Faculty Bibliography

Motor axons receive retrograde signals from skeletal muscle that are essential for the differentiation and stabilization of motor nerve terminals. Identification of these retrograde signals has proved elusive, but their production by muscle depends on the receptor tyrosine kinase, MuSK (muscle, skeletal receptor tyrosine-protein kinase), and Lrp4 (low-density lipoprotein receptor (LDLR)-related protein 4), an LDLR family member that forms a complex with MuSK, binds neural agrin and stimulates MuSK kinase activity. Here we show that Lrp4 also functions as a direct muscle-derived retrograde signal for early steps in presynaptic differentiation. We demonstrate that Lrp4 is necessary, independent of MuSK activation, for presynaptic differentiation in vivo, and we show that Lrp4 binds to motor axons and induces clustering of synaptic-vesicle and active-zone proteins. Thus, Lrp4 acts bidirectionally and coordinates synapse formation by binding agrin, activating MuSK and stimulating postsynaptic differentiation, and functioning in turn as a muscle-derived retrograde signal that is necessary and sufficient for presynaptic differentiation.

Sleep is composed of an alternating sequence of REM and non-REM episodes, but their respective roles are not known. We found that the overall firing rates of hippocampal CA1 neurons decreased across sleep concurrent with an increase in the recruitment of neuronal spiking to brief "ripple" episodes, resulting in a net increase in neural synchrony. Unexpectedly, within non-REM episodes, overall firing rates gradually increased together with a decrease in the recruitment of spiking to ripples. The rate increase within non-REM episodes was counteracted by a larger and more rapid decrease of discharge frequency within the interleaved REM episodes. Both the decrease in firing rates and the increase in synchrony during the course of sleep were correlated with the power of theta activity during REM episodes. These findings assign a prominent role of REM sleep in sleep-related neuronal plasticity.

Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity(1,2), the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method(3 )to assess the neural representation of the subjective values of risky and ambiguous options(4). This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations. In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.

Dopamine (DA) transporter (DAT) imaging has been studied as a diagnostic tool for degenerative parkinsonism. Our aim was to measure the prognostic value of imaging for motor and nonmotor outcomes in Parkinson's disease (PD). We prospectively evaluated a Parkinson's cohort after enrollment in a de novo clinical trial with a battery of motor (UPDRS), cognitive (Montreal Cognitive Assessment), and behavioral measures. DAT imaging with [(123)I][beta]-CIT and single-photon emission computerized tomography (SPECT) was performed at baseline and after 22 months. In total, 491 (91%) of the 537 subjects had evidence of DA deficiency on their baseline scan, consistent with PD, and were included in the analyses. The cohort was followed for 5.5 (0.8) years, with a mean duration of diagnosis of 6.3 (1.2). Lower striatal binding at baseline was independently associated with higher risk for clinical milestones and measures of disease severity, including motor-related disability, falling and postural instability, cognitive impairment, psychosis, and clinically important depressive symptoms. Subjects in the bottom quartile for striatal binding, compared to the top quartile, had an odds ratio (95% confidence interval) of 3.3 (1.7, 6.7) for cognitive impairment and 12.9 (2.6, 62.4) for psychosis. Change from baseline in imaging after 22 months was also independently associated with motor, cognitive, and behavioral outcomes. DAT imaging with [(123)I][beta]-CIT and SPECT, shortly after the diagnosis of PD, was independently associated with clinically important long-term motor and nonmotor outcomes. These results should be treated as hypothesis generating and require confirmation.

Neurophysiological evidence suggests that a specialized cortical network is involved in the visual perception of biological motion; however, the temporal dynamics underlying this network is largely unexplored. We used magnetoencephalography to determine the spatial distribution and task-related temporal dynamics of the oscillatory activity of random and human motion. We recorded cortical responses in healthy adults while they passively viewed point-light displays of static dots, random, and human motion. By analyzing differences in the time-frequency distributions between pairs of conditions, we found that: (a) the perception of both motion conditions resulted in a significant decrease in the alpha/beta band in the right superior occipital gyrus and a significant decrease in the beta band in the right insula and (b) the human motion condition was associated with specific alterations in alpha, beta, and gamma bands with significant reductions in the alpha band in the right superior temporal gyrus, right precuneus, and left inferior parietal lobule, significant reductions in the beta band in the bilateral superior temporal gyrus, together with a significant increase in the gamma band in the left inferior parietal lobule and superior temporal regions. These data suggest that although the perception of both random and human motion involves desynchronization of oscillatory activity in alpha and beta bands in similar cortical regions, only human motion is associated with a larger network and significant alterations in the alpha/beta band particularly in the right hemisphere.

There are two views on vertebrate retinogenesis: a deterministic model dependent on fixed lineages and a stochastic model in which choices of division modes and cell fates cannot be predicted. In this issue of Neuron, He et al. (2012) address this question in zebrafish using live imaging and mathematical modeling.

The conventional view of AD (Alzheimer's disease) is that much of the pathology is driven by an increased load of beta-amyloid in the brain of AD patients (the 'Amyloid Hypothesis'). Yet, many therapeutic strategies based on lowering beta-amyloid have so far failed in clinical trials. This failure of beta-amyloid-lowering agents has caused many to question the Amyloid Hypothesis itself. However, AD is likely to be a complex disease driven by multiple factors. In addition, it is increasingly clear that beta-amyloid processing involves many enzymes and signalling pathways that play a role in a diverse array of cellular processes. Thus the clinical failure of beta-amyloid-lowering agents does not mean that the hypothesis itself is incorrect; it may simply mean that manipulating beta-amyloid directly is an unrealistic strategy for therapeutic intervention, given the complex role of beta-amyloid in neuronal physiology. Another possible problem may be that toxic beta-amyloid levels have already caused irreversible damage to downstream cellular pathways by the time dementia sets in. We argue in the present review that a more direct (and possibly simpler) approach to AD therapeutics is to rescue synaptic dysfunction directly, by focusing on the mechanisms by which elevated levels of beta-amyloid disrupt synaptic physiology.

The variecolortides are a family of unusual natural products that combine motifs from a variety of biosynthetic streams. Herein, we present the gradual evolution of a convergent synthetic strategy that ultimately culminated in a reaction cascade featuring a hydrogen shift and a cycloaddition followed by a spontaneous air oxidation. Attempts to link an anthrone building block with an exo-methylene diketopiperazine using radical chemistry were ultimately unsuccessful, but led to interesting observations that shaped our successful strategy. The total synthesis of variecolortide C is presented for the first time.

Learning disabilities and other cognitive disorders represent one of the most important unmet medical needs and a significant source of lifelong disability. To accelerate progress in this area, an international consortium of researchers and clinicians, the Learning Disabilities Network (LeaDNet), was established in 2006. Initially, LeaDNet focused on neurofibromatosis type 1 (NF1), a common single gene disorder with a frequency of 1:3,000. Although NF1 is best recognized as an inherited tumor predisposition syndrome, learning, cognitive, and neurobehavioral deficits account for significant morbidity in this condition and can have a profound impact on the quality of life of affected individuals. Recently, there have been groundbreaking advances in our understanding of the molecular, cellular, and neural systems underpinnings of NF1-associated learning deficits in animal models, which precipitated clinical trials using a molecularly targeted treatment for these deficits. However, much remains to be learned about the spectrum of cognitive, neurological, and psychiatric phenotypes associated with the NF1 clinical syndrome. In addition, there is a pressing need to accelerate the identification of specific clinical targets and treatments for these phenotypes. The successes with NF1 have allowed LeaDNet investigators to broaden their initial focus to other genetic disorders characterized by learning disabilities and cognitive deficits including other RASopathies (caused by changes in the Ras signaling pathway). The ultimate mission of LeaDNet is to leverage an international translational consortium of clinicians and neuroscientists to integrate bench-to-bedside knowledge across a broad range of cognitive genetic disorders, with the goal of accelerating the development of rational and biologically based treatments.