Abstract:
:Conscious awareness plays a major role in human cognition and adaptive behavior, though its function in multisensory integration is not yet fully understood, hence, questions remain: How does the brain integrate the incoming multisensory signals with respect to different external environments? How are the roles of these multisensory signals defined to adhere to the anticipated behavioral-constraint of the environment? This work seeks to articulate a novel theory on conscious multisensory integration (CMI) that addresses the aforementioned research challenges. Specifically, the well-established contextual field (CF) in pyramidal cells and coherent infomax theory (Kay et al., 1998; Kay and Phillips, 2011) is split into two functionally distinctive integrated input fields: local contextual field (LCF) and universal contextual field (UCF). LCF defines the modulatory sensory signal coming from some other parts of the brain (in principle from anywhere in space-time) and UCF defines the outside environment and anticipated behavior (based on past learning and reasoning). Both LCF and UCF are integrated with the receptive field (RF) to develop a new class of contextually-adaptive neuron (CAN), which adapts to changing environments. The proposed theory is evaluated using human contextual audio-visual (AV) speech modeling. Simulation results provide new insights into contextual modulation and selective multisensory information amplification/suppression. The central hypothesis reviewed here suggests that the pyramidal cell, in addition to the classical excitatory and inhibitory signals, receives LCF and UCF inputs. The UCF (as a steering force or tuner) plays a decisive role in precisely selecting whether to amplify/suppress the transmission of relevant/irrelevant feedforward signals, without changing the content e.g., which information is worth paying more attention to? This, as opposed to, unconditional excitatory and inhibitory activity in existing deep neural networks (DNNs), is called conditional amplification/suppression.
journal_name
Front Comput Neuroscijournal_title
Frontiers in computational neuroscienceauthors
Adeel Adoi
10.3389/fncom.2020.00015subject
Has Abstractpub_date
2020-05-19 00:00:00pages
15issn
1662-5188journal_volume
14pub_type
杂志文章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
更新日期:2007-11-02 00:00:00
abstract::Internal coordination models hold that early nervous systems evolved in the first place to coordinate internal activity at a multicellular level, most notably the use of multicellular contractility as an effector for motility. A recent example of such a model, the skin brain thesis, suggests that excitable epithelia u...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2015.00110
更新日期:2015-09-15 00:00:00
abstract::The inverse problem for estimating model parameters from brain spike data is an ill-posed problem because of a huge mismatch in the system complexity between the model and the brain as well as its non-stationary dynamics, and needs a stochastic approach that finds the most likely solution among many possible solutions...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2015.00056
更新日期:2015-05-21 00:00:00
abstract::In order to be able to examine the extracellular potential's influence on network activity and to better understand dipole properties of the extracellular potential, we present and analyze a three-dimensional formulation of the cable equation which facilitates numeric simulations. When the neuron's intra- and extracel...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2015.00094
更新日期:2015-07-17 00:00:00
abstract::In synapses, calcium is required for modulating synaptic transmission, plasticity, synaptogenesis, and synaptic pruning. The regulation of calcium dynamics within neurons involves cellular mechanisms such as synaptically activated channels and pumps, calcium buffers, and calcium sequestrating organelles. Many experime...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2018.00058
更新日期:2018-07-27 00:00:00
abstract::Dopaminergic neurons in the mammalian substantia nigra display characteristic phasic responses to stimuli which reliably predict the receipt of primary rewards. These responses have been suggested to encode reward prediction-errors similar to those used in reinforcement learning. Here, we propose a model of dopaminerg...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2011.00021
更新日期:2011-05-18 00:00:00
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
更新日期:2014-06-11 00:00:00
abstract::The extent to which groups of neurons exhibit higher-order correlations in their spiking activity is a controversial issue in current brain research. A major difficulty is that currently available tools for the analysis of massively parallel spike trains (N >10) for higher-order correlations typically require vast sam...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2010.00016
更新日期:2010-07-02 00:00:00
abstract::What are the functional neuroimaging measurements required for more fully characterizing the events and locations of neocortical activity? A prime assumption has been that modulation of cortical activity will inevitably be reflected in changes in energy utilization (for the most part) changes of glucose and oxygen con...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2012.00101
更新日期:2013-01-24 00:00:00
abstract::Often we need to perform tasks in an environment that changes stochastically. In these situations it is important to learn the statistics of sequences of events in order to predict the future and the outcome of our actions. The statistical description of many of these sequences can be reduced to the set of probabiliti...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00032
更新日期:2013-04-12 00:00:00
abstract::A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data. Popular examples are principal component analysis (PCA), independent component analysis (ICA), anechoic demixing, and the time-varying synergy model (d'Avella ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00185
更新日期:2013-12-20 00:00:00
abstract::Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2017.00037
更新日期:2017-05-22 00:00:00
abstract::Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention mod...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00064
更新日期:2016-07-14 00:00:00
abstract::Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00058
更新日期:2016-06-10 00:00:00
abstract::The problem of cancer risk analysis is of great importance to health-service providers and medical researchers. In this study, we propose a novel Artificial Neural Network (ANN) algorithm based on the probabilistic framework, which aims to investigate patient patterns associated with their disease development. Compare...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00058
更新日期:2020-07-21 00:00:00
abstract::Common computational principles underlie processing of various visual features in the cortex. They are considered to create similar patterns of contextual modulations in behavioral studies for different features as orientation and direction of motion. Here, I studied the possibility that a single theoretical framework...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2012.00028
更新日期:2012-05-22 00:00:00
abstract::Synaptic transmission is both history-dependent and stochastic, resulting in varying responses to presentations of the same presynaptic stimulus. This complicates attempts to infer synaptic parameters and has led to the proposal of a number of different strategies for their quantification. Recently Bayesian approaches...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00116
更新日期:2016-11-25 00:00:00
abstract::Previous studies have shown that the auditory cortex can enhance the perception of behaviorally important sounds in the presence of background noise, but the mechanisms by which it does this are not yet elucidated. Rapid plasticity of spectrotemporal receptive fields (STRFs) in the primary (A1) cortical neurons is obs...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2019.00028
更新日期:2019-05-24 00:00:00
abstract::Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. W...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00112
更新日期:2013-09-17 00:00:00
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
更新日期:2013-07-01 00:00:00
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
更新日期:2011-06-01 00:00:00
abstract::Although the representation of space is as fundamental to visual processing as the representation of shape, it has received relatively little attention from neurophysiological investigations. In this study we characterize representations of space within visual cortex, and examine how they differ in a first direct comp...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2010.00159
更新日期:2011-02-01 00:00:00
abstract::Image registration and segmentation are the two most studied problems in medical image analysis. Deep learning algorithms have recently gained a lot of attention due to their success and state-of-the-art results in variety of problems and communities. In this paper, we propose a novel, efficient, and multi-task algori...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00017
更新日期:2020-03-20 00:00:00
abstract::Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated by a central patte...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00024
更新日期:2013-04-04 00:00:00
abstract::We describe a model for cortical development that resolves long-standing difficulties of earlier models. It is proposed that, during embryonic development, synchronous firing of neurons and their competition for limited metabolic resources leads to selection of an array of neurons with ultra-small-world characteristic...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00004
更新日期:2013-02-15 00:00:00
abstract::Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a cond...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2011.00060
更新日期:2011-12-16 00:00:00
abstract::The emergence of motion sensors as a tool that provides objective motor performance data on individuals afflicted with Parkinson's disease offers an opportunity to expand the horizon of clinical care for this neurodegenerative condition. Subjective clinical scales and patient based motor diaries have limited clinometr...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章,评审
doi:10.3389/fncom.2018.00072
更新日期:2018-09-11 00:00:00
abstract::Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community. However, current few-shot learners are mostly supervised and rely heavily on a large amount of labeled examples. Unsupervised learning is a more natural procedure...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00083
更新日期:2020-10-14 00:00:00
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
更新日期:2018-11-22 00:00:00
abstract::We present a network model of striatum, which generates "winnerless" dynamics typical for a network of sparse, unidirectionally connected inhibitory units. We observe that these dynamics, while interesting and a good match to normal striatal electrophysiological recordings, are fragile. Specifically, we find that rand...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2017.00070
更新日期:2017-07-27 00:00:00