Technion Medical School

Haifa, Israel

Technion Medical School

Haifa, Israel
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Major G.,University of Cardiff | Larkum M.E.,Charité - Medical University of Berlin | Schiller J.,Technion Medical School
Annual Review of Neuroscience | Year: 2013

Dendrites are the main recipients of synaptic inputs and are important sites that determine neurons' input-output functions. This review focuses on thin neocortical dendrites, which receive the vast majority of synaptic inputs in cortex but also have specialized electrogenic properties. We present a simplified working-model biophysical scheme of pyramidal neurons that attempts to capture the essence of their dendritic function, including the ability to behave under plausible conditions as dynamic computational subunits. We emphasize the electrogenic capabilities of NMDA receptors (NMDARs) because these transmitter-gated channels seem to provide the major nonlinear depolarizing drive in thin dendrites, even allowing full-blown NMDA spikes. We show how apparent discrepancies in experimental findings can be reconciled and discuss the current status of dendritic spikes in vivo; a dominant NMDAR contribution would indicate that the input-output relations of thin dendrites are dynamically set by network activity and cannot be fully predicted by purely reductionist approaches. Copyright ©2013 by Annual Reviews. All rights reserved.


Jadi M.P.,Salk Institute for Biological Studies | Behabadi B.F.,Qualcomm | Poleg-Polsky A.,U.S. National Institutes of Health | Schiller J.,Technion Medical School | Mel B.W.,University of Southern California
Proceedings of the IEEE | Year: 2014

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based 'technology' that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or 'neuron,' yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees. © 2014 IEEE.


Pradilla G.,Johns Hopkins University | Wicks R.T.,Johns Hopkins University | Hadelsberg U.,Technion Medical School | Gailloud P.,Johns Hopkins University | And 3 more authors.
World Neurosurgery | Year: 2013

Objective: Although digital subtraction angiography (DSA) remains the standard for intracranial aneurysm diagnosis, computed tomography angiography (CTA) is being increasingly used for this purpose. CTA has sensitivities and specificities reported as high as 97% and 100%, respectively. We analyzed a prospective cohort of 112 patients with 134 unruptured aneurysms who underwent community CTAs and confirmatory DSAs in a tertiary facility. Methods: Patients referred between 2007 and 2010 (mean age 53.2 years) with aneurysms identified by CTA underwent confirmatory DSA. The results were compared to determine accuracy of CTA in diagnosing aneurysms. Aneurysms diagnosed by CTA but ruled out by DSA or aneurysms missed by CTA but diagnosed by DSA were analyzed by size and location. Anatomical variants leading to false CTA positive results were noted. Results: CTA identified 132 aneurysms, of which 27 (20.5%) were false positives. Of these 27 aneurysms, 18 were completely negative but 9 had an anatomical structure that explained the CTA finding, 18 were either small (6-10 mm, 4%) or very small (1-5 mm, 63%), and 16 were located either in the anterior communicating artery (ACoA) region (33%) or at the basilar artery bifurcation (26%). Additionally, DSA identified 29 aneurysms (21.6%) missed by CTA. The most common locations for these were the cavernous segment of the internal carotid artery (24%) and the middle cerebral artery (24%), and all but 1 were very small (1-5 mm). Conclusion: The CTA accuracy rate may be lower than previously reported. CTA is particularly inaccurate in aneurysms 5 mm or smaller and those in the ACoA region.


Behabadi B.F.,University of Southern California | Polsky A.,U.S. National Institutes of Health | Jadi M.,Salk Institute for Biological Studies | Schiller J.,Technion Medical School | Mel B.W.,University of Southern California
PLoS Computational Biology | Year: 2012

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors. © 2012 Behabadi et al.


Jadi M.,University of Southern California | Jadi M.,Salk Institute for Biological Studies | Polsky A.,Technion Medical School | Schiller J.,Technion Medical School | Mel B.W.,University of Southern California
PLoS Computational Biology | Year: 2012

Cortical computations are critically dependent on interactions between pyramidal neurons (PNs) and a menagerie of inhibitory interneuron types. A key feature distinguishing interneuron types is the spatial distribution of their synaptic contacts onto PNs, but the location-dependent effects of inhibition are mostly unknown, especially under conditions involving active dendritic responses. We studied the effect of somatic vs. dendritic inhibition on local spike generation in basal dendrites of layer 5 PNs both in neocortical slices and in simple and detailed compartmental models, with equivalent results: somatic inhibition divisively suppressed the amplitude of dendritic spikes recorded at the soma while minimally affecting dendritic spike thresholds. In contrast, distal dendritic inhibition raised dendritic spike thresholds while minimally affecting their amplitudes. On-the-path dendritic inhibition modulated both the gain and threshold of dendritic spikes depending on its distance from the spike initiation zone. Our findings suggest that cortical circuits could assign different mixtures of gain vs. threshold inhibition to different neural pathways, and thus tailor their local computations, by managing their relative activation of soma- vs. dendrite-targeting interneurons. © 2012 Jadi et al.

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