In every moment, a multitude of information reaches our brain through the different senses. These sensory inputs need to be separated, ordered in space and time to derive a coherent representation of the environment. Yet, the perception of temporal order is seldom veridical. Reports illustrating the subjectivity of cross-modal temporal perception date back to 18^th and 19^th century astronomers; small but stable individual biases in the perceived timing of visual and auditory events caused significant differences in the measurements of stellar transit times which in turn resulted in bitter scientific disputes. These early reports inspired the pioneering work of Wilhelm Wundt and colleagues on cross-modal temporal perception (Sanford, 1888; Canales, 2010) and, hence, are seen as the origin of experimental psychology (Mollon and Perkins, 1996). Early psychologists like William James transferred the personal equation, developed by Bessel to solve the astronomers’ problem of stable cross-modal temporal biases by adding a fixed amount to an observer’s measurements, to cognitive processes. Yet, even though the relative timing of events is crucial for the perception of time and causality (Hume, 2012; Pöppel, 1988; Pöppel, 1997; Spence and Squire, 2003; Aghdaee et al., 2014), it has yet remained unsolved why humans consistently misjudge temporal order across different sensory modalities.

Determining the spatio-temporal order of events across sensory modalities poses an especially difficult challenge as information arriving through different senses travels at different speeds – in the environment and within the nervous system (Hirsh and Sherrick, 1961). Light travels faster than sound, but within the nervous system, auditory information reaches the brain faster than visual information (Fain, 2019). At a distance of approximately 10 m from the observer, the environmental and the physiological differences presumably cancel each other out (Pöppel, 1988). However, both the relative time of arrival at the sensors and neural transmission times vary with the physical properties of the stimulus (King, 2005). Curiously, the brain seems to be able to adjust the perception of temporal order for variations in signal strength (Kopinska and Harris, 2004) and physical distance (Engel and Dougherty, 1971; Alais and Carlile, 2005), yet, within their peripersonal space humans typically perceive visual events as delayed compared to sounds (Keetels and Vroomen, 2012; Zampini et al., 2003; Grabot and van Wassenhove, 2017).

Cross-modal temporal biases exhibit a paradoxical characteristic, they are remarkably stable across longer periods of time (Sanford, 1888; Grabot and van Wassenhove, 2017) while being malleable within short time periods. After humans are exposed to a series of asynchronous stimulus pairs with a constant lag between vision and audition (Fujisaki et al., 2004; Vroomen et al., 2004) (or vision and touch; Keetels and Vroomen, 2008), they perceive the temporal order of subsequent visual-auditory events as shifted in the lag-reversed direction. Such temporal recalibration effects typically last for several minutes. Moreover, on a moment-by-moment basis, the perceived relative timing of events in different modalities changes with the focus of attention. Titchener’s law of prior entry (Titchener, 1908) states that attention towards one sensory input channel is capable of speeding up perceptual processing of that sensory information resulting in a demonstrable shift of temporal order perception towards events in the attended sensory modality (Spence et al., 2001; Zampini et al., 2005; Vibell et al., 2007; Spence, 2010). The co-existence of short-term plasticity and long-term stability re-emphasizes the question that has troubled scientists for 250 years: why do cross-modal temporal biases persist despite the brain’s capability for recalibration?

A potential reason for the high stability of cross-modal temporal biases is that they are shaped during a sensitive period of development. Sensitive periods are limited periods during brain development in which the influence of sensory experience on the brain is particularly strong (Knudsen, 2004). During a sensitive period, the architecture of a neural circuit is shaped to meet an individual’s environment. The long-term result is a preference of the neural circuits for certain states of activity even if the environment dramatically changes (Röder et al., 2007; Röder et al., 2004; Sourav et al., 2019), without prohibiting short-term changes in the neural circuits’ activity patterns (Knudsen, 2004; Knudsen, 2002). The role of early sensory experience for the genesis of perceptual biases is extremely difficult to address in humans; only individuals whose early sensory environments were atypical due to natural causes open a window into the role of experience in perceptual development. We tested the hypothesis of a sensitive period for cross-modal perceptual biases by asking individuals born with dense, bilateral cataracts whose sight was restored 6 to 168 months after birth (Table 1) to temporally order spatially separated events across vision, audition and touch.

Thirteen individuals with a history of congenital bilateral, dense cataracts which had been surgically removed (CC-group) participated in two spatial temporal order judgement tasks, ten in a visual-auditory task (Expt. 1) and ten in a visual-tactile task (Expt. 2). To test for the role of vision during infancy as well as to control for effects related to having had eye surgery and persisting visual impairments, sixteen individuals, nine per experiment, who had undergone surgery for cataracts which had developed during childhood served as controls (DC-group). As both cataract-reversal groups differed in age (Table 1) and age is known to influence cross-modal temporal perception (Röder et al., 2013; Noel et al., 2016), their performance was not directly compared but each group was contrasted separately against age-matched typically sighted individuals (MCC- and MDC-groups). In every trial, two successive stimuli were presented, one in each hemifield (Figure 1A). Stimulus order and the time interval between the two stimuli (stimulus onset asynchrony; SOA) varied randomly across trials. Visual-auditory and visual-tactile stimulus pairs were randomly interleaved with unimodal stimulus pairs. Participants reported the side of the first stimulus irrespective of its modality (Zampini et al., 2003). For the CC-group, we predicted that due to their history of visual loss and persisting visual impairments participants would give auditory and tactile stimuli a higher preference than visual stimuli. Such a preference would result in a shift of the point of perceived simultaneity (PSS) –the SOA at which auditory-visual or tactile-visual pairs are perceived as simultaneous– towards SOAs with greater auditory or tactile lags, and an overall lower proportion of ‘visual first’-responses compared to their controls. Additionally, we predicted a lower visual spatio-temporal resolution resulting in a lower proportion of correct temporal order judgments for the CC-group.

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Most strikingly and contrary to our predictions, CC-individuals showed a bias toward perceiving visual stimuli as occurring earlier than auditory (Figure 1D,E; CC-group, Expt. 1, PSS, t(9) = −1.51, p=0.033, r_equiv = 0.57; ‘visual first’-response probability, χ² (1)=4.31, p=0.038, r_equiv = 0.55; see Supplementary file 1 for full statistical models) and tactile stimuli (CC-group, Expt. 2, PSS, t(9) = −3.04, p=0.009, r_equiv = 0.69; ‘visual first’-response probability, χ²(1)=12.46, p<0.001, r_equiv = 0.85), respectively. CC-individuals’ bias toward perceiving visual stimuli as earlier stood in contrast to the bias observed for their matched controls (CC- vs. MCC-group, Expt. 1, visual-auditory, PSS, t(18) = −2.34, p=0.005, r_equiv = 0.56; ‘visual first’-response probability, χ² (1)=8.48, p=0.004, r_equiv = 0.57; Expt. 2, visual-tactile, PSS, t(18) = −2.47, p=0.008, r_equiv = 0.53; ‘visual first’-response probability, χ² (1)=5.31, p=0.021, r_equiv = 0.45) who perceived auditory stimuli as occurring earlier than visual stimuli (MCC-group, Expt. 1, visual-auditory, PSS, t(9) = 2.30, p=0.009, r_equiv = 0.69; ‘visual first’-response probability, χ² (1)=4.18, p=0.041, r_equiv = 0.55) and did not show a significant bias for visual-tactile comparisons (MCC-group, Expt. 2, visual-tactile, PSS, t(9) = −0.48, p=0.321, r_equiv = 0.16; ‘visual first’-response probability, χ² (1)=0.15, p=0.701, r_equiv = 0.17). In contrast to the CC-group, DC-individuals showed the typical bias toward perceiving visual stimuli as occurring later than auditory and tactile stimuli (DC-group, Expt. 1, visual-auditory, PSS, t(8) = 1.42, p=0.017, r_equiv = 0.67; ‘visual first’-response probability, χ² (1)=7.14, p=0.008, r_equiv = 0.74; Expt. 2, visual-tactile, PSS, t(8) = 2.31, p=0.017, r_equiv = 0.67; ‘visual first’-response probability, χ² (1)=8.86, p=0.003, r_equiv = 0.79). In fact, their spatio-temporal bias toward perceiving visual stimuli as later than tactile stimuli was stronger than the bias of their matched controls (DC- vs. MDC-group, Expt. 1, visual-auditory, PSS, t(18) = 1.40, p=0.123, r_equiv = 0.29; ‘visual first’-response probability, χ² (1)=1.84, p=0.174, r_equiv = 0.23; Expt. 2, visual-tactile, PSS, t(18) = 2.17, p=0.019, r_equiv = 0.49; ‘visual first’-response probability, χ² (1)=8.08, p=0.004, r_equiv = 0.60; MDC-group, Expt. 1, visual-auditory, PSS, t(8) = 1.32, p=0.152, r_equiv = 0.36; ‘visual first’-response probability, χ² (1)=0.83, p=0.362, r_equiv = 0.13; Expt. 2, visual-tactile, PSS, t(8) = −0.36, p=0.361, r_equiv = 0.13; ‘visual first’-response probability, χ²=0.85, p=0.356, r_equiv = 0.15).

CC-individuals’ proportion of correct temporal order judgments for visual and cross-modal stimulus pairs (Figure 1F) was reduced compared to their controls’ temporal resolution (CC-group vs. MCC-group, Expt. 1, visual, χ² (1)=9.68, p=0.002, r_equiv = 0.62; Expt. 1, visual-auditory, χ² (1)=17.88, p<0.001, r_equiv = 0.78; Expt. 2, visual, χ² (1)=4.72, p=0.030, r_equiv = 0.42; Expt. 2, visual-tactile, χ² (1)=4.03, p=0.045, r_equiv = 0.39; see Supplementary file 1 for full statistical models), but no significant difference between the CC-group and their controls emerged for auditory and tactile stimulus pairs, (CC-group vs. MCC-group, Expt. 1, auditory, χ² (1)=1.42, p=0.233, r_equiv = 0.17; Expt. 2, tactile, χ² (1)=0.11, p=0.742, r_equiv = 0.15). DC-individuals’ spatio-temporal resolution was lower than the resolution of their controls independent of modality condition (DC-group vs. MDC-group, Expt. 1, all modalities, χ² (1)=4.98, p=0.026, r_equiv = 0.46; Expt. 2, all modalities, χ² (1)=11.99, p=0.001, r_equiv = 0.68).

Across participants, the size of the bias in the proportion of ‘visual first’-responses in bimodal trials correlated negatively with the proportion of correct temporal order judgements in these trials (Figure 1G; Expt. 1, visual-auditory, r = −0.39, p=0.018; Expt. 2, visual-tactile, r = −0.49, p=0.002). The distribution of reaction times in bimodal trials peaked at different SOAs across groups (Figure 1H; CC- vs. MCC-group, Expt. 1, visual-auditory, t(16) = 2.11, p=0.041, r_equiv = 0.40; Expt. 2, visual-tactile, t(18) = 1.56, p=0.067, r_equiv = 0.35) with peaks being shifted in the same direction as the PSS.

Here, we investigated whether biases in cross-modal temporal perception are shaped during a sensitive period in early development by testing sight-recovery individuals with a history of congenital loss of pattern vision. In two spatio-temporal order judgement tasks, individuals with reversed congenital cataracts disproportionally often reported visual stimuli as occurring earlier than auditory and tactile stimuli (Figure 1B–E), exhibiting a reversed cross-modal bias compared to typically sighted controls and sight-recovery individuals whose cataracts had developed during childhood. These results, for the first time, demonstrate a sensitive period for cross-modal temporal biases. Moreover, the ability to correctly determine the spatio-temporal order of separate events across different sensory modalities and within vision was reduced after a transient phase of visual loss both after birth and later in childhood (Figure 1F) suggesting a persistent impairment of visual and cross-modal temporal resolution following transient visual deprivation.

At first glance, CC-individuals’ bias to perceive visual events as earlier than auditory and tactile events seems to indicate that visual stimuli were processed faster than auditory and tactile stimuli following transient, congenital visual deprivation. However, CC-individuals’ response accuracy (Figure 1F) indicated temporal processing impairments for vision but not for audition and touch. Consistently, studies measuring event-related potentials have provided no evidence for a shorter latency of the first visual cortical response in CC-individuals (Sourav et al., 2018; Mondloch et al., 2013; McCulloch and Skarf, 1994) and behavioral studies have demonstrated no advantage in reaction times to simple visual stimuli (Putzar et al., 2012; de Heering et al., 2016). Moreover, reduced visual contrast – typical for cataract-reversal individuals – is associated with delayed responses of the visual system and lower visual temporal sensitivity (Watson, 1986; Stromeyer and Martini, 2003). In sum, there is currently no evidence indicating accelerated processing of visual information following congenital visual deprivation.

During sensitive periods, experience shapes neural circuits customizing them to an individual’s body and environment (Knudsen, 2004). CC-individuals’ reversed cross-modal bias towards perceiving visual stimuli as occurring earlier than auditory and tactile stimuli might be rooted in consistent exposure to lagging visual input during an early sensitive period. Residual light perception, which exists even in the presence of dense cataracts, is typically sluggish and retinal transduction rates have been reported to be reduced in patients with dense, untreated cataracts (Yamauchi et al., 2016). Moreover, a suppression of visual cortex activity has recently been observed in CC-individuals in the context of cross-modal stimulation (Guerreiro et al., 2016). Thus, CC-individuals likely were exposed to consistently delayed visual signals (with respect to auditory and tactile signals) before the cataracts were removed. Recalibration studies have shown that exposure to a consistent visual delay results in a bias towards perceiving visual input as earlier (Fujisaki et al., 2004; Vroomen et al., 2004), consistent with the present results in the CC-group. Thus, we suggest that the reversed bias exhibited by CC-individuals reflects adaptation to their atypical sensory environment during infancy, which results in structural differences in the neural circuits processing temporal order across modalities.

Individual cross-modal temporal biases in typically sighted humans might reflect the relative timing of sensory information across modalities during infancy, too. One-month old infants have been found to already show rudimentary cross-modal temporal biases for audition and vision (Lewkowicz, 1996). Slight differences in the relative rate of brain development across individuals, for example, in the myelination of neural circuits in different sensory areas, could give rise to the characteristic but stable (Sanford, 1888; Grabot and van Wassenhove, 2017) inter-individual differences in cross-modal temporal biases in humans. In turn, the variation of individual cross-modal temporal biases as a function of task (Freeman et al., 2013; Ipser et al., 2018; Ipser et al., 2017) might arise from differences in the relative rate of development across cortical areas. In sum, we suggest that individual cross-modal temporal biases (Zampini et al., 2003; Grabot and van Wassenhove, 2017) show a high stability because the brain had optimized cross-modal temporal perception (Roseboom et al., 2015) during a sensitive period which constitutes a setpoint for all future recalibration.

Additionally, the congenital absence of pattern vision might have increased CC-individuals’ attention towards this modality after sight restoration, resulting in a permanent prior entry effect for vision (Titchener, 1908; Spence et al., 2001; Vibell et al., 2007; Shore et al., 2001). However, a previous study found longer switch times from audition to vision but not from vision to audition in CC-individuals whose cataracts had been removed in the first months of life than in controls, which was interpreted as indicating an attentional bias towards audition over vision (de Heering et al., 2016). Moreover, an attentional bias towards vision would have been expected to result in relatively shorter visual reaction times and early cortical potentials, which, as argued at the beginning of the Discussion is incompatible with the literature (Sourav et al., 2018; Mondloch et al., 2013; McCulloch and Skarf, 1994; Putzar et al., 2012; de Heering et al., 2016). Thus, while scarce existing data points towards a reduced dominance of vision in CC-individuals, the consequences of congenital loss of pattern vision for modality-specific attention are not yet understood.

The finding, that CC-individuals but not DC-individuals showed a reversed visual-auditory and visual-tactile temporal bias strongly suggests that perceptual biases are shaped by sensory experience during the initial period of life. In contrast to CC-individuals, DC-individuals had encountered unimpaired cross-modal stimulation after birth, which we suggest had enabled them to establish a typical bias. An early sensitive period would have prevented DC-individuals –who lost their vision later– from adapting this typical bias to their changed sensory environment. As a consequence, their partially severe, persisting visual impairments might have caused an increase of the typical bias of perceiving vision as delayed. However, the bias of some DC-individuals seems too large to be accounted for by delays in visual processing alone. The very high temporal uncertainty of some DC-individuals might have resulted in an overestimation of their cross-modal biases (Figure 1G): In agreement with Bayes’ law, temporal perceptual judgments tend to rely more on prior information such as existing biases when the sensory information is uncertain (Shi and Burr, 2016; Vercillo et al., 2015). Consistent with this idea, the current data indicated a correlation between the size of the bias and the degree of sensory uncertainty. The sensitive period for cross-modal temporal perception might culminate during the first six months of life, the minimal duration of deprived vision in our CC-group. A previous study tested CC-individuals whose vision was restored within early infancy (4 months of age on average) in an audio-visual simultaneity judgment task with spatially aligned visual-auditory and visual-tactile stimulus pairs and did not report a reversed cross-modal bias (Chen et al., 2017). However, simultaneity judgments of spatially aligned cross-modal stimuli are simpler and less sensitive to biases than the spatial temporal order judgements we used (van Eijk et al., 2008; Linares and Holcombe, 2014). Moreover, both tasks rely on different neuronal processes (Basharat et al., 2018) and even one-month old infants seem to be able to evaluate simultaneity (Lewkowicz, 1996). Thus, it is questionable whether the previous and our experimental design addressed the same multisensory processes. In sum, our results provide strong evidence for a sensitive period for cross-modal temporal perception, which leads to the consolidation of cross-modal spatio-temporal biases during early human ontogeny.

Typically, reaction times increase with increasing perceptual uncertainty. In temporal order judgements, uncertainty is highest for simultaneously perceived cross-modal stimuli. Thus, reaction times are expected to be longest at the PSS, if the PSS reflects biases in the perceived relative timing of the modalities, but not if the PSS reflects a response bias towards one modality (Spence, 2010; Shore et al., 2001). Here, CC-individuals’ reaction times and thus sensory uncertainty peaked when the visual stimulus slightly lagged behind the auditory or the tactile stimulus (Figure 1H), whereas all other participants responded slowest when the visual stimulus led by a short amount of time. Thus, even though response speed was not stressed in the instructions, reaction times of the present study suggest that the observed biases reflect perceptual shifts in the relative timing of cross-modal sensory information.

Both cataract-reversal groups exhibited lower spatio-temporal accuracy (Figure 1F) –indicative of a decreased temporal resolution and an increased lapse rate (Figure 1B)– than their controls in the visual and the cross-modal tasks. Persisting visual impairments might have contributed to the reduced visual spatio-temporal resolution of both cataract-reversal groups given that visual contrast affects visual temporal perception (Watson, 1986; Stromeyer and Martini, 2003). The observation that a lower temporal resolution was found not only for visual but additionally for cross-modal temporal order judgments suggests a strong dependence of cross-modal temporal ordering on the visual sense. This might be related to the spatial nature of our task; training of non-spatial, purely visual temporal order judgments did not lead to an improved visual-auditory temporal resolution (Alais and Cass, 2010). The finding that both cataract groups exhibited a lower temporal resolution but only the CC-group an altered cross-modal bias strongly suggests that cross-modal spatio-temporal biases and resolution are dissociable processes. The conjunction of CC- and DC-individuals’ reduced resolution might point towards a long sensitive period for the development of spatio-temporal sensory resolution which would be compatible with the protracted developmental time course of cross-modal temporal ordering of spatially separate events (Röder et al., 2013).

Furthermore, the present finding of increased cross-modal temporal uncertainty could explain why recent studies have found altered multisensory integration for some but not all functions following congenital, transient periods of visual deprivation (Chen et al., 2017; Putzar et al., 2007; Guerreiro et al., 2015). An increased spatio-temporal uncertainty hinders the detection of temporal correlations (Parise and Ernst, 2016) between complex signals such as speech stimuli (Putzar et al., 2007; Guerreiro et al., 2015). At the same time, higher temporal uncertainty predicts wider temporal integration windows for simple, spatially-aligned stimuli (Chen et al., 2017), which in turn might have enabled typical multisensory redundancy gains for such cross-modal stimuli (Putzar et al., 2012; de Heering et al., 2016). It is interesting to note, that this pattern mirrors the typical development of multisensory temporal perception. Very young infants integrate simple visual and auditory stimuli across a wide window of asynchronies but do not integrate more complex stimuli based on other features than stimulus onset (Lewkowicz, 1996; Lewkowicz, 2012). The multisensory integration window narrows during childhood (Noel et al., 2016; Lewkowicz and Flom, 2014; Hillock et al., 2011), in parallel to the improvement of unisensory temporal perception (Brannon et al., 2007). Some developmental theories suggest that more complex temporal multisensory functions build on previously acquired temporal multisensory skills (Lewkowicz, 2000) predicting that the impact of transient loss of pattern vision on multisensory perception should as suggested for the visual system (Hyvärinen et al., 1981; Maurer et al., 2005), increase with increasing task difficulty.

In conclusion, congenital but not late transient visual deprivation was associated with a bias towards perceiving visual events as earlier than auditory or tactile events in sight-recovery individuals, suggesting that cross-modal temporal biases depend on sensory experiences during an early sensitive period.

All data have been deposited on Open Science Framework under CQN48.

1. 1. Badde S
   2. Ley P
   3. Rajendran SS
   4. Kekunnaya R
   5. Shareef I
   6. Röder B

   (2019) Open Science Framework

   Cross-modal temporal biases emerge during early sensitive periods.

   https://doi.org/10.17605/OSF.IO/CQN48

1. 1. Aghdaee SM
   2. Battelli L
   3. Assad JA

   (2014) Relative timing: from behaviour to neurons

   Philosophical Transactions of the Royal Society B: Biological Sciences 369:20120472.

   https://doi.org/10.1098/rstb.2012.0472

   • PubMed
   • Google Scholar
2. 1. Alais D
   2. Carlile S

   (2005) Synchronizing to real events: subjective audiovisual alignment scales with perceived auditory depth and speed of sound

   PNAS 102:2244–2247.

   https://doi.org/10.1073/pnas.0407034102

   • PubMed
   • Google Scholar
3. 1. Alais D
   2. Cass J

   (2010) Multisensory perceptual learning of temporal order: audiovisual learning transfers to vision but not audition

   PLOS ONE 5:e11283.

   https://doi.org/10.1371/journal.pone.0011283

   • PubMed
   • Google Scholar
4. 1. Badde S
   2. Ley P
   3. Rajendran SS
   4. Shareef I
   5. Kekunnaya R
   6. Röder B

   (2019) Resources of sensory experience during early sensitive periods shapes cross-modal temporal biases

   Open Science Framework 1:CQN48.

   https://doi.org/10.17605/OSF.IO/CQN48

   • Google Scholar
5. 1. Basharat A
   2. Adams MS
   3. Staines WR
   4. Barnett-Cowan M

   (2018) Simultaneity and temporal order judgments are coded differently and change with age: an event-related potential study

   Frontiers in Integrative Neuroscience 12:15.

   https://doi.org/10.3389/fnint.2018.00015

   • PubMed
   • Google Scholar
6. 1. Brannon EM
   2. Suanda S
   3. Libertus K

   (2007) Temporal discrimination increases in precision over development and parallels the development of numerosity discrimination

   Developmental Science 10:770–777.

   https://doi.org/10.1111/j.1467-7687.2007.00635.x

   • PubMed
   • Google Scholar
7. Book

   1. Canales J

   (2010) A Tenth of a Second: A History

   University of Chicago Press.

   https://doi.org/10.2979/victorianstudies.54.2.314

   • Google Scholar
8. 1. Chen YC
   2. Lewis TL
   3. Shore DI
   4. Maurer D

   (2017) Early binocular input is critical for development of audiovisual but not visuotactile simultaneity perception

   Current Biology 27:583–589.

   https://doi.org/10.1016/j.cub.2017.01.009

   • PubMed
   • Google Scholar
9. 1. de Heering A
   2. Dormal G
   3. Pelland M
   4. Lewis T
   5. Maurer D
   6. Collignon O

   (2016) A brief period of postnatal visual deprivation alters the balance between auditory and visual attention

   Current Biology 26:3101–3105.

   https://doi.org/10.1016/j.cub.2016.10.014

   • PubMed
   • Google Scholar
10. 1. Engel GR
    2. Dougherty WG

    (1971) Visual-auditory distance constancy

    Nature 234:308.

    https://doi.org/10.1038/234308a0

    • PubMed
    • Google Scholar
11. Book

    1. Fain GL

    (2019) Sensory Transduction

    Oxford University Press.

    https://doi.org/10.1007/978-1-4684-6760-4_13

    • Google Scholar
12. 1. Freeman ED
    2. Ipser A
    3. Palmbaha A
    4. Paunoiu D
    5. Brown P
    6. Lambert C
    7. Leff A
    8. Driver J

    (2013) Sight and sound out of synch: fragmentation and renormalisation of audiovisual integration and subjective timing

    Cortex 49:2875–2887.

    https://doi.org/10.1016/j.cortex.2013.03.006

    • PubMed
    • Google Scholar
13. 1. Fujisaki W
    2. Shimojo S
    3. Kashino M
    4. Nishida S

    (2004) Recalibration of audiovisual simultaneity

    Nature Neuroscience 7:773–778.

    https://doi.org/10.1038/nn1268

    • PubMed
    • Google Scholar
14. 1. Grabot L
    2. van Wassenhove V

    (2017) Time order as psychological bias

    Psychological Science 28:670–678.

    https://doi.org/10.1177/0956797616689369

    • PubMed
    • Google Scholar
15. 1. Guerreiro MJ
    2. Putzar L
    3. Röder B

    (2015) The effect of early visual deprivation on the neural bases of multisensory processing

    Brain 138:1499–1504.

    https://doi.org/10.1093/brain/awv076

    • PubMed
    • Google Scholar
16. 1. Guerreiro MJ
    2. Putzar L
    3. Röder B

    (2016) The effect of early visual deprivation on the neural bases of auditory processing

    The Journal of Neuroscience 36:1620–1630.

    https://doi.org/10.1523/JNEUROSCI.2559-15.2016

    • PubMed
    • Google Scholar
17. 1. Hillock AR
    2. Powers AR
    3. Wallace MT

    (2011) Binding of sights and sounds: age-related changes in multisensory temporal processing

    Neuropsychologia 49:461–467.

    https://doi.org/10.1016/j.neuropsychologia.2010.11.041

    • PubMed
    • Google Scholar
18. 1. Hirsh IJ
    2. Sherrick CE

    (1961) Perceived order in different sense modalities

    Journal of Experimental Psychology 62:423–432.

    https://doi.org/10.1037/h0045283

    • PubMed
    • Google Scholar
19. Book

    1. Hume D

    (2012)

    A Treatise of Human Nature

    Courier Corporation.

    • Google Scholar
20. 1. Hyvärinen J
    2. Carlson S
    3. Hyvärinen L

    (1981) Early visual deprivation alters modality of neuronal responses in area 19 of monkey cortex

    Neuroscience Letters 26:239–243.

    https://doi.org/10.1016/0304-3940(81)90139-7

    • PubMed
    • Google Scholar
21. 1. Ipser A
    2. Agolli V
    3. Bajraktari A
    4. Al-Alawi F
    5. Djaafara N
    6. Freeman ED

    (2017) Sight and sound persistently out of synch: stable individual differences in audiovisual synchronisation revealed by implicit measures of lip-voice integration

    Scientific Reports 7:46413.

    https://doi.org/10.1038/srep46413

    • PubMed
    • Google Scholar
22. 1. Ipser A
    2. Karlinski M
    3. Freeman ED

    (2018) Correlation of individual differences in audiovisual asynchrony across stimuli and tasks: new constraints on temporal renormalization theory

    Journal of Experimental Psychology: Human Perception and Performance 44:1283–1293.

    https://doi.org/10.1037/xhp0000535

    • PubMed
    • Google Scholar
23. 1. Keetels M
    2. Vroomen J

    (2008) Temporal recalibration to tactile-visual asynchronous stimuli

    Neuroscience Letters 430:130–134.

    https://doi.org/10.1016/j.neulet.2007.10.044

    • PubMed
    • Google Scholar
24. Book

    1. Keetels M
    2. Vroomen J

    (2012)

    Perception of synchrony between the senses

    In: Murray MM, Wallace MT, editors. The Neural Bases of Multisensory Processes. CRC Press/Taylor & Francis. pp. 147–177.

    • Google Scholar
25. 1. King AJ

    (2005) Multisensory integration: strategies for synchronization

    Current Biology 15:R339–R341.

    https://doi.org/10.1016/j.cub.2005.04.022

    • PubMed
    • Google Scholar
26. 1. Knudsen EI

    (2002) Instructed learning in the auditory localization pathway of the barn owl

    Nature 417:322–328.

    https://doi.org/10.1038/417322a

    • PubMed
    • Google Scholar
27. 1. Knudsen EI

    (2004) Sensitive periods in the development of the brain and behavior

    Journal of Cognitive Neuroscience 16:1412–1425.

    https://doi.org/10.1162/0898929042304796

    • PubMed
    • Google Scholar
28. 1. Kopinska A
    2. Harris LR

    (2004) Simultaneity constancy

    Perception 33:1049–1060.

    https://doi.org/10.1068/p5169

    • PubMed
    • Google Scholar
29. 1. Lewkowicz DJ

    (1996) Perception of auditory-visual temporal synchrony in human infants

    Journal of Experimental Psychology: Human Perception and Performance 22:1094–1106.

    https://doi.org/10.1037/0096-1523.22.5.1094

    • PubMed
    • Google Scholar
30. 1. Lewkowicz DJ

    (2000) The development of intersensory temporal perception: an epigenetic systems/limitations view

    Psychological Bulletin 126:281–308.

    https://doi.org/10.1037/0033-2909.126.2.281

    • PubMed
    • Google Scholar
31. Book

    1. Lewkowicz DJ

    (2012)

    Development of Multisensory Temporal Perception

    In: Murray MM, Wallace MT, editors. The Neural Bases of Multisensory Processes. CRC Press/Taylor & Francis. pp. 325–343.

    • Google Scholar
32. 1. Lewkowicz DJ
    2. Flom R

    (2014) The audiovisual temporal binding window narrows in early childhood

    Child Development 85:685–694.

    https://doi.org/10.1111/cdev.12142

    • PubMed
    • Google Scholar
33. 1. Linares D
    2. Holcombe AO

    (2014) Differences in perceptual latency estimated from judgments of temporal order, simultaneity and duration are inconsistent

    I-Perception 5:559–571.

    https://doi.org/10.1068/i0675

    • PubMed
    • Google Scholar
34. 1. Maurer D
    2. Lewis TL
    3. Mondloch CJ

    (2005) Missing sights: consequences for visual cognitive development

    Trends in Cognitive Sciences 9:144–151.

    https://doi.org/10.1016/j.tics.2005.01.006

    • PubMed
    • Google Scholar
35. 1. McCulloch DL
    2. Skarf B

    (1994) Pattern reversal visual evoked potentials following early treatment of unilateral, congenital cataract

    Archives of Ophthalmology 112:510–518.

    https://doi.org/10.1001/archopht.1994.01090160086026

    • PubMed
    • Google Scholar
36. 1. Mollon JD
    2. Perkins AJ

    (1996) Errors of judgement at Greenwich in 1796

    Nature 380:101–102.

    https://doi.org/10.1038/380101a0

    • PubMed
    • Google Scholar
37. 1. Mondloch CJ
    2. Segalowitz SJ
    3. Lewis TL
    4. Dywan J
    5. Le Grand R
    6. Maurer D

    (2013) The effect of early visual deprivation on the development of face detection

    Developmental Science 16:728–742.

    https://doi.org/10.1111/desc.12065

    • PubMed
    • Google Scholar
38. 1. Noel JP
    2. De Niear M
    3. Van der Burg E
    4. Wallace MT

    (2016) Audiovisual simultaneity judgment and rapid recalibration throughout the lifespan

    PLOS ONE 11:e0161698.

    https://doi.org/10.1371/journal.pone.0161698

    • PubMed
    • Google Scholar
39. 1. Parise CV
    2. Ernst MO

    (2016) Correlation detection as a general mechanism for multisensory integration

    Nature Communications 7:11543.

    https://doi.org/10.1038/ncomms11543

    • PubMed
    • Google Scholar
40. Book

    1. Pöppel E

    (1988)

    Mindworks: Time and Conscious Experience

    Harcourt Brace Jovanovich.

    • Google Scholar
41. 1. Pöppel E

    (1997) A hierarchical model of temporal perception

    Trends in Cognitive Sciences 1:56–61.

    https://doi.org/10.1016/S1364-6613(97)01008-5

    • PubMed
    • Google Scholar
42. 1. Putzar L
    2. Goerendt I
    3. Lange K
    4. Rösler F
    5. Röder B

    (2007) Early visual deprivation impairs multisensory interactions in humans

    Nature Neuroscience 10:1243–1245.

    https://doi.org/10.1038/nn1978

    • PubMed
    • Google Scholar
43. 1. Putzar L
    2. Gondan M
    3. Röder B

    (2012) Basic multisensory functions can be acquired after congenital visual pattern deprivation in humans

    Developmental Neuropsychology 37:697–711.

    https://doi.org/10.1080/87565641.2012.696756

    • PubMed
    • Google Scholar
44. 1. Röder B
    2. Rösler F
    3. Spence C

    (2004) Early vision impairs tactile perception in the blind

    Current Biology 14:121–124.

    https://doi.org/10.1016/j.cub.2003.12.054

    • PubMed
    • Google Scholar
45. 1. Röder B
    2. Kusmierek A
    3. Spence C
    4. Schicke T

    (2007) Developmental vision determines the reference frame for the multisensory control of action

    PNAS 104:4753–4758.

    https://doi.org/10.1073/pnas.0607158104

    • PubMed
    • Google Scholar
46. 1. Röder B
    2. Pagel B
    3. Heed T

    (2013) The implicit use of spatial information develops later for crossmodal than for intramodal temporal processing

    Cognition 126:301–306.

    https://doi.org/10.1016/j.cognition.2012.09.009

    • PubMed
    • Google Scholar
47. 1. Roseboom W
    2. Linares D
    3. Nishida S

    (2015) Sensory adaptation for timing perception

    Proceedings of the Royal Society B: Biological Sciences 282:20142833.

    https://doi.org/10.1098/rspb.2014.2833

    • Google Scholar
48. 1. Rosenthal R
    2. Rubin DB

    (2003) R equivalent: a simple effect size Indicator

    Psychological Methods 8:492–496.

    https://doi.org/10.1037/1082-989X.8.4.492

    • PubMed
    • Google Scholar
49. 1. Sanford EC

    (1888) Personal equation

    The American Journal of Psychology 2:3–38.

    https://doi.org/10.2307/1411405

    • Google Scholar
50. 1. Shi Z
    2. Burr D

    (2016) Predictive coding of multisensory timing

    Current Opinion in Behavioral Sciences 8:200–206.

    https://doi.org/10.1016/j.cobeha.2016.02.014

    • PubMed
    • Google Scholar
51. 1. Shore DI
    2. Spence C
    3. Klein RM

    (2001) Visual prior entry

    Psychological Science 12:205–212.

    https://doi.org/10.1111/1467-9280.00337

    • PubMed
    • Google Scholar
52. 1. Sourav S
    2. Bottari D
    3. Kekunnaya R
    4. Röder B

    (2018) Evidence of a retinotopic organization of early visual cortex but impaired extrastriate processing in sight recovery individuals

    Journal of Vision 18:22.

    https://doi.org/10.1167/18.3.22

    • PubMed
    • Google Scholar
53. 1. Sourav S
    2. Kekunnaya R
    3. Shareef I
    4. Banerjee S
    5. Bottari D
    6. Röder B

    (2019) A protracted sensitive period regulates the development of cross-modal sound-shape associations in humans

    Psychological Science 30:1473–1482.

    https://doi.org/10.1177/0956797619866625

    • PubMed
    • Google Scholar
54. 1. Spence C
    2. Shore DI
    3. Klein RM

    (2001) Multisensory prior entry

    Journal of Experimental Psychology: General 130:799–832.

    https://doi.org/10.1037/0096-3445.130.4.799

    • PubMed
    • Google Scholar
55. Book

    1. Spence C

    (2010)

    Prior entry: attention and temporal perception

    In: Nobre A. C, Coull J. T, editors. Attention and Time. Oxford University Press. pp. 89–104.

    • Google Scholar
56. 1. Spence C
    2. Squire S

    (2003) Multisensory integration: maintaining the perception of synchrony

    Current Biology 13:R519–R521.

    https://doi.org/10.1016/S0960-9822(03)00445-7

    • PubMed
    • Google Scholar
57. 1. Stromeyer CF
    2. Martini P

    (2003) Human temporal impulse response speeds up with increased stimulus contrast

    Vision Research 43:285–298.

    https://doi.org/10.1016/S0042-6989(02)00412-1

    • PubMed
    • Google Scholar
58. Book

    1. Titchener EB

    (1908)

    Lectures on the elementary psychology of feeling and attention

    Macmillan.

    • Google Scholar
59. 1. van Eijk RL
    2. Kohlrausch A
    3. Juola JF
    4. van de Par S

    (2008) Audiovisual synchrony and temporal order judgments: effects of experimental method and stimulus type

    Perception & Psychophysics 70:955–968.

    https://doi.org/10.3758/PP.70.6.955

    • PubMed
    • Google Scholar
60. 1. Vercillo T
    2. Burr D
    3. Sandini G
    4. Gori M

    (2015) Children do not recalibrate motor-sensory temporal order after exposure to delayed sensory feedback

    Developmental Science 18:703–712.

    https://doi.org/10.1111/desc.12247

    • PubMed
    • Google Scholar
61. 1. Vibell J
    2. Klinge C
    3. Zampini M
    4. Spence C
    5. Nobre AC

    (2007) Temporal order is coded temporally in the brain: early event-related potential latency shifts underlying prior entry in a cross-modal temporal order judgment task

    Journal of Cognitive Neuroscience 19:109–120.

    https://doi.org/10.1162/jocn.2007.19.1.109

    • PubMed
    • Google Scholar
62. 1. Vroomen J
    2. Keetels M
    3. de Gelder B
    4. Bertelson P

    (2004) Recalibration of temporal order perception by exposure to audio-visual asynchrony

    Cognitive Brain Research 22:32–35.

    https://doi.org/10.1016/j.cogbrainres.2004.07.003

    • PubMed
    • Google Scholar
63. Book

    1. Watson AB

    (1986)

    Temporal sensitivity

    In: Boff K, Thomas J, editors. Handbook of Perception and Human Performance. Wiley. pp. 6.1–6.6.

    • Google Scholar
64. 1. Yamauchi Y
    2. Mochizuki JI
    3. Hirakata A
    4. Uda S

    (2016) Single flash electroretinograms of mature cataractous and fellow eyes

    Clinical Ophthalmology 10:2031–2034.

    https://doi.org/10.2147/OPTH.S118677

    • PubMed
    • Google Scholar
65. 1. Zampini M
    2. Shore DI
    3. Spence C

    (2003) Audiovisual temporal order judgments

    Experimental Brain Research 152:198–210.

    https://doi.org/10.1007/s00221-003-1536-z

    • PubMed
    • Google Scholar
66. 1. Zampini M
    2. Guest S
    3. Shore DI
    4. Spence C

    (2005) Audio-visual simultaneity judgments

    Perception & Psychophysics 67:531–544.

    https://doi.org/10.3758/BF03193329

    • PubMed
    • Google Scholar

Acceptance summary:

In this study the authors compare congenital and developmental cataract survivors to typically developed individuals, to study the influence of early life experience on multisensory processing. It is this double comparison that allows them to suggest that perceptual biases develop in early life. We were most excited about the inclusion of the late-cataract control group, as well as the rich dataset, which includes replication of the findings during visuo-tactile and visuo-auditory multisensory processing. We believe this unique dataset will set a new bar for retrospective behavioural research of sensitive periods.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Cross-modal temporal biases emerge during early sensitive periods" for consideration by eLife. Your article has been reviewed by three peer reviewers, including Tamar R Makin as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by a Senior Editor.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work, as currently presented, will not be considered further for publication in eLife.

All reviewers were very excited about the general experimental approach involving comparisons of congenital versus developmental cataract survivors for studying the influence of early life experience on multisensory processing. The reviewers agreed that the presented findings were intriguing. However, even when considering the unique challenges of data collection with these precious populations, it felt that the interpretation of the findings was overly simplistic. In particular, they felt that several alternative accounts need to be better considered in order to interpret these findings more mechanistically. It was agreed that further experimental evidence will need to be presented in order to tease apart these alternative accounts, and in particular the role of attention. If a more comprehensive account for this data could be offered, then we will be very happy to consider a resubmission of the manuscript. Please note that the reviewers expressed an interest in the alternatives provided for interpreting the results, so they do not necessarily expect that these will be discounted as confounds. Instead, they are looking for more conclusive evidence for interpreting the mechanisms driving the findings. We leave it to the authors to decide what type of evidence could be raised to best address the reviewers issues, be it new experiments acquired from control participants, more detailed analysis of the existing data or presentation of additional data collected with the cataract groups. If you wish to resubmit your work after substantial revisions, please provide a point-by-point response to address each of the reviewers major comments. Of course, we understand should you wish to take this present version elsewhere at this time.

Reviewer #1:

I think it’s a very exciting dataset and the results are quite interesting. I also liked the main interpretation of the results. But at present, this all feels a little too speculative/tentative. I feel like important opportunities in analysis of this precious data have been missed, and that at present we are only provided a very partial glims at the results.

1) I'm not entirely clear about the choices for the statistical analysis, particularly with respect to the “bias” parameter. To begin with, why did they chose a hierarchical logistic regression? Why is it advantageous to, say, signal detection analysis which is often used to study biases? It is also not clear how the ISI parameter is handled in the model

2) considering the relative richness of the data collected, the analysis is quite simplistic and leaves something to be desired. Why did they not follow standard analysis procedures based on the ISI in their design (i.e. psychometric function, calculation of the slope/JND and point of subjective equality)? Considering the tendency to report “visual first” could be modulated by several dissociated factors (as elaborated in the Discussion), I feel like the traditional parameters could help interpret the described bias better. For example, attentional effects could be hypothesised to be impacting all ISI similarly (a shift of the curve), whereas the experience-based structural differences should be more time-dependent, based on biological onset asynchrony (i.e. shifting the slope)?

3) Perhaps the most interesting comparison is between the DC and CC groups, especially considering methodological and technical differences between the cataract groups and the controls. But this wasn't reported in the results? From the figures it appears that biases were indeed different (?) but it also seems that they might sustain different visual and tactile abilities (Figure 1D)? How would that potentially impact the main results?

4) The MDC group didn’t show the typical visual bias effect, this is a risk when using small sample sizes, and thus requires some consideration. Was this group not a representative control group? Again, based on Figure 1C it indeed appears that their performance at the bimanual condition was low. I appreciate that the interpretation of the DC group stands alone, by showing a bias effect in the vision direction (and opposite from the CC group). But still, this should be considered. Please don't address this question by showing no significant differences between the MDC and MCC groups, unless there are clear evidence to support this as lack of a difference (e.g. bayesian statistics)

Reviewer #2:

Badde and colleagues presented a cross-modal temporal task (which stimulus was presented first) to controls, individuals born with dense, bilateral cataracts whose sight was restored after birth (CC), and those who developed cataracts after childbirth (DC). They found that those born with cataracts that were subsequently removed (the CC group) were more likely to respond visual 1st (vs. auditory or tactile) compared to the DC and matched control groups. The results are intriguing. However, there are major concerns with regards to the interpretation that diminish enthusiasm for these findings.

The authors claim that "cross-modal perceptual biases are not innate but rather acquired during a sensitive period." My primary question is whether the observed effects are truly "cross-modal perceptual biases". An alternative hypothesis is based on the "law of prior entry", in which "the object of attention comes to consciousness more quickly than the objects which we are not attending to" (Titchener, 1908). The authors are aware of this, citing articles that show biases in temporal order when attending unequally across modalities (Titchener, 1908; Shore, Spence and Klein, 2001; Spence, Shore and Klein, 2001; Vibell et al., 2007). They then argue that (a) "attention has been ruled out as a cause of persistent biases in cross-modal spatiotemporal processing" and (b) "it is not obvious why CC- and DC-individuals would entertain opposing attentional foci given that both groups experienced transient severe visual impairment and suffer from remaining visual acuity impairments." For (a), I am not sure how their citation has ruled out attention as a cause of these biases from their Abstract: "we showed that temporal-order perception may be considered a psychological bias that attention can modulate but not fully eradicate". For (b), the argument would be that those w/o high-quality visual information at birth (CC) would need to attend more to the visual stimulus due to deficits/differences in their visual systems at birth, whereas those in DC group wouldn't need to, given that they were born with intact visual input.

This is not to say that the author's hypothesis or this alternative hypothesis aren't interesting, but more data would be needed to tease these apart. This leads to my second issue, the paper is lacking in mechanism. The Introduction (especially for the lay reader) provides minimal information about why this bias occurs, and why this matters. The paper could be improved substantially with a more mechanistic rationale, especially in the Introduction.

Finally, the authors note that the visual first bias in the CC group did not significantly correlate with duration of visual deprivation in CC group. Is this meaningful given the small number of subjects tested? It seems like there isn't enough evidence, as presented, to make this claim.

Reviewer #3:

The authors investigate cross-modal temporal perceptual biases in participants born with congenital bilateral cataract and treated on different ages. They find that in this population, the biases are opposite to healthy and developmental cataract populations. They conclude such biases develop in early sensitive period. The paper is intriguing and the results are important, however, it is to my view that the interpretation of the results and the main conclusion might be problematic.

1) The authors main point is trying to rule out the possibility of innate cross-modal perceptual biases. The option of those biases being innate might still be possible, but biases might be reversed due to lack of visual input at early age while the brain is still flexible enough. This possibility should be mentioned. So, throughout the paper, I believe the claim of lack of innateness should be transform to that of sensitive period and innateness should only be discussed as a possibility in the Discussion. If there are any developmental studies showing the emergence of the biases during the first few months after birth, they should be mentioned since they can support the authors' claim. The word "emerge" at the heading should also be change to something more accurate.

2) In the Introduction: "Moreover, it is not obvious why CC- and DC-individuals would entertain opposing attentional foci given that both groups experienced transient severe visual impairment and suffer from remaining visual acuity impairments." The authors cannot use this claim to rule out attentional foci since it is also not obvious why CC and DC individuals will have an opposing cross-modal effect as well (this study demonstrates this exact result). Attention could be opposite for the same unknown reason. I can think of one reason why CC and DC groups will entertain opposing attentional foci. Developmental individuals were used to having high resolution input, now resolution decreased to medium so they are less attentive to vision. CCs were used to having low resolution input, now resolution increased to medium, so they are more attentive. This could be one possible reason why both groups will have opposing results in visual tests.

3) DC group differed from the control group in the visuo-tactile experiment (with a trend in the visuo-auditory). Doesn't it mean that the sensitive period for the cross-modal perceptual biases is very long? Since those biases were altered (increased, not reversed) at a relatively late age? At least, this difference should be acknowledged in the Discussion acknowledging that there is no theory justifying this effect.

4) Overall, following my previous comments, I think one can only conclude that cross-modal biases are sensitive to visual experience. If a stronger claim is needed, it should take into account both CC and DC groups' results.

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Reviewer #1:

I think it’s a very exciting dataset and the results are quite interesting. I also liked the main interpretation of the results. But at present, this all feels a little too speculative/tentative. I feel like important opportunities in analysis of this precious data have been missed, and that at present we are only provided a very partial glims at the results.

1) I'm not entirely clear about the choices for the statistical analysis, particularly with respect to the “bias” parameter. To begin with, why did they chose a hierarchical logistic regression? Why is it advantageous to, say, signal detection analysis which is often used to study biases? It is also not clear how the ISI parameter is handled in the model

Our choice for an analysis with generalized linear mixed models was based on the sample size and composition. Even though large for this patient group, the sample size is small when compared to studies in healthy volunteers. And, though the participants were highly homogenous with respect to their visual history, they considerably varied in other parameters that are known to influence temporal order perception such as age. Mixed models are especially suited for such a situation because participants are included as random effects in the model. We have added this in the revised manuscript (subsection “Data Analysis”).

The bias parameter indicates the probability of a “visual first”-response across stimulus conditions. It is identical to the criterion in signal detection theory (c = (hit rate + false alarm rate)/2). In the revised manuscript, we now point this relation out (subsection “Data Analysis”).

The time interval between the stimuli was not included in this analysis because generalized mixed models require a considerable number of trials and this demand increases non-linearly with each additional factor. We now report an additional analysis based on the psychometric function (see below). Please note, an additional advantage of the original analysis is its robustness against outliers in the psychometric functions, which arise due to constraints in the number of trials that are inevitable in this type of research. (Several of the patients recruited in India were children. They simply cannot complete the same number of trials and with the same degree of concentration as university students who are used to computers or even psychological experiments). Thus, in the revised manuscript we report both analyses.

2) Considering the relative richness of the data collected, the analysis is quite simplistic and leaves something to be desired. Why did they not follow standard analysis procedures based on the ISI in their design (i.e. psychometric function, calculation of the slope/JND and point of subjective equality)? Considering the tendency to report “visual first” could be modulated by several dissociated factors (as elaborated in the Discussion), I feel like the traditional parameters could help interpret the described bias better. For example, attentional effects could be hypothesised to be impacting all ISI similarly (a shift of the curve), whereas the experience-based structural differences should be more time-dependent, based on biological onset asynchrony (i.e. shifting the slope)?

We have added a classical analysis of the point of subjective simultaneity; the results match those derived with the original bias measure, thus validating the latter.

The psychometric curves were shifted (Figure 1B); thus, the effect is of similar size across all short SOAs. This pattern is consistent with an auditory/tactile delay built into the neural circuits underlying temporal order judgments as well as with an attention-mediated visual processing gain following congenital loss of vision.

We analyzed both measures, the PSS and the original bias parameter, as the former is more precise but the latter more robust. In the revised manuscript, we moreover investigated the proportion correct and additionally report JNDs but only as a descriptive measure. Our JND estimates suffer from the fact that we sampled many short but only one long SOA, a design which was tailored to gather best-possible insights into the bias (subsection “Data Analysis”).

3) Perhaps the most interesting comparison is between the DC and CC groups, especially considering methodological and technical differences between the cataract groups and the controls. But this wasn't reported in the results? From the figures it appears that biases were indeed different (?) but it also seems that they might sustain different visual and tactile abilities (Figure 1D)? How would that potentially impact the main results?

We compared CC- and DC-groups each to their controls but not to each other because of the large age difference between groups (Table 1), a variable known to influence cross-modal temporal perception. The only way to investigate whether a difference between these groups is due to their different history of visual deprivation or their age is the comparison to an age matched healthy control group. The finding that both group comparisons revealed opposing effects, provides strong evidence for the role of vision following birth and against a role of unspecific factors such as the location of testing (the equipment was identical) for the reported group differences. We now describe this reasoning in further detail (Results paragraph one).

Our data indicate that DC-individuals show an impaired auditory and tactile resolution compared to their controls whereas these effects did not reach significance for the comparisons between CC-individuals and their normally sighted controls. Both groups differed from their controls with respect to bimodal and visual resolution (Results paragraph two).

We analyzed the correlation between resolution and bias. Participants with a lower temporal resolution relied more on temporal biases (Results paragraph three). This is reminiscent of the Bayesian framework in which the influence of the prior increases with decreasing reliability of the likelihood and makes intuitive sense: the less reliable the information extracted from the stimulus is, the more the brain relies on the readily available bias. This mechanism provides a potential explanation for the larger biases in DC-individuals compared to their controls (Discussion paragraph six). However, it cannot explain the main effect, the reversed direction of the bias in CC-individuals.

4) The MDC group didnt show the typical visual bias effect, this is a risk when using small sample sizes, and thus requires some consideration. Was this group not a representative control group? Again, based on Figure 1C it indeed appears that their performance at the bimanual condition was low. I appreciate that the interpretation of the DC group stands alone, by showing a bias effect in the vision direction (and opposite from the CC group). But still, this should be considered. Please don't address this question by showing no significant differences between the MDC and MCC groups, unless there are clear evidence to support this as lack of a difference (e.g. bayesian statistics)

The MDC-group did not show a significant bias in the proportion of “visual first” responses, yet, this does not allow us to conclude that they did not have a bias. Indeed, a closer look at the data suggests that the available power resulting from small sample sizes might play a role here. The apparent group difference is driven by one respectively two participants, which in a larger sample would not influence the statistical outcomes.

The sample sizes are too small to calculate reliable Bayes factors and collecting more participants for the control groups renders the comparison to the cataract-reversal groups problematic as the signal-to-noise ratio becomes skewed with unequal group sizes. We now show the distribution of biases across participants of each group using box-and-whisker plots (Figure 1D,E). This allows readers to convince themselves visually that both control samples show similar biases.

Finally, as stated in the comment, the key point for our study is the relation between the bias in the cataract-reversal groups compared to their matched controls.

Reviewer #2:

Badde and colleagues presented a cross-modal temporal task (which stimulus was presented first) to controls, individuals born with dense, bilateral cataracts whose sight was restored after birth (CC), and those who developed cataracts after childbirth (DC). They found that those born with cataracts that were subsequently removed (the CC group) were more likely to respond visual 1st (vs. auditory or tactile) compared to the DC and matched control groups. The results are intriguing. However, there are major concerns with regards to the interpretation that diminish enthusiasm for these findings.

The authors claim that "cross-modal perceptual biases are not innate but rather acquired during a sensitive period." My primary question is whether the observed effects are truly "cross-modal perceptual biases". An alternative hypothesis is based on the "law of prior entry", in which "the object of attention comes to consciousness more quickly than the objects which we are not attending to" (Titchener, 1908). The authors are aware of this, citing articles that show biases in temporal order when attending unequally across modalities (Titchener, 1908; Shore, Spence and Klein, 2001; Spence, Shore and Klein, 2001; Vibell et al., 2007). They then argue that (a) "attention has been ruled out as a cause of persistent biases in cross-modal spatiotemporal processing" and (b) "it is not obvious why CC- and DC-individuals would entertain opposing attentional foci given that both groups experienced transient severe visual impairment and suffer from remaining visual acuity impairments." For (a), I am not sure how their citation has ruled out attention as a cause of these biases from their Abstract: "we showed that temporal-order perception may be considered a psychological bias that attention can modulate but not fully eradicate". For (b), the argument would be that those w/o high-quality visual information at birth (CC) would need to attend more to the visual stimulus due to deficits/differences in their visual systems at birth, whereas those in DC group wouldn't need to, given that they were born with intact visual input.

We now discuss the possibility that congenital transient loss of pattern vision could lead to attentional biases that differ those of from normally sighted individuals and individuals with a later period of transient visual deprivation (Discussion paragraph five). In our (revised) view, the two accounts of the effect are not necessarily mutually exclusive: the pattern of sensory experience available at birth might calibrate modality-specific attentional biases as well as the underlying neural circuits recruited for temporal order perception.

To conclusively determine the role of attention for the observed reversal of cross-modal temporal biases, extensive new studies at the LV Prasad Eye Institute would be necessary. In order to collect data from a reasonable number of CC-individuals we would need 1-2 years under typical conditions. Participants for our studies are extremely difficult to recruit because we use strict selection criteria to maximize the likelihood that the tested CC-individuals were indeed born without any pattern vision. Currently under the condition of the pandemic it is unknown when we will be able to return to a typical testing schedule. Most of our participants come from rural areas and travel several hours in a bus to Hyderabad.

However, we think that our results are interesting irrespective of the role of attention for the effect. We can say for sure that whichever mechanism accounts for the reversal of cross-modal biases in CC-individuals, the perceived relative timing across modalities depends on early sensory (visual) experience during a sensitive period rather than, for instance, on visual experience later in life or on the current visual abilities. Thus, in the revised manuscript we relate our results to previously published studies, which seem to rather point against a shift of modality-specific attention towards vision in CC-individuals, but in the end due to the scarcity of studies directly targeting attention leave the possibility for such a mechanism open.

This is not to say that the author's hypothesis or this alternative hypothesis aren't interesting, but more data would be needed to tease these apart. This leads to my second issue, the paper is lacking in mechanism. The Introduction (especially for the lay reader) provides minimal information about why this bias occurs, and why this matters. The paper could be improved substantially with a more mechanistic rationale, especially in the Introduction.

We have rewritten large parts of the manuscript. The revised Introduction provides additional information about cross-modal temporal perception and describes mechanistic accounts of cross-modal temporal biases. The revised Discussion is more explicit about the mechanism which we consider being responsible for the reversed cross-modal bias in CC-individuals, and we now relate this “compensatory mechanism” to additional factors such as attention and response biases.

Finally, the authors note that the visual first bias in the CC group did not significantly correlate with duration of visual deprivation in CC group. Is this meaningful given the small number of subjects tested? It seems like there isn't enough evidence, as presented, to make this claim.

We have removed the correlational analysis.

Reviewer #3:

The authors investigate cross-modal temporal perceptual biases in participants born with congenital bilateral cataract and treated on different ages. They find that in this population, the biases are opposite to healthy and developmental cataract populations. They conclude such biases develop in early sensitive period. The paper is intriguing and the results are important, however, it is to my view that the interpretation of the results and the main conclusion might be problematic.

1) The authors main point is trying to rule out the possibility of innate cross-modal perceptual biases. The option of those biases being innate might still be possible, but biases might be reversed due to lack of visual input at early age while the brain is still flexible enough. This possibility should be mentioned. So, throughout the paper, I believe the claim of lack of innateness should be transform to that of sensitive period and innateness should only be discussed as a possibility in the discussion. If there are any developmental studies showing the emergence of the biases during the first few months after birth, they should be mentioned since they can support the authors' claim. The word "emerge" at the heading should also be change to something more accurate.

A stated in this comment, theoretically innate biases could be reversed during a sensitive period. Since we agree with Lewkowicz (2011, Infancy) that research on developmental principles should not be narrowed down to the simplistic dichotomy of nature – nurture, but rather investigate how experience dynamically contributes to brain development, we more precisely argue along these lines throughout the revised manuscript.

We now report findings which suggest that very young infants already show biases in the perception of cross-modal synchrony (Discussion paragraph three) and discuss parallels between the typical development of multisensory temporal perception and multisensory temporal perception in individuals with reversed congenital cataracts (paragraph nine).

We have changed the title of our manuscript.

2) In the Introduction: "Moreover, it is not obvious why CC- and DC-individuals would entertain opposing attentional foci given that both groups experienced transient severe visual impairment and suffer from remaining visual acuity impairments." The authors cannot use this claim to rule out attentional foci since it is also not obvious why CC and DC individuals will have an opposing cross-modal effect as well (this study demonstrates this exact result). Attention could be opposite for the same unknown reason. I can think of one reason why CC and DC groups will entertain opposing attentional foci. Developmental individuals were used to having high resolution input, now resolution decreased to medium so they are less attentive to vision. CCs were used to having low resolution input, now resolution increased to medium, so they are more attentive. This could be one possible reason why both groups will have opposing results in visual tests.

We now discuss the possibility that congenital loss of pattern vision leads to increased attention towards that modality (Discussion paragraph four).

3) DC group differed from the control group in the visuo-tactile experiment (with a trend in the visuo-auditory). Doesn't it mean that the sensitive period for the cross-modal perceptual biases is very long? Since those biases were altered (increased, not reversed) at a relatively late age? At least, this difference should be acknowledged in the Discussion acknowledging that there is no theory justifying this effect.

An increased bias towards perceiving vision as delayed in DC-individuals is incompatible with the idea of an extended sensitive period: if an extended sensitive period existed, the group difference between the DC- and the MDC-group should go in the same direction as that between the CC- and the MCC-group (since the DC- and CC-group share similarly altered experiences). Therefore, we hypothesize that the opposite cross-modal bias in the DC- compared to the CC-group fits well with the idea of a short sensitive period.

Unlike the normally sighted control group, DC-individuals might experience residual delays of visual processing for which the brain never learned to compensate because the sensitive period had closed early. An additional explanation for their increased cross-modal bias in the typical direction might be that DC-individuals rely stronger on typical biases because they experience greater temporal uncertainty. This idea is compatible with a common finding in individuals with restored hearing: Late deaf cochlear implant recipients show enhanced use of multisensory cues (Rouger et al., 2007, PNAS) while congenitally deaf cochlear implant recipients show no or impaired use of multisensory cues if the implants were received late (Schorr et al., 2005, PNAS). We now discuss this account in the manuscript (Discussion paragraph six).

4) Overall, following my previous comments, I think one can only conclude that cross-modal biases are sensitive to visual experience. If a stronger claim is needed, it should take into account both CC and DC groups' results.

We agree and now interpret the results as indicator for a sensitive period.

Author details

1. Stephanie Badde

   1. Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany
   2. Department of Psychology and Center of Neural Science, New York University, New York, United States

   Contribution

   Data curation, Software, Formal analysis, Supervision, Visualization, Methodology, Writing - original draft, Writing - review and editing

   For correspondence

   stephanie.badde@nyu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4005-5503

2. Pia Ley

   Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany

   Contribution

   Software, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Siddhart S Rajendran

   1. Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany
   2. Child Sight Institute, Jasti V Ramanamma Children's Eye Care Center, LV Prasad Eye Institute, Hyderabad, India

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

4. Idris Shareef

   1. Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany
   2. Child Sight Institute, Jasti V Ramanamma Children's Eye Care Center, LV Prasad Eye Institute, Hyderabad, India

   Contribution

   Data curation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9258-2199

5. Ramesh Kekunnaya

   1. Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany
   2. Child Sight Institute, Jasti V Ramanamma Children's Eye Care Center, LV Prasad Eye Institute, Hyderabad, India

   Contribution

   Resources, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5789-2300

6. Brigitte Röder

   Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

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