Faculty Bibliography

Tau plays a pivotal role in the pathogenesis of neurodegenerative disorders: mutations in the gene encoding for tau (MAPT) are linked to Fronto-temporal Dementia (FTD) and hyper-phosphorylated aggregates of tau forming neurofibrillary tangles (NFTs) that constitute a pathological hallmark of Alzheimer disease (AD) and FTD. Accordingly, tau is a favored therapeutic target for the treatment of these diseases. Given the criticality of tau to dementia's pathogenesis and therapy, it is important to understand the physiological function of tau in the central nervous system. Analysis of Mapt knock out (Mapt^-/-) mice has yielded inconsistent results. Some studies have shown that tau deletion does not alter memory while others have described synaptic plasticity and memory alterations in Mapt^-/- mice. To help clarifying these contrasting results, we analyzed a distinct Mapt^-/- model on a B6129PF3/J genetic background. We found that tau deletion leads to aging-dependent short-term memory deficits, hyperactivity and synaptic plasticity defects. In contrast, Mapt^+/- mice only showed a mild short memory deficit in the novel object recognition task. Thus, while tau is important for normal neuronal functions underlying learning and memory, partial reduction of tau expression may have fractional deleterious effects.

Inhibitory interneurons represent 10-15% of the neurons in the somatosensory cortex, and their activity powerfully shapes sensory processing. Three major groups of GABAergic interneurons have been defined according to developmental, molecular, morphological, electrophysiological, and synaptic features. Dendritic-targeting somatostatin-expressing interneurons (SST-INs) have been shown to display diverse morphological, electrophysiological and molecular properties and activity patterns in vivo. However, the correlation between these properties and SST-IN subtype is unclear. In this study we aimed to correlate the morphological diversity of layer 5 (L5) SST-INs with their electrophysiological and molecular diversity in mice of either sex. Our morphological analysis demonstrated the existence of three subtypes of L5 SST-INs with distinct electrophysiological properties: T-shaped Martinotti cells innervate L1, and are low-threshold spiking; fanning-out Martinotti cells innervate L2/3 and the lower half of L1, and show adapting firing patterns; non-Martinotti cells innervate L4, and show a quasi-fast spiking firing pattern. We estimated the proportion of each subtype in L5 and found that T-shaped Martinotti, fanning-out Martinotti and Non-Martinotti cells represent ∼10, ∼50 and ∼40% of L5 SST-INs, respectively. Lastly we examined the connectivity between the three SST-IN subtypes and L5 pyramidal cells (PCs). We found that L5 T-shapped Martinotti cells inhibit the L1 apical tuft of nearby PCs; L5 fanning-out Martinotti cells also inhibit nearby PCs but they target the dendrite mainly in L2/3. On the other hand non-Martinotti cells inhibit the dendrites of L4 neurons while avoiding L5 PCs. Our data suggest that morphologically distinct SST-INs gate different excitatory inputs in the barrel cortex.SIGNIFICANCE STATEMENTMorphologically diverse layer 5 SST-INs show different patterns of activity in behaving animals. However, little is known about the abundance and connectivity of each morphological type and the correlation between morphological subtype and spiking properties. We demonstrate a correlation between the morphological and electrophysiological diversity of layer 5 SST-INs. Based on these findings we built a classifier to infer the abundance of each morphological subtype. Lastly, using paired recordings combined with morphological analysis, we investigated the connectivity of each morphological subtype. Our data suggest that, by targeting different cell types and cellular compartments, morphologically diverse SST-INs might gate different excitatory inputs in the mouse barrel cortex.

With ever-increasing advancements in technology, neuroscientists are able to collect data in greater volumes and with finer resolution. The bottleneck in understanding how the brain works is consequently shifting away from the amount and type of data we can collect and toward what we actually do with the data. There has been a growing interest in leveraging this vast volume of data across levels of analysis, measurement techniques, and experimental paradigms to gain more insight into brain function. Such efforts are visible at an international scale, with the emergence of big data neuroscience initiatives, such as the BRAIN initiative (Bargmann et al., 2014), the Human Brain Project, the Human Connectome Project, and the National Institute of Mental Health's Research Domain Criteria initiative. With these large-scale projects, much thought has been given to data-sharing across groups (Poldrack and Gorgolewski, 2014; Sejnowski et al., 2014); however, even with such data-sharing initiatives, funding mechanisms, and infrastructure, there still exists the challenge of how to cohesively integrate all the data. At multiple stages and levels of neuroscience investigation, machine learning holds great promise as an addition to the arsenal of analysis tools for discovering how the brain works.

We demonstrate that cortical interneurons derived from ventral eminences, including the caudal ganglionic eminence, undergo programmed cell death. Moreover, with the exception of VIP interneurons, this occurs in a manner that is activity-dependent. In addition, we demonstrate that, within interneurons, Calcineurin, a calcium-dependent protein phosphatase, plays a critical role in sequentially linking activity to maturation (E15-P5) and survival (P5-P20). Specifically, embryonic inactivation of Calcineurin results in a failure of interneurons to morphologically mature and prevents them from undergoing apoptosis. By contrast, early postnatal inactivation of Calcineurin increases apoptosis. We conclude that Calcineurin serves a dual role of promoting first the differentiation of interneurons and, subsequently, their survival.

Walking is the predominant locomotor behavior expressed by land-dwelling vertebrates, but it is unknown when the neural circuits that are essential for limb control first appeared. Certain fish species display walking-like behaviors, raising the possibility that the underlying circuitry originated in primitive marine vertebrates. We show that the neural substrates of bipedalism are present in the little skate Leucoraja erinacea, whose common ancestor with tetrapods existed ∼420 million years ago. Leucoraja exhibits core features of tetrapod locomotor gaits, including left-right alternation and reciprocal extension-flexion of the pelvic fins. Leucoraja also deploys a remarkably conserved Hox transcription factor-dependent program that is essential for selective innervation of fin/limb muscle. This network encodes peripheral connectivity modules that are distinct from those used in axial muscle-based swimming and has apparently been diminished in most modern fish. These findings indicate that the circuits that are essential for walking evolved through adaptation of a genetic regulatory network shared by all vertebrates with paired appendages. VIDEO ABSTRACT.

The axon initial segment (AIS) is the site of action potential generation and a locus of activity-dependent homeostatic plasticity. A multimeric complex of sodium channels, linked via a cytoskeletal scaffold of ankyrin G and beta IV spectrin to submembranous actin rings, mediates these functions. The mechanisms that specify the AIS complex to the proximal axon and underlie its plasticity remain poorly understood. Here we show phosphorylated myosin light chain (pMLC), an activator of contractile myosin II, is highly enriched in the assembling and mature AIS, where it associates with actin rings. MLC phosphorylation and myosin II contractile activity are required for AIS assembly, and they regulate the distribution of AIS components along the axon. pMLC is rapidly lost during depolarization, destabilizing actin and thereby providing a mechanism for activity-dependent structural plasticity of the AIS. Together, these results identify pMLC/myosin II activity as a common link between AIS assembly and plasticity.

Forming valid predictions about the environment is crucial to survival. However, whether humans are able to form valid predictions about natural stimuli based on their temporal statistical regularities remains unknown. Here we presented subjects with tone sequences whose pitch fluctuation over time capture long-range temporal dependence structures prevalent in natural stimuli. We found that subjects were able to exploit such naturalistic statistical regularities to make valid predictions about upcoming items in a sequence. Magnetoencephalography (MEG) recordings revealed that slow, arrhythmic cortical dynamics tracked the evolving pitch sequence over time such that neural activity at a given moment was influenced by the pitch of up to seven previous tones. Importantly, such history integration contained in neural activity predicted the expected pitch of the upcoming tone, providing a concrete computational mechanism for prediction. These results establish humans' ability to make valid predictions based on temporal regularities inherent in naturalistic stimuli and further reveal the neural mechanisms underlying such predictive computation.SIGNIFICANCE STATEMENTA fundamental question in neuroscience is how the brain predicts upcoming events in the environment. To date, this question has primarily been addressed in experiments using relatively simple stimulus sequences. Here, we study predictive processing in the human brain using auditory tone sequences that exhibit temporal statistical regularities similar to those found in natural stimuli. We observed that humans are able to form valid predictions based on such complex temporal statistical regularities. We further show that neural response to a given tone in the sequence reflects integration over the preceding tone sequence, and that this history dependence forms the foundation for prediction. These findings deepen our understanding of how humans form predictions in an ecologically valid environment.

The energetic costs of behavioral chronic stress are unlikely to be sustainable without neuronal plasticity. Mitochondria have the capacity to handle synaptic activity up to a limit before energetic depletion occurs. Protective mechanisms driven by the induction of neuronal genes likely evolved to buffer the consequences of chronic stress on excitatory neurons in prefrontal cortex (PFC), as this circuitry is vulnerable to excitotoxic insults. Little is known about the genes involved in mitochondrial adaptation to the build up of chronic stress. Using combinations of genetic manipulations and stress for analyzing structural, transcriptional, mitochondrial and behavioral outcomes, we characterized NR4A1 as a stress-inducible modifier of mitochondrial energetic competence and dendritic spine number in PFC. NR4A1 acted as transcription factor for changing the expression of target genes previously involved in mitochondrial uncoupling, AMPK activation and synaptic growth. Maintenance of NR4A1 activity by chronic stress played a critical role in the regressive synaptic organization in PFC of mouse models of stress (male only). Knockdown, dominant negative and knockout of NR4A1 in mice and rats (male only) protected pyramidal neurons against the adverse effects of chronic stress. In human PFC tissues of men and women, high levels of the transcriptionally-active NR4A1 correlated with measures of synaptic loss and cognitive impairment. In the context of chronic stress, prolonged expression and activity of NR4A1 may lead to responses of mitochondria and synaptic connectivity that do not match environmental demand, resulting in circuit malfunction between PFC and other brain regions constituting a pathological feature across disorders.SIGNIFICANCE STATEMENTThe bioenergetics cost of chronic stress is too high to be sustainable by pyramidal prefrontal neurons. Cellular checkpoints have evolved to adjust responses of mitochondria and synapses to the build up of chronic stress. NR4A1 plays such role by controlling mitochondria energetic competence with respect to synapse number. As an immediate-early gene, NR4A1 promotes neuronal plasticity but sustained expression or activity can be detrimental. NR4A1 expression and activity is sustained by chronic stress in animal models and in human studies of neuropathologies sensitive to the build up of chronic stress. Therefore, antagonism of NR4A1 is a promising avenue for preventing the regressive synaptic reorganization in cortical systems in the context of chronic stress.

The neuromuscular synapse is a relatively large synapse with hundreds of active zones in presynaptic motor nerve terminals and more than ten million acetylcholine receptors (AChRs) in the postsynaptic membrane. The enrichment of proteins in presynaptic and postsynaptic membranes ensures a rapid, robust, and reliable synaptic transmission. Over fifty years ago, classic studies of the neuromuscular synapse led to a comprehensive understanding of how a synapse looks and works, but these landmark studies did not reveal the molecular mechanisms responsible for building and maintaining a synapse. During the past two-dozen years, the critical molecular players, responsible for assembling the specialized postsynaptic membrane and regulating nerve terminal differentiation, have begun to be identified and their mechanism of action better understood. Here, we describe and discuss five of these key molecular players, paying heed to their discovery as well as describing their currently understood mechanisms of action. In addition, we discuss the important gaps that remain to better understand how these proteins act to control synaptic differentiation and maintenance.