Unique contributions of perceptual and conceptual humanness to object representations in the human brain

Dynamics of visual object coding within and across the hemispheres: Objects in the periphery

The human brain continuously integrates information across its two hemispheres to construct a coherent representation of the perceptual world. Characterizing how visual information is represented in each hemisphere over time is crucial for understanding how hemispheric transfer contributes to perception. Here, we investigated information processing within each hemisphere over time and the degree to which it is distinct or duplicated across hemispheres. We presented participants with object images lateralized to the left or right visual fields while measuring their brain activity with electroencephalography. Stimulus coding was more robust and emerged earlier in the contralateral than the ipsilateral hemisphere. Presentation of two stimuli, one to each hemifield, reduced the fidelity of representations in both hemispheres relative to one stimulus alone, signifying hemispheric interference. Last, we found that processing within the contralateral, but not ipsilateral, hemisphere was biased to image-related over concept-related information. Together, these results suggest that hemispheric transfer operates to filter irrelevant information and efficiently prioritize processing of meaning.

Measuring self-similarity in empirical signals to understand musical beat perception

Experiencing music often entails the perception of a periodic beat. Despite being a widespread phenomenon across cultures, the nature and neural underpinnings of beat perception remain largely unknown. In the last decade, there has been a growing interest in developing methods to probe these processes, particularly to measure the extent to which beat-related information is contained in behavioral and neural responses. Here, we propose a theoretical framework and practical implementation of an analytic approach to capture beat-related periodicity in empirical signals using frequency-tagging. We highlight its sensitivity in measuring the extent to which the periodicity of a perceived beat is represented in a range of continuous time-varying signals with minimal assumptions. We also discuss a limitation of this approach with respect to its specificity when restricted to measuring beat-related periodicity only from the magnitude spectrum of a signal and introduce a novel extension of the approach based on autocorrelation to overcome this issue. We test the new autocorrelation-based method using simulated signals and by re-analyzing previously published data and show how it can be used to process measurements of brain activity as captured with surface EEG in adults and infants in response to rhythmic inputs. Taken together, the theoretical framework and related methodological advances confirm and elaborate the frequency-tagging approach as a promising window into the processes underlying beat perception and, more generally, temporally coordinated behaviors.

Mapping the dynamics of visual feature coding: Insights into perception and integration

The basic computations performed in the human early visual cortex are the foundation for visual perception. While we know a lot about these computations, a key missing piece is how the coding of visual features relates to our perception of the environment. To investigate visual feature coding, interactions, and their relationship to human perception, we investigated neural responses and perceptual similarity judgements to a large set of visual stimuli that varied parametrically along four feature dimensions. We measured neural responses using electroencephalography (N = 16) to 256 grating stimuli that varied in orientation, spatial frequency, contrast, and colour. We then mapped the response profiles of the neural coding of each visual feature and their interactions, and related these to independently obtained behavioural judgements of stimulus similarity. The results confirmed fundamental principles of feature coding in the visual system, such that all four features were processed simultaneously but differed in their dynamics, and there was distinctive conjunction coding for different combinations of features in the neural responses. Importantly, modelling of the behaviour revealed that every stimulus feature contributed to perceptual judgements, despite the untargeted nature of the behavioural task. Further, the relationship between neural coding and behaviour was evident from initial processing stages, signifying that the fundamental features, not just their interactions, contribute to perception. This study highlights the importance of understanding how feature coding progresses through the visual hierarchy and the relationship between different stages of processing and perception.

An online browser-based attentional blink replication using visual objects

The complex relationship between attention and visual perception can be exemplified and investigated through the Attentional Blink. The attentional blink is characterised by impaired attention to the second of two target stimuli, when both occur within 200 - 500ms. The attentional blink has been well studied in experimental lab settings. However, despite the rise of online methods for behavioural research, their suitability for studying the attentional blink has not been fully addressed yet, the main concern being the lack of control and timing variability for stimulus presentation. Here, we investigated the suitability of online testing for studying the attentional blink with visual objects. Our results show a clear attentional blink effect between 200 to 400ms following the distractor including a Lag 1 sparing effect in line with previous research despite significant inter-subject and timing variability. This work demonstrates the suitability of online methods for studying the attentional blink with visual objects, opening new avenues to explore its underlying processes.

Capacity for movement is an organisational principle in object representations

The ability to perceive moving objects is crucial for threat identification and survival. Recent neuroimaging evidence has shown that goal-directed movement is an important element of object processing in the brain. However, prior work has primarily used moving stimuli that are also animate, making it difficult to disentangle the effect of movement from aliveness or animacy in representational categorisation. In the current study, we investigated the relationship between how the brain processes movement and aliveness by including stimuli that are alive but still (e.g., plants), and stimuli that are not alive but move (e.g., waves). We examined electroencephalographic (EEG) data recorded while participants viewed static images of moving or non-moving objects that were either natural or artificial. Participants classified the images according to aliveness, or according to capacity for movement. Movement explained significant variance in the neural data over and above that of aliveness, showing that capacity for movement is an important dimension in the representation of visual objects in humans.