Visual motion integration is mediated by directional ambiguities in local motion signals.

Abstract:

:The output of primary visual cortex (V1) is a piecemeal representation of the visual scene and the response of any one cell cannot unambiguously guide sensorimotor behavior. It remains unsolved how subsequent stages of cortical processing combine ("pool") these early visual signals into a coherent representation. We (Webb et al., 2007, 2011) have shown that responses of human observers on a pooling task employing broadband, random dot motion can be accurately predicted by decoding the maximum likelihood direction from a population of motion-sensitive neurons. Whereas Amano et al. (2009) found that the vector average velocity of arrays of narrowband, two-dimensional (2-d) plaids predicts perceived global motion. To reconcile these different results, we designed two experiments in which we used 2-d noise textures moving behind spatially distributed apertures and measured the point of subjective equality between pairs of global noise textures. Textures in the standard stimulus moved rigidly in the same direction, whereas their directions in the comparison stimulus were sampled from a set of probability distributions. Human observers judged which noise texture had a more clockwise (CW) global direction. In agreement with Amano and colleagues, observers' perceived global motion coincided with the vector average stimulus direction. To test if directional ambiguities in local motion signals governed perceived global direction, we manipulated the fidelity of the texture motion within each aperture. A proportion of the apertures contained texture that underwent rigid translation and the remainder contained dynamic (temporally uncorrelated) noise to create locally ambiguous motion. Perceived global motion matched the vector average when the majority of apertures contained rigid motion, but with increasing levels of dynamic noise shifted toward the maximum likelihood direction. A class of population decoders utilizing power-law non-linearities can accommodate this flexible pooling.

journal_name

Front Comput Neurosci

authors

Rocchi F,Ledgeway T,Webb BS

doi

10.3389/fncom.2013.00167

subject

Has Abstract

pub_date

2013-11-18 00:00:00

pages

167

issn

1662-5188

journal_volume

7

pub_type

杂志文章
  • Letting the daylight in: Reviewing the reviewers and other ways to maximize transparency in science.

    abstract::With the emergence of online publishing, opportunities to maximize transparency of scientific research have grown considerably. However, these possibilities are still only marginally used. We argue for the implementation of (1) peer-reviewed peer review, (2) transparent editorial hierarchies, and (3) online data publi...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2012.00020

    authors: Wicherts JM,Kievit RA,Bakker M,Borsboom D

    更新日期:2012-04-03 00:00:00

  • Causal Inference for Cross-Modal Action Selection: A Computational Study in a Decision Making Framework.

    abstract::Animals try to make sense of sensory information from multiple modalities by categorizing them into perceptions of individual or multiple external objects or internal concepts. For example, the brain constructs sensory, spatial representations of the locations of visual and auditory stimuli in the visual and auditory ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00062

    authors: Daemi M,Harris LR,Crawford JD

    更新日期:2016-06-23 00:00:00

  • Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis.

    abstract::The accurate automatic segmentation of gliomas and its intra-tumoral structures is important not only for treatment planning but also for follow-up evaluations. Several methods based on 2D and 3D Deep Neural Networks (DNN) have been developed to segment brain tumors and to classify different categories of tumors from ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00006

    authors: Natekar P,Kori A,Krishnamurthi G

    更新日期:2020-02-07 00:00:00

  • Probabilistic Circuits for Autonomous Learning: A Simulation Study.

    abstract::Modern machine learning is based on powerful algorithms running on digital computing platforms and there is great interest in accelerating the learning process and making it more energy efficient. In this paper we present a fully autonomous probabilistic circuit for fast and efficient learning that makes no use of dig...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00014

    authors: Kaiser J,Faria R,Camsari KY,Datta S

    更新日期:2020-02-25 00:00:00

  • Neural Coding With Bursts-Current State and Future Perspectives.

    abstract::Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章,评审

    doi:10.3389/fncom.2018.00048

    authors: Zeldenrust F,Wadman WJ,Englitz B

    更新日期:2018-07-06 00:00:00

  • Inhibition potentiates the synchronizing action of electrical synapses.

    abstract::In vivo and in vitro experimental studies have found that blocking electrical interactions connecting GABAergic interneurons reduces oscillatory activity in the gamma range in cortex. However, recent theoretical works have shown that the ability of electrical synapses to promote or impede synchrony, when alone, depend...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/neuro.10.008.2007

    authors: Pfeuty B,Golomb D,Mato G,Hansel D

    更新日期:2007-11-02 00:00:00

  • Information diversity in structure and dynamics of simulated neuronal networks.

    abstract::Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neurona...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2011.00026

    authors: Mäki-Marttunen T,Aćimović J,Nykter M,Kesseli J,Ruohonen K,Yli-Harja O,Linne ML

    更新日期:2011-06-01 00:00:00

  • Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits.

    abstract::Synchronization of neural activity across brain regions is critical to processes that include perception, learning, and memory. After traumatic brain injury (TBI), neuronal degeneration is one possible effect and can alter communication between neural circuits. Consequently, synchronization between neurons may change ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00018

    authors: Schumm SN,Gabrieli D,Meaney DF

    更新日期:2020-03-03 00:00:00

  • Correlation-based analysis and generation of multiple spike trains using hawkes models with an exogenous input.

    abstract::The correlation structure of neural activity is believed to play a major role in the encoding and possibly the decoding of information in neural populations. Recently, several methods were developed for exactly controlling the correlation structure of multi-channel synthetic spike trains (Brette, 2009; Krumin and Shoh...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2010.00147

    authors: Krumin M,Reutsky I,Shoham S

    更新日期:2010-11-19 00:00:00

  • Learning modular policies for robotics.

    abstract::A promising idea for scaling robot learning to more complex tasks is to use elemental behaviors as building blocks to compose more complex behavior. Ideally, such building blocks are used in combination with a learning algorithm that is able to learn to select, adapt, sequence and co-activate the building blocks. Whil...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章,评审

    doi:10.3389/fncom.2014.00062

    authors: Neumann G,Daniel C,Paraschos A,Kupcsik A,Peters J

    更新日期:2014-06-11 00:00:00

  • Topological View of Flows Inside the BOLD Spontaneous Activity of the Human Brain.

    abstract::Spatio-temporal brain activities with variable delay detectable in resting-state functional magnetic resonance imaging (rs-fMRI) give rise to highly reproducible structures, termed cortical lag threads, that propagate from one brain region to another. Using a computational topology of data approach, we found that pers...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00034

    authors: Don APH,Peters JF,Ramanna S,Tozzi A

    更新日期:2020-04-22 00:00:00

  • Sex Differences in Fiber Connection between the Striatum and Subcortical and Cortical Regions.

    abstract::The striatum is an important subcortical structure with extensive connections to other regions of the brain. These connections are believed to play important roles in behaviors such as reward-related processes and impulse control, which show significant sex differences. However, little is known about sex differences i...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00100

    authors: Lei X,Han Z,Chen C,Bai L,Xue G,Dong Q

    更新日期:2016-09-23 00:00:00

  • On the role of spatial phase and phase correlation in vision, illusion, and cognition.

    abstract::Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00045

    authors: Gladilin E,Eils R

    更新日期:2015-04-21 00:00:00

  • Analog Signaling With the "Digital" Molecular Switch CaMKII.

    abstract::Molecular switches, such as the protein kinase CaMKII, play a fundamental role in cell signaling by decoding inputs into either high or low states of activity; because the high activation state can be turned on and persist after the input ceases, these switches have earned a reputation as "digital." Although this on/o...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00092

    authors: Clarke SE

    更新日期:2018-11-22 00:00:00

  • Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation.

    abstract::The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior oli...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章,评审

    doi:10.3389/fncom.2014.00097

    authors: Luque NR,Garrido JA,Carrillo RR,D'Angelo E,Ros E

    更新日期:2014-08-15 00:00:00

  • Steering the Volume of Tissue Activated With a Directional Deep Brain Stimulation Lead in the Globus Pallidus Pars Interna: A Modeling Study With Heterogeneous Tissue Properties.

    abstract::Objective: To study the effect of directional deep brain stimulation (DBS) electrode configuration and vertical electrode spacing on the volume of tissue activated (VTA) in the globus pallidus, pars interna (GPi). Background: Directional DBS leads may allow clinicians to precisely direct current fields to different fu...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.561180

    authors: Zhang S,Tagliati M,Pouratian N,Cheeran B,Ross E,Pereira E

    更新日期:2020-09-25 00:00:00

  • Reducing the Effect of Spurious Phase Variations in Neural Oscillatory Signals.

    abstract::The phase-reset model of oscillatory EEG activity has received a lot of attention in the last decades for decoding different cognitive processes. Based on this model, the ERPs are assumed to be generated as a result of phase reorganization in ongoing EEG. Alignment of the phase of neuronal activities can be observed w...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00082

    authors: Mortezapouraghdam Z,Corona-Strauss FI,Takahashi K,Strauss DJ

    更新日期:2018-10-08 00:00:00

  • Bursting Neurons in the Hippocampal Formation Encode Features of LFP Rhythms.

    abstract::Burst spike patterns are common in regions of the hippocampal formation such as the subiculum and medial entorhinal cortex (MEC). Neurons in these areas are immersed in extracellular electrical potential fluctuations often recorded as the local field potential (LFP). LFP rhythms within different frequency bands are li...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00133

    authors: Constantinou M,Gonzalo Cogno S,Elijah DH,Kropff E,Gigg J,Samengo I,Montemurro MA

    更新日期:2016-12-26 00:00:00

  • Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

    abstract::Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00062

    authors: Yi GS,Wang J,Tsang KM,Wei XL,Deng B

    更新日期:2015-05-27 00:00:00

  • Brain Network Analysis and Classification Based on Convolutional Neural Network.

    abstract::Background: Convolution neural networks (CNN) is increasingly used in computer science and finds more and more applications in different fields. However, analyzing brain network with CNN is not trivial, due to the non-Euclidean characteristics of brain network built by graph theory. Method: To address this problem, we...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00095

    authors: Meng L,Xiang J

    更新日期:2018-12-10 00:00:00

  • Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

    abstract::Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2017.00087

    authors: Meyer-Bäse A,Roberts RG,Illan IA,Meyer-Bäse U,Lobbes M,Stadlbauer A,Pinker-Domenig K

    更新日期:2017-10-05 00:00:00

  • Neuromodulation impact on nonlinear firing behavior of a reduced model motoneuron with the active dendrite.

    abstract::Neuromodulatory inputs from brainstem systems modulate the normal function of spinal motoneurons by altering the activation properties of persistent inward currents (PICs) in their dendrites. However, the effect of the PIC on firing outputs also depends on its location in the dendritic tree. To investigate the interac...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00110

    authors: Kim H,Heckman CJ

    更新日期:2014-09-09 00:00:00

  • Tracking cortical entrainment in neural activity: auditory processes in human temporal cortex.

    abstract::A primary objective for cognitive neuroscience is to identify how features of the sensory environment are encoded in neural activity. Current auditory models of loudness perception can be used to make detailed predictions about the neural activity of the cortex as an individual listens to speech. We used two such mode...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00005

    authors: Thwaites A,Nimmo-Smith I,Fonteneau E,Patterson RD,Buttery P,Marslen-Wilson WD

    更新日期:2015-02-10 00:00:00

  • A Neuronal Network Model for Pitch Selectivity and Representation.

    abstract::Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is de...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00057

    authors: Huang C,Rinzel J

    更新日期:2016-06-16 00:00:00

  • Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data.

    abstract::Automatic segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) images is essential for clinical assessment and treatment planning of MS. Recent years have seen an increasing use of Convolutional Neural Networks (CNNs) for this task. Although these methods provide accurate segmentation,...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00019

    authors: Ackaouy A,Courty N,Vallée E,Commowick O,Barillot C,Galassi F

    更新日期:2020-03-09 00:00:00

  • Interareal coupling reduces encoding variability in multi-area models of spatial working memory.

    abstract::Persistent activity observed during delayed-response tasks for spatial working memory (Funahashi et al., 1989) has commonly been modeled by recurrent networks whose dynamics is described as a bump attractor (Compte et al., 2000). We examine the effects of interareal architecture on the dynamics of bump attractors in s...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00082

    authors: Kilpatrick ZP

    更新日期:2013-07-01 00:00:00

  • A Spiking Neural Model of HT3D for Corner Detection.

    abstract::Obtaining good quality image features is of remarkable importance for most computer vision tasks. It has been demonstrated that the first layers of the human visual cortex are devoted to feature detection. The need for these features has made line, segment, and corner detection one of the most studied topics in comput...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00037

    authors: Bachiller-Burgos P,Manso LJ,Bustos P

    更新日期:2018-06-01 00:00:00

  • Short-Term Facilitation may Stabilize Parametric Working Memory Trace.

    abstract::Networks with continuous set of attractors are considered to be a paradigmatic model for parametric working memory (WM), but require fine tuning of connections and are thus structurally unstable. Here we analyzed the network with ring attractor, where connections are not perfectly tuned and the activity state therefor...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2011.00040

    authors: Itskov V,Hansel D,Tsodyks M

    更新日期:2011-10-24 00:00:00

  • A Phenomenological Model of the Electrically Stimulated Auditory Nerve Fiber: Temporal and Biphasic Response Properties.

    abstract::We present a phenomenological model of electrically stimulated auditory nerve fibers (ANFs). The model reproduces the probabilistic and temporal properties of the ANF response to both monophasic and biphasic stimuli, in isolation. The main contribution of the model lies in its ability to reproduce statistics of the AN...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00008

    authors: Horne CD,Sumner CJ,Seeber BU

    更新日期:2016-02-08 00:00:00

  • A Role for Electrotonic Coupling Between Cortical Pyramidal Cells.

    abstract::Many brain regions communicate information through synchronized network activity. Electrical coupling among the dendrites of interneurons in the cortex has been implicated in forming and sustaining such activity in the cortex. Evidence for the existence of electrical coupling among cortical pyramidal cells, however, h...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2019.00033

    authors: Crodelle J,Zhou D,Kovačič G,Cai D

    更新日期:2019-05-28 00:00:00