Taking advantage of misclassifications to boost classification rate in decision fusion

This paper presents methods to boost the classification rate in decision fusion with partially redundant information. This is accomplished by utilizing the information of known mis- classifications of certain classes to systematically modify class output. For example,, if it is known beforehand that tool A mis- classifies class 1 as often as class 2, then it appears to be prudent to integrate that information into the reasoning process if class 1 is indicated by tool B and class 2 is observed by tool A. Particularly this preferred mis-classification information is contained in the asymmetric (cross-correlation) entries of the confusion matrix. An operation we call cross-correlation is performed where this information is explicitly used to modify class output before the first fused estimate is calculated. We investigate several methods for cross-correlation and discuss the advantages and disadvantages of each. We then apply the concepts introduced to the diagnostic realm where we aggregate the output of several different diagnostic tools. We show how the proposed approach fits into an information fusion architecture and finally present results motivated from diagnosing on-board faults in aircraft engines

Long-Term Effects of Traumatic Brain Injury on Anxiety-Like Behaviors in Mice: Behavioral and Neural Correlates

Traumatic brain injury (TBI) has been frequently linked to affective disorders such as anxiety and depression. However, much remains to be understood about the underlying molecular and signaling mechanisms that mediate affective dysfunctions following injury. A lack of consensus in animal studies regarding what the affective sequelae of TBI are has been a major hurdle that has slowed progress, with studies reporting the full range of effects: increase, decrease, and no change in anxiety following injury. Here, we addressed this issue directly by investigating long-term anxiety outcomes in mice following a moderate to severe controlled cortical impact (CCI) injury using a battery of standard behavioral tests—the open field (OF), elevated zero maze (EZM), and elevated plus maze (EPM). Mice were tested on weeks 1, 3, 5 and 7 post-injury. Our results show that the effect of injury is time- and task-dependent. Early on—up to 3 weeks post-injury, there is an increase in anxiety-like behaviors in the elevated plus and zero mazes. However, after 5 weeks post-injury, anxiety-like behavior decreases, as measured in the OF and EZM. Immunostaining in the basolateral amygdala (BLA) for GAD, a marker for GABA, at the end of the behavioral testing showed the late decrease in anxiety behavior was correlated with upregulation of inhibition. The approach adopted in this study reveals a complex trajectory of affective outcomes following injury, and highlights the importance of comparing outcomes in different assays and time-points, to ensure that the affective consequences of injury are adequately assessed

Factoring a priori classifier performance into decision fusion

In this paper we present methods to enhance the classification rate in decision fusion with partially redundant information by manipulating the input to the fusion scheme using a priori performance information. Intuitively, it seems to make sense to trust a more reliable tool more than a less reliable one without discounting the less reliable one completely. For a multi-class classifier, the reliability per class must be considered. In addition, complete ignorance for any given class must also be factored into the fusion process to ensure that all faults are equally well represented. However, overly trusting the best classifier will not permit the fusion tool to achieve results that rate beyond the best classifiers performance. We assume that the performance of classifiers to be fused is known, and show how to take advantage of this information. In particular, we glean pertinent performance information from the classifier confusion matrices and their cousin, the relevance matrix. We further demonstrate how to integrate a priori performance information within an hierarchical fusion architecture. We investigate several schemes for these operations and discuss the advantages and disadvantages of each. We then apply the concepts introduced to the diagnostic realm where we aggregate the output of several different diagnostic tools. We present results motivated from diagnosing on-board faults in aircraft engines

Taking advantage of misclassifications to boost classification rate in decision fusion

This paper presents methods to boost the classification rate in decision fusion with partially redundant information. This is accomplished by utilizing the information of known mis- classifications of certain classes to systematically modify class output. For example,, if it is known beforehand that tool A mis- classifies class 1 as often as class 2, then it appears to be prudent to integrate that information into the reasoning process if class 1 is indicated by tool B and class 2 is observed by tool A. Particularly this preferred mis-classification information is contained in the asymmetric (cross-correlation) entries of the confusion matrix. An operation we call cross-correlation is performed where this information is explicitly used to modify class output before the first fused estimate is calculated. We investigate several methods for cross-correlation and discuss the advantages and disadvantages of each. We then apply the concepts introduced to the diagnostic realm where we aggregate the output of several different diagnostic tools. We show how the proposed approach fits into an information fusion architecture and finally present results motivated from diagnosing on-board faults in aircraft engines

Effects of N-Cadherin Disruption on Spine Morphological Dynamics

Structural changes at synapses are thought to be a key mechanism for the encoding of memories in the brain. Recent studies have shown that changes in the dynamic behavior of dendritic spines accompany bidirectional changes in synaptic plasticity, and that the disruption of structural constraints at synapses may play a mechanistic role in spine plasticity. While the prolonged disruption of N-cadherin, a key synaptic adhesion molecule, has been shown to alter spine morphology, little is known about the short-term regulation of spine morphological dynamics by N-cadherin. With time-lapse, confocal imaging in cultured hippocampal neurons, we examined the progression of structural changes in spines following an acute treatment with AHAVD, a peptide known to interfere with the function of N-cadherin. We characterized fast and slow timescale spine dynamics (minutes and hours, respectively) in the same population of spines. We show that N-cadherin disruption leads to enhanced spine motility and reduced length, followed by spine loss. The structural effects are accompanied by a loss of functional connectivity. Further, we demonstrate that early structural changes induced by AHAVD treatment, namely enhanced motility and reduced length, are indicators for later spine fate, i.e., spines with the former changes are more likely to be subsequently lost. Our results thus reveal the short-term regulation of synaptic structure by N-cadherin and suggest that some forms of morphological dynamics may be potential readouts for subsequent, stimulus-induced rewiring in neuronal networks

N-Cadherin, Spine Dynamics, and Synaptic Function

Dendritic spines are one-half (the postsynaptic half) of most excitatory synapses. Ever since the direct observation over a decade ago that spines can continually change size and shape, spine dynamics has been of great research interest, especially as a mechanism for structural synaptic plasticity. In concert with this ongoing spine dynamics, the stability of the synapse is also needed to allow continued, reliable synaptic communication. Various cell-adhesion molecules help to structurally stabilize a synapse and its proteins. Here, we review the effects of disrupting N-cadherin, a prominent trans-synaptic adhesion molecule, on spine dynamics, as reported in Mysore et al. (2007). We highlight the novel method adopted therein to reliably detect even subtle changes in fast and slow spine dynamics. We summarize the structural, functional, and molecular consequences of acute N-cadherin disruption, and tie them in, in a working model, with longer-term effects on spines and synapses reported in the literature

Activity-Regulated N-Cadherin Endocytosis

SummaryEnduring forms of synaptic plasticity are thought to require ongoing regulation of adhesion molecules, such as N-cadherin, at synaptic junctions. Little is known about the activity-regulated trafficking of adhesion molecules. Here we demonstrate that surface N-cadherin undergoes a surprisingly high basal rate of internalization. Upon activation of NMDA receptors (NMDAR), the rate of N-cadherin endocytosis is significantly reduced, resulting in an accumulation of N-cadherin in the plasma membrane. β-catenin, an N-cadherin binding partner, is a primary regulator of N-cadherin endocytosis. Following NMDAR stimulation, β-catenin accumulates in spines and exhibits increased binding to N-cadherin. Overexpression of a mutant form of β-catenin, Y654F, prevents the NMDAR-dependent regulation of N-cadherin internalization, resulting in stabilization of surface N-cadherin molecules. Furthermore, the stabilization of surface N-cadherin blocks NMDAR-dependent synaptic plasticity. These results indicate that NMDAR activity regulates N-cadherin endocytosis, providing a mechanistic link between structural plasticity and persistent changes in synaptic efficacy

Mechanistic target of rapamycin is necessary for changes in dendritic spine morphology associated with long-term potentiation

Abstract Alterations in the strength of excitatory synapses in the hippocampus is believed to serve a vital function in the storage and recall of new information in the mammalian brain. These alterations involve the regulation of both functional and morphological features of dendritic spines, the principal sites of excitatory synaptic contact. New protein synthesis has been implicated extensively in the functional changes observed following long-term potentiation (LTP), and changes to spine morphology have similarly been documented extensively following synaptic potentiation. However, mechanistic links between de novo translation and the structural changes of potentiated spines are less clear. Here, we assess explicitly the potential contribution of new protein translation under control of the mechanistic target of rapamycin (mTOR) to LTP-associated changes in spine morphology. Utilizing genetic and pharmacological manipulations of mTORC1 function in combination with confocal microscopy in live dissociated hippocampal cultures, we demonstrate that chemically-induced LTP (cLTP) requires do novo protein synthesis and intact mTORC1 signaling. We observed a striking diversity in response properties across morphological classes, with mushroom spines displaying a particular sensitivity to altered mTORC1 signaling across varied levels of synaptic activity. Notably, while pharmacological inhibition of mTORC1 signaling significantly diminished glycine-induced changes in spine morphology, transient genetic upregulation of mTORC1 signaling was insufficient to produce spine enlargements on its own. In contrast, genetic upregulation of mTORC1 signaling promoted rapid expansion in spine head diameter when combined with otherwise sub-threshold synaptic stimulation. These results suggest that synaptic activity-derived signaling pathways act in combination with mTORC1-dependent translational control mechanisms to ultimately regulate changes in spine morphology. As several monogenic neurodevelopmental disorders with links to Autism and Intellectual Disability share a common feature of dysregulated mTORC1 signaling, further understanding of the role of this signaling pathway in regulating synapse function and morphology will be essential in the development of novel therapeutic interventions.https://deepblue.lib.umich.edu/bitstream/2027.42/139019/1/13041_2017_Article_330.pd

Modeling Structural Plasticity in the Barn Owl Auditory Localization System with a Spike-Time Dependent Hebbian Learning Rule

Auditory localization behavior in barn owls is mediated by the integration of topographically encoded visual and auditory space maps. In juvenile owls, disruption of the audio-visual map alignment by exposure to spectacles that laterally shift the visual input results in behavioral adaptation over the course of several weeks. It has been reported in literature that this adaptation is produced by architectural plasticity in the neural circuits encoding the space maps. It is known that this plasticity is guided by visual input in a topographic manner, and that the error signal is embedded in the firing dynamics of neurons in the inferior colliculus. In this work, we use leaky integrate-and-fire neurons to model the key elements in the auditory localization circuit of barn owls. We demonstrate that a Hebbian spike-time dependent learning rule, coupled with an activity-dependent mechanism that promotes growth, can account for the essentials of circuit-level plasticity associated with prism experience. We point out the importance of inhibition in both the normal functioning of this circuit, and prism-induced plasticity, and comment on potential mechanisms for activity-induced growth