FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ

Connectomic analysis of thalamus-driven disinhibition in cortical layer 4

Sensory signals are transmitted via the thalamus primarily to layer 4 (L4) of the primary sensory cortices. While information about average neuronal connectivity in L4 is available, its detailed higher-order circuit structure is not known. Here, we used three-dimensional electron microscopy for a connectomic analysis of the thalamus-driven inhibitory network in L4. We find that thalamic input drives a subset of interneurons with high specificity, which in turn target excitatory neurons with subtype specificity. These interneurons create a directed disinhibitory network directly driven by the thalamic input. Neuronal activity recordings show that strong synchronous sensory activation yields about 1.5-fold stronger activation of star pyramidal cells than spiny stellates, in line with differential windows of opportunity for activation of excitatory neurons in the thalamus-driven disinhibitory circuit model. With this, we have identified a high degree of specialization of the microcircuitry in L4 of the primary sensory cortex

Dynamic assembly of ribbon synapses and circuit maintenance in a vertebrate sensory system

Ribbon synapses transmit information in sensory systems, but their development is not well understood. To test the hypothesis that ribbon assembly stabilizes nascent synapses, we performed simultaneous time-lapse imaging of fluorescently-tagged ribbons in retinal cone bipolar cells (BCs) and postsynaptic densities (PSD95-FP) of retinal ganglion cells (RGCs). Ribbons and PSD95-FP clusters were more stable when these components colocalized at synapses. However, synapse density on ON-alpha RGCs was unchanged in mice lacking ribbons (ribeye knockout). Wildtype BCs make both ribbon-containing and ribbon-free synapses with these GCs even at maturity. Ribbon assembly and cone BC-RGC synapse maintenance are thus regulated independently. Despite the absence of synaptic ribbons, RGCs continued to respond robustly to light stimuli, although quantitative examination of the responses revealed reduced frequency and contrast sensitivity

The Cognitive Ecology of the Internet

In this chapter, we analyze the relationships between the Internet and its users in terms of situated cognition theory. We first argue that the Internet is a new kind of cognitive ecology, providing almost constant access to a vast amount of digital information that is increasingly more integrated into our cognitive routines. We then briefly introduce situated cognition theory and its species of embedded, embodied, extended, distributed and collective cognition. Having thus set the stage, we begin by taking an embedded cognition view and analyze how the Internet aids certain cognitive tasks. After that, we conceptualize how the Internet enables new kinds of embodied interaction, extends certain aspects of our embodiment, and examine how wearable technologies that monitor physiological, behavioral and contextual states transform the embodied self. On the basis of the degree of cognitive integration between a user and Internet resource, we then look at how and when the Internet extends our cognitive processes. We end this chapter with a discussion of distributed and collective cognition as facilitated by the Internet

Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images

We describe a protocol for fully automated detection and segmentation of asymmetric, presumed excitatory, synapses in serial electron microscopy images of the adult mammalian cerebral cortex, taken with the focused ion beam, scanning electron microscope (FIB/SEM). The procedure is based on interactive machine learning and only requires a few labeled synapses for training. The statistical learning is performed on geometrical features of 3D neighborhoods of each voxel and can fully exploit the high z-resolution of the data. On a quantitative validation dataset of 111 synapses in 409 images of 1948×1342 pixels with manual annotations by three independent experts the error rate of the algorithm was found to be comparable to that of the experts (0.92 recall at 0.89 precision). Our software offers a convenient interface for labeling the training data and the possibility to visualize and proofread the results in 3D. The source code, the test dataset and the ground truth annotation are freely available on the website http://www.ilastik.org/synapse-detection

TrakEM2 Software for Neural Circuit Reconstruction

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis

Dissociation of accumulated genetic risk and disease severity in patients with schizophrenia

Genotype–phenotype correlations of common monogenic diseases revealed that the degree of deviation of mutant genes from wild-type structure and function often predicts disease onset and severity. In complex disorders such as schizophrenia, the overall genetic risk is still often >50% but genotype–phenotype relationships are unclear. Recent genome-wide association studies (GWAS) replicated a risk for several single-nucleotide polymorphisms (SNPs) regarding the endpoint diagnosis of schizophrenia. The biological relevance of these SNPs, however, for phenotypes or severity of schizophrenia has remained obscure. We hypothesized that the GWAS ‘top-10' should as single markers, but even more so upon their accumulation, display associations with lead features of schizophrenia, namely positive and negative symptoms, cognitive deficits and neurological signs (including catatonia), and/or with age of onset of the disease prodrome as developmental readout and predictor of disease severity. For testing this hypothesis, we took an approach complementary to GWAS, and performed a phenotype-based genetic association study (PGAS). We utilized the to our knowledge worldwide largest phenotypical database of schizophrenic patients (n>1000), the GRAS (Göttingen Research Association for Schizophrenia) Data Collection. We found that the ‘top-10' GWAS-identified risk SNPs neither as single markers nor when explored in the sense of a cumulative genetic risk, have any predictive value for disease onset or severity in the schizophrenic patients, as demonstrated across all core symptoms. We conclude that GWAS does not extract disease genes of general significance in schizophrenia, but may yield, on a hypothesis-free basis, candidate genes relevant for defining disease subgroups

Stroke risk associated with balloon based catheter ablation for atrial fibrillation: Rationale and design of the MACPAF Study

<p>Abstract</p> <p>Background</p> <p>Catheter ablation of the pulmonary veins has become accepted as a standard therapeutic approach for symptomatic paroxysmal atrial fibrillation (AF). However, there is some evidence for an ablation associated (silent) stroke risk, lowering the hope to limit the stroke risk by restoration of rhythm over rate control in AF. The purpose of the prospective randomized single-center study "Mesh Ablator versus Cryoballoon Pulmonary Vein Ablation of Symptomatic Paroxysmal Atrial Fibrillation" (MACPAF) is to compare the efficacy and safety of two balloon based pulmonary vein ablation systems in patients with symptomatic paroxysmal AF.</p> <p>Methods/Design</p> <p>Patients are randomized 1:1 for the Arctic Front^®or the HD Mesh Ablator^®catheter for left atrial catheter ablation (LACA). The predefined endpoints will be assessed by brain magnetic resonance imaging (MRI), neuro(psycho)logical tests and a subcutaneously implanted reveal recorder for AF detection. According to statistics 108 patients will be enrolled.</p> <p>Discussion</p> <p>Findings from the MACPAF trial will help to balance the benefits and risks of LACA for symptomatic paroxysmal AF. Using serial brain MRIs might help to identify patients at risk for LACA-associated cerebral thromboembolism. Potential limitations of the study are the single-center design, the existence of a variety of LACA-catheters, the missing placebo-group and the impossibility to assess the primary endpoint in a blinded fashion.</p> <p>Trial registration</p> <p>clinicaltrials.gov NCT01061931</p

Neural Computation via Neural Geometry: A Place Code for Inter-whisker Timing in the Barrel Cortex?

The place theory proposed by Jeffress (1948) is still the dominant model of how the brain represents the movement of sensory stimuli between sensory receptors. According to the place theory, delays in signalling between neurons, dependent on the distances between them, compensate for time differences in the stimulation of sensory receptors. Hence the location of neurons, activated by the coincident arrival of multiple signals, reports the stimulus movement velocity. Despite its generality, most evidence for the place theory has been provided by studies of the auditory system of auditory specialists like the barn owl, but in the study of mammalian auditory systems the evidence is inconclusive. We ask to what extent the somatosensory systems of tactile specialists like rats and mice use distance dependent delays between neurons to compute the motion of tactile stimuli between the facial whiskers (or ‘vibrissae’). We present a model in which synaptic inputs evoked by whisker deflections arrive at neurons in layer 2/3 (L2/3) somatosensory ‘barrel’ cortex at different times. The timing of synaptic inputs to each neuron depends on its location relative to sources of input in layer 4 (L4) that represent stimulation of each whisker. Constrained by the geometry and timing of projections from L4 to L2/3, the model can account for a range of experimentally measured responses to two-whisker stimuli. Consistent with that data, responses of model neurons located between the barrels to paired stimulation of two whiskers are greater than the sum of the responses to either whisker input alone. The model predicts that for neurons located closer to either barrel these supralinear responses are tuned for longer inter-whisker stimulation intervals, yielding a topographic map for the inter-whisker deflection interval across the surface of L2/3. This map constitutes a neural place code for the relative timing of sensory stimuli