Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales

Crombie, Davide; Spacek, Martin A.; Leibold, Christian; Busse, Laura

doi:10.1101/2021.04.30.442134

Cited by 6 publications

(10 citation statements)

References 163 publications

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“…Such fluctuations are a ubiquitous and well-documented phenomenon that has previously been shown to strongly impact neuronal population activity [44,49,50]. We therefore used attentional state (estimated by pupil size) as a representative example of known behavioural modulators of neuronal responses.…”

Section: Resultsmentioning

confidence: 99%

“…To this end, we computed crosstrial averages for sub-groups of trials in which the animal exhibited similar pupil sizes. If population responses are modulated by attentional state [44,49,50], examining only trials that occurred during similar attentional states should reduce unexplained variability. However, grouping trials by average pupil size did not improve specificity or behavioural relevance in Data set 2 (Fig 6C; Data set 1 did not contain measurements of pupil size).…”

Section: Resultsmentioning

confidence: 99%

“…We investigated this idea in two different ways. First, we grouped trials by pupil size, which is known to reflect spontaneous fluctuations in attentional state that strongly shape neuronal population activity [44,49,50]. Second, to account for modulating variables in a more agnostic way, we searched for distinct trial clusters that featured similar neuronal population responses.…”

Section: Discussionmentioning

confidence: 99%

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What does the mean mean? A simple test for neuroscience

Tlaie

Shapcott

Tiesinga³

et al. 2021

Preprint

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Trial-averaged metrics, e.g. in the form of tuning curves and population response vectors, are a basic and widely accepted way of characterizing neuronal activity. But how relevant are such trial-averaged responses to neuronal computation itself? Here we present a simple test to estimate whether average responses reflect aspects of neuronal activity that contribute to neuronal processing in a specific context. The test probes two assumptions inherent in the usage of average neuronal metrics: 1. Reliability: Neuronal responses repeat consistently enough across single trial that their average response template remains recognizable to downstream regions. 2. Behavioural relevance: If a single-trial response is more similar to the average template, it will be easier for the animal to identify the correct stimulus or action. We apply this test to a large publicly available data set featuring electrophysiological recordings from 71 brain areas in behaving mice. We show that single-trial responses were less correlated to the average response template than one would expect if they represented discrete versions of the template, down-sampled to the number of spikes in the single trial. Moreover, single-trial responses were barely stimulus-specific — they could not be clearly assigned to the average response template of one stimulus. Most importantly, better-matched single-trial responses did not more accurately predict behaviour for any of the recorded brain areas. We conclude that in this data set, average responses do not seem particularly relevant to neuronal computation in a majority of brain areas, and we encourage other researchers to apply similar tests when using trial-averaged neuronal metrics.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

What does the mean mean? A simple test for neuroscience

Tlaie

Shapcott

Tiesinga³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In the present study we also investigated the relation between eye pupil changes and confidence. In particular, we analyzed pupil velocity since recent studies suggest that temporal derivative of pupil dilation reflects closely arousal fluctuations (Crombie et al, 2021;Okun et al, 2019;Reimer et al, 2014Reimer et al, , 2016.…”

Section: Discussionmentioning

confidence: 99%

“…Pupil segments were then down-sampled by averaging the pupil size of consecutive 100 ms time windows. From the clean segments, we computed pupil velocity (v = Δs/Δt; where s is pupil size and t is time) since recent studies suggest that temporal derivative of pupil size reflect more closely the dynamics of arousal fluctuation (Crombie et al, 2021;Okun et al, 2019;Reimer et al, 2014Reimer et al, , 2016.…”

Section: Pupil Analysesmentioning

confidence: 99%

What confidence and the eyes can tell about interacting with a partner

Sanchez

Tomei

Mamassian

et al. 2023

Preprint

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Every decision we make is accompanied by a sense of confidence. Confidence mechanisms allow evaluating the evidence that supports our decisions such as the quality of our perceptual representations. Confidence is thought to play a critical role in guiding decision-making, but only a few empirical studies have actually investigated the function of confidence. To address this, we designed a perceptual task in which participants provided a confidence judgment on the accuracy of their perceptual decision. Then, they viewed the response of a machine or human partner, and they were instructed to decide whether to keep or change their initial response. We observed that confidence predicted participants' decision to keep or change their initial responses more than task difficulty and perceptual accuracy. This suggests that confidence, as a subjective evaluation of uncertainty, enables us to weigh our decisions in order to adapt our decision-making behavior driving the interaction with a partner. Furthermore, confidence judgments could be predicted by eye pupil dynamics, suggesting that arousal changes are linked to confidence computations. This study contributes to our understanding of the function of confidence in decision-making and highlights the possibility of using pupil dynamics as a proxy of confidence.

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Behavioral state tunes mouse vision to ethological features through pupil dilation

Franke

Willeke

Ponder

et al. 2021

Preprint

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Across animal species, sensory processing dynamically adapts to behavioral context. In the mammalian visual system, sensory neural responses and behavioral performance increase during an active behavioral state characterized by locomotion activity and pupil dilation, whereas preferred stimuli of individual neurons typically remain unchanged. Here, we address how behavioral states modulate stimulus selectivity in the context of colored natural scenes using a combination of large-scale population imaging, behavior, pharmacology, and deep neural network modeling. In visual cortex of awake mice, we identified a consistent shift of individual neuron color preferences towards ultraviolet stimuli during active behavioral periods that was particularly pronounced in the upper visual field. We found that the spectral shift in neural tuning is mediated by pupil dilation, resulting in a dynamic switch from rod- to cone-driven visual responses for constant ambient light levels. We further showed that this shift selectively enhances the discriminability of ultraviolet objects and facilitates the detection of ethological stimuli, such as aerial predators against the ultraviolet background of the twilight sky. Our results suggest a novel functional role for pupil dilation during active behavioral states as a bottom-up mechanism that, together with top-down neuromodulatory mechanisms, dynamically tunes visual representations to different behavioral demands.

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Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales

Cited by 6 publications

References 163 publications

What does the mean mean? A simple test for neuroscience

What does the mean mean? A simple test for neuroscience

What confidence and the eyes can tell about interacting with a partner

Behavioral state tunes mouse vision to ethological features through pupil dilation

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