Models Of Directional Selection Research Articles

Finding Direction in the Search for Selection

Tests for positive selection have mostly been developed to look for diversifying selection where change away from the current amino acid is often favorable. However, in many cases we are interested in directional selection where there is a shift toward specific amino acids, resulting in increased fitness in the species. Recently, a few methods have been developed to detect and characterize directional selection on a molecular level. Using the results of evolutionary simulations as well as HIV drug resistance data as models of directional selection, we compare two such methods with each other, as well as against a standard method for detecting diversifying selection. We find that the method to detect diversifying selection also detects directional selection under certain conditions. One method developed for detecting directional selection is powerful and accurate for a wide range of conditions, while the other can generate an excessive number of false positives.

Construction of direction selectivity through local energy computations in primary visual cortex.

Despite detailed knowledge about the anatomy and physiology of neurons in primary visual cortex (V1), the large numbers of inputs onto a given V1 neuron make it difficult to relate them to the neuron’s functional properties. For example, models of direction selectivity (DS), such as the Energy Model, can successfully describe the computation of phase-invariant DS at a conceptual level, while leaving it unclear how such computations are implemented by cortical circuits. Here, we use statistical modeling to derive a description of DS computation for both simple and complex cells, based on physiologically plausible operations on their inputs. We present a new method that infers the selectivity of a neuron’s inputs using extracellular recordings in macaque in the context of random bar stimuli and natural movies in cat. Our results suggest that DS is initially constructed in V1 simple cells through summation and thresholding of non-DS inputs with appropriate spatiotemporal relationships. However, this de novo construction of DS is rare, and a majority of DS simple cells, and all complex cells, appear to receive both excitatory and suppressive inputs that are already DS. For complex cells, these numerous DS inputs typically span a fraction of their overall receptive fields and have similar spatiotemporal tuning but different phase and spatial positions, suggesting an elaboration to the Energy Model that incorporates spatially localized computation. Furthermore, we demonstrate how these computations might be constructed from biologically realizable components, and describe a statistical model consistent with the feed-forward framework suggested by Hubel and Wiesel.

A model of direction selectivity in the starburst amacrine cell network

Displaced starburst amacrine cells (SACs) are retinal interneurons that exhibit GABAA receptor-mediated and Cl − cotransporter-mediated, directionally selective (DS) light responses in the rabbit retina. They depolarize to stimuli that move centrifugally through the receptive field surround and hyperpolarize to stimuli that move centripetally through the surround (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006). They also play a key role in the activity of DS ganglion cells (DS GC; Amthor et al, Vis Neurosci 19:495–509 2002; Euler et al, Nature 418:845–852, 2002; Fried et al, Nature 420:411– 414, 2002; Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799 2006; Yoshida et al, Neuron 30:771–780, 2001). In this paper we present a model of strong DS behavior of SACs which relies on the GABA-mediated communication within a tightly interconnected network of these cells and on the glutamate signal that the SACs receive from bipolar cells (a presynaptic cell that receives input from cones). We describe how a moving light stimulus can produce a large, sustained depolarization of the SAC dendritic tips that point in the direction that the stimulus moves (i.e., centrifugal motion), but produce a minimal depolarization of the dendritic tips that point in the opposite direction (i.e., centripetal motion). This DS behavior, which is quantified based on the relative size and duration of the depolarizations evoked by stimulus motion at dendritic tips pointing in opposite directions, is robust to changes of many different parameter values and consistent with experimental data. In addition, the DS behavior is strengthened under the assumptions that the Cl− cotransporters Na + -K + -Cl − and K + -Cl − are located in different regions of the SAC dendritic tree (Gavrikov et al, PNAS 103(49):18793–18798, 2006) and that GABA evokes a long-lasting response (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799, 2006). A possible mechanism is discussed based on the generation of waves of local glutamate and GABA secretion, and their postsynaptic interplay as the waves travel between cell compartments.

Assessing the role of abundance in marine bivalve extinction over the post-Paleozoic

Abundance is one of the primary factors believed to influence extinction yet little is known about its relationship to extinction rates over geologic time. Using data from the Paleobiology Database we show that abundance was an important factor in the extinction dynamics of marine bivalve genera over the post-Paleozoic. Contrary to expectations, our analyses reveal a nonlinear relationship between abundance and extinction rates, with rare and abundant genera exhibiting rates elevated over those of genera of moderate abundance. This U-shaped pattern is a persistent feature of the post-Paleozoic history of marine bivalves and provides one possible explanation for why we find strong support for heterogeneous extinction rates among genera grouped by similarity in abundance yet effectively no net relationship among these rates when using models of directional selection on abundance.

Direction selectivity of simple cells in the primary visual cortex: Comparison of two alternative mathematical models. II: Velocity tuning and response to moving bars

The two models of direction selectivity, presented in a previous paper, are used to investigate the response of simple cells to moving bars with different length, luminance and orientation. Most results agree with experimental data reported in the literature. However, a striking difference between the models is observable after a reduction in bar length. The antiphase model predicts that the optimal direction of movement for a short bar is equal to the optimal direction for a long bar, whereas the in-phase model predicts that the two optimal directions are orthogonal. This difference may allow experimental discrimination between the two models.

Cation--chloride cotransporters mediate neural computation in the retina.

The ability of directionally selective (DS) retinal ganglion cells to respond selectively to stimulus motion in one direction is a classic unresolved example of computation in a local neural circuit. Recent evidence indicates that DS responses occur first in the retina in the dendrites of starburst amacrine cells (interneurons presynaptic to the ganglion cells). We report that the directional responses of starburst-cell dendrites and DS ganglion cells are highly sensitive to the polarity of the transmembrane chloride gradient. Reducing the transmembrane chloride gradient by ion substitution or by blocking the K-Cl cotransporter resulted in the starburst cells responding equally to light moving in opposite directions. Conversely, increasing the chloride gradient by blocking the Na-K-Cl cotransporter eliminated responses to light moving in either direction. Moreover, in each case, blocking the chloride cotransporters or reducing the transmembrane chloride gradient eliminated the directional responses of DS ganglion cells in a manner opposite that of the starburst cells. These results indicate that chloride cotransporters play a key role in the generation of direction selectivity and that the directional responses of starburst cells and DS ganglion cells are exquisitely sensitive to the chloride equilibrium potential. The findings further suggest that the directional responses of DS ganglion cells are mediated in part by the directional release of gamma-aminobutyric acid from starburst dendrites and that the asymmetric distribution of the two cotransporters along starburst-cell dendrites mediates direction selectivity. A model of direction selectivity in the retina that incorporates these and other findings is discussed.

Analog VLSI Circuits for Short-Term Dynamic Synapses

Short-term dynamical synapses increase the computational power of neuronal networks. These synapses act as additional filters to the inputs of a neuron before the subsequent integration of these signals at its cell body. In this work, we describe a model of depressing and facilitating synapses derived from a hardware circuit implementation. This model is equivalent to theoretical models of short-term synaptic dynamics in network simulations. These circuits have been added to a network of leaky integrate-and-fire neurons. A cortical model of direction-selectivity that uses short-term dynamic synapses has been implemented with this network.

Modeling direction selectivity of simple cells in striate visual cortex within the framework of the canonical microcircuit

Nearly all models of direction selectivity (DS) in visual cortex are based on feedforward connection schemes, where geniculate input provides all excitatory synaptic input to both pyramidal and inhibitory neurons. Feedforward inhibition then suppresses feedforward excitation for nonoptimal stimuli. Anatomically, however, the majority of asymmetric, excitatory, synaptic contacts onto cortical cells is provided by other cortical neurons, as embodied in the Canonical Microcircuit of Douglas and Martin (1991). In this view, weak geniculate input is strongly amplified in the preferred direction by the action of intracortical excitatory connections, while in the null direction inhibition reduces geniculate-induced excitation. We investigate analytically and through biologically realistic computer simulations the functioning of a cortical network based on massive excitatory, cortico-cortical feedback. The behavior of this network is compared to physiological data as well as to the behavior of a purely feedforward model of DS based on nonlagged input. Our model explains a number of puzzling features of direction selective simple cells, including the small somatic input conductance changes that have been measured experimentally during stimulation in the null direction, and the persistence of DS while fully blocking inhibition in a single cell. Although the operation at the heart of our network is amplification, the network passes the linearity test of (Jagadeesh et al., 1993). We make specific predictions concerning the effect of selective blockade of cortical inhibition on the velocity-response curve.