Research
Research line: Characterizing neural mechanisms underlying the efficiency of naturalistic vision
The efficient detection of goal-relevant objects in our environment is of critical importance in daily life. For example, the majority of road accidents are caused by insufficient attention to relevant objects (e.g., pedestrians) in scenes. Our daily-life visual environments, such as city streets and living rooms, contain a multitude of objects. Out of this overwhelming amount of sensory information, our brains must efficiently select and recognize those objects that are relevant for current goals. Visual and attention systems have developed and evolved to optimally perform real-world tasks like these, as reflected in the remarkable efficiency of naturalistic object detection. It is increasingly appreciated that the brain makes use of a wide range of available information to facilitate object detection in real scenes. Our research aims to characterize the neural mechanisms that contribute to the efficiency of goal-directed naturalistic human vision.
Behavioral studies have identified several factors that contribute to the efficiency of naturalistic object detection, including: 1. The use of effective attentional templates; 2. Attentional guidance by scene context and episodic memory; 3. Context-based predictions facilitating object recognition; and 4. Inter-object grouping based on real-world regularities. While these factors are increasingly appreciated and studied in behavioral and theoretical work, little is known about their neural basis. Our goal is to fill this gap, using fMRI, MEG, and TMS to improve our understanding of the neural mechanisms underlying the efficiency of object perception in natural scenes.
Figure from Peelen et al. (2024)
Examples of recent research:
Lerebourg M, de Lange FP, Peelen MV (in press). Attentional guidance through object associations in visual cortex. Sci Adv
Gayet S, Battistoni E, Thorat S, Peelen MV (2024). Searching near and far: the attentional template incorporates viewing distance. J Exp Psychol Hum Percept Perform 50:216-231
Aldegheri G, Gayet S, Peelen MV (2023). Scene context automatically drives predictions of object transformations. Cognition 238:105521
Gayet S, Peelen MV (2022). Preparatory attention incorporates contextual expectations. Curr Biol 32:687-692
Wischnewski M, Peelen MV (2021). Causal neural mechanisms of context-based object recognition. eLife 10:e69736
For reviews, see:
Peelen MV, Berlot E, de Lange FP (2024). Predictive processing of scenes and objects. Nat Rev Psych 3:13-26
Willems RM*, Peelen MV* (2021). How context changes the neural basis of perception and language. iScience 24:102392
Kaiser D, Quek GL, Cichy RM, Peelen MV (2019). Object vision in a structured world. Trends Cogn Sci 23:672-685
Battistoni E, Stein T, Peelen MV (2017). Preparatory attention in visual cortex. Ann N Y Acad Sci 1396:92-107
Peelen MV, Kastner S (2014). Attention in the real world: Toward understanding its neural basis. Trends Cogn Sci 18:242-250
Research line: Category specificity in the ventral stream
Evidence for category specificity in the organization of human perception and cognition, and in the organization of the ventral stream, stretches back to the beginnings of modern cognitive neuroscience. Classic neuropsychological patient studies revealed striking dissociations in the performance of patients on judgments about living and non-living objects, as well as more selective deficits relating to specific categories such as human body parts.
The advent of functional neuroimaging built on these findings by exploring the topography and properties of visual object representations in healthy participants. Large-scale patterns of activity that span the ventral temporal cortex distinguish inanimate from animate categories. Several focal regions exhibit strong and highly selective responses to more-specific categories, such as scenes, faces, tools, body parts and words. Numerous fMRI studies have established the regular and consistent arrangement of such regions, which collectively span the ventral and lateral posterior surface of the brain and extend from the occipital cortex deep into the medial temporal cortex. The selectivity and functional significance of some of these regions has been further demonstrated by brain stimulation methods (such as transcranial magnetic stimulation) that reveal selective behavioral impairments - for example in making judgments about faces, objects, bodies, scenes or tools - when normal neural activity is disrupted.
That these regions respond selectively to their preferred category, relative to items of other kinds, is widely accepted; however, debates continue over nearly every other conceivable basic question about these regions. How do they contribute to behaviour? Why do they consistently fall in the same cortical territory across individuals? How are they connected? How do they develop? Ongoing work in the lab addresses these questions. In particular, we study what these regions represent about their preferred category, and how these representations contribute - as parts of broader domain-specific networks (figure below) - to achieving real-world goals such as navigation, reading, recognizing conspecifics, using tools, and understanding others’ actions and emotions.
Figure from Peelen & Downing (2017)
Examples of recent research:
Leticevscaia O, Brandman T, Peelen MV (in press). Scene context and attention independently facilitate MEG decoding of object category. Vis Res
Shang L, Yeh LC, Zhao Y, Wiegand I, Peelen MV (2024). Category-based attention facilitates memory search. eNeuro 11(2)
Yeh, LC, Peelen MV (2022). The time course of categorical and perceptual similarity effects in visual search. J Exp Psychol Hum Percept Perform 48:1069-1082
Thorat S, Peelen MV (2022). Body shape as a visual feature: evidence from spatially-global attentional modulation in human visual cortex. NeuroImage 255:119207
Wischnewski M, Peelen MV (2021). Causal evidence for a double dissociation between object- and scene-selective regions of visual cortex: A preregistered TMS replication study. J Neurosci 41:751-756
Brandman T, Avancini C, Leticevscaia O, Peelen MV (2020). Auditory and semantic cues facilitate decoding of visual object category in MEG. Cereb Cortex 30:597-606
Thorat S, Proklova D, Peelen MV (2019). The nature of the animacy organization in human ventral temporal cortex. eLife 8:e47142
Proklova D, Kaiser D, Peelen MV (2019). MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects. NeuroImage 193:167-177
For reviews, see:
Peelen MV, Downing PE (2017). Category selectivity in human visual cortex: Beyond visual object recognition. Neuropsychologia 105:177-183
Downing PE, Peelen MV (2016). Body selectivity in occipitotemporal cortex: causal evidence. Neuropsychologia 83:138-148
Research line: Factors determining object visibility
What determines how quickly we become aware of the presence of an object in our environment? While the visibility (or detectability) of a visual stimulus is primarily determined by its physical characteristics, such as its luminance contrast relative to other elements in the visual field (bottom-up saliency), several other factors also play a role. In our research, we investigate how expectation, attention, knowledge, and experience influence how quickly observers detect or localize objects. For example, we found that the simple detection of an object (on a uniform background) is influenced by the observer’s expectations and attentional set (Stein & Peelen, 2015). Extensive visual experience with object configurations (e.g., lamp above table; Stein et al., 2015) and object categories (e.g., faces and bodies; Stein et al., 2016; Thorat et al., 2022) also influences how quickly participants become aware of an object. Finally, emotional faces, and objects associated with rewarding outcomes, also have an advantage in being noticed (Hickey et al., 2015), though great care is needed to distinguish between high-level aspects, such as social or emotional significance, and co-varying low-level visual properties (Gayet et al., 2019; Stein et al., 2018).
Beyond revealing factors that influence detectability, we are also interested in determining what drives these differences; specifically, do differences in detectability reflect differences in unconscious processing? To address this question, in collaboration with Timo Stein, we use behavioural paradigms, such as continuous flash suppression and backward masking, in combination with tasks probing detection and awareness of stimulus manipulations (Stein & Peelen, 2021).
Figure from Stein & Peelen (2021)
Examples of recent research:
Yeh LC, Thorat S, Peelen MV (2024). Predicting cued and oddball visual search performance from neural representational similarity. J Neurosci 44: e1107232024
Thorat S, Peelen MV (2022). Body shape as a visual feature: evidence from spatially-global attentional modulation in human visual cortex. NeuroImage 255:119207
Stein T, Peelen MV (2021). Dissociating conscious and unconscious influences on visual detection effects. Nat Hum Behav 1-13
Gayet S, Stein T, Peelen MV (2019). The danger of interpreting detection differences between image categories. Emotion 19:928-932
Stein T, Awad D, Gayet S, Peelen MV (2018). Unconscious processing of facial dominance: The role of low-level factors in access to awareness. J Exp Psychol Gen. 147:e1-e13
Stein T, Reeder RR, Peelen MV (2016). Privileged access to awareness for faces and objects of expertise. J Exp Psychol Hum Percept Perform 42:788-98
Stein T, Peelen MV (2015). Content-specific expectations enhance stimulus detectability by increasing perceptual sensitivity. J Exp Psychol Gen 144:1089-104
Hickey C, Kaiser D, Peelen MV (2015). Reward guides attention to object categories in real-world scenes. J Exp Psychol Gen 144:264-73
Stein T, Kaiser D, Peelen MV (2015). Interobject grouping facilitates visual awareness. J Vis 15:10
For reviews, see:
Kaiser D, Quek GL, Cichy RM, Peelen MV (2019). Object Vision in a Structured World. Trends Cogn Sci 23:672-685
Battistoni E, Stein T, Peelen MV (2017). Preparatory attention in visual cortex. Ann N Y Acad Sci 1396:92-107