Faculty Bibliography

Neural decoding is an important approach for extracting information from population codes. We previously proposed a novel transductive neural decoding paradigm and applied it to reconstruct the rat's position during navigation based on unsorted rat hippocampal ensemble spiking activity. Here, we investigate several important technical issues of this new paradigm using one data set of one animal. Several extensions of our decoding method are discussed.

In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model's statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (baroreflex) sensitivity (BRS), are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second-order non-linearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of non-linearity. We here present a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, non-invasive assessment in clinical practice. We also discuss the limitations and other alternative modeling strategies of our point process approach.

Functional neuronal homeostasis has been studied in a variety of model systems and contexts. Many studies have shown that there are a number of changes that can be activated within individual cells or networks in order to compensate for perturbations or changes in levels of activity. Dissociating the cell autonomous from the network-mediated events has been complicated due to the difficulty of sparsely targeting specific populations of neurons in vivo. Here, we make use of a recent in vivo approach we developed that allows for the sparse labeling and manipulation of activity within superficial caudal ganglionic eminence (CGE)-derived GABAergic interneurons. Expression of the inward rectifying potassium channel Kir2.1 cell-autonomously reduced neuronal activity and lead to specific developmental changes in their intrinsic electrophysiological properties and the synaptic input they received. In contrast to previous studies on homeostatic scaling of pyramidal cells, we did not detect any of the typically observed compensatory mechanisms in these interneurons. Rather, we instead saw a specific alteration of the kinetics of excitatory synaptic events within the reelin-expressing subpopulation of interneurons. These results provide the first in vivo observations for the capacity of interneurons to cell-autonomously regulate their excitability.

Background: Biomarkers such as amyloid beta (e.g. Ab42) and hyperphosphorylated tau (e.g. pTau181) in cerebral spinal fluid (CSF) and hippocampal volume loss measured by magnetic resonance imaging (MRI) are useful for identifying cognitively normal elderly likely to have "preclinical" Alzheimer's disease (AD), but such methods are invasive and/or expensive. We investigated whether cognitive tasks dependent on brain regions affected in early AD can serve as proxies of AD biomarkers. Research indicates that the hippocampal formation (Hipp), particularly CA3/dentate gyrus (CA3/DG) and the entorhinal cortex (EC) are affected in preclinical AD. Therefore, we hypothesized that performance on a CA3/DG-dependent spatial pattern separation task (PST) and a Hipp/ EC-dependent discrimination and generalization task (DGT) would be impaired in cognitively normal individuals with biomarker evidence for AD. Methods: We collected initial data on our tasks from 31 cognitively normal NYU Alzheimer's Disease Center/Center for Brain Health participants who had MRI and who also provided CSF for longitudinal studies. In the PST, participants discriminated between two identical dots, one in a previously viewed location and one in a new location. In the DGT, participants learned to discriminate pairs of stimuli determined by shapes or colors in a discrimination phase, then had to generalize the "preferred" shapes and colors to novel stimuli in a generalization phase. Results: Linear regression analyses (with age and years of education as covariates) were used to determine whether task performance correlates with bilateral Hipp volume (used as a surrogate for CA3/DG and controlled for total intracranial volume) and CSF biomarkers. Performance on the PST correlates with bilateral Hipp volume (n = 31; R 2 = 0.151, P = 0.004) and CSF Ab42/pTau181 ratio (n = 26; R 2 = 0.182, P = 0.026). Performance on generalization correlates with Ab42 (R 2 = 0.182, P = 0.026) and marginally with Ab42/pTau181 ratio (R 2 = 0.119, P = 0.079). Performance on discrimination correlates with Ab42/ pTau181 ratio only (R 2 = 0.159, P = 0.039). A standard memory test (NYU Paragraph Recall) shows no significant correlations. Conclusions: These preliminary results are consistent with our hypothesis that cognitive tasks dependent on brain regions affected by early AD pathology may provide a non-invasive and cost-effective method to identify and track change in clinically normal individuals at high risk for progressing to theMCI and dementia stages of AD

Background: Neurotrophin signaling of cholinergic basal forebrain (CBF) neurons is critical for survival and plasticity. Microaspiration of identified CBF neurons from postmortem human brain revealed a shift in balance of neurotrophin receptors toward cell death pathways during the progression of Alzheimer's disease (AD). Methods: In this study transcriptomic data from mouse basal forebrain cholinergic neurons (BFCNs; NCBI GEO GSE13379) were used to derive parameters for a deterministic kinetic model of the nerve growth factor (NGF) signaling pathway from Reactome, with TrkB receptor mechanisms added. This method is called Transcriptome-To-Reactome (TTR)-. The biosimulation was performed using COPASI software and included 11 compartments 435 species, and 263 reactions; 245 genes were used to determine initial values of species and kinetic values of reactions. The mouse BFCN model was considered baseline and a biosimulation was run with two doses of NGF, 500 m M and 10 mM, delivered as a bolus and for a 10 and 240 second duration, respectively. This approach tested selectively for p75 NTR and TrkA receptor mediated mechanisms. A second biosimulation test used a combination of 25 mM brain derived neurotrophic factor (BDNF) and 10 m M NGF as a continuous exposure for 60 min duration; this approach evaluated stimulation of p75 NTR TrkA, and TrkB. Based on the human microarray results demonstrating downregulation of TrkA (50%) and TrkB (60%), the corresponding parameters in the TTR biosimulation were decreased by the same amount. Results: Baseline results were validated from published literature on neuronal calcium levels mediated via the phospholipase C-g and inositol- 3-phosphate pathway at both bolus doses of NGF alone. With the corresponding parameters decreased in the TTR biosimulation, Figure 1: A) The reaction flux for c-RAF1 phosphorylation of MEK1 was delayed to peak value by 1.5 min from exposure, but the peak value was increased to 5 times the baseline value; B) Moreover, a slight shift t!

Homeostatic scaling of synaptic strengths is essential for maintenance of network "gain", but also poses a risk of losing the distinctions among relative synaptic weights, which are possibly cellular correlates of memory storage. Multiplicative scaling of all synapses has been proposed as a mechanism that would preserve the relative weights among them, because they would all be proportionately adjusted. It is crucial for this hypothesis that all synapses be affected identically, but whether or not this actually occurs is difficult to determine directly. Mathematical tests for multiplicative synaptic scaling are presently carried out on distributions of miniature synaptic current amplitudes, but the accuracy of the test procedure has not been fully validated. We now show that the existence of an amplitude threshold for empirical detection of miniature synaptic currents limits the use of the most common method for detecting multiplicative changes. Our new method circumvents the problem by discarding the potentially distorting subthreshold values after computational scaling. This new method should be useful in assessing the underlying neurophysiological nature of a homeostatic synaptic scaling transformation, and therefore in evaluating its functional significance.