A single unified package capable of performing acquisition, analysis and simulations, and creating publication-quality graphics, would substantially simplify this workflow, making it more efficient. They may use yet another package to create publication-quality graphics. Hence, the majority of electrophysiologists find themselves acquiring data with one package, importing the acquired data into another package to perform data analysis, and using another package to perform simulations. Software packages for electrophysiological research are usually specialized to perform either data acquisition, data analysis or neuronal simulations, with little crossover in functionality. NeuroMatic version 3.0 can be found at and. Since its original release, NeuroMatic has been used in a wide range of scientific studies and its user base has grown considerably. Moreover, NeuroMatic has the advantage of working within Igor Pro, a platform-independent environment that includes an extensive library of built-in functions, a history window for reviewing the user's workflow and the ability to produce publication-quality graphics. The merging of a wide range of tools into a single package facilitates a more integrated style of research, from the development of online analysis functions during data acquisition, to the simulation of synaptic conductance trains during dynamic-clamp experiments. To address this, we developed NeuroMatic, an open-source software toolkit that performs data acquisition (episodic, continuous and triggered recordings), data analysis (spike rasters, spontaneous event detection, curve fitting, stationarity) and simulations (stochastic synaptic transmission, synaptic short-term plasticity, integrate-and-fire and Hodgkin-Huxley-like single-compartment models). It also complicates certain experimental approaches such as online analysis. This makes it difficult to conserve experimental metadata and track the analysis performed.
If one of the inputs is a multidimensional raster and the other input is a constant, the operator will perform the operation for all slices for all variables against the constant value, and the output will be a multidimensional raster. If both inputs have one variable but different names, set the matchMultidimensionalVariable geoprocessing environment to False to perform the operation. The variables in the inputs must have same dimensions or common dimension but no uncommon dimensions. If both inputs are multidimensional rasters with same number of variables, the operator will perform the operation for all slices with same dimension value, and the output will be a multidimensional raster. If one of the inputs is a multiband raster and the other input is a constant, the operator will perform the operation against the constant value for each band in the multiband input, and the output will be a multiband raster. The number of bands in each multiband input must be the same. If both inputs are multiband rasters, the operator will perform the operation on each band from one input, and the output will be a multiband raster. If both inputs are single-band rasters, or one of the inputs is a constant, the output will be a single-band raster. The order of the input is relevant for this operator. Two inputs are necessary for the evaluation to take place. For more information, see complex statement rules section of Build complex statements. To avoid this potential problem, use appropriate parentheses in the expression so that the execution order of the operators is explicitly defined. When multiple Relational and/or Boolean operators are used consecutively in a single expression, in some cases, it may fail to execute. To change the order of execution, use parentheses. Therefore, when Boolean operators are used in the same expression as Relational operators, the Boolean operators will be executed first. In the relational evaluation, if the condition is true (the first input value is greater than the second input value), the output is 1 if it is false, the output is 0. The relational greater-than operation evaluates the first input value in relation to the second input value on a cell-by-cell basis within the Analysis window.
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