Real-Time Decoding of an Integrate and Fire Encoder

Neuronal encoding models range from the detailed biophysically-based Hodgkin Huxley model, to the statistical linear time invariant model specifying firing rates in terms of the extrinsic signal. Decoding the former becomes intractable, while the latter does not adequately capture the nonlinearities present in the neuronal encoding system. For use in practical applications, we wish to record the output of neurons, namely spikes, and decode this signal fast in order to act on this signal, for example to drive a prosthetic device. Here, we introduce a causal, real-time decoder of the biophysically-based Integrate and Fire encoding neuron model. We show that the upper bound of the real-time reconstruction error decreases polynomially in time, and that the L[subscript 2] norm of the error is bounded by a constant that depends on the density of the spikes, as well as the bandwidth and the decay of the input signal. We numerically validate the effect of these parameters on the reconstruction error.National Science Foundation (U.S.) (Emerging Frontiers in Research and Innovation Grant 1137237

Novel Therapeutic Approaches in Neoplastic Meningitis

Simple Summary Neoplastic meningitis (NM) is a frequent complication of cancer and is associated with a poor prognosis. The currently available therapies aim to alleviate symptoms and preserve the quality of life. It comprises a multimodal approach, including surgery, intrathecal and systemic chemotherapy, and radiotherapy. The specific treatment is individualized, based on clinical practice guidelines and expert opinion. There are multiple clinical trials undertaken to evaluate the efficacy of novel therapies, including targeted and immunotherapies. This article presents an updated review of treatment approaches in NM. Abstract Central nervous system (CNS) metastasis from systemic cancers can involve the brain parenchyma, leptomeninges, or the dura. Neoplastic meningitis (NM), also known by different terms, including leptomeningeal carcinomatosis and carcinomatous meningitis, occurs due to solid tumors and hematologic malignancies and is associated with a poor prognosis. The current management paradigm entails a multimodal approach focused on palliation with surgery, radiation, and chemotherapy, which may be administered systemically or directly into the cerebrospinal fluid (CSF). This review focuses on novel therapeutic approaches, including targeted and immunotherapeutic agents under investigation, that have shown promise in NM arising from solid tumors

Combination of EGFR-Directed Tyrosine Kinase Inhibitors (EGFR-TKI) with Radiotherapy in Brain Metastases from Non-Small Cell Lung Cancer: A 2010-2019 Retrospective Cohort Study

Introduction: Traditionally, brain metastases have been treated with stereotactic radiosurgery (SRS), whole-brain radiation (WBRT), and/or surgical resection. Non-small cell lung cancers (NSCLC), over half of which carry EGFR mutations, are the leading cause of brain metastases. EGFR-directed tyrosine kinase inhibitors (TKI) have shown promise in NSCLC; but their utility in NSCLC brain metastases (NSCLCBM) remains unclear. This work sought to investigate whether combining EGFR-TKI with WBRT and/or SRS improves overall survival (OS) in NSCLCBM. Methods: A retrospective review of NSCLCBM patients diagnosed during 2010–2019 at a tertiary-care US center was performed and reported following the ‘strengthening the reporting of observational studies in epidemiology’ (STROBE) guidelines. Data regarding socio-demographic and histopathological characteristics, molecular attributes, treatment strategies, and clinical outcomes were collected. Concurrent therapy was defined as the combination of EGFR-TKI and radiotherapy given within 28 days of each other. Results: A total of 239 patients with EGFR mutations were included. Of these, 32 patients had been treated with WBRT only, 51 patients received SRS only, 36 patients received SRS and WBRT only, 18 were given EGFR-TKI and SRS, and 29 were given EGFR-TKI and WBRT. Median OS for the WBRT-only group was 3.23 months, for SRS + WBRT it was 3.17 months, for EGFR-TKI + WBRT 15.50 months, for SRS only 21.73 months, and for EGFR-TKI + SRS 23.63 months. Multivariable analysis demonstrated significantly higher OS in the SRS-only group (HR = 0.38, 95% CI 0.17–0.84, p = 0.017) compared to the WBRT reference group. There were no significant differences in overall survival for the SRS + WBRT combination cohort (HR = 1.30, 95% CI = 0.60, 2.82, p = 0.50), EGFR-TKIs and WBRT combination cohort (HR = 0.93, 95% CI = 0.41, 2.08, p = 0.85), or the EGFR-TKI + SRS cohort (HR = 0.46, 95% CI = 0.20, 1.09, p = 0.07). Conclusions: NSCLCBM patients treated with SRS had a significantly higher OS compared to patients treated with WBRT-only. While sample-size limitations and investigator-associated selection bias may limit the generalizability of these results, phase II/III clinicals trials are warranted to investigate synergistic efficacy of EGFR-TKI and SRS

Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents

Recent advances in the healthcare industry have led to an abundance of unstructured data, making it challenging to perform tasks such as efficient and accurate information retrieval at scale. Our work offers an all-in-one scalable solution for extracting and exploring complex information from large-scale research documents, which would otherwise be tedious. First, we briefly explain our knowledge synthesis process to extract helpful information from unstructured text data of research documents. Then, on top of the knowledge extracted from the documents, we perform complex information retrieval using three major components- Paragraph Retrieval, Triplet Retrieval from Knowledge Graphs, and Complex Question Answering (QA). These components combine lexical and semantic-based methods to retrieve paragraphs and triplets and perform faceted refinement for filtering these search results. The complexity of biomedical queries and documents necessitates using a QA system capable of handling queries more complex than factoid queries, which we evaluate qualitatively on the COVID-19 Open Research Dataset (CORD-19) to demonstrate the effectiveness and value-add

Optimization of culture conditions for extracellular fungal lipase production by submerged fermentation process

The present study aimed to optimize culture conditions for optimal growth and production of extracellular lipase. Lipolytic fungal strain named as S3St2 previously isolated from a petrol pump soil sample of Newai Town was used for optimization study. Among the tested carbohydrate carbon sources, polysaccharide-starch exhibited maximum lipase production (21.25±0.70 IU/ml/min) with highest specific activity (1.47±0.06 U/mg). Lipase activity and specific activity were higher with mustard oil 1 % (v/v) among all lipidic carbon sources. Among inorganic nitrogen source, potassium nitrate was found best inducer of lipase activity, malt extract supported the fungus growth (dry weight of cell pellets was 0.467 g) and exhibited maximum lipase activity among all organic nitrogen sources. Lipase activity was optimum at pH 8.0, indicates alkalophillic nature of production media supports the growth of fungus. Higher lipase activity (27.92±0.87 IU/ml/min) was detected at 28ºC. The incubation time of 5 days was found optimum for maximum lipase production (31.51±0.21 IU/ml/min)

Modulations in Oscillatory Activity of Globus Pallidus Internus Neurons During a Directed Hand Movement Task—A Primary Mechanism for Motor Planning

Globus pallidus internus (GPi) neurons in the basal ganglia are traditionally thought to play a significant role in the promotion and suppression of movement via a change in firing rates. Here, we hypothesize that a primary mechanism of movement control by GPi neurons is through specific modulations in their oscillatory patterns. We analyzed neuronal spiking activity of 83 GPi neurons recorded from two healthy nonhuman primates executing a radial center-out motor task. We found that, in directionally tuned neurons, the power in the gamma band is significantly (p < 0.05) greater than that in the beta band (a “cross-over” effect), during the planning stages of movements in their preferred direction. This cross-over effect is not observed in the non-directionally tuned neurons. These data suggest that, during movement planning, information encoding by GPi neurons may be governed by a sudden emergence and suppression of oscillatory activities, rather than simply by a change in average firing rates

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function