scholarly journals Response Latency Tuning by Retinal Circuits Modulates Signal Efficiency

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ádám Jonatán Tengölics ◽  
Gergely Szarka ◽  
Alma Ganczer ◽  
Edina Szabó-Meleg ◽  
Miklós Nyitrai ◽  
...  
Keyword(s):  
Visual Perception ◽  
Response Latency ◽  
Ganglion Cells ◽  
Spike Timing ◽  
Response Latencies ◽  
Retinal Circuitry ◽  
Subtype Specificity ◽  
Retinal Pathways ◽  
Wide Variability ◽  
Parallel Feature

Abstract In the visual system, retinal ganglion cells (RGCs) of various subtypes encode preprocessed photoreceptor signals into a spike output which is then transmitted towards the brain through parallel feature pathways. Spike timing determines how each feature signal contributes to the output of downstream neurons in visual brain centers, thereby influencing efficiency in visual perception. In this study, we demonstrate a marked population-wide variability in RGC response latency that is independent of trial-to-trial variability and recording approach. RGC response latencies to simple visual stimuli vary considerably in a heterogenous cell population but remain reliable when RGCs of a single subtype are compared. This subtype specificity, however, vanishes when the retinal circuitry is bypassed via direct RGC electrical stimulation. This suggests that latency is primarily determined by the signaling speed through retinal pathways that provide subtype specific inputs to RGCs. In addition, response latency is significantly altered when GABA inhibition or gap junction signaling is disturbed, which further supports the key role of retinal microcircuits in latency tuning. Finally, modulation of stimulus parameters affects individual RGC response delays considerably. Based on these findings, we hypothesize that retinal microcircuits fine-tune RGC response latency, which in turn determines the context-dependent weighing of each signal and its contribution to visual perception.

scholarly journals Suppression without inhibition: A novel mechanism in the retina accounts for saccadic suppression

2020 ◽  
Author(s):  
Saad Idrees ◽  
Matthias-Philipp Baumann ◽  
Maria M. Korympidou ◽  
Timm Schubert ◽  
Alexandra Kling ◽  
...  
Keyword(s):  
Eye Movements ◽  
Visual Perception ◽  
Receptive Field ◽  
Calcium Imaging ◽  
Ganglion Cells ◽  
Saccadic Eye Movements ◽  
Visual Sensitivity ◽  
Saccadic Suppression ◽  
Retinal Processing ◽  
Retinal Pathways

AbstractVisual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such suppression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find a novel retinal processing motif underlying retinal saccadic suppression, “dynamic reversal suppression”, which is triggered by sequential stimuli containing contrast reversals. This motif does not involve inhibition but relies on nonlinear transformation of the inherently slow responses of cone photoreceptors by downstream retinal pathways. Two further components of suppression are present in ON ganglion cells and originate in the cells’ receptive field surround, highlighting a novel disparity between ON and OFF ganglion cells. Our results are relevant for any sequential stimulation encountered frequently in naturalistic scenarios.

Bipolar cell pathways for color vision in non-primate dichromats

2010 ◽  
Vol 28 (1) ◽  
pp. 51-60 ◽  
Author(s):  
CHRISTIAN PULLER ◽  
SILKE HAVERKAMP
Keyword(s):  
Color Vision ◽  
Bipolar Cell ◽  
Ganglion Cells ◽  
Color Discrimination ◽  
Model Systems ◽  
Retinal Ganglion ◽  
Retinal Pathways ◽  
Retinal Information Processing ◽  
Cone Opsins ◽  
Retinal Information

AbstractColor vision in mammals is based on the expression of at least two cone opsins that are sensitive to different wavelengths of light. Furthermore, retinal pathways conveying color-opponent signals are required for color discrimination. Most of the primates are trichromats, and “color-coded channels” of their retinas are unveiled to a large extent. In contrast, knowledge of cone-selective pathways in nonprimate dichromats is only slowly emerging, although retinas of dichromats like mice or rats are extensively studied as model systems for retinal information processing. Here, we review recent progress of research on color-coded pathways in nonprimate dichromats to identify differences or similarities between di- and trichromatic mammals. In addition, we applied immunohistochemical methods and confocal microscopy to retinas of different species and present data on their neuronal properties, which are expected to contribute to color vision. Basic neuronal features such as the “blue cone bipolar cell” exist in every species investigated so far. Moreover, there is increasing evidence for chromatic OFF channels in dichromats and retinal ganglion cells that relay color-opponent signals to the brain. In conclusion, di- and trichromats share similar retinal pathways for color transmission and processing.

Response Latency with Constant and Variable Interval Schedules

1965 ◽  
Vol 20 (3) ◽  
pp. 969-972 ◽  
Author(s):  
William Bevan ◽  
Donald L. Hardesty ◽  
Lloyd L. Avant
Keyword(s):  
Response Latency ◽  
Average Duration ◽  
Variable Interval ◽  
Visual Signals ◽  
Interval Duration ◽  
Response Latencies ◽  
Interval Group ◽  
The Difference ◽  
The Relationship ◽  
Constant Interval

12 independent groups were used to examine the relationship between response latency and regularity of signal occurrence. In each of 6 groups 20 simple visual signals were presented sequentially at one of 6 constant intervals. Interval durations were 10, 20, 40, 80, 160, or 320 sec. For each constant-interval group tested, there was also a variable-interval group with intervals of the same average duration. For all intervals except one (40 sec.), the variable-interval groups had longer response latencies than the constant-interval groups, the difference in response latency between the constant- and variable-interval groups increasing as a function of the duration of the interval, up to intervals of 160 sec. For both constant- and variable-interval groups, response latency varied directly with interval duration.

scholarly journals Low error discrimination using a correlated population code

2012 ◽  
Vol 108 (4) ◽  
pp. 1069-1088 ◽  
Author(s):  
Greg Schwartz ◽  
Jakob Macke ◽  
Dario Amodei ◽  
Hanlin Tang ◽  
Michael J. Berry
Keyword(s):  
Spatial Information ◽  
Ganglion Cells ◽  
Discrimination Performance ◽  
Spike Timing ◽  
Multiple Time ◽  
Entropy Model ◽  
Decoding Algorithms ◽  
Single Spike ◽  
Order Of Magnitude ◽  
Spike Latency

We explored the manner in which spatial information is encoded by retinal ganglion cell populations. We flashed a set of 36 shape stimuli onto the tiger salamander retina and used different decoding algorithms to read out information from a population of 162 ganglion cells. We compared the discrimination performance of linear decoders, which ignore correlation induced by common stimulation, with nonlinear decoders, which can accurately model these correlations. Similar to previous studies, decoders that ignored correlation suffered only a modest drop in discrimination performance for groups of up to ∼30 cells. However, for more realistic groups of 100+ cells, we found order-of-magnitude differences in the error rate. We also compared decoders that used only the presence of a single spike from each cell with more complex decoders that included information from multiple spike counts and multiple time bins. More complex decoders substantially outperformed simpler decoders, showing the importance of spike timing information. Particularly effective was the first spike latency representation, which allowed zero discrimination errors for the majority of shape stimuli. Furthermore, the performance of nonlinear decoders showed even greater enhancement compared with linear decoders for these complex representations. Finally, decoders that approximated the correlation structure in the population by matching all pairwise correlations with a maximum entropy model fit to all 162 neurons were quite successful, especially for the spike latency representation. Together, these results suggest a picture in which linear decoders allow a coarse categorization of shape stimuli, whereas nonlinear decoders, which take advantage of both correlation and spike timing, are needed to achieve high-fidelity discrimination.

Foot Placement and Response Latency: A Test of Fitts' Law

1980 ◽  
Vol 24 (1) ◽  
pp. 626-628 ◽  
Author(s):  
Howard J Glaser ◽  
Charles G. Halcomb
Keyword(s):  
Response Latency ◽  
Movement Time ◽  
Three Dimensional ◽  
Vertical Plane ◽  
Brake Pedal ◽  
Lateral Separation ◽  
Response Latencies ◽  
Foot Placement ◽  
Fitts Law ◽  
Experimental Response

Response latencies were compared for three-dimensional brake/accelerator placements (depth, height, and lateral separation). Brake pedal width was found to be the only factor significantly affecting movement time. A comparison between Fitts' and Welford's movement time predictions and experimental response latencies resulted in correlations of .549 (p<.0001) and .543 (p<.0001). Neither movement time equations were able to predict response latencies when the brake pedal was placed 2.54 cm behind the vertical plane of the accelerator. Fitts' and Welford's equations are seen to have limited use in predicting three-dimensional foot movements.

scholarly journals Correlations Without Synchrony

1999 ◽  
Vol 11 (7) ◽  
pp. 1537-1551 ◽  
Author(s):  
Carlos D. Brody
Keyword(s):  
Spike Train ◽  
Response Latency ◽  
Quantitative Methods ◽  
Neuronal Excitability ◽  
Spike Trains ◽  
Spike Timing ◽  
Previous Article ◽  
Timing Synchronization

Peaks in spike train correlograms are usually taken as indicative of spike timing synchronization between neurons. Strictly speaking, however, a peak merely indicates that the two spike trains were not independent. Two biologically plausible ways of departing from independence that are capable of generating peaks very similar to spike timing peaks are described here: covariations over trials in response latency and covariations over trials in neuronal excitability. Since peaks due to these interactions can be similar to spike timing peaks, interpreting a correlogram may be a problem with ambiguous solutions. What peak shapes do latency or excitability interactions generate? When are they similar to spike timing peaks? When can they be ruled out from having caused an observed correlogram peak? These are the questions addressed here. The previous article in this issue proposes quantitative methods to tell cases apart when latency or excitability covariations cannot be ruled out.

scholarly journals Uniform Range of Conduction Times From the Lateral Amygdala to Distributed Perirhinal Sites

2002 ◽  
Vol 87 (3) ◽  
pp. 1213-1221 ◽  
Author(s):  
J. Guillaume Pelletier ◽  
Denis Paré
Keyword(s):  
Response Latency ◽  
Declarative Memory ◽  
Time Windows ◽  
Activity Patterns ◽  
Critical Role ◽  
Memory Storage ◽  
Response Latencies ◽  
Lateral Amygdala ◽  
Electrical Stimuli ◽  
Antidromic Response

Much data indicate that the perirhinal (PRH) cortex plays a critical role in declarative memory and that the amygdala facilitates this process under emotionally arousing conditions. However, assuming that the amygdala does so by promoting Hebbian interactions in the PRH cortex is hard to reconcile with the fact that variable distances separate amygdala neurons from their PRH projection sites. Indeed, to achieve a synchronized activation of distributed PRH sites, amygdala axons should display a uniform range of conduction times, irrespective of distance to target. To determine if amygdala axons meet this condition, we measured the antidromic response latencies of lateral amygdala (LA) neurons to electrical stimuli delivered at various rostrocaudal levels of the PRH cortex in cats anesthetized with isoflurane. Although large variations in antidromic response latencies were observed, they were unrelated to the distance between the PRH stimulation sites and LA neurons. To determine whether this result was an artifact due to current spread, two control experiments were performed. First, we examined the antidromic response latency of intrinsic PRH neurons. Although we used the same methods as in the first experiment, the antidromic response latency of PRH neurons to electrical stimuli applied in the PRH cortex increased linearly with the distance between the stimulating and recording sites. Second, we measured the antidromic response latency of PRH neurons projecting to the LA. In this pathway, we also found a statistically significant correlation between conduction times and distance to target. Thus these results support the intriguing possibility that the conduction velocity and/or trajectory of LA axons are adjusted to compensate for variations in distance between the LA and distinct rostrocaudal PRH sites. We hypothesize that because of their uniform range of conduction times to the PRH cortex, LA neurons can generate short time windows of depolarization facilitating Hebbian associations between coincident, but spatially distributed, activity patterns in the PRH cortex. In this context, the temporal scatter of conduction times in the LA to PRH pathway is conceived as a mechanism used to lengthen the period of depolarization to compensate for conduction delays within intrinsic PRH pathways. In part, this mechanism might explain how the amygdala promotes memory storage in emotionally arousing conditions.

scholarly journals Predicting takeover response to silent automated vehicle failures

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242825
Author(s):  
Callum Mole ◽  
Jami Pekkanen ◽  
William Sheppard ◽  
Tyron Louw ◽  
Richard Romano ◽  
...  
Keyword(s):  
Cognitive Load ◽  
Predictive Model ◽  
Response Latency ◽  
Automated Vehicles ◽  
Experimental Examination ◽  
Response Latencies ◽  
Automated Vehicle ◽  
Failure Severity ◽  
Latency Variability ◽  
Human Monitoring

Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures.

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