title: A method for real-time visual stimulus selection in the study of cortical object perception.
abstract: The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit's image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across pre-determined 1cm(3) rain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds et al., 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) real-time estimation of cortical responses to stimuli is reasonably consistent; 3) search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond.
authors.affiliation: Fordham University, Computer and Information Science Department, Bronx, New York, USA; Carnegie Mellon University, Center for the Neural Basis of Cognition, Pittsburgh, PA, USA. Electronic address: dleeds@fordham.edu.
authors.forename: Daniel D
authors.initials: DD
authors.lastname: Leeds
authors.affiliation: Carnegie Mellon University, Psychology Department, Pittsburgh, PA, USA; Carnegie Mellon University, Center for the Neural Basis of Cognition, Pittsburgh, PA, USA. Electronic address: michaeltarr@cmu.edu.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Tarr
mesh_terms: D001676:Biofeedback, Psychology / Q000379:methods* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D003199:Computer Systems; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface; D014793:Visual Cortex / Q000502:physiology*; D055815:Young Adult
keywords: Computational modeling; Functional magnetic resonance imaging; Object recognition; Real-time signal processing; Real-time stimulus selection