Faculty Bibliography

In the past two decades, major breakthroughs that improve our understanding of the pathophysiology and therapy of kidney stones (KS) have been lacking. The disease continues to be challenging for patients, physicians, and healthcare systems alike. In this context, epidemiological studies are striving to elucidate the worldwide changes in the patterns and the burden of the disease and identify modifiable risk factors that contribute to the development of kidney stones. Our expanding knowledge of the epidemiology of kidney stones is of paramount importance and largely upgrades the modern management of the disease. In this paper, we review the variables affecting prevalence and incidence, including age, gender, race, ethnicity, occupation, climate, geography, systemic diseases, diabetes, vascular disease, chronic kidney disease, and dietary risk factors relevant to kidney stones.

Brain accumulation of soluble oligomers of the amyloid-β peptide (AβOs) has been implicated in synapse failure and memory impairment in Alzheimer's disease. Here, we initially show that treatment with NUsc1, a single-chain variable fragment antibody (scFv) that selectively targets a subpopulation of AβOs and shows minimal reactivity to Aβ monomers and fibrils, prevents the inhibition of long-term potentiation in hippocampal slices and memory impairment induced by AβOs in mice. As a therapeutic approach for intracerebral antibody delivery, we developed an adeno-associated virus vector to drive neuronal expression of NUsc1 (AAV-NUsc1) within the brain. Transduction by AAV-NUsc1 induced NUsc1 expression and secretion in adult human brain slices, and inhibited AβO binding to neurons and AβO-induced loss of dendritic spine loss in primary rat hippocampal cultures. Treatment of mice with AAV-NUsc1 prevented memory impairment induced by AβOs and, remarkably, reversed memory deficits in aged APPswe/PS1ΔE9 Alzheimer's disease model mice. These results support the feasibility of immunotherapy using viral vector-mediated gene delivery of NUsc1 or other AβO-specific single-chain antibodies as a potential therapeutic approach in Alzheimer's disease.

To adapt to their environments, animals learn associations between sensory stimuli and unconditioned stimuli. In invertebrates, olfactory associative learning primarily occurs in the mushroom body, which is segregated into separate compartments. Within each compartment, Kenyon cells (KCs) encoding sparse odor representations project onto mushroom body output neurons (MBONs) whose outputs guide behavior. Associated with each compartment is a dopamine neuron (DAN) that modulates plasticity of the KC-MBON synapses within the compartment. Interestingly, DAN-induced plasticity of the KC-MBON synapse is imbalanced in the sense that it only weakens the synapse and is temporally sparse. We propose a normative mechanistic model of the MBON as a linear discriminant analysis (LDA) classifier that predicts the presence of an unconditioned stimulus (class identity) given a KC odor representation (feature vector). Starting from a principled LDA objective function and under the assumption of temporally sparse DAN activity, we derive an online algorithm which maps onto the mushroom body compartment. Our model accounts for the imbalanced learning at the KC-MBON synapse and makes testable predictions that provide clear contrasts with existing models.

Recent experiments have revealed that neural population codes in many brain areas continuously change even when animals have fully learned and stably perform their tasks. This representational 'drift' naturally leads to questions about its causes, dynamics and functions. Here we explore the hypothesis that neural representations optimize a representational objective with a degenerate solution space, and noisy synaptic updates drive the network to explore this (near-)optimal space causing representational drift. We illustrate this idea and explore its consequences in simple, biologically plausible Hebbian/anti-Hebbian network models of representation learning. We find that the drifting receptive fields of individual neurons can be characterized by a coordinated random walk, with effective diffusion constants depending on various parameters such as learning rate, noise amplitude and input statistics. Despite such drift, the representational similarity of population codes is stable over time. Our model recapitulates experimental observations in the hippocampus and posterior parietal cortex and makes testable predictions that can be probed in future experiments.

The lateral entorhinal cortex (LEC) provides multisensory information to the hippocampus, directly to the distal dendrites of CA1 pyramidal neurons. LEC neurons perform important functions for episodic memory processing, coding for contextually salient elements of an environment or experience. However, we know little about the functional circuit interactions between the LEC and the hippocampus. We combine functional circuit mapping and computational modeling to examine how long-range glutamatergic LEC projections modulate compartment-specific excitation-inhibition dynamics in hippocampal area CA1. We demonstrate that glutamatergic LEC inputs can drive local dendritic spikes in CA1 pyramidal neurons, aided by the recruitment of a disinhibitory VIP interneuron microcircuit. Our circuit mapping and modeling further reveal that LEC inputs also recruit CCK interneurons that may act as strong suppressors of dendritic spikes. These results highlight a cortically driven GABAergic microcircuit mechanism that gates nonlinear dendritic computations, which may support compartment-specific coding of multisensory contextual features within the hippocampus.

The amygdala has long held the center seat in the neural basis of threat conditioning. However, a rapidly growing literature has elucidated extra-amygdala circuits in this process, highlighting the sensory cortex for its critical role in the mnemonic aspect of the process. While this literature is largely focused on the auditory system, substantial human and rodent findings on the olfactory system have emerged. The unique nature of the olfactory neuroanatomy and its intimate association with emotion compels a review of this recent literature to illuminate its special contribution to threat memory. Here, integrating recent evidence in humans and animal models, we posit that the olfactory (piriform) cortex is a primary and necessary component of the distributed threat memory network, supporting mnemonic ensemble coding of acquired threat. We further highlight the basic circuit architecture of the piriform cortex characterized by distributed, auto-associative connections, which is prime for highly efficient content-addressable memory computing to support threat memory. Given the primordial role of the piriform cortex in cortical evolution and its simple, well-defined circuits, we propose that olfaction can be a model system for understanding (transmodal) sensory cortical mechanisms underlying threat memory.

A major therapeutic goal in demyelinating diseases, such as Multiple Sclerosis, is to improve remyelination, thereby restoring effective axon conduction and preventing neurodegeneration. In the adult central nervous system (CNS), parenchymal oligodendrocyte progenitor cells (pOPCs) and, to a lesser extent, pre-existing oligodendrocytes (OLs) and oligodendrocytes generated from neural stem cells (NSCs) in the sub-ventricular zone (SVZ) are capable of forming new myelin sheaths. Due to their self-renewal capabilities and the ability of their progeny to migrate widely within the CNS, NSCs represent an additional source of remyelinating cells that may be targeted to supplement repair by pOPCs. However, in demyelinating disorders and disease models, the NSC contribution to myelin repair is modest and most evident in regions close to the SVZ. We hypothesized that NSC-derived cells may compete with OPCs to remyelinate the same axons, with pOPCs serving as the primary remyelinating cells due to their widespread distribution within the adult CNS, thereby limiting the contribution of NSC-progeny. Here, we have used a dual reporter, genetic fate mapping strategy, to characterize the contribution of pOPCs and NSC-derived OLs to remyelination after cuprizone-induced demyelination. We confirmed that, while pOPCs are the main remyelinating cells in the corpus callosum, NSC-derived cells are also activated and recruited to demyelinating lesions. Blocking pOPC differentiation genetically, resulted in a significant increase in the recruitment NSC-derived cells into the demyelinated corpus callosum and their differentiation into OLs. These results strongly suggest that pOPCs and NSC-progeny compete to repair white matter lesions. They underscore the potential significance of targeting NSCs to improve repair when the contribution of pOPCs is insufficient to affect full remyelination.

Pain is driven by sensation and emotion, and in turn, it motivates decisions and actions. To fully appreciate the multidimensional nature of pain, we formulate the study of pain within a closed-loop framework of sensory-motor prediction. In this closed-loop cycle, prediction plays an important role, as the interaction between prediction and actual sensory experience shapes pain perception and subsequently, action. In this Perspective, we describe the roles of two prominent computational theories-Bayesian inference and reinforcement learning-in modeling adaptive pain behaviors. We show that prediction serves as a common theme between these two theories, and that each of these theories can explain unique aspects of the pain perception-action cycle. We discuss how these computational theories and models can improve our mechanistic understandings of pain-centered processes such as anticipation, attention, placebo hypoalgesia, and pain chronification.

Fluorescent protein biomaterials have important applications such as bioimaging in pharmacological studies. Self-assembly of proteins, especially into fibrils, is known to produce fluorescence in the blue band. Capable of self-assembly into nanofibers, we have shown we can modulate its aggregation into mesofibers by encapsulation of a small hydrophobic molecule. Conversely, azobenzenes are hydrophobic small molecules that are virtually non-fluorescent in solution due to their highly efficient photoisomerization. However, they demonstrate fluorogenic properties upon confinement in nanoscale assemblies by reducing the non-radiative photoisomerization. Here, we report the fluorescence of a hybrid protein-small molecule system in which azobenzene is confined in our protein assembly leading to fiber thickening and increased fluorescence. We show our engineered protein Q encapsulates AzoCholine, bearing a photoswitchable azobenzene moiety, in the hydrophobic pore to produce fluorescent mesofibers. This study further investigates the photocontrol of protein conformation as well as fluorescence of an azobenze-containing biomaterial.