Sporadic late-onset Alzheimer’s disease (LOAD), the most common form of dementia in the elderly, causes progressive and severe loss of cognitive abilities. With greater numbers of people living to advanced ages, LOAD will increasingly burden both the healthcare system and society. There are currently no available disease-modifying therapies, and the failure of several recent pathology-based strategies has highlighted the urgent need for effective therapeutic targets. With aging as the greatest risk factor for LOAD, targeting mechanisms by which aging contributes to disease could prove an effective strategy to delay progression to clinical dementia by intervention in elderly individuals in an early prodromal stage of disease. Excess neural activity in the hippocampus, a recently described phenomenon associated with age-dependent memory loss, was first identified in animal models of aging and subsequently translated to clinical conditions of aging and early-stage LOAD. Critically, elevated activity was similarly localized to specific circuits within the hippocampal formation in aged animals and humans. Here we review evidence for hippocampal hyperactivity as a significant contributor to age-dependent cognitive decline and the progressive accumulation of pathology in LOAD. We also describe studies demonstrating the efficacy of reducing hyperactivity with an initial test therapy, levetiracetam (Keppra), an atypical antiepileptic. By targeting excess neural activity, levetiracetam may improve cognition and attenuate the accumulation of pathology contributing to progression to the dementia phase of LOAD.Electronic supplementary materialThe online version of this article (doi:10.1007/s13311-017-0541-z) contains supplementary material, which is available to authorized users.

The easy accessibility of energy-rich palatable food makes it difficult to resist food temptation. Drosophila larvae are surrounded by sugar-rich food most of their lives, raising the question of how these animals modulate food-seeking behaviors in tune with physiological needs. Here we describe a circuit mechanism defined by neurons expressing tdc2-Gal4 (a tyrosine decarboxylase 2 promoter-directed driver) that selectively drives a distinct foraging strategy in food-deprived larvae. Stimulation of this otherwise functionally latent circuit in tdc2-Gal4 neurons was sufficient to induce exuberant feeding of liquid food in fed animals, whereas targeted lesions in a small subset of tdc2-Gal4 neurons in the subesophageal ganglion blocked hunger-driven increases in the feeding response. Furthermore, regulation of feeding rate enhancement by tdc2-Gal4 neurons requires a novel signaling mechanism involving the VEGF2-like receptor, octopamine, and its receptor. Our findings provide fresh insight for the neurobiology and evolution of appetitive motivation. T he adaptive control of foraging decisions is crucial to survival and reproduction and is mediated by complex brain mechanisms. For example, in hungry animals, feeding behaviors can be modulated by diverse neural systems including those responsible for receiving and processing sensory properties and assigning reward and motivational significance of food stimuli (1-3). At present, elucidation of molecular and circuit mechanisms underlying the adaptive control of feeding behavior remains highly challenging.Our previous studies have shown that Drosophila larvae, like mammals, display diverse adaptive foraging strategies in response to appetizing odors or satiety state and food quality (4-6). For example, larvae fed for ad libitum intake tend to prefer soft, liquid sugar media that contain readily ingestible sugar solution but decline solid media in which sugar solution is embedded in gelled agar and is less accessible (5). However, as food deprivation is prolonged, larvae will become increasingly persistent in extracting the sugar solution from solid media (7). We have also shown that an evolutionarily conserved signaling cascade, involving neuropeptide F (NPF, the fly homolog of neuropeptide Y, or NPY) and insulin-like peptides (dILPs), selectively integrates motivational state (hunger) with persistence to pulverize solid food (5, 7).The observation that the conserved NPY-like system selectively promotes food acquisition behaviors that require high energetic cost has led us to postulate that fly larvae may use other conserved neural mechanisms to regulate acquisition of readily accessible palatable food. In this work, we provide evidence which supports this hypothesis. We show that an octopamine (OA)/β-adrenergic-like receptor (Octß3R)-dependent circuit mechanism selectively regulates appetite for soft sugar media. This circuit mechanism seems to involve two subsets of tdc2-Gal4 neurons in the subesophogeal ganglia (SOG). One of them mediates the hunger-driven increase ...

Similar to elderly humans, aged outbred Long Evans rats exhibit individual differences in memory abilities, including a subset of aged rats that maintain memory function on par with young adults. Such individuals provide a basis for investigating mechanisms of resilience to age-related decline. The present study examined hippocampal gene expression in young adults and aged rats with preserved memory function under behavioral task conditions well-established for assessing information processing central to the formation of episodic memory. While behavioral measures and hippocampal gene induction associated with neural activity and synaptic plasticity were similar across age groups, a marker for inhibitory interneuron function in the hippocampal formation was distinctively increased only in aged rats but not in young adults. Because heightened hippocampal neural activity is associated with age-related memory impairment across species, including rats, monkeys and humans, this finding may represent an adaptive homeostatic adjustment necessary to maintain neural plasticity and memory function in aging.

Imaging methods such as magnetic resonance imaging (MRI), micro-computed tomography (microCT) and light-sheet microscopy (LSM) of cleared tissue samples can generate intact anatomic and molecular whole-brain data. However, each modality produces unique artifacts based on the physical principles of the technique, including intensity inhomogeneity due to magnetic field bias in MRI or microscope optics in LSM and beam hardening in microCT 1, 2, 3 . These artifacts and the size of the datasets generated pose a substantial challenge in data handling, cross-modal image registration, and analysis. Visualization and anatomically relevant analysis of high-resolution, multi-field-of-view (mFOV) datasets require preprocessing to remove artifacts, stitching into a complete volume, and registration to a reference atlas 3,4 .Each step presents specific challenges. First, stitching acquired fields of view (FOVs) into a complete volume is computation and time intensive. Second,

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Quantifying terabyte-scale multi-modal human and animal imaging data requires scalable analysis tools. We developed CloudReg, an open-source, automatic, terabyte-scale, cloud-based image analysis pipeline that pre-processes and registers cross-modal volumetric datasets with artifacts via spatially-varying polynomial intensity transform. CloudReg accurately registers the following datasets to their respective atlases: in vivo human and ex vivo macaque brain magnetic resonance imaging, ex vivo mouse brain micro-computed tomography, and cleared murine brain light-sheet microscopy.

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