The influence of semantics on long-term visual memory capacity in children and adults.

Human visual memory capacity has a rapid developmental progression. Here we examine whether image semantics modulate this progression. We assessed the performance of children (6-14 years) and young adults (19-36 years) on a visual memory task using real-world (or meaningful) as well as abstract image sets, which were matched in low-level image attributes. For real images, we find comparable performance across the two age groups, consistent with previously reported results. However, for abstract images, we find a clear age-related difference indicating greater reliance of children's memory processes on semantics, suggesting that strategies for encoding abstract patterns keep improving even into late childhood. We complemented these studies with computational experiments designed to examine the role of increasing experience with real-world images on real and abstract image encoding, to examine whether the observed age-related differences, as well as the general privilege of real over abstract images, can emerge directly through experience with meaningful images. Our results provide support for this possibility and set the stage for a finer-grained investigation of the timeline along which children's memory capacity for abstract images reaches adult levels.

Impact of early visual experience on later usage of color cues.

Human visual recognition is remarkably robust to chromatic changes. In this work, we provide a potential account of the roots of this resilience based on observations with 10 congenitally blind children who gained sight late in life. Several months or years following their sight-restoring surgeries, the removal of color cues markedly reduced their recognition performance, whereas age-matched normally sighted children showed no such decrement. This finding may be explained by the greater-than-neonatal maturity of the late-sighted children's color system at sight onset, inducing overly strong reliance on chromatic cues. Simulations with deep neural networks corroborate this hypothesis. These findings highlight the adaptive significance of typical developmental trajectories and provide guidelines for enhancing machine vision systems.

Temporal windows of unconscious processing cannot easily be disrupted.

Conscious perception is preceded by long periods of unconscious processing. These periods are crucial for analyzing temporal information and for solving the many ill-posed problems of vision. An important question is what starts and ends these windows and how they may be interrupted. Most experimental paradigms do not offer the methodology required for such investigation. Here, we used the sequential metacontrast paradigm, in which two streams of lines, expanding from the center to the periphery, are presented, and participants are asked to attend to one of the motion streams. If several lines in the attended motion stream are offset, the offsets are known to integrate mandatorily and unconsciously, even if separated by up to 450 ms. Using this paradigm, we here found that external visual objects, such as an annulus, presented during the motion stream, do not disrupt mandatory temporal integration. Thus, if a window is started once, it appears to remain open even in the presence of disruptions that are known to interrupt visual processes normally. Further, we found that interrupting the motion stream with a gap disrupts temporal integration but does not terminate the overall unconscious processing window. Thus, while temporal integration is key to unconscious processing, not all stimuli in the same processing window are integrated together. These results strengthen the case for unconscious processing taking place in windows of sensemaking, during which temporal integration occurs in a flexible and perceptually meaningful manner.

Recognizing distant faces.

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies have investigated facial recognition at short, fixed distances. Under these conditions, the photometric and configural information related to the eyes, nose and mouth are typically found to be primary determinants of facial identity. Here we characterize face recognition performance as a function of viewing distance and investigate whether the primacy of the internal features continues to hold across increasing viewing distances. We find that exploring the distance dimension reveals a qualitatively different salience distribution across a face. Observers' recognition performance significantly exceeds that obtained with the internal facial physiognomy, and also exceeds the computed union of performances with internal and external features alone, suggesting that in addition to the mutual configuration of the eyes, nose and mouth, it is the relationships between these features and external head contours that are crucial for recognition. We have also conducted computational studies with convolutional neural networks trained on the task of face recognition to examine whether this representational bias could emerge spontaneously through exposure to faces. The results provide partial support for this possibility while also highlighting important differences between the human and artificial system. These findings have implications for the nature of facial representations useful for a visual system, whether human or machine, for recognition over large and varying distances.

Prenatal auditory experience and its sequelae.

Towards the end of the second trimester of gestation, a human fetus is able to register environmental sounds. This in utero auditory experience is characterized by comprising strongly low-pass-filtered versions of sounds from the external world. Here, we present computational tests of the hypothesis that this early exposure to severely degraded auditory inputs serves an adaptive purpose-it may induce the neural development of extended temporal integration. Such integration can facilitate the detection of information carried by low-frequency variations in the auditory signal, including emotional or other prosodic content. To test this prediction, we characterized the impact of several training regimens, biomimetic and otherwise, on a computational model system trained and tested on the task of emotion recognition. We find that training with an auditory trajectory recapitulating that of a neurotypical infant in the pre-to-postnatal period results in temporally extended receptive field structures and yields the best subsequent accuracy and generalization performance on the task of emotion recognition. This strongly suggests that the progression from low-pass-filtered to full-frequency inputs is likely to be an adaptive feature of our development, conferring significant benefits to later auditory processing abilities relying on temporally extended analyses. Additionally, this finding can help explain some of the auditory impairments associated with preterm births, suggests guidelines for the design of auditory environments in neonatal care units, and points to enhanced training procedures for computational models.

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration.

Integration across space and time is essential for the analysis of motion, low contrast, and many more stimuli. A crucial question is what determines the duration of integration. Based on classical models of decision-making, one might expect that integration terminates as soon as sufficient evidence about a stimulus is accumulated and a threshold is crossed. However, there is very little research on this question as most experimental paradigms cannot monitor processing following stimulus presentation. In particular, it is difficult to determine when processing terminates. Here, using the sequential metacontrast paradigm (SQM), in which information is mandatorily integrated along motion trajectories, we show that the processing load determines the extent of integration but that evidence accumulation does not. Further, the extent of integration is determined by absolute time instead of the number of elements presented. These results have important implications for understanding the time course and mechanisms of temporal integration.

Development of Visual Memory Capacity Following Early-Onset and Extended Blindness.

It is unknown whether visual memory capacity can develop if onset of pattern vision is delayed for several years following birth. We had an opportunity to address this question through our work with an unusual population of 12 congenitally blind individuals ranging in age from 8 to 22 years. After providing them with sight surgery, we longitudinally evaluated their visual memory capacity using an image-memorization task. Our findings revealed poor visual memory capacity soon after surgery but significant improvement in subsequent months. Although there may be limits to this improvement, performance 1 year after surgery was found to be comparable with that of control participants with matched visual acuity. These findings provide evidence for plasticity of visual memory mechanisms into late childhood but do not rule out vulnerability to early deprivation. Our computational simulations suggest that a potential mechanism to account for changes in memory performance may be progressive representational elaboration in image encoding.

A guideline for linking brain wave findings to the various aspects of discrete perception.

Brain waves, determined by electrical and magnetic brain recordings (e.g., EEG and MEG), and fluctuating behavioral responses, determined by response time or accuracy measures, are frequently taken to support discrete perception. For example, it has been proposed that humans experience only one conscious percept per brain wave (e.g., during one alpha cycle). However, the proposed link between brain waves and discrete perception is typically rather vague. More importantly, there are many models and aspects of discrete perception and it is often not apparent in what theoretical framework brain wave findings are interpreted and to what specific aspects of discrete perception they relate. Here, we review different approaches to discrete perception and highlight issues with particular interpretations. We then discuss how certain findings on brain waves may relate to certain aspects of discrete perception. The main purpose of this meta-contribution is to give a short overview of discrete models of perception and to illustrate the need to make explicit what aspects of discrete theories are addressed by what aspects of brain wave findings.

Potential downside of high initial visual acuity.

Children who are treated for congenital cataracts later exhibit impairments in configural face analysis. This has been explained in terms of a critical period for the acquisition of normal face processing. Here, we consider a more parsimonious account according to which deficits in configural analysis result from the abnormally high initial retinal acuity that children treated for cataracts experience, relative to typical newborns. According to this proposal, the initial period of low retinal acuity characteristic of normal visual development induces extended spatial processing in the cortex that is important for configural face judgments. As a computational test of this hypothesis, we examined the effects of training with high-resolution or blurred images, and staged combinations, on the receptive fields and performance of a convolutional neural network. The results show that commencing training with blurred images creates receptive fields that integrate information across larger image areas and leads to improved performance and better generalization across a range of resolutions. These findings offer an explanation for the observed face recognition impairments after late treatment of congenital blindness, suggest an adaptive function for the acuity trajectory in normal development, and provide a scheme for improving the performance of computational face recognition systems.