Abstract:
:Relatively recent advances in patch clamp recordings and iontophoresis have enabled unprecedented study of neuronal post-synaptic integration ("dendritic integration"). Findings support a separate layer of integration in the dendritic branches before potentials reach the cell's soma. While integration between branches obeys previous linear assumptions, proximal inputs within a branch produce threshold nonlinearity, which some authors have likened to the sigmoid function. Here we show the implausibility of a sigmoidal relation and present a more realistic transfer function in both an elegant artificial form and a biophysically derived form that further considers input locations along the dendritic arbor. As the distance between input locations determines their ability to produce nonlinear interactions, models incorporating dendritic topology are essential to understanding the computational power afforded by these early stages of integration. We use the biophysical transfer function to emulate empirical data using biophysical parameters and describe the conditions under which the artificial and biophysically derived forms are equivalent.
journal_name
Front Comput Neuroscijournal_title
Frontiers in computational neuroscienceauthors
Singh MF,Zald DHdoi
10.3389/fncom.2015.00098subject
Has Abstractpub_date
2015-08-10 00:00:00pages
98issn
1662-5188journal_volume
9pub_type
杂志文章abstract::Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the mean values and correlations betw...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/neuro.10.022.2009
更新日期:2009-11-17 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::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
更新日期:2020-03-09 00:00:00
abstract::Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool i...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00042
更新日期:2020-06-26 00:00:00
abstract::We do not claim that the brain is completely deterministic, and we agree that noise may be beneficial in some cases. But we suggest that neuronal variability may be often overestimated, due to uncontrolled internal variables, and/or the use of inappropriate reference times. These ideas are not new, but should be re-ex...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00007
更新日期:2013-02-25 00:00:00
abstract::The histograms of response times of optimal YES/NO decisions that are computed from a single sensory Poisson neuron are highly structured. In particular, response times in NO decisions are quantized to a small set of times, while response times in YES decisions have a multimodal structure. Both the times of NO decisio...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2014.00042
更新日期:2014-04-11 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::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
更新日期:2010-11-19 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::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::The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical ...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00115
更新日期:2013-08-13 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::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::In temporal lobe epilepsy (TLE), the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal d...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2017.00061
更新日期:2017-07-11 00:00:00
abstract::Stability is an important dynamical property of complex systems and underpins a broad range of coherent self-organized behavior. Based on evidence that some neurological disorders correspond to linear instabilities, we hypothesize that stability constrains the brain's electrical activity and influences its structure a...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00031
更新日期:2013-04-12 00:00:00
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
更新日期:2020-02-07 00:00:00
abstract::We often encounter pairs of variables in the world whose mutual relationship can be described by a function. After training, human responses closely correspond to these functional relationships. Here we study how humans predict unobserved segments of a function that they have been trained on and we compare how human p...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2014.00121
更新日期:2014-09-30 00:00:00
abstract::Short-term synaptic plasticity is highly diverse across brain area, cortical layer, cell type, and developmental stage. Since short-term plasticity (STP) strongly shapes neural dynamics, this diversity suggests a specific and essential role in neural information processing. Therefore, a correct characterization of sho...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2013.00075
更新日期:2013-06-06 00:00:00
abstract::Dynamics of a homogeneous neural population interacting with active extracellular medium were considered. The corresponding mathematical model was tuned specifically to describe the behavior of interneurons with tonic GABA conductance under the action of non-stationary ambient GABA. The feedback provided by the GABA m...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2018.00019
更新日期:2018-04-05 00:00:00
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
更新日期:2014-09-09 00:00:00
abstract::Biological realism of dendritic morphologies is important for simulating electrical stimulation of brain tissue. By adding point process modeling and conditional sampling to existing generation strategies, we provide a novel means of reproducing the nuanced branching behavior that occurs in different layers of granule...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2020.00023
更新日期:2020-04-09 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::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
更新日期:2012-04-03 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::Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the informa...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2016.00112
更新日期:2016-10-18 00:00:00
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
更新日期:2015-02-10 00:00:00
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
更新日期:2014-08-15 00:00:00
abstract::A classic problem in neuroscience is how temporal sequences (TSs) can be recognized. This problem is exemplified in the olfactory system, where an odor is defined by the TS of olfactory bulb (OB) output that occurs during a sniff. This sequence is discrete because the output is subdivided by gamma frequency oscillatio...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2014.00108
更新日期:2014-09-17 00:00:00
abstract::Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evalua...
journal_title:Frontiers in computational neuroscience
pub_type: 杂志文章
doi:10.3389/fncom.2011.00048
更新日期:2011-11-10 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