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Perineuronal nets (PNNs) are specialized extracellular matrix structures that surround subsets of neurons throughout the central nervous system (CNS). They are made up of chondroitin sulfate proteoglycans (CSPGs), hyaluronan, tenascin-R, and many other link proteins that together make up their rigid and lattice-like structure. Modulation of PNNs can alter synaptic plasticity and thereby affect learning, memory, and cognition. In the present study, we degraded PNNs in the medial prefrontal (mPFC) and posterior parietal (PPC) cortices of Long-Evans rats using the enzyme chondroitinase ABC (ChABC), which cleaves apart CSPGs. We then measured the consequences of PNN degradation on spatial working memory (WM) with a trial-unique, non-matching-to location (TUNL) automated touchscreen task. All rats were trained with a standard 6 sec delay and 20 sec inter-trial interval (ITI) and then tested under four different conditions: a 6 sec delay, a variable 2 or 6 sec delay, a 2 sec delay with a 1 sec ITI (interference condition), and a 20 sec delay. Rats that received mPFC ChABC treatment initially performed TUNL with higher accuracy, more selection trials completed, and fewer correction trials completed compared to controls in the 20 sec delay condition but did not perform differently from controls in any other condition. Rats that received PPC ChABC treatment did not perform significantly differently from controls in any condition. Posthumous immunohistochemistry confirmed an increase in CSPG degradation products (C4S stain) in the mPFC and PPC following ChABC infusions while WFA staining intensity and parvalbumin positive neuron number were decreased following mPFC, but not PPC, ChABC infusions. These findings suggest that PNNs in the mPFC play a subtle role in spatial WM, but PNNs in the PPC do not. Furthermore, it appears that PNNs in the mPFC are involved in adapting to a challenging novel delay, but that they do not play an essential role in spatial WM function.

This paper focuses on analyzing traffic facilities for an intermediate time frame. There are two methodologies examined in this work, the first uses extrapolated, historical traffic count data and the second uses an urban transportation model. Using several intersections within Huntsville, Ala., as case study intersection locations, this paper applies both methodologies to forecast near-future traffic and compares the forecasted results with the actual traffic counts to determine which methodology better replicated actual volumes. The results of this work indicate that a properly validated and applied urban transportation planning model has the ability to provide more accurate traffic forecasts to support the traffic engineering analysis decision than the commonly used extrapolated traffic trends. CE Database subject headings: Traffic models; Traffic engineering; Forecasting; Traffic analysis; Urban planning.

This paper examines the practically of using a single internal trip purpose to generate the production and attraction values for traffic analysis zones in small urban community travel models. In previous research efforts, Quick-Response techniques, originally developed for cities with populations between 50,000 and 199,999, have been successfully applied to perform trip generation in small urban community travel models. Focusing on the reduction of data requirements and complexity of the trip generation analysis, a single trip purpose technique, based solely on aggregate numbers of households and businesses in a traffic analysis zone, has been proposed as a method to simplify the trip generation computation and reduce data requirements. This paper presents the fundamentals of the Quick-Response and single trip purpose techniques, tests the advantage of multiple trip purposes in a small sample network, and applies the two methodologies in a small urban community within Alabama to determine if significant differences exist when performing trip generation. The paper concludes that, for smaller urban community travel models, where different trip purposes are assumed to have similar trip lengths, both the Quick-Response and the single trip purpose technique produce similar results for the total productions and attractions in a traffic analysis zone. This similarity, and the results of the test showing that different trip purposes are not vital for trip distribution in small networks, substantiate the use of the simplified single trip purpose technique for trip generation. CE Database keywords: Travel modes; Transportation planning; Urban areas; Traffic analysis.

Urban travel modeling techniques have not found widespread use in small urban communities because traditional forecasting models, designed for use in large urban cities, are very data intensive. In recent years, however, there has been a greater awareness of transportation problems occurring in small urban areas, which are generally defined as communities with a population less than 50,000. Previous transportation planning research efforts directed towards small urban areas have identified the need for planning techniques that are less data intense and less expensive to implement when compared with traditional transportation modeling methods. This paper presents an application of the urban transportation planning processes that has limited data collection and cost requirements, developed specifically for application in smaller urban areas. The data requirements are reduced through the use of a single internal trip purpose based on the total number of households and businesses in each traffic analysis zone. This single trip purpose forecasting technique was used to develop travel models for 18 Alabama cities with populations ranging between 5,000 and 55,000. Validation and analysis of the travel models show that the single internal trip purpose presented in this paper can accurately be used to forecast traffic in smaller areas without extensive data collection efforts. CE Database keywords: Urban areas; Interurban travel; Traffic models; Alabama.

Personal computer implementations of urban transportation planning (UTP) packages have resulted in a proliferation of modeling efforts. However, staff experience and availability, particularly at small planning agencies, has not kept up with this proliferation, and many agencies that could benefit from a model go without. As many UTP models are complex and difficult to use, improved graphical interfaces and visualization tools are needed to create more intuitive modeling environments that take advantage of limited or dwindling staff resources. Furthermore, new opportunities exist as more and more graphic-based data are becoming available via the internet and CD-ROM from sources such as the Census Department, the Bureau of Transportation Statistics, and aerial/ortho-photography projects. In this paper, tools are presented and steps are recommended for developing UTP models using desktop geographic information systems. Using the city of Ames, Iowa, as a case study, these procedures and tools are shown to facilitate integration of spatially referenced data for efficient model development. Several GIS-based techniques are also presented for enhanced visualization of model adjustments in calibration and validation.

This paper examines a new methodology to predict external trip exchanges in small urban communities. The paper documents a study performed on several small communities in Alabama and includes a video surveillance data collection methodology, data analysis, model development, and test versus existing models. The new model presented in this paper is shown to provide more accurate results when compared to existing models and demonstrated transferability to a similar city. DOI: 10.1061/(ASCE)0733-9488(2006) 132:2(112) CE Database subject headings: Methodology; Urban areas; Alabama; Traffic surveillance; Transportation management.