Philip R. Baldwin

Dynamic Gain Control of Dopamine Delivery in Freely Moving Animals

Activity changes in a large subset of midbrain dopamine neurons fulfill numerous assumptions of learning theory by encoding a prediction error between actual and predicted reward. This computational interpretation of dopaminergic spike activity invites the important question of how changes in spike rate are translated into changes in dopamine delivery at target neural structures. Using electrochemical detection of rapid dopamine release in the striatum of freely moving rats, we established that a single dynamic model can capture all the measured fluctuations in dopamine delivery. This model revealed three independent short-term adaptive processes acting to control dopamine release. These short-term components generalized well across animals and stimulation patterns and were preserved under anesthesia. The model has implications for the dynamic filtering interposed between changes in spike production and forebrain dopamine release.

BOLD responses to negative reward prediction errors in human habenula

Although positive reward prediction error, a key element in learning that is signaled by dopamine cells, has been extensively studied, little is known about negative reward prediction errors in humans. Detailed animal electrophysiology shows that the habenula, an integrative region involved in many processes including learning, reproduction, and stress responses, also encodes negative reward-related events such as negative reward prediction error signals. In humans, however, the habenulas extremely small size has prevented direct assessments of its function. We developed a method to functionally locate and study the habenula in humans using fMRI, based on the expected reward-dependent response phenomenology of habenula and striatum and, we provide conclusive evidence for activation in human habenula to negative reward prediction errors.

The medial habenula: still neglected

The habenula is a small, bilateral brain structure located at the dorsal end of the diencephalon. This structure sends projections to the dopaminergic striatum and receives inputs from the limbic forebrain, making the habenula a unique modulator of cross-talk between these brain regions. Despite strong interest in the habenula during the seventies and eighties (Herkenham and Nauta, 1977; Beckstead, 1979; Beckstead et al., 1979; Herkenham and Nauta, 1979; Caldecott-Hazard et al., 1988), interest waned due to lack of a clearly identifiable functional role. Following Matsumoto and Hikosakas seminal work on the lateral habenula as a predictor of negative reward in monkeys, the habenula has undergone a resurgence of scientific interest. Matsumoto and Hikosaka demonstrated an increase in habenular neuron firing when monkeys did not receive an expected juice reward (Matsumoto and Hikosaka, 2007). Studies have shown that increased habenular activity inactivates dopaminergic cells in the Rostromedial Tegmental Nucleus (RMTg) through GABAergic mechanisms (Jhou et al., 2009a,b). Additional studies link habenular activity to the regulation of serotonin and norepinephrine, suggesting the habenula modulates multiple brain systems (Strecker and Rosengren, 1989; Amat et al., 2001). These discoveries ushered in a series of new studies that have refocused attention on the lateral habenula and the importance of this small brain structure (Bianco and Wilson, 2009; Jhou et al., 2009a; Matsumoto and Hikosaka, 2009; Sartorius et al., 2010; Savitz et al., 2011). Recently, Geisler and Trimble reviewed this renewed interest in: The Lateral Habenula: No Longer Neglected (Geisler and Trimble, 2008). While the lateral habenula (LHb) has been extensively studied, the anatomically and histochemically distinct medial habenula (MHb) remains largely understudied. This short review argues that the MHb is functionally important and should be studied more aggressively.

Perceptions about e-cigarette safety may lead to e-smoking during pregnancy

Electronic cigarettes (e-cigarettes) are nicotine-delivery devices that are increasingly used, especially by young people. Because e-cigarettes lack many of the substances found in regular tobacco, they are often perceived as a safer smoking alternative, especially in high-risk situations such as pregnancy. However, studies suggest that it is exposure to nicotine that is most detrimental to prenatal development. The authors studied perceptions of tobacco and e-cigarette health risks using a multiple-choice survey. To study the perceived safety of e-cigarettes versus tobacco cigarettes, 184 modified Global Health Youth Surveys (WHO, http://www.who.int/tobacco/surveillance/gyts/en/ ) were completed electronically or on paper. Age range, smoking status, and perceptions about tobacco cigarettes and e-cigarettes were studied. The results verified that younger people use e-cigarettes more than older people. Tobacco cigarettes were perceived as more harmful than e-cigarettes to health in general, including lung cancer and pregnancy. Although more research is necessary, the authors postulate that the perception that e-cigarettes are safer during pregnancy may induce pregnant women to use these devices more freely. Given that nicotine is known to cause fetal harm, pregnant mothers who smoke e-cigarettes could cause even greater harm to the fetus because e-cigarettes are perceived as being safer than tobacco cigarettes. Until more data about the effects of nicotine during pregnancy are available, the authors advocate for labeling of e-cigarettes as potentially harmful, at least during pregnancy.

The Role of the Habenula in Nicotine Addiction

To thrive in any given environment, mobile creatures must be able to learn from the outcomes of both successful and disappointing events. To learn from success, the brain relies on signals originating in the ventral tegmental area and substantia nigra that result in increased release of dopamine in the striatum. Recently, it was shown that to learn from disappointment the brain relies on signals originating in the lateral habenula, which indirectly inhibit dopaminergic activity. The habenula is a small brain region that has been shown in mice to be critical for the appearance of nicotine withdrawal symptoms. The nicotinic acetylcholine receptor subunits expressed in the medial habenula are necessary to observe withdrawal symptoms in mice, and blocking nicotinic activity in the medial habenula only is sufficient to precipitate withdrawal in dependent mice. In addition, recent genome wide association studies have shown that in humans, genetic variants in the same nicotinic receptor subunits are at least partially responsible for the genetic predisposition to become a smoker. The habenula is linked not only to nicotine, but also to the effects of several other drugs. We postulate that the continuous use of drugs of abuse results in habenular hyperactivity as a compensatory mechanism for artificially elevated dopamine release. Drug withdrawal would then result in non-compensated habenular hyperactivity, and could be thought of as a state of continuous disappointment (or a negative emotional state), driving repeated drug use. We believe that drugs that alter habenular activity may be effective therapies against tobacco smoke and drug addiction in general.

Characterizing white matter changes in cigarette smokers via diffusion tensor imaging.

BACKGROUND Tobacco use remains the most preventable cause of death; however, its effects on the brain, and particularly white matter, remain elusive. Previous diffusion tensor imaging (DTI) studies have failed to yield consistent findings, with some reporting elevated measures of fractional anisotropy (FA) and others reporting lowered FA. METHODS In our study, we sought to elucidate the effects of tobacco on white matter by using enhanced imaging acquisition parameters and multiple analysis methods, including tract-based spatial statistics (TBSS) with crossing fiber measures and probabilistic tractography. RESULTS Our TBSS results revealed that chronic cigarette smokers have decreased FA in corpus callosum and bilateral anterior internal capsule, as well as specific reduced anisotropy in the two major fiber directions in a crossing fiber model. Further, our tractography results indicated that smokers have decreased FA in tracts projecting to the frontal cortex from (1) nucleus accumbens, (2) habenula, and (3) motor cortex. We also observed that smokers have greater disruptions in those regions when they had recently smoked compared to when they abstained from smoking for 24h. Our results also support previous evidence showing hemispheric asymmetry, with greater damage to the left side compared to the right. CONCLUSIONS These findings provide more conclusive evidence of white matter disruptions caused by nicotine use. By better understanding the neural disruptions correlating with cigarette smoking we can elucidate the addictive course and explore targeted treatment regimens for nicotine dependence.

High resolution single particle refinement in EMAN2.1

EMAN2.1 is a complete image processing suite for quantitative analysis of grayscale images, with a primary focus on transmission electron microscopy, with complete workflows for performing high resolution single particle reconstruction, 2-D and 3-D heterogeneity analysis, random conical tilt reconstruction and subtomogram averaging, among other tasks. In this manuscript we provide the first detailed description of the high resolution single particle analysis pipeline and the philosophy behind its approach to the reconstruction problem. High resolution refinement is a fully automated process, and involves an advanced set of heuristics to select optimal algorithms for each specific refinement task. A gold standard FSC is produced automatically as part of refinement, providing a robust resolution estimate for the final map, and this is used to optimally filter the final CTF phase and amplitude corrected structure. Additional methods are in-place to reduce model bias during refinement, and to permit cross-validation using other computational methods.

Hippocampal volume and the rapid antidepressant effect of ketamine.

Accumulating evidence underscores the utility of ketamine in treating severely treatment-resistant depressed patients. We investigated the relationship between the rapid antidepressant effects of ketamine and hippocampal volume, a biomarker of antidepressant treatment outcome. We gave 16 medication-free, major depressive disorder (MDD) patients a single, sub-anesthetic dose infusion of ketamine (0.5 mg/kg, over 40 min). We assessed depression severity pre-treatment, and at 24 h post-treatment, with the Montgomery-Åsberg Depression Rating Scale (MADRS). Prior to treatment, patients underwent magnetic resonance imaging (MRI) to estimate their hippocampal volume: We obtained viable MRI data in 13 patients. Delta MADRS (post- minus pre-treatment) was significantly correlated with the pre-treatment volumes of the left hippocampus (r = 0.66; p = 0.01), but not the right hippocampus (r = 0.49; p = 0.09). The correlation between delta MADRS and the left hippocampus remained high (r > 0.6; p = 0.13), after controlling for several demographic and clinical variables, although the p value increased due to the reduced degree of freedom (df = 5). Ketamine exerts enhanced antidepressant effects in patients with a relatively smaller hippocampus, a patient population that has been repeatedly shown to be refractory to traditional antidepressants.

Alterations in interhemispheric functional and anatomical connectivity are associated with tobacco smoking in humans

Abnormal interhemispheric functional connectivity correlates with several neurologic and psychiatric conditions, including depression, obsessive-compulsive disorder, schizophrenia, and stroke. Abnormal interhemispheric functional connectivity also correlates with abuse of cannabis and cocaine. In the current report, we evaluated whether tobacco abuse (i.e., cigarette smoking) is associated with altered interhemispheric connectivity. To that end, we examined resting state functional connectivity (RSFC) using magnetic resonance imaging (MRI) in short term tobacco deprived and smoking as usual tobacco smokers, and in non-smoker controls. Additionally, we compared diffusion tensor imaging (DTI) in the same subjects to study differences in white matter. The data reveal a significant increase in interhemispheric functional connectivity in sated tobacco smokers when compared to controls. This difference was larger in frontal regions, and was positively correlated with the average number of cigarettes smoked per day. In addition, we found a negative correlation between the number of DTI streamlines in the genual corpus callosum and the number of cigarettes smoked per day. Taken together, our results implicate changes in interhemispheric functional and anatomical connectivity in current cigarette smokers.

Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography.

Single particle cryo-electron tomography (cryoSPT) extracts features from cryo-electron tomograms, followed by 3D classification, alignment and averaging to generate improved 3D density maps of such features. Robust methods to correct for the contrast transfer function (CTF) of the electron microscope are necessary for cryoSPT to reach its resolution potential. Many factors can make CTF correction for cryoSPT challenging, such as lack of eucentricity of the specimen stage, inherent low dose per image, specimen charging, beam-induced specimen motions, and defocus gradients resulting both from specimen tilting and from unpredictable ice thickness variations. Current CTF correction methods for cryoET make at least one of the following assumptions: that the defocus at the center of the image is the same across the images of a tiltseries, that the particles all lie at the same Z-height in the embedding ice, and/or that the specimen, the cryo-electron microscopy (cryoEM) grid and/or the carbon support are flat. These experimental conditions are not always met. We have developed a CTF correction algorithm for cryoSPT without making any of the aforementioned assumptions. We also introduce speed and accuracy improvements and a higher degree of automation to the subtomogram averaging algorithms available in EMAN2. Using motion-corrected images of isolated virus particles as a benchmark specimen, recorded with a DE20 direct detection camera, we show that our CTF correction and subtomogram alignment routines can yield subtomogram averages close to 4/5 Nyquist frequency of the detector under our experimental conditions.