An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites

Abstract

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.

Cognitive functions of intracellular mechanisms for contextual amplification

“…Phillips & Silverstein, 2003;Self, Kooijmansa, Supèr, Lamme, & Roelfsema, 2012). As this apical amplification could have far-reaching implications for our understanding of brain and cognition (Jadi, Behabadi, Poleg-Polsky, Schiller, & Mel, 2014;Major, Larkum, & Schiller, 2013;Phillips et al, 2015), its essentials are outlined in Figs. 1 and 2.…”

“…NMDAR antagonists abolish calcium transients in apical dendrites (Palmer et al, 2014), whereas in basal dendrites they linearize response but do not abolish it (Branco & Häusser, 2011;Schiller, Major, Koester, & Schiller, 2000). Linearization of integration in the basal dendrites will degrade their normal operation by removing non-linear aspects of their integration (Jadi et al, 2014) but basal inputs will nevertheless still be able to drive output. Thus this shows how the extensive evidence relating NMDAR hypofunction to schizophrenia (Phillips & Silverstein, 2003Moghaddam & Javitt, 2012) can be reconciled with both the specificity of schizophrenic symptoms and the ubiquity of NMDARs.…”

On the functions, mechanisms, and malfunctions of intracortical contextual modulation

“…This includes changes to either input gain or response gain, but requires output to be at or near zero when there is no driving input. We do not identify it with non-linear interactions in general because it is possible that some RF selectivity depends on other forms of non-linear interaction (Jadi et al, 2014), such as the multiplicative interactions required to compute coordinate transformations (Phillips and Silverstein, 2013).…”

“…Larkum, Zhu, and Sakmann, 1999). The far-reaching implications of such mechanisms are only now becoming clear, however (Larkum et al, 2009;Larkum, 2013;Major, Larkum and Schiller, 2013;Jadi et al, 2014). In vitro studies of rat somatosensory cortex show that, in addition to the somatic sodium spike initiation zone that triggers axonal action potentials, Layer 5 pyramidal cells have an initiation zone at the base of the apical tuft.…”

Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan

“…Furthermore, some of them are isomorphic (e.g. the augmented two-layer neuron model 2LM is isomorphic to a traditional ANN [61]). …”