A new correlation-based measure of spike timing reliability

Schreiber, Susanne; Fellous, Jean-Marc; Whitmer, Diane; Tiesinga, Paul; Sejnowski, Terrence J.

doi:10.1016/s0925-2312(02)00838-x

Cited by 306 publications

(314 citation statements)

References 6 publications

Supporting

Mentioning

313

Contrasting

Order By: Relevance

“…In one method, spike trains are transformed into a continuous waveform for each trial; each spike is convolved with a Gaussian distribution that has a standard deviation sigma 135,136 . The stronger the spike alignment between two trials, the larger the overlap between the two waveforms will be (calculated as the cosine of the angle between the two waveforms when the waveforms are considered as vectors).…”

Section: Indirect Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Regulation of spike timing in visual cortical circuits

2008

View full text Add to dashboard Cite

A train of action potentials (a spike train) can carry information in both the average firing rate and the pattern of spikes in the train. But can such a spike-pattern code be supported by cortical circuits? Neurons in vitro produce a spike pattern in response to the injection of a fluctuating current. However, cortical neurons in vivo are modulated by local oscillatory neuronal activity and by top-down inputs. In a cortical circuit, precise spike patterns thus reflect the interaction between internally generated activity and sensory information encoded by input spike trains. We review the evidence for precise and reliable spike timing in the cortex and discuss its computational role.Reliability and precision are two different quantities. When you make an appointment with your friend, she can either keep the appointment or not show up at all. If she does show up, she might or might not be on time. The former uncertainty is related to reliability, whereas the latter is related to precision. When the same stimulus waveform is repeatedly injected at the soma of a neuron in vitro (FIG. 1a), a similar spike train is obtained on each trial 1,2 (FIG. 1b). When approximately the same number of spikes occur on each trial the neuron is said to be reliable, whereas when the spikes occur almost at the same time across trials it is said to be precise (FIG. 1c). For a single neuron, the potential information content of precise and reliable spike times is many times larger than that which is contained in the firing rate, which is averaged across a typical interval of a hundred milliseconds [3][4][5][6] . The information contained in spike timing is available immediately, rather than after an averaging period. Furthermore, the timing of patterns of spikes can potentially transmit even more information than the timing of the individual constituent spikes 3,7 . The potential relevance of spike patterns becomes apparent when we consider neurons at the population level: when a group of similar neurons (a 'pool') produces precise and reliable spike trains, the neurons they project to receive volleys of synchronous spikes 8,9 . This opens up the possibility of communicating between different cortical areas through synchronous spike volleys.In contrast to the in vitro situation described above, in the intact cortex most excitatory synaptic inputs arrive at the dendrites rather than at the soma (FIG. 1d), and synaptic transmission is typically unreliable [10][11][12][13] . Furthermore, most of these dendritic inputs are not directly related to ongoing sensory stimulation; rather, they reflect spatiotemporally structured internal activity. Therefore, when the same stimulus is presented repeatedly, the resulting spike trains are usually neither precise nor reliable when they are aligned to the stimulus onset 6 . Instead, HHMI Author ManuscriptHHMI Author Manuscript HHMI Author Manuscript neural activity in vivo might be dominated by internally generated complex reverberations or rhythmic oscillations, and precise and reliable sp...

show abstract

Section: Indirect Methodsmentioning

confidence: 99%

“…For the purpose of the reliability calculation (described in a previous publication; see REF. 135 ), each spike is replaced by a waveform of width sigma. The parameter sigma represents the temporal resolution of the spike times.…”

Section: Feedforward Informationmentioning

confidence: 99%

Regulation of spike timing in visual cortical circuits

2008

View full text Add to dashboard Cite

show abstract

“…We here describe two spike train distances, D V proposed by Victor and Purpura (1996), D R by van Rossum (2001), and a dissimilarity measure D S based on the correlation-based spike train similarity measure proposed by Schreiber et al (2003). We furthermore describe the calculation of a spike train distance D B based on binning (Schnupp et al, 2006).…”

Section: Spike Train Distancesmentioning

confidence: 99%

“…A wide variety of methods have been applied to quantify the similarity between spike trains (e. g. Mainen and Sejnowski, 1995;Victor and Purpura, 1996;Hunter et al, 1998;van Rossum, 2001;Schreiber et al, 2003;Kreuz et al, 2007). A particular class of measures designed to study the neural code are time scale parametric spike train distances, mainly represented by the distances proposed by Victor and Purpura (1996) and van Rossum (2001).…”

Section: Introductionmentioning

confidence: 99%

“…The van Rossum distance has recently been used in a series of studies on the time scale of discrimination of natural sounds in songbirds (e. g. Narayan et al, 2006;Wang et al, 2007). The correlation-based reliability measure of Schreiber et al (2003) has also been used to analyze auditory responses (Wang et al, 2007). A common conclusion of many of these studies is that the optimal time scale found indicates that the temporal structure of the responses and not only the total spike counts are relevant for the neural encoding of the stimuli.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

What can spike train distances tell us about the neural code?

Chicharro

Kreuz

Andrzejak

2011

Journal of Neuroscience Methods

View full text Add to dashboard Cite

Time scale parametric spike train distances like the Victor and the van Rossum distances are often applied to study the neural code based on neural stimuli discrimination. Different neural coding hypotheses, such as rate or coincidence coding, can be assessed by combining a time scale parametric spike train distance with a classifier in order to obtain the optimal discrimination performance. The time scale for which the responses to different stimuli are distinguished best is assumed to be the discriminative precision of the neural code. The relevance of temporal coding is evaluated by comparing the optimal discrimination performance with the one achieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance, the discriminative precision, and the relevance of temporal coding. Furthermore, we evaluate the information these quantities provide about the neural code. We show that the discriminative precision is too unspecific to be interpreted in terms of the time scales relevant for encoding. Accordingly, the time scale parametric nature of the distances is mainly an advantage because it allows maximizing the discrimination performance across a whole set of measures with different sensitivities determined by the time scale parameter, but not due to the possibility to examine the temporal properties of the neural code.

show abstract

Adult‐like neural representation of species‐specific songs in the auditory forebrain of zebra finch nestlings

Schroeder

Remage‐Healey

2021

Developmental Neurobiology

View full text Add to dashboard Cite

Encoding of conspecific signals during development can reinforce species barriers as well as set the stage for learning and production of species‐typical vocalizations. In altricial songbirds, the development of the auditory system is not complete at hatching, so it is unknown the degree to which recently hatched young can process auditory signals like birdsong. We measured in vivo extracellular responses to song stimuli in a zebra finch (Taeniopygia guttata) secondary auditory forebrain region, the caudomedial nidopallium (NCM). We recorded from three age groups between 13 days post‐hatch and adult to identify possible shifts in stimulus encoding that occur before the opening of the sensitive period of song motor learning. We did not find differences in putative cell type composition, firing rate, response strength, and selectivity across ages. Across ages narrow‐spiking units had higher firing rates, response strength, accuracy, and trial‐by‐trial reliability along with lower selectivity than broad‐spiking units. In addition, we showed that stimulus‐specific adaptation, a characteristic of adult NCM, was also present in nestlings and fledglings. These results indicate that most features of secondary auditory processing are already adult‐like shortly after hatching. Furthermore, we showed that selectivity for species‐specific stimuli is similar across all ages, with the greatest fidelity in temporal coding in response to conspecific song and domesticated Bengalese finch song, and reduced fidelity in response to owl finch song, a more ecologically relevant heterospecific, and white noise. Our study provides the first evidence that the electrophysiological properties of higher‐order auditory neurons are already mature in nestling songbirds.

show abstract

A new correlation-based measure of spike timing reliability

Cited by 306 publications

References 6 publications

Regulation of spike timing in visual cortical circuits

Regulation of spike timing in visual cortical circuits

What can spike train distances tell us about the neural code?

Adult‐like neural representation of species‐specific songs in the auditory forebrain of zebra finch nestlings

Contact Info

Product

Resources

About