scholarly journals Robust point-process Granger causality analysis in presence of exogenous temporal modulations and trial-by-trial variability in spike trains

2021 ◽  
Vol 17 (1) ◽  
pp. e1007675
Author(s):  
Antonino Casile ◽  
Rose T. Faghih ◽  
Emery N. Brown
Keyword(s):  
Granger Causality ◽  
Point Process ◽  
Temporal Structure ◽  
Temporal Variations ◽  
Spike Trains ◽  
Neuronal Firing ◽  
Connectivity Pattern ◽  
Relative Reduction ◽  
Neuronal Responses ◽  
Neurophysiological Studies

Assessing directional influences between neurons is instrumental to understand how brain circuits process information. To this end, Granger causality, a technique originally developed for time-continuous signals, has been extended to discrete spike trains. A fundamental assumption of this technique is that the temporal evolution of neuronal responses must be due only to endogenous interactions between recorded units, including self-interactions. This assumption is however rarely met in neurophysiological studies, where the response of each neuron is modulated by other exogenous causes such as, for example, other unobserved units or slow adaptation processes. Here, we propose a novel point-process Granger causality technique that is robust with respect to the two most common exogenous modulations observed in real neuronal responses: within-trial temporal variations in spiking rate and between-trial variability in their magnitudes. This novel method works by explicitly including both types of modulations into the generalized linear model of the neuronal conditional intensity function (CIF). We then assess the causal influence of neuron i onto neuron j by measuring the relative reduction of neuron j’s point process likelihood obtained considering or removing neuron i. CIF’s hyper-parameters are set on a per-neuron basis by minimizing Akaike’s information criterion. In synthetic data sets, generated by means of random processes or networks of integrate-and-fire units, the proposed method recovered with high accuracy, sensitivity and robustness the underlying ground-truth connectivity pattern. Application of presently available point-process Granger causality techniques produced instead a significant number of false positive connections. In real spiking responses recorded from neurons in the monkey pre-motor cortex (area F5), our method revealed many causal relationships between neurons as well as the temporal structure of their interactions. Given its robustness our method can be effectively applied to real neuronal data. Furthermore, its explicit estimate of the effects of unobserved causes on the recorded neuronal firing patterns can help decomposing their temporal variations into endogenous and exogenous components.

scholarly journals Robust point-process Granger causality analysis in presence of exogenous temporal modulations and trial-by-trial variability in spike trains

2020 ◽  
Author(s):  
Antonino Casile ◽  
Rose T. Faghih ◽  
Emery N. Brown
Keyword(s):  
Granger Causality ◽  
Point Process ◽  
Temporal Variability ◽  
Temporal Structure ◽  
Ground Truth ◽  
Temporal Variations ◽  
Spike Trains ◽  
Causal Relationships ◽  
Neuronal Responses ◽  
Flow Of Information

AbstractAssessing directional influences between neurons is instrumental to understand how brain circuits process information. To this end, Granger causality, a technique originally developed for time-continuous signals, has been extended to discrete spike trains. A fundamental assumption of this technique is that the temporal evolution of neuronal responses must be due only to endogenous interactions between recorded units, including self-interactions. This assumption is however rarely met in neurophysiological studies, where the response of each neuron is modulated by other exogenous causes such as, for example, other unobserved units or slow adaptation processes.Here, we propose a novel point-process Granger causality technique that is robust with respect to the two most common exogenous modulations observed in real neuronal responses: within-trial temporal variations in spiking rate and between-trial variability in their magnitudes. This novel method works by explicitly including both types of modulations into the generalized linear model of the neuronal conditional intensity function (CIF). We then assess the causal influence of neuron i onto neuron j by measuring the relative reduction of neuron j’s point process likelihood obtained considering or removing neuron i. CIF’s hyper-parameters are set on a per-neuron basis by minimizing Akaike’s information criterion.In simulated data, the proposed method recovered with high accuracy the underlying ground-truth connectivity pattern. Application of presently available point-process Granger causality techniques produced instead a significant number of false positive connections. In real spiking responses recorded from neurons in the monkey pre-motor cortex (area F5), our method revealed many causal relationships between neurons as well as the temporal structure of their interactions. Given its robustness our method can be effectively applied to real neuronal data. Furthermore, its explicit estimate of the effects of unobserved causes on the recorded neuronal firing patterns can help decomposing their temporal variations into endogenous and exogenous components.Author summaryModern techniques in Neuroscience allow to investigate the brain at the network level by studying the flow of information between neurons. To this end, Granger causality has been extended to point process spike trains. A fundamental assumption of this technique is that there should be no unobserved causes of temporal variability in the recorded spike trains. This, however, greatly limits its applicability to real neuronal recordings as very often not all the sources of variability in neuronal responses can be concurrently recorded.We present here a robust point-process Granger causality technique that overcome this problem by explicitly incorporating unobserved sources of variability into the model of neuronal spiking responses. In synthetic data sets, our new technique correctly recovered the underlying ground-truth functional connectivity between simulated units with a great degree of accuracy. Furthermore, its application to real neuronal recordings revealed many causal relationships between neurons as well as the temporal structure of their interactions.Our results suggest that our novel Granger causality method is robust and it can be used to study the flow of information in the spiking patterns of simultaneously recorded neurons even in presence of unobserved causes of temporal variability.

Synchronization of neuronal responses in the optic tectum of awake pigeons

1996 ◽  
Vol 13 (3) ◽  
pp. 575-584 ◽  
Author(s):  
Sergio Neuenschwander ◽  
Andreas K. Engel ◽  
Peter König ◽  
Wolf Singer ◽  
Francisco J. Varela
Keyword(s):  
Optic Tectum ◽  
Visual Processing ◽  
Cross Correlation ◽  
Spike Trains ◽  
Neuronal Firing ◽  
Neuronal Responses ◽  
Temporal Relationships ◽  
Cross Correlation Analysis ◽  
Deep Layers ◽  
Zero Phase

AbstractMultiunit activity was recorded in the optic tectum of awake pigeons with two electrodes at sites varying in depth and separated by 0.3 to 3.0 mm. Autocorrelation and cross-correlation functions were computed from the recorded spike trains to determine temporal relationships in the neuronal firing patterns. Cross-correlation analysis revealed that spatially separate groups of cells in the tectum show synchronous responses to a visual stimulus. Strong synchronization occurred in both superficial and deep layers of the tectum, in general with zero-phase shift. The response synchronization in the avian optic tectum resembles that observed in the mammalian cortex, suggesting that it may subserve common functions in visual processing.

Interval Coding. II. Dendrite-Dependent Mechanisms

2007 ◽  
Vol 97 (4) ◽  
pp. 2744-2757 ◽  
Author(s):  
Brent Doiron ◽  
Anne-Marie M. Oswald ◽  
Leonard Maler
Keyword(s):  
Neural Coding ◽  
Pyramidal Neurons ◽  
Temporal Structure ◽  
Spike Trains ◽  
Sensory Cells ◽  
Cellular Mechanics ◽  
Dynamic Stimuli ◽  
Multiple Dimensions ◽  
Sensory Modalities ◽  
The Rich

The rich temporal structure of neural spike trains provides multiple dimensions to code dynamic stimuli. Popular examples are spike trains from sensory cells where bursts and isolated spikes can serve distinct coding roles. In contrast to analyses of neural coding, the cellular mechanics of burst mechanisms are typically elucidated from the neural response to static input. Bridging the mechanics of bursting with coding of dynamic stimuli is an important step in establishing theories of neural coding. Electrosensory lateral line lobe (ELL) pyramidal neurons respond to static inputs with a complex dendrite-dependent burst mechanism. Here we show that in response to dynamic broadband stimuli, these bursts lack some of the electrophysiological characteristics observed in response to static inputs. A simple leaky integrate-and-fire (LIF)-style model with a dendrite-dependent depolarizing afterpotential (DAP) is sufficient to match both the output statistics and coding performance of experimental spike trains. We use this model to investigate a simplification of interval coding where the burst interspike interval (ISI) codes for the scale of a canonical upstroke rather than a multidimensional stimulus feature. Using this stimulus reduction, we compute a quantization of the burst ISIs and the upstroke scale to show that the mutual information rate of the interval code is maximized at a moderate DAP amplitude. The combination of a reduced description of ELL pyramidal cell bursting and a simplification of the interval code increases the generality of ELL burst codes to other sensory modalities.

scholarly journals The development of auditory temporal processing during the first year of life

2021 ◽  
Author(s):  
Laurianne Cabrera ◽  
Bonnie K. Lau
Keyword(s):  
Temporal Processing ◽  
Temporal Structure ◽  
Temporal Information ◽  
First Year ◽  
Auditory Temporal Processing ◽  
Speech Stimuli ◽  
Temporal Cues ◽  
Neurophysiological Studies ◽  
Psychophysical Studies ◽  
First Year Of Life

The processing of auditory temporal information is important for the extraction of voice pitch, linguistic information, as well as the overall temporal structure of speech. However, many aspects regarding its early development remains not well understood. This paper reviews the development of different aspects of auditory temporal processing during the first year of life when infants are acquiring their native language. First, potential mechanisms of neural immaturity are discussed in the context of neurophysiological studies. Next, what is known about infant auditory capabilities is considered with a focus on psychophysical studies involving non-speech stimuli to investigate the perception of temporal fine structure and envelope cues. This is followed by a review of studies involving speech stimuli, including those that present vocoded signals as a method of degrading the spectro-temporal information available to infant listeners. Finally, we highlight key findings from the cochlear implant literature that illustrate the importance of temporal cues in speech perception.

Internal Pallidal Neuronal Activity During Mild Drug-Related Dyskinesias in Parkinson's Disease: Decreased Firing Rates and Altered Firing Patterns

2007 ◽  
Vol 97 (4) ◽  
pp. 2627-2641 ◽  
Author(s):  
J. I. Lee ◽  
L. Verhagen Metman ◽  
S. Ohara ◽  
P. M. Dougherty ◽  
J. H. Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Firing Rate ◽  
Spike Trains ◽  
Neuronal Firing ◽  
Low Doses ◽  
Significant Group ◽  
Firing Patterns ◽  
Firing Rates ◽  
Before And After

The neuronal basis of hyperkinetic movement disorders has long been unclear. We now test the hypothesis that changes in the firing pattern of neurons in the globus pallidus internus (GPi) are related to dyskinesias induced by low doses of apomorphine in patients with advanced Parkinson's disease (PD). During pallidotomy for advanced PD, the activity of single neurons was studied both before and after administration of apomorphine at doses just adequate to induce dyskinesias (21 neurons, 17 patients). After the apomorphine injection, these spike trains demonstrated an initial fall in firing from baseline. In nine neurons, the onset of on was simultaneous with that of dyskinesias. In these spike trains, the initial fall in firing rate preceded and was larger than the fall at the onset of on with dyskinesias. Among the three neurons in which the onset of on occurred before that of dyskinesias, the firing rate did not change at the time of onset of dyskinesias. After injection of apomorphine, dyskinesias during on with dyskinesias often fluctuated between transient periods with dyskinesias and those without. Average firing rates were not different between these two types of transient periods. Transient periods with dyskinesias were characterized by interspike interval (ISI) independence, stationary spike trains, and higher variability of ISIs. A small but significant group of neurons demonstrated recurring ISI patterns during transient periods of on with dyskinesias. These results suggest that mild dyskinesias resulting from low doses of apomorphine are related to both low GPi neuronal firing rates and altered firing patterns.

Spatio-temporal variations of caddisfly assemblages in a chalk stream, Balaton Upland, Hungary

Zoosymposia ◽  
2011 ◽  
Vol 5 (1) ◽  
pp. 439-452
Author(s):  
ILDIKÓ SZIVÁK ◽  
ARNOLD MÓRA ◽  
JÚLIA KATALIN TÖRÖK
Keyword(s):  
Indicator Species ◽  
Cold Water ◽  
Human Impacts ◽  
Temporal Structure ◽  
Temporal Distribution ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Aquatic Habitats ◽  
Indicator Value ◽  
Spatio Temporal

In 2006–2007 larval caddisfly assemblages of a semi-natural calcareous stream (Örvényesi Creek) were studied. Characteristic sections can be detected along the whole length of the stream, which passes through diverse types of vegetation, resulting in highly heterogeneous aquatic habitats. Based on an annual survey of different aquatic habitats, our aims were to give an overview of the spatio-temporal distribution of the larval caddisfly assemblages in the Örvényesi Creek and to find indicator species characterizing different sections of the stream. In order to show the spatio-temporal patterns, samples were collected at 7 locations with different streambed morphology, from spring to the mouth of the stream. Caddisfly larvae were collected in every 3rd week during a 1 year period using the “kick and sweep” method. Multivariate analyses were carried out to explore the spatio-temporal structure of caddisfly assemblages. The indicator value method was applied to detect indicator species for different sections of the stream. A rich caddisfly fauna (20 taxa) was found in the Örvényesi Creek. Fast-running and relatively cold-water hypocrenal sections were characterized by Beraea maurus and Apatania muliebris at high indicator value. Three Limnephilidae species (Limnephilus rhombicus, Limnephilus lunatus and Glyphotaelius pellucidus) were identified as significant indicator species for slow flowing, lentic habitats. Along the length of the stream, distinctive spatial and temporal changes were detected in the distribution of the caddisfly assemblages. These changes were mainly connected to variations in morphology of the streambed, phenology of individual taxa, extreme weather conditions and human impacts.

scholarly journals Predicting spike timing in highly synchronous auditory neurons at different sound levels

2013 ◽  
Vol 110 (7) ◽  
pp. 1672-1688 ◽  
Author(s):  
Bertrand Fontaine ◽  
Victor Benichoux ◽  
Philip X. Joris ◽  
Romain Brette
Keyword(s):  
Temporal Structure ◽  
Spike Trains ◽  
Sound Level ◽  
Spike Timing ◽  
Spike Threshold ◽  
Integrate And Fire ◽  
Fire Models ◽  
Wide Range

A challenge for sensory systems is to encode natural signals that vary in amplitude by orders of magnitude. The spike trains of neurons in the auditory system must represent the fine temporal structure of sounds despite a tremendous variation in sound level in natural environments. It has been shown in vitro that the transformation from dynamic signals into precise spike trains can be accurately captured by simple integrate-and-fire models. In this work, we show that the in vivo responses of cochlear nucleus bushy cells to sounds across a wide range of levels can be precisely predicted by deterministic integrate-and-fire models with adaptive spike threshold. Our model can predict both the spike timings and the firing rate in response to novel sounds, across a large input level range. A noisy version of the model accounts for the statistical structure of spike trains, including the reliability and temporal precision of responses. Spike threshold adaptation was critical to ensure that predictions remain accurate at different levels. These results confirm that simple integrate-and-fire models provide an accurate phenomenological account of spike train statistics and emphasize the functional relevance of spike threshold adaptation.

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