Faculty Bibliography

BACKGROUND: The ventral midbrain contains a diverse array of neurons, including dopaminergic neurons of the ventral tegmental area (VTA) and substantia nigra (SN) and neurons of the red nucleus (RN). Dopaminergic and RN neurons have been shown to arise from ventral mesencephalic precursors that express Sonic Hedgehog (Shh). However, Shh expression, which is initially confined to the mesencephalic ventral midline, expands laterally and is then downregulated in the ventral midline. In contrast, expression of the Hedgehog target gene Gli1 initiates in the ventral midline prior to Shh expression, but after the onset of Shh expression it is expressed in precursors lateral to Shh-positive cells. Given these dynamic gene expression patterns, Shh and Gli1 expression could delineate different progenitor populations at distinct embryonic time points. RESULTS: We employed genetic inducible fate mapping (GIFM) to investigate whether precursors that express Shh (Shh-GIFM) or transduce Shh signaling (Gli1-GIFM) at different time points give rise to different ventral midbrain cell types. We find that precursors restricted to the ventral midline are labeled at embryonic day (E)7.5 with Gli1-GIFM, and with Shh-GIFM at E8.5. These precursors give rise to all subtypes of midbrain dopaminergic neurons and the anterior RN. A broader domain of progenitors that includes the ventral midline is marked with Gli1-GIFM at E8.5 and with Shh-GIFM at E9.5; these fate-mapped cells also contribute to all midbrain dopaminergic subtypes and to the entire RN. In contrast, a lateral progenitor domain that is labeled with Gli1-GIFM at E9.5 and with Shh-GIFM at E11.5 has a markedly reduced potential to give rise to the RN and to SN dopaminergic neurons, and preferentially gives rise to the ventral-medial VTA. In addition, cells derived from Shh- and Gli1-expressing progenitors located outside of the ventral midline give rise to astrocytes. CONCLUSIONS: We define a ventral midbrain precursor map based on the timing of Gli1 and Shh expression, and suggest that the diversity of midbrain dopaminergic neurons is at least partially determined during their precursor stage when their medial-lateral position, differential gene expression and the time when they leave the ventricular zone influence their fate decisions

Loline (1) is a small alkaloid that, in spite of its simple-looking structure, has posed surprising challenges to synthetic chemists. It has been known for more than a century and has been the subject of extensive biological investigations, but only two total syntheses have been achieved to date. Here, we report an asymmetric total synthesis of loline that, with less then ten steps, is remarkably short. Our synthesis incorporates a Sharpless epoxidation, a Grubbs olefin metathesis and an unprecedented transannular aminobromination, which converts an eight-membered cyclic carbamate into a bromopyrrolizidine. The synthesis is marked by a high degree of chemo- and stereoselectivity and gives access to several members of the loline alkaloid family. It delivers sufficient material to support a programme aimed at studying the complex interactions between plants, fungi, insects and bacteria brokered by loline alkaloids.

The false-suffocation hypothesis of panic disorder (Klein, 1993) suggested delta-opioid receptors as a possible source of the respiratory dysfunction manifested in panic attacks occurring in panic disorder (Preter and Klein, 2008). This study sought to determine if a lack of delta-opioid receptors in a mouse model affects respiratory response to elevated CO(2), and whether the response is modulated by benzodiazepines, which are widely used to treat panic disorder. In a whole-body plethysmograph, respiratory responses to 5% CO(2) were compared between delta-opioid receptor knockout mice and wild-type mice after saline, diazepam (1mg/kg), and alprazolam (0.3mg/kg) injections. The results show that lack of delta-opioid receptors does not affect normal response to elevated CO(2), but does prevent benzodiazepines from modulating that response. Thus, in the presence of benzodiazepine agonists, respiratory responses to elevated CO(2) were enhanced in delta-opioid receptor knockout mice compared to wild-type mice. This suggests an interplay between benzodiazepine receptors and delta-opioid receptors in regulating the respiratory effects of elevated CO(2), which might be related to CO(2) induced panic

Multichannel electroencephalography (EEG) offers a non-invasive tool to explore spatio-temporal dynamics of brain activity. With EEG recordings consisting of multiple trials, traditional signal processing approaches that ignore inter-trial variability in the data may fail to accurately estimate the underlying spatio-temporal brain patterns. Moreover, precise characterization of such inter-trial variability per se can be of high scientific value in establishing the relationship between brain activity and behavior. In this paper, a statistical modeling framework is introduced for learning spatio-temporal decompositions of multiple-trial EEG data recorded under two contrasting experimental conditions. By modeling the variance of source signals as random variables varying across trials, the proposed two-stage hierarchical Bayesian model is able to capture inter-trial amplitude variability in the data in a sparse way where a parsimonious representation of the data can be obtained. A variational Bayesian (VB) algorithm is developed for statistical inference of the hierarchical model. The efficacy of the proposed modeling framework is validated with the analysis of both synthetic and real EEG data. In the simulation study we show that even at low signal-to-noise ratios our approach is able to recover with high precision the underlying spatio-temporal patterns and the dynamics of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data.

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates

Tumor necrosis factor-alpha-converting enzyme (TACE; also known as ADAM17) is a proteolytic sheddase that is responsible for the cleavage of several membrane-bound molecules. We report that TACE cleaves neuregulin-1 (NRG1) type III in the epidermal growth factor domain, probably inactivating it (as assessed by deficient activation of the phosphatidylinositol-3-OH kinase pathway), and thereby negatively regulating peripheral nervous system (PNS) myelination. Lentivirus-mediated knockdown of TACE in vitro in dorsal root ganglia neurons accelerates the onset of myelination and results in hypermyelination. In agreement, motor neurons of conditional knockout mice lacking TACE specifically in these cells are significantly hypermyelinated, and small-caliber fibers are aberrantly myelinated. Further, reduced TACE activity rescues hypomyelination in NRG1 type III haploinsufficient mice in vivo. We also show that the inhibitory effect of TACE is neuron-autonomous, as Schwann cells lacking TACE elaborate myelin of normal thickness. Thus, TACE is a modulator of NRG1 type III activity and is a negative regulator of myelination in the PNS.

How complex networks of activators and repressors lead to exquisitely specific cell-type determination during development is poorly understood. In the Drosophila eye, expression patterns of Rhodopsins define at least eight functionally distinct though related subtypes of photoreceptors. Here, we describe a role for the transcription factor gene defective proventriculus (dve) as a critical node in the network regulating Rhodopsin expression. dve is a shared component of two opposing, interlocked feedforward loops (FFLs). Orthodenticle and Dve interact in an incoherent FFL to repress Rhodopsin expression throughout the eye. In R7 and R8 photoreceptors, a coherent FFL relieves repression by Dve while activating Rhodopsin expression. Therefore, this network uses repression to restrict and combinatorial activation to induce cell-type-specific expression. Furthermore, Dve levels are finely tuned to yield cell-type- and region-specific repression or activation outcomes. This interlocked FFL motif may be a general mechanism to control terminal cell-fate specification.

Rationale: Posttranslational phosphorylation of connexin43 (Cx43) has been proposed as a key regulatory event in normal cardiac gap junction expression and pathological gap junction remodeling. Nonetheless, the role of Cx43 phosphorylation in the context of the intact organism is poorly understood. Objective: To establish whether specific Cx43 phosphorylation events influence gap junction expression and pathological remodeling. Methods and Results: We generated Cx43 germline knock-in mice in which serines 325/328/330 were replaced with phosphomimetic glutamic acids (S3E) or nonphosphorylatable alanines (S3A). The S3E mice were resistant to acute and chronic pathological gap junction remodeling and displayed diminished susceptibility to the induction of ventricular arrhythmias. Conversely, the S3A mice showed deleterious effects on cardiac gap junction formation and function, developed electric remodeling, and were highly susceptible to inducible arrhythmias. Conclusions: These data demonstrate a mechanistic link between posttranslational phosphorylation of Cx43 and gap junction formation, remodeling, and arrhythmic susceptibility

Hippocampal sharp waves (SPWs) and associated fast ('ripple') oscillations (SPW-Rs) in the CA1 region are among the most synchronous physiological patterns in the mammalian brain. Using two-dimensional arrays of electrodes for recording local field potentials and unit discharges in freely moving rats, we studied the emergence of ripple oscillations (140-220 Hz) and compared their origin and cellular-synaptic mechanisms with fast gamma oscillations (90-140 Hz). We show that (1) hippocampal SPW-Rs and fast gamma oscillations are quantitatively distinct patterns but involve the same networks and share similar mechanisms; (2) both the frequency and magnitude of fast oscillations are positively correlated with the magnitude of SPWs; (3) during both ripples and fast gamma oscillations the frequency of network oscillation is higher in CA1 than in CA3; and (4) the emergence of CA3 population bursts, a prerequisite for SPW-Rs, is biased by activity patterns in the dentate gyrus and entorhinal cortex, with the highest probability of ripples associated with an 'optimum' level of dentate gamma power. We hypothesize that each hippocampal subnetwork possesses distinct resonant properties, tuned by the magnitude of the excitatory drive

Task-based neuroimaging studies face the challenge of developing tasks capable of equivalently probing reading networks across different age groups. Resting-state fMRI, which requires no specific task, circumvents these difficulties. Here, in 25 children (8-14 years) and 25 adults (21-46 years), we examined the extent to which individual differences in reading competence can be related to resting-state functional connectivity (RSFC) of regions implicated in reading. In both age groups, reading standard scores correlated positively with RSFC between the left precentral gyrus and other motor regions, and between Broca's and Wernicke's areas. This suggests that, regardless of age group, stronger coupling among motor regions, as well as between language/speech regions, subserves better reading, presumably reflecting automatized articulation. We also observed divergent RSFC-behavior relationships in children and adults, particularly those anchored in the left fusiform gyrus (FFG) (the visual word form area). In adults, but not children, better reading performance was associated with stronger positive correlations between FFG and phonology-related regions (Broca's area and the left inferior parietal lobule), and with stronger negative relationships between FFG and regions of the 'task-negative' default network. These results suggest that both positive RSFC (functional coupling) between reading regions and negative RSFC (functional segregation) between a reading region and default network regions are important for automatized reading, characteristic of adult readers. Together, our task-independent RSFC findings highlight the importance of appreciating developmental changes in the neural correlates of reading competence, and suggest that RSFC may serve to facilitate the identification of reading disorders in different age groups