Visual demand and visual field presentation influence natural scene processing

BackgroundBottom-up and top-down processes are involved in visual analysis of scenes. Here we examined the influence of top-down visual demand on natural scene processing.MethodsWe measured accuracy and response time in adults performing two stimuli-equivalent tasks. Unfiltered, low or high spatial frequency (SF) natural scenes were presented in central, left, or right visual fields (CVF, LVF, RVF). The tasks differed only by the instructed visual demand. In the detection task, participants had to decide whether a scene was present or not. In the categorization task, they had to decide whether the scene was a city or a forest.ResultsHigher accuracy was seen for the LVF in the detection task, but for categorization, greater accuracy was seen for the RVF. The interaction between Task and SF revealed coarse-to-fine processing in the categorization task for both accuracy and reaction time, which nearly disappeared in the detection task. Considering the interaction of Task, VF and SF, a left-hemisphere specialisation (i.e., RVF advantage) was observed for the categorisation of HSF scenes for accuracy alone, whereas a LVF advantage was seen for all SFs in the detection task for both accuracy and reaction time.ConclusionOur results revealed that the nature of top-down visual demand is essential to understanding how visual analysis is achieved in each hemisphere. Moreover, this study examining the effects of visual demand, visual field presentation, and SF content of stimuli through the use of ecological stimuli provides a tool to enrich the clinical examination of visual and neurovisual patients.

[1]  Zoï Kapoula,et al.  Saccades during symmetrical vergence , 2008, Graefe's Archive for Clinical and Experimental Ophthalmology.

[2]  Ian H. Robertson,et al.  Unilateral Neglect: Clinical and Experimental Studies edited by Ian H. Robertson and John C. Marshall , 1994 .

[3]  K. Heilman,et al.  Neglect and Related Disorders , 1984, Seminars in neurology.

[4]  Carole Peyrin,et al.  Hemispheric specialization for spatial frequency processing in the analysis of natural scenes , 2003, Brain and Cognition.

[5]  R. V. Abadi,et al.  Saccadic instabilities and voluntary saccadic behaviour , 2005, Experimental Brain Research.

[6]  Aikaterini Gari,et al.  Quod Erat Demonstrandum: From Herodotus’ ethnographic journeys to cross-cultural research , 2009 .

[7]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[8]  S. Thorpe,et al.  Rapid categorization of foveal and extrafoveal natural images: Associated ERPs and effects of lateralization , 2005, Brain and Cognition.

[9]  S. Siegel,et al.  Nonparametric Statistics for the Behavioral Sciences , 2022, The SAGE Encyclopedia of Research Design.

[10]  S. Bookheimer.  Functional MRI of language: new approaches to understanding the cortical organization of semantic processing. , 2002, Annual review of neuroscience.

[11]  F. Craik,et al.  Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[12]  P H Schiller,et al.  Look and see: how the brain moves your eyes about. , 2001, Progress in brain research.

[13]  D. Berson,et al.  Retinal and cortical inputs to cat superior colliculus: composition, convergence and laminar specificity. , 1988, Progress in brain research.

[14]  L. Chalupa,et al.  The visual neurosciences , 2004 .

[15]  Yuko Ohno,et al.  Properties of perimetric threshold estimates from Full Threshold, SITA Standard, and SITA Fast strategies. , 2002, Investigative ophthalmology & visual science.

[16]  D. Navon.  Forest before trees: The precedence of global features in visual perception , 1977, Cognitive Psychology.

[17]  A. Oliva,et al.  From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition , 1994 .

[18]  R. Dolan,et al.  Distinct spatial frequency sensitivities for processing faces and emotional expressions , 2003, Nature Neuroscience.

[19]  K. Heilman,et al.  Pseudoneglect: Effects of hemispace on a tactile line bisection task , 1980, Neuropsychologia.

[20]  D R Badcock,et al.  Low-Frequency Filtering and the Processing of Local—Global Stimuli , 1990, Perception.

[21]  A. Torralba,et al.  The role of context in object recognition , 2007, Trends in Cognitive Sciences.

[22]  S. Thorpe,et al.  Speed of processing in the human visual system , 1996, Nature.

[23]  Martial Mermillod,et al.  Effect of temporal constraints on hemispheric asymmetries during spatial frequency processing , 2006, Brain and Cognition.

[24]  B. Fischer,et al.  Dead zone for express saccades , 2004, Experimental Brain Research.

[25]  B. Fischer,et al.  Human express saccades: extremely short reaction times of goal directed eye movements , 2004, Experimental Brain Research.

[26]  Joseph B. Hellige,et al.  Hemispheric differences are found in the identification, but not the detection, of low versus high spatial frequencies , 1990, Perception & psychophysics.

[27]  John H. R. Maunsell,et al.  How parallel are the primate visual pathways? , 1993, Annual review of neuroscience.

[28]  A. Stuart,et al.  Non-Parametric Statistics for the Behavioral Sciences. , 1957 .

[29]  H. Hughes,et al.  Global Precedence, Spatial Frequency Channels, and the Statistics of Natural Images , 1996, Journal of Cognitive Neuroscience.

[30]  B. Fischer,et al.  The analysis of saccadic eye movements from gap and overlap paradigms. , 1997, Brain research. Brain research protocols.

[31]  M. Saslow.  Effects of components of displacement-step stimuli upon latency for saccadic eye movement. , 1967, Journal of the Optical Society of America.

[32]  Hitoshi Honda,et al.  Idiosyncratic left–right asymmetries of saccadic latencies: examination in a gap paradigm , 2002, Vision Research.

[33]  R. C. Oldfield.  The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[34]  J. Bullier.  Integrated model of visual processing , 2001, Brain Research Reviews.

[35]  Kenji Kawano,et al.  Global and fine information coded by single neurons in the temporal visual cortex , 1999, Nature.

[36]  M. Bar.  A Cortical Mechanism for Triggering Top-Down Facilitation in Visual Object Recognition , 2003, Journal of Cognitive Neuroscience.

[37]  Christoph M. Michel,et al.  Hemispheric specialization of human inferior temporal cortex during coarse-to-fine and fine-to-coarse analysis of natural visual scenes , 2005, NeuroImage.

[38]  Nathalie Guyader,et al.  Neural correlates of spatial frequency processing: A neuropsychological approach , 2006, Brain Research.

[39]  Sylvie Chokron,et al.  Paying attention to reading direction , 2008, Nature Reviews Neuroscience.

[40]  Monica Baciu,et al.  Cerebral regions and hemispheric specialization for processing spatial frequencies during natural scene recognition. An event-related fMRI study , 2004, NeuroImage.

[41]  Olivier Gout,et al.  Plasticité des aires visuelles corticales après une lésion rétrochiasmatique : approche en neuro-imagerie , 2009 .

[42]  Stephen Christman,et al.  Visual hemispheric asymmetries depend on which spatial frequencies are task relevant , 1992, Brain and Cognition.

[43]  Sylvie Chokron,et al.  Effects of Reading Direction on Visuospatial Organization: A Critical Review , 2009, Quod Erat Demonstrandum: From Herodotus’ ethnographic journeys to cross-cultural research.

[44]  Paul H Artes,et al.  Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma. , 2005, Investigative ophthalmology & visual science.

[45]  G. Schöner,et al.  Dynamic Field Theory of Movement Preparation , 2022 .

[46]  Carole Peyrin,et al.  Specific impairments in visual processing following lesion side in hemianopic patients , 2010, Cortex.

[47]  A. Oliva,et al.  Coarse Blobs or Fine Edges? Evidence That Information Diagnosticity Changes the Perception of Complex Visual Stimuli , 1997, Cognitive Psychology.

[48]  R. Cabeza.  Hemispheric asymmetry reduction in older adults: the HAROLD model. , 2002, Psychology and aging.