Methylphenidate is the psychostimulant medication most commonly prescribed to treat attention deficit hyperactivity disorder (ADHD). Recent trends in the high usage of methylphenidate for both therapeutic and nontherapeutic purposes prompted us to investigate the long-term effects of exposure to the drug on neuronal adaptation. We compared the effects of chronic methylphenidate or cocaine (15 mg/kg, 14 days for both) exposure in mice on dendritic spine morphology and ⌬FosB expression in mediumsized spiny neurons (MSN) from ventral and dorsal striatum. Chronic methylphenidate increased the density of dendritic spines in MSN-D1 (MSN-expressing dopamine D1 receptors) from the core and shell of nucleus accumbens (NAcc) as well as MSN-D2 (MSNexpressing dopamine D2 receptors) from the shell of NAcc. In contrast, cocaine increased the density of spines in both populations of MSN from all regions of striatum. In general, the effect of methylphenidate on the increase of shorter spines (class 2) was less than that of cocaine. Interestingly, the methylphenidate-induced increase in the density of relatively longer spines (class 3) in the shell of NAcc was bigger than that induced by cocaine. Furthermore, methylphenidate exposure increased expression of ⌬FosB only in MSN-D1 from all areas of striatum, and surprisingly, the increase was greater than that induced by cocaine. Thus, our results show differential effects of methylphenidate and cocaine on neuronal adaptation in specific types of MSN in reward-related brain regions.ethylphenidate is the psychostimulant medication most commonly prescribed to treat attention deficit hyperactivity disorder (ADHD) (1, 2). Over the past 2 decades, the number of children, adolescents, and adults for whom methylphenidate has been prescribed has surged (2, 3). ADHD is associated with a dopamine imbalance, and methylphenidate likely helps ADHD patients by blocking dopamine reuptake and thereby increasing synaptic dopamine (4). Methylphenidate and cocaine have similar chemical structures and their pharmacological effects appear to be similar (5), prompting concern that methylphenidate may have addictive properties. Indeed, methylphenidate is widely abused for improving concentration and enhancing performance, or for recreational purposes (3, 6-10). Notably, a recent report has indicated that more than 7 million people in the US have abused ADHD stimulants, and as many as 750,000 teenagers and young adults may show signs of addiction (11). The increasing abuse of methylphenidate as well as the exposure of individuals through its therapeutic use prompted us to investigate possible long-term effects of methylphenidate on brain chemistry and neuronal structure.Substantial evidence suggests that adaptive changes in dopaminergic function in the ventral tegmental area (VTA) and nucleus accumbens (NAcc) underlie psychostimulant-induced behaviors (12). In addition to dopamine, glutamate is required for the behavioral sensitization, drug seeking, and compulsive relapse in response to psychostimulants ...

A-type K+ currents have unique kinetic and voltage-dependent properties that allow them to finely tune synaptic integration, action potential (AP) shape and firing patterns. In hippocampal CA1 pyramidal neurons, Kv4 channels make up the majority of the somatodendritic A-type current. Studies in heterologous expression systems have shown that Kv4 channels interact with transmembrane dipeptidyl-peptidase-like proteins (DPPLs) to regulate the surface trafficking and biophysical properties of Kv4 channels. To investigate the influence of DPPLs in a native system, we conducted voltage-clamp experiments in patches from CA1 pyramidal neurons expressing short-interfering RNA (siRNA) targeting the DPPL variant known to be expressed in hippocampal pyramidal neurons, DPPX (siDPPX). In accordance with heterologous studies, we found that DPPX downregulation in neurons resulted in depolarizing shifts of the steady-state inactivation and activation curves, a shallower conductance-voltage slope, slowed inactivation, and a delayed recovery from inactivation for A-type currents. We carried out current-clamp experiments to determine the physiological effect of the A-type current modifications by DPPX. Neurons expressing siDPPX exhibited a surprisingly large reduction in subthreshold excitability as measured by a decrease in input resistance, delayed time to AP onset, and an increased AP threshold. Suprathreshold DPPX downregulation resulted in slower AP rise and weaker repolarization. Computer simulations supported our experimental results and demonstrated how DPPX remodeling of A-channel properties can result in opposing sub- and suprathreshold effects on excitability. The Kv4 auxiliary subunit DPPX thus acts to increase neuronal responsiveness and enhance signal precision by advancing AP initiation and accelerating both the rise and repolarization of APs.

Acquisition and quantitative analysis of high resolution images of dendritic spines are challenging tasks but are necessary for the study of animal models of neurological and psychiatric diseases. Currently available methods for automated dendritic spine detection are for the most part customized for 2D image slices, not volumetric 3D images. In this work, a fully automated method is proposed to detect and segment dendritic spines from 3D confocal microscopy images of medium-sized spiny neurons (MSNs). MSNs constitute a major neuronal population in striatum, and abnormalities in their function are associated with several neurological and psychiatric diseases. Such automated detection is critical for the development of new 3D neuronal assays which can be used for the screening of drugs and the studies of their therapeutic effects. The proposed method utilizes a generalized gradient vector flow (GGVF) with a new smoothing constraint and then detects feature points near the central regions of dendrites and spines. Then, the central regions are refined and separated based on eigen-analysis and multiple shape measurements. Finally, the spines are segmented in 3D space using the fast marching algorithm, taking the detected central regions of spines as initial points. The proposed method is compared with three popular existing methods for centerline extraction and also with manual results for dendritic spine detection in 3D space. The experimental results and comparisons show that the proposed method is able to automatically and accurately detect, segment, and quantitate dendritic spines in 3D images of MSNs.

Secretin is a polypeptide hormone that stimulates secretion of bicarbonate from the exocrine pancreas and, in healthy human subjects, causes transient pancreatic duct dilation observable sonographically. In humans with chronic pancreatitis, secretin administration fails to cause pancreatic duct dilation, theoretically due to the restrictive effects of periductal fibrosis. We characterized the effect of exogenous secretin administration on the width of the pancreatic duct in nine healthy domestic cats. Cats were given a commercially available secretin product (ChiRho Stim) while the pancreatic duct was monitored sonographically. Mean pancreatic duct diameter increased from 0.77 +/- 0.33 to 1.42 +/- 0.40 mm after secretin administration (P = 0.0017). The mean percent increase in pancreatic duct diameter over basal diameter for all time points up to 15 min postsecretin administration was 101.9 +/- 58.8%. Applicability of this technique to diagnose chronic pancreatitis in cats will need to be investigated.

Visual tracking algorithms have important robotic applications such as mobile robot guidance and servoed wide area surveillance systems. These applications ideally require vision algorithms which are robust to camera motion and scene change but are cheap and fast enough to run on small, low power embedded systems. Unfortunately most robust visual tracking algorithms are either computationally expensive or are restricted to a stationary camera. This paper describes a new color based tracking algorithm, the Adaptive Background CAMSHIFT (ABCshift) tracker and an associated technique, mean shift servoing, for efficient pan-tilt servoing of a motorized camera platform. ABCshift achieves robustness against camera motion and other scene changes by continuously relearning its background model at every frame. This also enables robustness in difficult scenes where the tracked object moves past backgrounds with which it shares significant colors. Despite this continuous machine learning, ABCshift needs minimal training and is remarkably computationally cheap. We first demonstrate how ABCshift tracks robustly in situations where related algorithms fail, and then show how it can be used for real time tracking with pan-tilt servo control using only a small embedded microcontroller.