scholarly journals Multimodal Computational Modeling of Visual Object Recognition Deficits but Intact Repetition Priming in Schizophrenia

2020 ◽  
Vol 11 ◽  
Author(s):  
Pejman Sehatpour ◽  
Anahita Bassir Nia ◽  
Devin Adair ◽  
Zhishun Wang ◽  
Heloise M. DeBaun ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Hippocampal Formation ◽  
Critical Role ◽  
Sensory Information ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Visual Stream ◽  
Lateral Occipital Complex ◽  
Line Drawings ◽  
Perceptual Closure

The term perceptual closure refers to the neural processes responsible for “filling-in” missing information in the visual image under highly adverse viewing conditions such as fog or camouflage. Here we used a closure task that required the participants to identify barely recognizable fragmented line-drawings of common objects. Patients with schizophrenia have been shown to perform poorly on this task. Following priming, controls and importantly patients can complete the line-drawings at greater levels of fragmentation behaviorally, suggesting an improvement in their ability to perform the task. Closure phenomena have been shown to involve a distributed network of cortical regions, notably the lateral occipital complex (LOC) of the ventral visual stream, dorsal visual stream (DS), hippocampal formation (HIPP) and the prefrontal cortex (PFC). We have previously demonstrated the failure of closure processes in schizophrenia and shown that the dysregulation in the sensory information transmitted to the prefrontal cortex plays a critical role in this failure. Here, using a multimodal imaging approach in patients, combining event related electrophysiological recordings (ERP) and functional magnetic resonance imaging (fMRI), we characterize the spatiotemporal dynamics of priming in perceptual closure. Using directed functional connectivity measures we demonstrate that priming modifies the network-level interactions between the nodes of closure processing in a manner that is functionally advantageous to patients resulting in the mitigation of their deficit in perceptual closure.

Graded Size Sensitivity of Object-Exemplar–Evoked Activity Patterns Within Human LOC Subregions

2008 ◽  
Vol 100 (4) ◽  
pp. 2038-2047 ◽  
Author(s):  
Evelyn Eger ◽  
Christian A. Kell ◽  
Andreas Kleinschmidt
Keyword(s):  
Sensory Information ◽  
Size Difference ◽  
Support Vector ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Object Identity ◽  
Invariant Representation ◽  
Size Change ◽  
Population Activity ◽  
Lateral Occipital Complex

A central issue for understanding visual object recognition is how the cortical hierarchy represents incoming sensory information and transforms it across successive processing stages. The format of object representation in the human brain has thus far mostly been studied using adaptation paradigms because the neuronal layout of object selectivities was thought to be beyond the resolution of conventional functional MRI (fMRI). Recently, however, multivariate pattern recognition succeeded in discriminating fMRI responses of object-selective cortex to different object exemplars within a given category. Here, we use increased spatial fMRI resolution to explore size sensitivity and tolerance to size change of response patterns evoked by object exemplars across a range of three sizes. Results from Support Vector Classification on responses of the human lateral occipital complex (LOC) show that discrimination of size (for a given object) and discrimination of objects across changes in size depended on the amount of size difference. Even across the largest amount of size change, accuracy for generalization was still significant in LOC, whereas the same comparison was at chance performance in early visual (calcarine) cortex. Analyzing subregions, we further found an anterior-posterior gradient in the degree of size sensitivity and size generalization within the posterior-dorsal and anterior-ventral parts of LOC. These results speak against fully size-invariant representation of object information in human LOC and are hence congruent with findings in monkeys showing object identity and size information in population activity of inferotemporal cortex. Moreover, these results provide evidence for a fine-grained functional heterogeneity within human LOC beyond the commonly used LO/fusiform subdivision.

scholarly journals Fast recurrent processing via ventral prefrontal cortex is needed by the primate ventral stream for robust core visual object recognition

2020 ◽  
Author(s):  
Kohitij Kar ◽  
James J DiCarlo
Keyword(s):  
Prefrontal Cortex ◽  
Object Recognition ◽  
Late Phase ◽  
Ventral Stream ◽  
Neural Population ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Neural Network Models ◽  
Recurrent Processing ◽  
Ventral Prefrontal Cortex

SummaryDistributed neural population spiking patterns in macaque inferior temporal (IT) cortex that support core visual object recognition require additional time to develop for specific (“late-solved”) images suggesting the necessity of recurrent processing in these computations. Which brain circuit motifs are most responsible for computing and transmitting these putative recurrent signals to IT? To test whether the ventral prefrontal cortex (vPFC) is a critical recurrent circuit node in this system, here we pharmacologically inactivated parts of the vPFC and simultaneously measured IT population activity, while monkeys performed object discrimination tasks. Our results show that vPFC inactivation deteriorated the quality of the late-phase (>150 ms from image onset) IT population code, along with commensurate, specific behavioral deficits for “late-solved” images. Finally, silencing vPFC caused the monkeys’ IT activity patterns and behavior to become more like those produced by feedforward artificial neural network models of the ventral stream. Together with prior work, these results argue that fast recurrent processing through the vPFC is critical to the production of behaviorally-sufficient object representations in IT.

Haptic object recognition is influenced by the orientation of the body relative to gravity

2012 ◽  
Vol 25 (0) ◽  
pp. 122
Author(s):  
Michael Barnett-Cowan ◽  
Jody C. Culham ◽  
Jacqueline C. Snow
Keyword(s):  
Object Recognition ◽  
Character Recognition ◽  
Reference Frames ◽  
Sensory Information ◽  
The Body ◽  
Body Orientation ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Leftward Bias ◽  
Haptic Object

The orientation at which objects are most easily recognized — the perceptual upright (PU) — is influenced by body orientation with respect to gravity. To date, the influence of these cues on object recognition has only been measured within the visual system. Here we investigate whether objects explored through touch alone are similarly influenced by body and gravitational information. Using the Oriented CHAracter Recognition Test (OCHART) adapted for haptics, blindfolded right-handed observers indicated whether the symbol ‘p’ presented in various orientations was the letter ‘p’ or ‘d’ following active touch. The average of ‘p-to-d’ and ‘d-to-p’ transitions was taken as the haptic PU. Sensory information was manipulated by positioning observers in different orientations relative to gravity with the head, body, and hand aligned. Results show that haptic object recognition is equally influenced by body and gravitational references frames, but with a constant leftward bias. This leftward bias in the haptic PU resembles leftward biases reported for visual object recognition. The influence of body orientation and gravity on the haptic PU was well predicted by an equally weighted vectorial sum of the directions indicated by these cues. Our results demonstrate that information from different reference frames influence the perceptual upright in haptic object recognition. Taken together with similar investigations in vision, our findings suggest that reliance on body and gravitational frames of reference helps maintain optimal object recognition. Equally relying on body and gravitational information may facilitate haptic exploration with an upright posture, while compensating for poor vestibular sensitivity when tilted.

scholarly journals Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream

2020 ◽  
Author(s):  
Franziska Geiger ◽  
Martin Schrimpf ◽  
Tiago Marques ◽  
James J. DiCarlo
Keyword(s):  
Visual System ◽  
Visual Processing ◽  
Ventral Stream ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Visual Stream ◽  
Ongoing Research ◽  
Ventral Visual Stream ◽  
And Behavior ◽  
The Brain

AbstractAfter training on large datasets, certain deep neural networks are surprisingly good models of the neural mechanisms of adult primate visual object recognition. Nevertheless, these models are poor models of the development of the visual system because they posit millions of sequential, precisely coordinated synaptic updates, each based on a labeled image. While ongoing research is pursuing the use of unsupervised proxies for labels, we here explore a complementary strategy of reducing the required number of supervised synaptic updates to produce an adult-like ventral visual stream (as judged by the match to V1, V2, V4, IT, and behavior). Such models might require less precise machinery and energy expenditure to coordinate these updates and would thus move us closer to viable neuroscientific hypotheses about how the visual system wires itself up. Relative to the current leading model of the adult ventral stream, we here demonstrate that the total number of supervised weight updates can be substantially reduced using three complementary strategies: First, we find that only 2% of supervised updates (epochs and images) are needed to achieve ~80% of the match to adult ventral stream. Second, by improving the random distribution of synaptic connectivity, we find that 54% of the brain match can already be achieved “at birth” (i.e. no training at all). Third, we find that, by training only ~5% of model synapses, we can still achieve nearly 80% of the match to the ventral stream. When these three strategies are applied in combination, we find that these new models achieve ~80% of a fully trained model’s match to the brain, while using two orders of magnitude fewer supervised synaptic updates. These results reflect first steps in modeling not just primate adult visual processing during inference, but also how the ventral visual stream might be “wired up” by evolution (a model’s “birth” state) and by developmental learning (a model’s updates based on visual experience).

scholarly journals A Locus in Human Extrastriate Cortex for Visual Shape Analysis

1997 ◽  
Vol 9 (1) ◽  
pp. 133-142 ◽  
Author(s):  
Nancy Kanwisher ◽  
Roger P. Woods ◽  
Marco Iacoboni ◽  
John C. Mazziotta
Keyword(s):  
Regional Blood Flow ◽  
Extrastriate Cortex ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Line Drawings ◽  
3 Dimensional ◽  
Positron Emission ◽  
Independent Analysis ◽  
The Right ◽  
Visual Shape

Positron emission tomography (PET) was used to locate an area in human extrastriate cortex that subserves a specific component process of visual object recognition. Regional blood flow increased in a bilateral extrastriate area on the inferolateral surface of the brain near the border between the occipital and temporal lobes (and a smaller area in the right fusiform gyms) when subjects viewed line drawings of 3-dimensional objects compared to viewing scrambled drawings with no clear shape interpretation. Responses were Seen for both novel and familiar objects, implicating this area in the bottom-up (i.e., memory-independent) analysis of visual shape.

Developmental Trajectory of Visual Object Recognition Revealed by fMRI

2007 ◽  
Author(s):  
K. Suzanne Scherf ◽  
Marlene Behrmann ◽  
Kate Humphreys ◽  
Beatriz Luna
Keyword(s):  
Object Recognition ◽  
Developmental Trajectory ◽  
Visual Object ◽  
Visual Object Recognition
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