Altered ultrasonic vocalization and impaired learning and memory in Angelman syndrome mouse model with a large maternal deletion from Ube3a to Gabrb3.

Angelman syndrome (AS) is a neurobehavioral disorder associated with mental retardation, absence of language development, characteristic electroencephalography (EEG) abnormalities and epilepsy, happy disposition, movement or balance disorders, and autistic behaviors. The molecular defects underlying AS are heterogeneous, including large maternal deletions of chromosome 15q11-q13 (70%), paternal uniparental disomy (UPD) of chromosome 15 (5%), imprinting mutations (rare), and mutations in the E6-AP ubiquitin ligase gene UBE3A (15%). Although patients with UBE3A mutations have a wide spectrum of neurological phenotypes, their features are usually milder than AS patients with deletions of 15q11-q13. Using a chromosomal engineering strategy, we generated mutant mice with a 1.6-Mb chromosomal deletion from Ube3a to Gabrb3, which inactivated the Ube3a and Gabrb3 genes and deleted the Atp10a gene. Homozygous deletion mutant mice died in the perinatal period due to a cleft palate resulting from the null mutation in Gabrb3 gene. Mice with a maternal deletion (m-/p+) were viable and did not have any obvious developmental defects. Expression analysis of the maternal and paternal deletion mice confirmed that the Ube3a gene is maternally expressed in brain, and showed that the Atp10a and Gabrb3 genes are biallelically expressed in all brain sub-regions studied. Maternal (m-/p+), but not paternal (m+/p-), deletion mice had increased spontaneous seizure activity and abnormal EEG. Extensive behavioral analyses revealed significant impairment in motor function, learning and memory tasks, and anxiety-related measures assayed in the light-dark box in maternal deletion but not paternal deletion mice. Ultrasonic vocalization (USV) recording in newborns revealed that maternal deletion pups emitted significantly more USVs than wild-type littermates. The increased USV in maternal deletion mice suggests abnormal signaling behavior between mothers and pups that may reflect abnormal communication behaviors in human AS patients. Thus, mutant mice with a maternal deletion from Ube3a to Gabrb3 provide an AS mouse model that is molecularly more similar to the contiguous gene deletion form of AS in humans than mice with Ube3a mutation alone. These mice will be valuable for future comparative studies to mice with maternal deficiency of Ube3a alone.

Neuronal Survival of the Fittest: The Importance of Aerobic Capacity in Exercise-Induced Neurogenesis and Cognition

It is commonly accepted that aerobic exercise increases hippocampal neurogenesis, learning and memory, as well as stress resiliency. However, human populations are widely variable in their inherent aerobic fitness as well as their capacity to show increased aerobic fitness following a period of regimented exercise. It is unclear whether these inherent or acquired components of aerobic fitness play a role in neurocognition. To isolate the potential role of inherent aerobic fitness, we exploited a rat model of high (HCR) and low (LCR) inherent aerobic capacity for running. At a baseline, HCR rats have two- to three-fold higher aerobic capacity than LCR rats. We found that HCR rats also had two- to three- fold more young neurons in the hippocampus than LCR rats as well as rats from the heterogeneous founder population. We then asked whether this enhanced neurogenesis translates to enhanced hippocampal cognition, as is typically seen in exercise-trained animals. Compared to LCR rats, HCR rats performed with high accuracy on tasks designed to test neurogenesis-dependent pattern separation ability by examining investigatory behavior between very similar objects or locations. To investigate whether an aerobic response to exercise is required for exercise-induced changes in neurogenesis and cognition, we utilized a rat model of high (HRT) and low (LRT) aerobic response to treadmill training. At a baseline, HRT and LRT rats have comparable aerobic capacity as measured by a standard treadmill fit test, yet after a standardized training regimen, HRT but not LRT rats robustly increase their aerobic capacity for running. We found that sedentary LRT and HRT rats had equivalent levels of hippocampal neurogenesis, but only HRT rats had an elevation in the number of young neurons in the hippocampus following training, which was positively correlated with accuracy on pattern separation tasks. Taken together, these data suggest that a significant elevation in aerobic capacity is necessary for exercise-induced hippocampal neurogenesis and hippocampal neurogenesis-dependent learning and memory. To investigate the potential for high aerobic capacity to be neuroprotective, doxorubicin chemotherapy was administered to LCR and HCR rats. While doxorubicin induces a progressive decrease in aerobic capacity as well as neurogenesis, HCR rats remain at higher levels on those measures compared to even saline-treated LCR rats. HCR and LCR rats that received exercise training throughout doxorubicin treatment demonstrated positive effects of exercise on aerobic capacity and neurogenesis, regardless of inherent aerobic capacity. Overall, these findings demonstrate that inherent and acquired components of aerobic fitness play a crucial role not only in the cardiorespiratory system but also the fitness of the brain.

Advances in understanding mechanisms of thalamic relays in cognition and behavior.

The main impetus for a mini-symposium on corticothalamic interrelationships was the recent number of studies highlighting the role of the thalamus in aspects of cognition beyond sensory processing. The thalamus contributes to a range of basic cognitive behaviors that include learning and memory, inhibitory control, decision-making, and the control of visual orienting responses. Its functions are deeply intertwined with those of the better studied cortex, although the principles governing its coordination with the cortex remain opaque, particularly in higher-level aspects of cognition. How should the thalamus be viewed in the context of the rest of the brain? Although its role extends well beyond relaying of sensory information from the periphery, the main function of many of its subdivisions does appear to be that of a relay station, transmitting neural signals primarily to the cerebral cortex from a number of brain areas. In cognition, its main contribution may thus be to coordinate signals between diverse regions of the telencephalon, including the neocortex, hippocampus, amygdala, and striatum. This central coordination is further subject to considerable extrinsic control, for example, inhibition from the basal ganglia, zona incerta, and pretectal regions, and chemical modulation from ascending neurotransmitter systems. What follows is a brief review on the role of the thalamus in aspects of cognition and behavior, focusing on a summary of the topics covered in a mini-symposium held at the Society for Neuroscience meeting, 2014.

Inhibition-Induced Forgetting Results from Resource Competition between Response Inhibition and Memory Encoding Processes.

UNLABELLED: Response inhibition is a key component of executive control, but its relation to other cognitive processes is not well understood. We recently documented the "inhibition-induced forgetting effect": no-go cues are remembered more poorly than go cues. We attributed this effect to central-resource competition, whereby response inhibition saps attention away from memory encoding. However, this proposal is difficult to test with behavioral means alone. We therefore used fMRI in humans to test two neural predictions of the "common resource hypothesis": (1) brain regions associated with response inhibition should exhibit greater resource demands during encoding of subsequently forgotten than remembered no-go cues; and (2) this higher inhibitory resource demand should lead to memory encoding regions having less resources available during encoding of subsequently forgotten no-go cues. Participants categorized face stimuli by gender in a go/no-go task and, following a delay, performed a surprise recognition memory test for those faces. Replicating previous findings, memory was worse for no-go than for go stimuli. Crucially, forgetting of no-go cues was predicted by high inhibitory resource demand, as quantified by the trial-by-trial ratio of activity in neural "no-go" versus "go" networks. Moreover, this index of inhibitory demand exhibited an inverse trial-by-trial relationship with activity in brain regions responsible for the encoding of no-go cues into memory, notably the ventrolateral prefrontal cortex. This seesaw pattern between the neural resource demand of response inhibition and activity related to memory encoding directly supports the hypothesis that response inhibition temporarily saps attentional resources away from stimulus processing. SIGNIFICANCE STATEMENT: Recent behavioral experiments showed that inhibiting a motor response to a stimulus (a "no-go cue") impairs subsequent memory for that cue. Here, we used fMRI to test whether this "inhibition-induced forgetting effect" is caused by competition for neural resources between the processes of response inhibition and memory encoding. We found that trial-by-trial variations in neural inhibitory resource demand predicted subsequent forgetting of no-go cues and that higher inhibitory demand was furthermore associated with lower concurrent activation in brain regions responsible for successful memory encoding of no-go cues. Thus, motor inhibition and stimulus encoding appear to compete with each other: when more resources have to be devoted to inhibiting action, less are available for encoding sensory stimuli.

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast.

Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.