Neural dynamics underlying coherent motion perception in children and adults

Manning, Catherine; Kaneshiro, Blair; Kohler, Peter J.; Duta, Mihaela; Scerif, Gaia; Norcia, Anthony M.

doi:10.1016/j.dcn.2019.100670

Cited by 12 publications

(28 citation statements)

References 58 publications

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“… Nickl-Jockschat et al (2014) further showed in their activation likelihood estimation meta-analysis that structural deficits of MT were unique to the right hemisphere portion of the area MT in addition to hypoactivation of the left fusiform gyrus during face processing. In terms of motion and M pathway processing, as discussed above, it appears that maturation occurs at ages around 10 years ( Crewther et al, 1999 ; Langrova et al, 2006 ; Manning et al, 2019 ). Thus, we are suggesting that maturation in the case of high autistic tendency leaves a higher remnant PIm → MT projection in the mature visual system.…”

Section: Update - Abnormal Dorsal Stream Development and Connectivity In Autismmentioning

confidence: 98%

“… Langrova et al (2006) showed the presence of an early positivity in the motion onset VEP at a latency of around 200 ms that was clearly present in a group of 6–7 years children, still discernible at age 12, but had vanished beyond about 16 year age. More recently, Manning et al (2019) showed, using high density EEG recordings of onset to coherent dot motion in neurotypical development from 6 year to adult, that the younger children showed an extra contribution over lateral occipital cortex that was no longer present by ages 10–12 year.…”

Section: Updating Primate Developmental Visual Neurosciencementioning

confidence: 99%

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Neural Mechanisms of Visual Motion Anomalies in Autism: A Two-Decade Update and Novel Aetiology

Spiteri

Crewther

2021

Front. Neurosci.

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The 21st century has seen dramatic changes in our understanding of the visual physio-perceptual anomalies of autism and also in the structure and development of the primate visual system. This review covers the past 20 years of research into motion perceptual/dorsal stream anomalies in autism, as well as new understanding of the development of primate vision. The convergence of this literature allows a novel developmental hypothesis to explain the physiological and perceptual differences of the broad autistic spectrum. Central to these observations is the development of motion areas MT+, the seat of the dorsal cortical stream, central area of pre-attentional processing as well as being an anchor of binocular vision for 3D action. Such development normally occurs via a transfer of thalamic drive from the inferior pulvinar → MT to the anatomically stronger but later-developing LGN → V1 → MT connection. We propose that autistic variation arises from a slowing in the normal developmental attenuation of the pulvinar → MT pathway. We suggest that this is caused by a hyperactive amygdala → thalamic reticular nucleus circuit increasing activity in the PIm → MT via response gain modulation of the pulvinar and hence altering synaptic competition in area MT. We explore the probable timing of transfer in dominance of human MT from pulvinar to LGN/V1 driving circuitry and discuss the implications of the main hypothesis.

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Section: Update - Abnormal Dorsal Stream Development and Connectivity In Autismmentioning

confidence: 98%

Section: Updating Primate Developmental Visual Neurosciencementioning

confidence: 99%

Neural Mechanisms of Visual Motion Anomalies in Autism: A Two-Decade Update and Novel Aetiology

Spiteri

Crewther

2021

Front. Neurosci.

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“…During visual processing, EEG activity is dominated by N2, an ERP component related to visual motion perception. N2 is a negative-going deflection typically observed in posterior occipital and parietal areas, and responds to changes in visual motion (Luck 2014). Previous studies found N2 around 130-150 ms after stimulus onset in adults (Probst et al 1993;Kremláček et al 2004), and after around 180-220 ms in infants aged 8 months (Van der Meer et al 2008).…”

Section: Introductionmentioning

confidence: 96%

“…When we walk backward, on the other hand, the same point will contract and the flow will radiate toward the point (Bruce et al 2003 ). If our speed increases, the velocity in the optic flow will change accordingly, leading to changes in brain activity (Vilhelmsen et al 2015 ) that show a gradual developmental progression through childhood (Manning et al 2019 ). Thus, we rely on optic flow every time we move (Warren et al 2001 ), and it is a crucial source of information to control our walking direction and speed.…”

Section: Introductionmentioning

confidence: 99%

“…Wann et al ( 2011 ) reported that children at 6–11 years are not yet able to properly assess the speed of an approaching vehicle, resulting in impaired ability of safely crossing a busy road. Moreover, children aged 6–12 years show differential mechanisms of motion processing when compared to adults (Manning et al 2019 ). According to the World Health Organization ( 2013 ), traffic accidents are a major cause of serious injuries among children and are ranked as the second most frequent cause of death in children between 10 and 14 years worldwide.…”

Section: Introductionmentioning

confidence: 99%

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Development of motion speed perception from infancy to early adulthood: a high-density EEG study of simulated forward motion through optic flow

et al. 2021

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This study investigated evoked and oscillatory brain activity in response to forward visual motion at three different ecologically valid speeds, simulated through an optic flow pattern consisting of a virtual road with moving poles at either side of it. Participants were prelocomotor infants at 4–5 months, crawling infants at 9–11 months, primary school children at 6 years, adolescents at 12 years, and young adults. N2 latencies for motion decreased significantly with age from around 400 ms in prelocomotor infants to 325 ms in crawling infants, and from 300 and 275 ms in 6- and 12-year-olds, respectively, to 250 ms in adults. Infants at 4–5 months displayed the longest latencies and appeared unable to differentiate between motion speeds. In contrast, crawling infants at 9–11 months and 6-year-old children differentiated between low, medium and high speeds, with shortest latency for low speed. Adolescents and adults displayed similar short latencies for the three motion speeds, indicating that they perceived them as equally easy to detect. Time–frequency analyses indicated that with increasing age, participants showed a progression from low- to high-frequency desynchronized oscillatory brain activity in response to visual motion. The developmental differences in motion speed perception are interpreted in terms of a combination of neurobiological development and increased experience with self-produced locomotion. Our findings suggest that motion speed perception is not fully developed until adolescence, which has implications for children’s road traffic safety.

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Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates

et al. 2020

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Children make faster and more accurate decisions about perceptual information as they get older, but it is unclear how different aspects of the decision-making process change with age. Here, we used hierarchical Bayesian diffusion models to decompose performance in a perceptual task into separate processing components, testing age-related differences in model parameters and links to neural data. We collected behavioural and EEG data from 96 6-to 12-year-old children and 20 adults completing a motion discrimination task. We used a component decomposition technique to identify two response-locked EEG components with ramping activity preceding the response in children and adults: one with activity that was maximal over centro-parietal electrodes and one that was maximal over occipital electrodes. Younger children had lower drift rates (reduced sensitivity), wider boundary separation (increased response caution) and longer non-decision times than older children and adults. Yet, model comparisons suggested that the best model of children's data included age effects only on drift rate and boundary separation (not non-decision time). Next, we extracted the slope of ramping activity in our EEG components and covaried these with drift rate. The slopes of both EEG components related positively to drift rate, but the best model with EEG covariates included only the centro-parietal component. By decomposing performance into distinct components and relating them to neural markers, diffusion models have the potential to identify the reasons why children with developmental conditions perform differently to typically developing children and to uncover processing differences inapparent in the response time and accuracy data alone.

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Neural dynamics underlying coherent motion perception in children and adults

Cited by 12 publications

References 58 publications

Neural Mechanisms of Visual Motion Anomalies in Autism: A Two-Decade Update and Novel Aetiology

Neural Mechanisms of Visual Motion Anomalies in Autism: A Two-Decade Update and Novel Aetiology

Development of motion speed perception from infancy to early adulthood: a high-density EEG study of simulated forward motion through optic flow

Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates

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