Logic Pro 9 System Requirements

[Kayleigh Telega]

Thesystem used for testing in the first two published methods papers consisted of a computer with a 2GHz Core 2 Duo processor, 512 Mb RAM, a dual-headed video card with 128Mb video RAM, and two National Instruments 6229 PCI DAQ cards with twoBNC 2090 break-out boxes. Considerably improved temporal performance canbe achieved with more modern PCs. For example, our most recent methods paper (J Neurophys, 2013) used a system consisting of a Dell Optiplex 980 computer with a Core i5 processor clocked at 3.60 GHz, with 4GB or RAM and running on Windows 7. The video system in that machine consisted of two Radeon HD 3400 graphics cards with 2GB of video RAM. Unsurpisingly, even faster performance (with typical cycle intervals around 0.3 ms and video refreshes requiring only 1.5 ms) has been observed on a Core i7 system (unpublished).

A typical experimental set-up includes two or three monitors: thedual video card output is divided among two displays, one which showsthe experimental "control screen" and the other for use as thesubject's screen. The subject's display output is often sent to twomonitors using a VGA or DVI signal splitter so that the experimentercan see what the subject sees and simultaneously provide the subjectwith a separate, optimally-positioned display.

The Matlab DataAcquisition Toolbox supports a variety of DAQ devices by severalmanufacturers. In addition to those from NationalInstruments, devices from Measurement Computingare also known to work with MonkeyLogic. A list ofmanufacturers supported by the Data Acquisition Toolbox is availabeon the Mathworks site. Note, however, that boards must allow samplingin the free-running state (i.e., the device has not been "started" fordata logging, yet samples can still be retrieved with "getsample"), inorder to work with MonkeyLogic when two boards are used in parallel(see next section) for more rapid behavioral signal sampling. Devicesfrom Agilent do not havethis capability, and so are not recommended.

While some behavioral tasks may rely upon simple keyboard input,most users employ an eye-tracker, joystick, or button-box. In the Asaad Lab, we use the Penny Giles JC200 joystick for human and nonhuman primates. Eye-tracking is currently performed with SR Research systems in both the Freedman and Asaad labs, and we have also used Iscan systems in the past; any eye-tracker that can output separate X and Y (and optionally pupil) measurements via analog signal should work.

MonkeyLogic has built-in routines for eye- and joystick-calibration and tracking, as well as for reading analog or digital buttons or levers (see the eyejoytrack command for more detailed information on monitoring these inputs). Eye-trackers and joysticks are expected to provide separate X and Y voltages, and these can be calibrated from within MonkeyLogic to correct for differences in offset, scaling, and 2-D skew (see Input Calibration for details).

Create a directory called "monkeylogic" and add it to the MATLABpath, copying the unzipped contents of the downloaded package into it. Also add the directory containing the SVI toolbox functions to the MATLAB path. Next, create directories for each experiment; in each directory, you will place an experiment's conditions file, timing script , stimulus images, andany other needed files (e.g., block-selection routines, etc). Behavioral data files for a thatparticular experiment will be written into this directory as well.These experiment directories do not need to be added to theMATLAB path.

Launch the MonkeyLogic menu by typing "monkeylogic" at the MATLABcommand prompt. Once a conditions fileand timing script(s) have beencreated, clicking on the "Load Conditions File" button at the top ofthe menu will allow you to select that conditions file to import, alongwith any stimuli used by that file and the timing scripts associatedwith it. In addition, once the various parameters on the main menu have been configured, these settingscan be saved by clicking on the "Save Settings" button (note: thesesettings will also be saved whenever an experiment is launched usingthe "Run" button).

A joystick and eye-tracking system are optional (keyboard input isminimally required for an interactive task). Pre-calibrating the inputs(e.g., on the eye-tracker system itself rather than in Matlab throughthe main menu) allows faster task execution, though even whenperforming an on-line calibrated transformation the operating frequencyshould be greater than 1 kHz.

A separate data acquisition system is assumed to be in use to storeneural events (for example single units and LFPs) and other continuousinputs (such as eye position, joystick position, photodiode state,etc). Note: slow analog data (e.g., eye-position) will bestored locally in the BHV file aswell, but splitting these signals into the neural data acquisitionsystem is prudent because it provides exact, sub-millisecond alignmentof these signals in relation to the neural events. Behavioral codes (event-markers)will be stored locally allowing complete analysis of behavior, and canbe exported in real-time to the acquisition system to allow temporalalignment of the behavioral events with those data acquired separately.

If you are running an experiment in which eventmarkers are not frequently sent to a neural data acquisition system (e.g., running an fMRI experiment where MonkeyLogic and the scanner are started simultaneously, but then do not communicate once the task has begun), you will need to rely on the BHV file variable AbsoluteTrialStartTime. Because Windows occasionally updates its clock with respect to a remote server, there can be discontinuties or inaccuracies in the clock over time, making these values inaccurate. Rarely, this may happen during an experiment. To stop clock syncing during an experiment, you should edit the Windows Registry.

For older versions of MonkeyLogic: While most main menu functions work whenMATLAB is running in standard mode (with Java enabled), some functions-- and the behavioral task itself -- will not work reliably so long asJava is enabled, either in the Matlab environment or in anotherapplication (e.g., web browser). If Java is currently running,unexpected and sporadic crashes will occur. To run MATLAB without Java,type:

WAF supports any number of availability zones within a single AWS region. For a list of regions that Alert Logic supports, see Supported AWS regions. The CloudFormation template configures an even distribution of worker nodes across availability zones. The CloudFormation template maintains the number of worker nodes equal to the number of availability zones. For example, two availability zones always have at least two WAF workers.

WAF workers and management WAF appliances are bound to specific AWS instance types. Management WAF appliances run on General Purpose Large instance types. Worker appliances run on Compute Optimized Large and Xlarge instance types. The default instance types are c5.large for workers and m5.large for the management WAF. The CloudFormation template allows for selecting instance types when run.

Traffic capacity is peak capacity measured using inbound and outbound traffic combined, assuming a representative sample of e-commerce web traffic. Actual performance may vary and depends on factors such as ratio of inbound to outbound traffic, request complexity, variability in input, and concurrency.

The EBS volume size is the minimum recommended. The EBS volume is used for caching and as a temporary store for log data in transit to the management WAF instance. If traffic caching is not enabled, it is possible to run with smaller volume sizes. Cache directory sizing is configured dynamically relative to the available disk space; a smaller volume size means the cache will be smaller. If the EBS volume disk space runs out, the WAF instance stops logging and issues an alert to the Alert Logic monitoring system.

WAF supports Secure Sockets Layer (SSL) end-to-end encryption, as required in AWS (by HIPAA, for example) both for standalone and for autoscaling deployments. If SSL encryption is required all the way to the backend server, WAF must be configured to re-encrypt traffic before forwarding it to the server. To re-encrypt traffic, select SSL for both inbound and outbound traffic when configuring the website in WAF. To comply with HIPAA requirements for high availability configurations, Elastic Load Balancing must be configured as a TCP load balancer so the initial SSL request from the client is not terminated until it reaches WAF.

WAF runs on select instance types in the AWS Marketplace ranging from a c5.large and c5a.large to c5.12xlarge and c5a.12xlarge. The actual performance for a specific application depends on factors such as request size, complexity, and the ratio of inbound to outbound traffic as a rough estimate. Traffic capacity is peak capacity measured using inbound and outbound traffic combined, assuming a representative sample of e-commerce web traffic.

The EBS volume size is the minimum recommended. If traffic caching is not enabled, you can run WAF with smaller volume sizes. Cache directory sizing is configured dynamically relative to the available disk space; a smaller volume size means the cache will be smaller. Total cache directory size is roughly 20 percent of available disk space. If the EBS volume disk space runs out, the WAF instance stops logging and issues an alert to the Alert Logic monitoring system. Alert Logic recommends you create separate partitions for root (/) and log data (/wsm/log) to prevent log data partition disk space issues from causing further failures in processing traffic.

You can deploy WAF in autoscaling configurations to provide high availability and performance adaptation to web applications with high and fluctuating traffic loads. An alternative configuration is a fixed capacity active/active deployment with two or more WAF nodes running parallel behind Elastic Load Balancing. In such a deployment, deploy the WAF instances in different Availability Zones.

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