Faculty Bibliography

Serine-threonine protein kinases are critical to CNS function, yet there is a dearth of highly selective, CNS-active kinase inhibitors for in vivo investigations. Further, prevailing assumptions raise concerns about whether single kinase inhibitors can show in vivo efficacy for CNS pathologies, and debates over viable approaches to the development of safe and efficacious kinase inhibitors are unsettled. It is critical, therefore, that these scientific challenges be addressed in order to test hypotheses about protein kinases in neuropathology progression and the potential for in vivo modulation of their catalytic activity. Identification of molecular targets whose in vivo modulation can attenuate synaptic dysfunction would provide a foundation for future disease-modifying therapeutic development as well as insight into cellular mechanisms. Clinical and preclinical studies suggest a critical link between synaptic dysfunction in neurodegenerative disorders and the activation of p38alphaMAPK mediated signaling cascades. Activation in both neurons and glia also offers the unusual potential to generate enhanced responses through targeting a single kinase in two distinct cell types involved in pathology progression. However, target validation has been limited by lack of highly selective inhibitors amenable to in vivo use in the CNS. Therefore, we employed high-resolution co-crystallography and pharmacoinformatics to design and develop a novel synthetic, active site targeted, CNS-active, p38alphaMAPK inhibitor (MW108). Selectivity was demonstrated by large-scale kinome screens, functional GPCR agonist and antagonist analyses of off-target potential, and evaluation of cellular target engagement. In vitro and in vivo assays demonstrated that MW108 ameliorates beta-amyloid induced synaptic and cognitive dysfunction. A serendipitous discovery during co-crystallographic analyses revised prevailing models about active site targeting of inhibitors, providing insights that will facilitate future kinase inhibitor design. Overall, our studies deliver highly selective in vivo probes appropriate for CNS investigations and demonstrate that modulation of p38alphaMAPK activity can attenuate synaptic dysfunction.

The development of transistors with high gain is essential for applications ranging from switching elements and drivers to transducers for chemical and biological sensing. Organic transistors have become well-established based on their distinct advantages, including ease of fabrication, synthetic freedom for chemical functionalization, and the ability to take on unique form factors. These devices, however, are largely viewed as belonging to the low-end of the performance spectrum. Here we present organic electrochemical transistors with a transconductance in the mS range, outperforming transistors from both traditional and emerging semiconductors. The transconductance of these devices remains fairly constant from DC up to a frequency of the order of 1 kHz, a value determined by the process of ion transport between the electrolyte and the channel. These devices, which continue to work even after being crumpled, are predicted to be highly relevant as transducers in biosensing applications.

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical findings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Amyloid plaques are a key pathological hallmark of Alzheimer's disease (AD). The detection of amyloid plaques in the brain is important for the diagnosis of AD, as well as for following potential amyloid targeting therapeutic interventions. Our group has developed several contrast agents to detect amyloid plaques using magnetic resonance microimaging (microMRI) in AD transgenic mice, where we used mannitol to enhance blood brain barrier (BBB) permeability. In the present study, we used bifunctional ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles, chemically coupled with Abeta1-42 peptide to image amyloid plaque deposition in the mouse brain. We coupled the nanoparticles to polyethylene glycol (PEG) in order to improve BBB permeability. These USPIO-PEG-Abeta1-42 nanoparticles were injected intravenously in AD model transgenic mice followed by initial and subsequent muMRI. A 3D gradient multi-echo sequence was used for imaging with a 100 microm isotropic resolution. The amyloid plaques detected by T2*-weighted muMRI were confirmed with matched histological sections. The region of interest-based quantitative measurement of T2* values obtained from the muMRI showed contrast injected AD Tg mice had significantly reduced T2* values compared to wild-type mice. In addition, the scans were examined with voxel-based analysis (VBA) using statistical parametric mapping (SPM) for comparison of USPIO-PEG-Abeta1-42 injected AD transgenic and USPIO alone injected AD transgenic mice. The regional differences seen by VBA in the USPIO-PEG-Abeta1-42 injected AD transgenic correlated with the amyloid plaque distribution histologically. Our results indicate that USPIO-PEG-Abeta1-42 can be used for amyloid plaque detection by intravenous injection without the need to co-inject an agent which increases permeability of the BBB. This technique could aid the development of novel amyloid targeting drugs by allowing therapeutic effects to be followed longitudinally in model AD mice.

How epilepsy affects brain functional networks remains poorly understood. Here we investigated resting state functional connectivity of the temporal region in temporal lobe epilepsy. Thirty-two patients with unilateral temporal lobe epilepsy underwent resting state blood-oxygenation level dependent functional magnetic resonance imaging. We defined regions of interest a priori focusing on structures involved, either structurally or metabolically, in temporal lobe epilepsy. These structures were identified in each patient based on their individual anatomy. Our principal findings are decreased local and inter-hemispheric functional connectivity and increased intra-hemispheric functional connectivity ipsilateral to the seizure focus compared to normal controls. Specifically, several regions in the affected temporal lobe showed increased functional coupling with the ipsilateral insula and immediately neighboring subcortical regions. Additionally there was significantly decreased functional connectivity between regions in the affected temporal lobe and their contralateral homologous counterparts. Intriguingly, decreased local and inter-hemispheric connectivity was not limited or even maximal for the hippocampus or medial temporal region, which is the typical seizure onset region. Rather it also involved several regions in temporal neo-cortex, while also retaining specificity, with neighboring regions such as the amygdala remaining unaffected. These findings support a view of temporal lobe epilepsy as a disease of a complex functional network, with alterations that extend well beyond the seizure onset area, and the specificity of the observed connectivity changes suggests the possibility of a functional imaging biomarker for temporal lobe epilepsy.

Microtubule-based axonal transport is believed to become globally disrupted in Alzheimer's disease in part due to alterations of tau expression or phosphorylation. We previously showed that axonal transport rates along retinal ganglion axons are unaffected by deletion of normal mouse tau or by overexpression of wild-type human tau. Here, we report that htau mice expressing 3-fold higher levels of human tau in the absence of mouse tau also display normal fast and slow transport kinetics despite the presence of abnormally hyperphosphorylated tau in some neurons. In addition, markers of slow transport (neurofilament light subunit) and fast transport (snap25) exhibit normal distributions along optic axons of these mice. These studies demonstrate that human tau overexpression, even when associated with a limited degree of tau pathology, does not necessarily impair general axonal transport function in vivo.

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

How is the cerebellum capable of efficient motor learning and control despite very low firing of the inferior olive (IO) inputs, which are postulated to carry errors needed for learning and contribute to on-line motor control? IO neurons form the largest electrically coupled network in the adult human brain. Here, we discuss how intermediate coupling strengths can lead to chaotic resonance and increase information transmission of the error signal despite the very low IO firing rate. This increased information transmission can then lead to more efficient learning than with weak or strong coupling. In addition, we argue that a dynamic modulation of IO electrical coupling via the Purkinje cell-deep cerebellar neurons - IO triangle could speed up learning and improve on-line control. Initially strong coupling would allow transmission of large errors to multiple functionally related Purkinje cells, resulting in fast but coarse learning as well as significant effects on deep cerebellar nucleus and on-line motor control. In the late phase of learning decreased coupling would allow desynchronized IO firing, allowing high-fidelity transmission of error, resulting in slower but fine learning, and little on-line motor control effects.