Spike sorting for large, dense electrode arrays

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely spaced recording sites, and electrodes with thousands of sites are under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons from the raw data captured from the probes. Here we present a set of tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus and thalamus of rat, mouse, macaque and marmoset, demonstrating error rates as low as 5%

Coupled variability in primary sensory areas and the hippocampus during spontaneous activity

The cerebral cortex is an anatomically divided and functionally specialized structure. It includes distinct areas, which work on different states over time. The structural features of spiking activity in sensory cortices have been characterized during spontaneous and evoked activity. However, the coordination among cortical and sub-cortical neurons during spontaneous activity across different states remains poorly characterized. We addressed this issue by studying the temporal coupling of spiking variability recorded from primary sensory cortices and hippocampus of anesthetized or freely behaving rats. During spontaneous activity, spiking variability was highly correlated across primary cortical sensory areas at both small and large spatial scales, whereas the cortico-hippocampal correlation was modest. This general pattern of spiking variability was observed under urethane anesthesia, as well as during waking, slow-wave sleep and rapid-eye-movement sleep, and was unchanged by novel stimulation. These results support the notion that primary sensory areas are strongly coupled during spontaneous activity.project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NAPV was supported by Centro Universitario do Rio Grande do Norte, Champalimaud Foundation, and Brazilian National Council for Scientific and Technological Development (CNPq, Grant 249991/2013-6), CC-S (SFRH/BD/51992/2012). AJR (IF/00883/2013). SR by UFRN, CNPq (Research Productivity Grant 308775/2015-5), and S. Paulo Research Foundation FAPESP - Center for Neuromathematics (Grant 2013/07699-0)info:eu-repo/semantics/publishedVersio

Proximity curves for potential-based clustering

YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Sexual Development in Plasmodium: Lessons from Functional Analyses

Malaria is a devastating global disease with several hundred million clinical cases and just under 1 million deaths each yea

Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism.

Differences in cortical morphology-in particular, cortical volume, thickness and surface area-have been reported in individuals with autism. However, it is unclear what aspects of genetic and transcriptomic variation are associated with these differences. Here we investigate the genetic correlates of global cortical thickness differences (ΔCT) in children with autism. We used Partial Least Squares Regression (PLSR) on structural MRI data from 548 children (166 with autism, 295 neurotypical children and 87 children with ADHD) and cortical gene expression data from the Allen Institute for Brain Science to identify genetic correlates of ΔCT in autism. We identify that these genes are enriched for synaptic transmission pathways and explain significant variation in ΔCT. These genes are also significantly enriched for genes dysregulated in the autism post-mortem cortex (Odd Ratio (OR) = 1.11, Pcorrected  10-14), driven entirely by downregulated genes (OR = 1.87, Pcorrected  10-15). We validated the enrichment for downregulated genes in two independent data sets: Validation 1 (OR = 1.44, Pcorrected = 0.004) and Validation 2 (OR = 1.30; Pcorrected = 0.001). We conclude that transcriptionally downregulated genes implicated in autism are robustly associated with global changes in cortical thickness variability in children with autism

A whole cell pathway screen reveals seven novel chemosensitizers to combat chloroquine resistant malaria

Due to the widespread prevalence of resistant parasites, chloroquine (CQ) was removed from front-line antimalarial chemotherapy in the 1990s despite its initial promise of disease eradication. Since then, resistance-conferring mutations have been identified in transporters such as the PfCRT, that allow for the efflux of CQ from its primary site of action, the parasite digestive vacuole. Chemosensitizing/ chemoreversing compounds interfere with the function of these transporters thereby sensitizing parasites to CQ once again. However, compounds identified thus far have disappointing in vivo efficacy and screening for alternative candidates is required to revive this strategy. In this study, we propose a simple and direct means to rapidly screen for such compounds using a fluorescent-tagged CQ molecule. When this screen was applied to a small library, seven novel chemosensitizers (octoclothepin, methiothepin, metergoline, loperamide, chlorprothixene, L-703,606 and mibefradil) were quickly elucidated, including two which showed greater potency than the classical chemosensitizers verapamil and desipramine

Raster-scanned carbon ion therapy for malignant salivary gland tumors: acute toxicity and initial treatment response

<p>Abstract</p> <p>Background and purpose</p> <p>To investigate toxicity and efficacy in high-risk malignant salivary gland tumors (MSGT) of the head and neck. Local control in R2-resected adenoid cystic carcinoma was already improved with a combination of IMRT and carbon ion boost at only mild side-effects, hence this treatment was also offered to patients with MSGT and microscopic residual disease (R1) or perineural spread (Pn+).</p> <p>Methods</p> <p>From November 2009, all patients with MSGT treated with carbon ion therapy were evaluated. Acute side effects were scored according to CTCAE v.4.03. Tumor response was assessed according to RECIST where applicable.</p> <p>Results</p> <p>103 patients were treated from 11/2009 to 03/2011, median follow-up is 6 months. 60 pts received treatment following R2 resections or as definitive radiation, 43 patients received adjuvant radiation for R1 and/or Pn+. 16 patients received carbon ion treatment for re-irradiation. Median total dose was 73.2 GyE (23.9 GyE carbon ions + 49,9 Gy IMRT) for primary treatment and 44.9 GyE carbon ions for re-irradiation. All treatments were completed as planned and generally well tolerated with no > CTC°III toxicity. Rates of CTC°III toxicity (mucositis and dysphagia) were 8.7% with side-effects almost completely resolved at first follow-up.</p> <p>47 patients showed good treatment responses (CR/PR) according to RECIST.</p> <p>Conclusion</p> <p>Acute toxicity remains low in IMRT with carbon ion boost also in R1-resected patients and patients undergoing re-irradiation. R2-resected patients showed high rates of treatment response, though follow-up is too short to assess long-term disease control.</p

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente