapy can be considered, where the targets are not specific symptoms, but the underlying cellular phenomena of the disease.

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<![CDATA[Chronic Presence of Oligomeric Aβ Differentially Modulates Spine Parameters in the Hippocampus and Cortex of Mice With Low APP Transgene Expression]]> https://www.researchpad.co/article/elastic_article_12892 Alzheimer’s disease is regarded as a synaptopathy with a long presymptomatic phase. Soluble, oligomeric amyloid-β (Aβ) is thought to play a causative role in this disease, which eventually leads to cognitive decline. However, most animal studies have employed mice expressing high levels of the Aβ precursor protein (APP) transgene to drive pathology. Here, to understand how the principal neurons in different brain regions cope with moderate, chronically present levels of Aβ, we employed transgenic mice expressing equal levels of mouse and human APP carrying a combination of three familial AD (FAD)-linked mutations (Swedish, Dutch, and London), that develop plaques only in old age. We analyzed dendritic spine parameters in hippocampal and cortical brain regions after targeted expression of EGFP to allow high-resolution imaging, followed by algorithm-based evaluation of mice of both sexes from adolescence to old age. We report that Aβ species gradually accumulated throughout the life of APPSDL mice, but not the oligomeric forms, and that the amount of membrane-associated oligomers decreased at the onset of plaque formation. We observed an age-dependent loss of thin spines under most conditions as an indicator of a loss of synaptic plasticity in older mice. We further found that hippocampal pyramidal neurons respond to increased Aβ levels by lowering spine density and shifting spine morphology, which reached significance in the CA1 subfield. In contrast, the spine density in cortical pyramidal neurons of APPSDL mice was unchanged. We also observed an increase in the protein levels of PSD-95 and Arc in the hippocampus and cortex, respectively. Our data demonstrated that increased concentrations of Aβ have diverse effects on dendritic spines in the brain and suggest that hippocampal and cortical neurons have different adaptive and compensatory capacity during their lifetime. Our data also indicated that spine morphology differs between sexes in a region-specific manner.

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<![CDATA[Investigating the Added Value of FreeSurfer’s Manual Editing Procedure for the Study of the Reading Network in a Pediatric Population]]> https://www.researchpad.co/article/elastic_article_12889 Insights into brain anatomy are important for the early detection of neurodevelopmental disorders, such as dyslexia. FreeSurfer is one of the most frequently applied automatized software tools to study brain morphology. However, quality control of the outcomes provided by FreeSurfer is often ignored and could lead to wrong statistical inferences. Additional manual editing of the data may be a solution, although not without a cost in time and resources. Past research in adults on comparing the automatized method of FreeSurfer with and without additional manual editing indicated that although editing may lead to significant differences in morphological measures between the methods in some regions, it does not substantially change the sensitivity to detect clinical differences. Given that automated approaches are more likely to fail in pediatric—and inherently more noisy—data, we investigated in the current study whether FreeSurfer can be applied fully automatically or additional manual edits of T1-images are needed in a pediatric sample. Specifically, cortical thickness and surface area measures with and without additional manual edits were compared in six regions of interest (ROIs) of the reading network in 5-to-6-year-old children with and without dyslexia. Results revealed that additional editing leads to statistical differences in the morphological measures, but that these differences are consistent across subjects and that the sensitivity to reveal statistical differences in the morphological measures between children with and without dyslexia is not affected, even though conclusions of marginally significant findings can differ depending on the method used. Thereby, our results indicate that additional manual editing of reading-related regions in FreeSurfer has limited gain for pediatric samples.

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<![CDATA[Spontaneous and evoked neurotransmission are partially segregated at inhibitory synapses]]> https://www.researchpad.co/article/elastic_article_12726 Synaptic transmission is initiated via spontaneous or action-potential evoked fusion of synaptic vesicles. At excitatory synapses, glutamatergic receptors activated by spontaneous and evoked neurotransmission are segregated. Although inhibitory synapses also transmit signals spontaneously or in response to action potentials, they differ from excitatory synapses in both structure and function. Therefore, we hypothesized that inhibitory synapses may have different organizing principles. We report picrotoxin, a GABAAR antagonist, blocks neurotransmission in a use-dependent manner at rat hippocampal synapses and therefore can be used to interrogate synaptic properties. Using this tool, we uncovered partial segregation of inhibitory spontaneous and evoked neurotransmission. We found up to 40% of the evoked response is mediated through GABAARs which are only activated by evoked neurotransmission. These data indicate GABAergic spontaneous and evoked neurotransmission processes are partially non-overlapping, suggesting they may serve divergent roles in neuronal signaling.

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<![CDATA[A molecular filter for the cnidarian stinging response]]> https://www.researchpad.co/article/elastic_article_12714 All animals detect and integrate diverse environmental signals to mediate behavior. Cnidarians, including jellyfish and sea anemones, both detect and capture prey using stinging cells called nematocytes which fire a venom-covered barb via an unknown triggering mechanism. Here, we show that nematocytes from Nematostella vectensis use a specialized voltage-gated calcium channel (nCaV) to distinguish salient sensory cues and control the explosive discharge response. Adaptations in nCaV confer unusually sensitive, voltage-dependent inactivation to inhibit responses to non-prey signals, such as mechanical water turbulence. Prey-derived chemosensory signals are synaptically transmitted to acutely relieve nCaV inactivation, enabling mechanosensitive-triggered predatory attack. These findings reveal a molecular basis for the cnidarian stinging response and highlight general principles by which single proteins integrate diverse signals to elicit discrete animal behaviors.

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<![CDATA[Tactile Feedback in Closed-Loop Control of Myoelectric Hand Grasping: Conveying Information of Multiple Sensors Simultaneously via a Single Feedback Channel]]> https://www.researchpad.co/article/elastic_article_10929 The appropriate sensory information feedback is important for the success of an object grasping and manipulation task. In many scenarios, the need arises for multiple feedback information to be conveyed to a prosthetic hand user simultaneously. The multiple sets of information may either (1) directly contribute to the performance of the grasping or object manipulation task, such as the feedback of the grasping force, or (2) simply form additional independent set(s) of information. In this paper, the efficacy of simultaneously conveying two independent sets of sensor information (the grasp force and a secondary set of information) through a single channel of feedback stimulation (vibrotactile via bone conduction) to the human user in a prosthetic application is investigated. The performance of the grasping task is not dependent to the second set of information in this study. Subject performance in two tasks: regulating the grasp force and identifying the secondary information, were evaluated when provided with either one corresponding information or both sets of feedback information. Visual feedback is involved in the training stage. The proposed approach is validated on human-subject experiments using a vibrotactile transducer worn on the elbow bony landmark (to realize a non-invasive bone conduction interface) carried out in a virtual reality environment to perform a closed-loop object grasping task. The experimental results show that the performance of the human subjects on either task, whilst perceiving two sets of sensory information, is not inferior to that when receiving only one set of corresponding sensory information, demonstrating the potential of conveying a second set of information through a bone conduction interface in an upper limb prosthetic task.

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<![CDATA[Nonspecific Expression in Limited Excitatory Cell Populations in Interneuron-Targeting Cre-driver Lines Can Have Large Functional Effects]]> https://www.researchpad.co/article/elastic_article_10924 Transgenic Cre-recombinase expressing mouse lines are widely used to express fluorescent proteins and opto-/chemogenetic actuators, making them a cornerstone of modern neuroscience. The investigation of interneurons in particular has benefitted from the ability to genetically target specific cell types. However, the specificity of some Cre driver lines has been called into question. Here, we show that nonspecific expression in a subset of hippocampal neurons can have substantial nonspecific functional effects in a somatostatin-Cre (SST-Cre) mouse line. Nonspecific targeting of CA3 pyramidal cells caused large optogenetically evoked excitatory currents in remote brain regions. Similar, but less severe patterns of nonspecific expression were observed in a widely used SST-IRES-Cre line, when crossed with a reporter mouse line. Viral transduction on the other hand yielded more specific expression but still resulted in nonspecific expression in a minority of pyramidal layer cells. These results suggest that a careful analysis of specificity is mandatory before the use of Cre driver lines for opto- or chemogenetic manipulation approaches.

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<![CDATA[Prevalence and Incidence of Neuromyelitis Optica Spectrum Disorder in Korea: Population Based Study]]> https://www.researchpad.co/article/elastic_article_10898

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<![CDATA[The Language of Innovation]]> https://www.researchpad.co/article/elastic_article_10245 Predicting innovation is a peculiar problem in data science. Following its definition, an innovation is always a never-seen-before event, leaving no room for traditional supervised learning approaches. Here we propose a strategy to address the problem in the context of innovative patents, by defining innovations as never-seen-before associations of technologies and exploiting self-supervised learning techniques. We think of technological codes present in patents as a vocabulary and the whole technological corpus as written in a specific, evolving language. We leverage such structure with techniques borrowed from Natural Language Processing by embedding technologies in a high dimensional euclidean space where relative positions are representative of learned semantics. Proximity in this space is an effective predictor of specific innovation events, that outperforms a wide range of standard link-prediction metrics. The success of patented innovations follows a complex dynamics characterized by different patterns which we analyze in details with specific examples. The methods proposed in this paper provide a completely new way of understanding and forecasting innovation, by tackling it from a revealing perspective and opening interesting scenarios for a number of applications and further analytic approaches.

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