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 sample sizes. While multiple single-cell recordings become increasingly available, experimental approaches to investigate the role of higher-order correlations suffer from the limitations of available analysis techniques. We have recently presented a novel method for cumulant-based inference of higher-order correlations (CuBIC) that detects correlations of higher order even from relatively short data stretches of length T = 10-100 s. CuBIC employs the compound Poisson process (CPP) as a statistical model for the population spike counts, and assumes spike trains to be stationary in the analyzed data stretch. In the present study, we describe a non-stationary version of the CPP by decoupling the correlation structure from the spiking intensity of the population. This allows us to adapt CuBIC to time-varying firing rates. Numerical simulations reveal that the adaptation corrects for false positive inference of correlations in data with pure rate co-variation, while allowing for temporal variations of the firing rates has a surprisingly small effect on CuBICs sensitivity for correlations.
journal_name
Front Comput Neuroscijournal_title
Frontiers in computational neuroscienceauthors
Staude B,Grün S,Rotter Sdoi
10.3389/fncom.2010.00016subject
Has Abstractpub_date
2010-07-02 00:00:00issn
1662-5188journal_volume
4pub_type
杂志文章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::Balanced states in large networks are a usual hypothesis for explaining the variability of neural activity in cortical systems. In this regime the statistics of the inputs is characterized by static and dynamic fluctuations. The dynamic fluctuations have a Gaussian distribution. Such statistics allows to use reverse c...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2011.00041
更新日期:2011-10-12 00:00:00
abstract::For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which n...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2012.00062
更新日期:2012-09-06 00:00:00
abstract::The motor system generates time-varying commands to move our limbs and body. Conventional descriptions of motor control and learning rely on dynamical representations of our body's state (forward and inverse models), and control policies that must be integrated forward to generate feedforward time-varying commands; th...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2015.00032
更新日期:2015-03-19 00:00:00
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
更新日期:2018-12-10 00:00:00
abstract::Brain computer interfaces allow users to preform various tasks using only the electrical activity of the brain. BCI applications often present the user a set of stimuli and record the corresponding electrical response. The BCI algorithm will then have to decode the acquired brain response and perform the desired task....
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00130
更新日期:2016-12-20 00:00:00
abstract::We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2014.00140
更新日期:2014-11-07 00:00:00
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
更新日期:2016-12-26 00:00:00
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 the...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00015
更新日期:2020-05-19 00:00:00
abstract::Despite an abundance of computational models for learning of synaptic weights, there has been relatively little research on structural plasticity, i.e., the creation and elimination of synapses. Especially, it is not clear how structural plasticity works in concert with spike-timing-dependent plasticity (STDP) and wha...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00093
更新日期:2016-09-08 00:00:00
abstract::Proprioceptive afferents from muscle spindles encode information about peripheral joint movements for the central nervous system (CNS). The sensitivity of muscle spindle is nonlinearly dependent on the activation of gamma (γ) motoneurons in the spinal cord that receives inputs from the motor cortex. How fusimotor cont...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2012.00066
更新日期:2012-08-30 00:00:00
abstract::Affective human-robot interaction requires lightweight software and cheap wearable devices that could further this field. However, the estimation of emotions in real-time poses a problem that has not yet been optimized. An optimization is proposed for the emotion estimation methodology including artifact removal, feat...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2019.00080
更新日期:2019-11-26 00:00:00
abstract::Cooperation and competition, as two common and opposite examples of interpersonal dynamics, are thought to be reflected by different cognitive, neural, and behavioral patterns. According to the conventional approach, they have been explored by measuring subjects' reactions during individual performance or turn-based i...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章,评审
doi:10.3389/fncom.2017.00086
更新日期:2017-09-29 00:00:00
abstract::A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge th...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2010.00141
更新日期:2010-11-23 00:00:00
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
更新日期:2015-05-27 00:00:00
abstract::Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in deci...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00033
更新日期:2016-04-20 00:00:00
abstract::We address a question on the effect of common stochastic inputs on the correlation of the spike trains of two neurons when they are coupled through direct connections. We show that the change in the correlation of small amplitude stochastic inputs can be better detected when the neurons are connected by direct excitat...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00108
更新日期:2013-08-14 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::Recent research in neuroscience indicates the importance of tripartite synapses and gliotransmission mediated by astrocytes in neuronal system modulation. Although the astrocyte and neuronal network functions are interrelated, they are fundamentally different in their signaling patterns and, possibly, the time scales ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2019.00092
更新日期:2020-01-22 00:00:00
abstract::Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational stu...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2012.00056
更新日期:2012-08-24 00:00:00
abstract::The human brain is a complex system composed by several large scale intrinsic networks with distinct functions. The low frequency oscillation (LFO) signal of blood oxygen level dependent (BOLD), measured through resting-state fMRI, reflects the spontaneous neural activity of these networks. We propose to characterize ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2018.00064
更新日期:2018-08-03 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::Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2015.00047
更新日期:2015-04-30 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::Scaffolds and patterned substrates are among the most successful strategies to dictate the connectivity between neurons in culture. Here, we used numerical simulations to investigate the capacity of physical obstacles placed on a flat substrate to shape structural connectivity, and in turn collective dynamics and effe...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00077
更新日期:2020-08-31 00:00:00
abstract::This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy co...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2017.00010
更新日期:2017-02-21 00:00:00
abstract::Sensitivity analysis can provide useful information when one is interested in identifying the parameter θ of a system since it measures the variations of the output u when θ changes. In the literature two different sensitivity functions are frequently used: the traditional sensitivity functions (TSF) and the generaliz...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2010.00138
更新日期:2010-09-30 00:00:00
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
更新日期:2019-05-28 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 role of dendritic spiking mechanisms in neural processing is so far poorly understood. To investigate the role of calcium spikes in the functional properties of the single neuron and recurrent networks, we investigated a three compartment neuron model of the layer 5 pyramidal neuron with calcium dynamics in the di...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00076
更新日期:2016-07-22 00:00:00