scholarly journals Object expectations alter information use during visual recognition

2019 ◽  
Author(s):  
Laurent Caplette ◽  
Frédéric Gosselin ◽  
Gregory West
Keyword(s):  
Real World ◽  
Visual Information ◽  
Visual Recognition ◽  
Recognition Task ◽  
Complex Objects ◽  
Diagnostic Features ◽  
Spatial Frequencies ◽  
Everyday Object ◽  
Specific Object ◽  
Coarse Information

Prior expectations influence how we perceive and recognize objects. However, how they do so remains unclear, especially in the case of real-world complex objects. Expectations of objects may affect which features are used to recognize them subsequently. In this study, we used reverse correlation in neurotypical participants to reveal with high precision how the use of spatial frequencies across time is modulated by everyday object expectations in a recognition task. We show that coarse information leads to accurate responses earlier when an object is expected, indicating that subjects use diagnostic features earlier in this situation. We also demonstrate an increased variability in the later use of coarse information depending on the expected object, indicating that subjects adopt a more specialized recognition strategy when they have a specific object expectation. In summary, our results reveal how expectations of real-world complex objects affect the use of visual information across time.

Real-World Scene Categorisation by a Self-Organising Neural Network

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 292-292
Author(s):  
A Oliva ◽  
J Hérault ◽  
A Guerin-Dugue
Keyword(s):  
Neural Network ◽  
Real World ◽  
Scene Recognition ◽  
Sufficient Information ◽  
Two Dimensional ◽  
Coarse Scale ◽  
Spatial Frequencies ◽  
Coarse Information ◽  
Output Space ◽  
World Image

There is now a great deal of evidence that the visual system identifies the category of a scene before identifying its component objects. Schyns and Oliva (1994 Psychological Science5 195 – 200) showed that scene recognition could be initiated with only coarse blobs (information from which the identity of objects could not be recognised). Thus, one possible strategy for object recognition would be first to recognise the background scene from very coarse information and then recognise the component objects from fine-scale information. However, this will only be useful to the extent that there is enough coarse-scale information for the background scene to be recognised. We present a scene categorisation model in which low and very low spatial frequencies alone offer sufficient information to produce consistent clusters of five distinct scene categories (beach, city, forest, room, and valley). A new self-organising neural network—curvilinear component analysis (P Demartines, J Herault, 1997 IEEE Transactions on Neural Networks8 149 – 154)—was used to project nonlinearly a filtered version of a real-world image onto a two-dimensional output space. The resulting projection preserved the semantic proximities between the scene categories. These results offer formal evidence that there is enough coarse-scale information for recognition.

scholarly journals Two Phases of V1 Activity for Visual Recognition of Natural Images

2010 ◽  
Vol 22 (6) ◽  
pp. 1262-1269 ◽  
Author(s):  
Joan A. Camprodon ◽  
Ehud Zohary ◽  
Verena Brodbeck ◽  
Alvaro Pascual-Leone
Keyword(s):  
Visual Information ◽  
Visual Recognition ◽  
Striate Cortex ◽  
Recognition Task ◽  
Good Method ◽  
Natural Scenes ◽  
Two Phases ◽  
Functional Relevance ◽  
Feedback Connections ◽  
And Behavior

Present theories of visual recognition emphasize the role of interactive processing across populations of neurons within a given network, but the nature of these interactions remains unresolved. In particular, data describing the sufficiency of feedforward algorithms for conscious vision and studies revealing the functional relevance of feedback connections to the striate cortex seem to offer contradictory accounts of visual information processing. TMS is a good method to experimentally address this issue, given its excellent temporal resolution and its capacity to establish causal relations between brain function and behavior. We studied 20 healthy volunteers in a visual recognition task. Subjects were briefly presented with images of animals (birds or mammals) in natural scenes and were asked to indicate the animal category. MRI-guided stereotaxic single TMS pulses were used to transiently disrupt striate cortex function at different times after image onset (SOA). Visual recognition was significantly impaired when TMS was applied over the occipital pole at SOAs of 100 and 220 msec. The first interval has consistently been described in previous TMS studies and is explained as the interruption of the feedforward volley of activity. Given the late latency and discrete nature of the second peak, we hypothesize that it represents the disruption of a feedback projection to V1, probably from other areas in the visual network. These results provide causal evidence for the necessity of recurrent interactive processing, through feedforward and feedback connections, in visual recognition of natural complex images.

scholarly journals Semantic and Physical Properties of Peripheral Vision Are Used for Scene Categorization in Central Vision

2021 ◽  
Vol 33 (5) ◽  
pp. 799-813
Author(s):  
Carole Peyrin ◽  
Alexia Roux-Sibilon ◽  
Audrey Trouilloud ◽  
Sarah Khazaz ◽  
Malena Joly ◽  
...  
Keyword(s):  
Physical Properties ◽  
Visual Information ◽  
Visual Recognition ◽  
Peripheral Vision ◽  
Spatial Configuration ◽  
Inferior Frontal Gyrus ◽  
Amplitude Spectrum ◽  
Visual Signal ◽  
Central Vision ◽  
Spatial Frequencies

Abstract Theories of visual recognition postulate that our ability to understand our visual environment at a glance is based on the extraction of the gist of the visual scene, a first global and rudimentary visual representation. Gist perception would be based on the rapid analysis of low spatial frequencies in the visual signal and would allow a coarse categorization of the scene. We aimed to study whether the low spatial resolution information available in peripheral vision could modulate the processing of visual information presented in central vision. We combined behavioral measures (Experiments 1 and 2) and fMRI measures (Experiment 2). Participants categorized a scene presented in central vision (artificial vs. natural categories) while ignoring another scene, either semantically congruent or incongruent, presented in peripheral vision. The two scenes could either share the same physical properties (similar amplitude spectrum and spatial configuration) or not. Categorization of the central scene was impaired by a semantically incongruent peripheral scene, in particular when the two scenes were physically similar. This semantic interference effect was associated with increased activation of the inferior frontal gyrus. When the two scenes were semantically congruent, the dissimilarity of their physical properties impaired the categorization of the central scene. This effect was associated with increased activation in occipito-temporal areas. In line with the hypothesis of predictive mechanisms involved in visual recognition, results suggest that semantic and physical properties of the information coming from peripheral vision would be automatically used to generate predictions that guide the processing of signal in central vision.

scholarly journals High spatial frequency information in primes hastens happy faces categorization in autistic adults.

2021 ◽  
Author(s):  
Adeline Lacroix ◽  
Ladislas Nalborczyk ◽  
Frederic Dutheil ◽  
Klara Kovarski ◽  
Sylvie Chokron ◽  
...  
Keyword(s):  
Visual Information ◽  
Critical Role ◽  
High Spatial Frequency ◽  
Decision Time ◽  
Control Group ◽  
Main Hypothesis ◽  
Spatial Frequencies ◽  
Coarse Information ◽  
Autistic Adults ◽  
Emotional Face

Where does the remarkable human ability to quickly identify facial emotion come from? Coarse-to-Fine integration of visual information may play a critical role. Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide inhibition of irrelevant information and facilitate fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging and may contribute to socio-emotional difficulties. It has been suggested that perceptual changes, such as a bias toward HSF or a reduced LSF processing, could partly explain atypical face processing in autism. However, alterations in predictive processes related to LSF have not been investigated so far. Here, we analyzed the data of 27 autistic adults and 34 matched typically developing (TD) controls on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs. LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face stimulus in the context of incongruent information, compared to HSF primes, in the control group but not in the autistic group. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups and irrespective of the congruency. Moreover, whereas the advantage of HSF vs. LSF primes was stronger for angry than happy faces in the control group, it was stronger for happy than angry faces in autistic participants. Additional exploratory analyses using drift diffusion modelling confirmed HSF advantage for achieving the task and showed a longer non-decision time (i.e., encoding and motor response) in autism compared to control. Our main hypothesis of predictive impairments in autism in relation to LSF was not corroborated by our data. However, our analyses suggest specificities in autistic individuals according to the type of emotion processed and in the slower non-decision-related processes.

Effect of sleep on memory for binding different types of visual information

2020 ◽  
Author(s):  
John J Shaw ◽  
Zhisen Urgolites ◽  
Padraic Monaghan
Keyword(s):  
Visual Information ◽  
Storage Capacity ◽  
Declarative Memory ◽  
Recognition Task ◽  
Forced Choice ◽  
Long Term Memory ◽  
Term Memory ◽  
Different Types ◽  
Types Of Information

Visual long-term memory has a large and detailed storage capacity for individual scenes, objects, and actions. However, memory for combinations of actions and scenes is poorer, suggesting difficulty in binding this information together. Sleep can enhance declarative memory of information, but whether sleep can also boost memory for binding information and whether the effect is general across different types of information is not yet known. Experiments 1 to 3 tested effects of sleep on binding actions and scenes, and Experiments 4 and 5 tested binding of objects and scenes. Participants viewed composites and were tested 12-hours later after a delay consisting of sleep (9pm-9am) or wake (9am-9pm), on an alternative forced choice recognition task. For action-scene composites, memory was relatively poor with no significant effect of sleep. For object-scene composites sleep did improve memory. Sleep can promote binding in memory, depending on the type of information to be combined.

STIMULUS COMPLEXITY, EEG ABUNDANCE GRADIENTS, AND DETECTION EFFICIENCY IN A VISUAL RECOGNITION TASK

1975 ◽  
Vol 66 (3) ◽  
pp. 289-298 ◽  
Author(s):  
ANTHONY GALE ◽  
GRAHAM SPRATT ◽  
BRUCE CHRISTIE ◽  
ADRIAN SMALLBONE
Keyword(s):  
Visual Recognition ◽  
Detection Efficiency ◽  
Recognition Task ◽  
Stimulus Complexity

scholarly journals Predictive coding of action intentions in dorsal and ventral visual stream is based on visual anticipations, memory-based information and motor preparation

2018 ◽  
Author(s):  
Simona Monaco ◽  
Giulia Malfatti ◽  
Alessandro Zendron ◽  
Elisa Pellencin ◽  
Luca Turella
Keyword(s):  
Visual Information ◽  
Visual Memory ◽  
Visual Recognition ◽  
Predictive Coding ◽  
Action Planning ◽  
Neural Signals ◽  
Motor Representation ◽  
Visual Stream ◽  
Ventral Visual Stream ◽  
Action Intention

AbstractPredictions of upcoming movements are based on several types of neural signals that span the visual, somatosensory, motor and cognitive system. Thus far, pre-movement signals have been investigated while participants viewed the object to be acted upon. Here, we studied the contribution of information other than vision to the classification of preparatory signals for action, even in absence of online visual information. We used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) to test whether the neural signals evoked by visual, memory-based and somato-motor information can be reliably used to predict upcoming actions in areas of the dorsal and ventral visual stream during the preparatory phase preceding the action, while participants were lying still. Nineteen human participants (nine women) performed one of two actions towards an object with their eyes open or closed. Despite the well-known role of ventral stream areas in visual recognition tasks and the specialization of dorsal stream areas in somato-motor processes, we decoded action intention in areas of both streams based on visual, memory-based and somato-motor signals. Interestingly, we could reliably decode action intention in absence of visual information based on neural activity evoked when visual information was available, and vice-versa. Our results show a similar visual, memory and somato-motor representation of action planning in dorsal and ventral visual stream areas that allows predicting action intention across domains, regardless of the availability of visual information.

scholarly journals The Binding Ring Illusion: assimilation affects the perceived size of a circular array

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 58 ◽  
Author(s):  
J Daniel McCarthy ◽  
Colin Kupitz ◽  
Gideon P Caplovitz
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Circular Array ◽  
Multiple Sources ◽  
Spatial Frequencies ◽  
Constructive Process ◽  
Novel Variant ◽  
Assimilation Process ◽  
Circular Contour ◽  
High Level

Our perception of an object’s size arises from the integration of multiple sources of visual information including retinal size, perceived distance and its size relative to other objects in the visual field. This constructive process is revealed through a number of classic size illusions such as the Delboeuf Illusion, the Ebbinghaus Illusion and others illustrating size constancy. Here we present a novel variant of the Delbouef and Ebbinghaus size illusions that we have named the Binding Ring Illusion. The illusion is such that the perceived size of a circular array of elements is underestimated when superimposed by a circular contour – a binding ring – and overestimated when the binding ring slightly exceeds the overall size of the array. Here we characterize the stimulus conditions that lead to the illusion, and the perceptual principles that underlie it. Our findings indicate that the perceived size of an array is susceptible to the assimilation of an explicitly defined superimposed contour. Our results also indicate that the assimilation process takes place at a relatively high level in the visual processing stream, after different spatial frequencies have been integrated and global shape has been constructed. We hypothesize that the Binding Ring Illusion arises due to the fact that the size of an array of elements is not explicitly defined and therefore can be influenced (through a process of assimilation) by the presence of a superimposed object that does have an explicit size.

scholarly journals Refixation Patterns of Mind-wandering during Real-world Scene Perception

2020 ◽  
Author(s):  
Han Zhang ◽  
Nicola C Anderson ◽  
Kevin Miller
Keyword(s):  
Eye Movements ◽  
Cognitive Processing ◽  
Real World ◽  
Visual Processing ◽  
Visual Information ◽  
Scene Perception ◽  
Mind Wandering ◽  
Quantification Analysis ◽  
The Difference ◽  
Thought Probes

Recent studies have shown that mind-wandering (MW) is associated with changes in eye movement parameters, but have not explored how MW affects the sequential pattern of eye movements involved in making sense of complex visual information. Eye movements naturally unfold over time and this process may reveal novel information about cognitive processing during MW. The current study used Recurrence Quantification Analysis (Anderson, Bischof, Laidlaw, Risko, & Kingstone, 2013) to describe the pattern of refixations (fixations directed to previously-inspected regions) during MW. Participants completed a real-world scene encoding task and responded to thought probes assessing intentional and unintentional MW. Both types of MW were associated with worse memory of the scenes. Importantly, RQA showed that scanpaths during unintentional MW were more repetitive than during on-task episodes, as indicated by a higher recurrence rate and more stereotypical fixation sequences. This increased repetitiveness suggests an adaptive response to processing failures through re-examining previous locations. Moreover, this increased repetitiveness contributed to fixations focusing on a smaller spatial scale of the stimuli. Finally, we were also able to validate several traditional measures: both intentional and unintentional MW were associated with fewer and longer fixations; Eye-blinking increased numerically during both types of MW but the difference was only significant for unintentional MW. Overall, the results advanced our understanding of how visual processing is affected during MW by highlighting the sequential aspect of eye movements.

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