Representational dynamics of object recognition: Feedforward and feedback information flows

Goddard, Erin; Carlson, Thomas A.; Dermody, Nadene; Woolgar, Alexandra

doi:10.1016/j.neuroimage.2016.01.006

Cited by 77 publications

(137 citation statements)

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“…We found that information flow was initially dominated by feedforward propagation of information from occipital to frontal lobe, then later dominated by information flowing in the opposite direction, with information coding in the frontal ROI predicting subsequent information coding in occipital cortex (see also, [51,63]). Moreover, the onset of feedback dominating the flow of information between frontal and occipital cortex corresponded to the time at which the occipital lobes showed a divergence between task-relevant and task-irrelevant information.…”

Section: What Regions Drive the E↵ects Of Attention On The Occipital mentioning

confidence: 82%

“…To characterize the exchange of stimulus-related information between the occipital and frontal ROIs we used an information flow analysis [51]. Since we have fine temporal resolution measures of each pairwise classification, in each attention condition, we used the pattern of classification performance across these measures as a 'fingerprint' for the neural stimulus representation, and tested for evidence of Granger causal interactions between the ROIs (see Methods for details).…”

Section: Frontal Influence On the Occipital Representation Of Object mentioning

confidence: 99%

“…following the rationale we developed in earlier work [51]. Specifically, we tested for Granger causal relationships between the patterns of classifier performance based on the occipital and frontal datasets.…”

Section: Information Flowsmentioning

confidence: 99%

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Spatial and feature-selective attention have distinct effects on population-level tuning

Goddard

Woolgar

2019

Preprint

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1Selective attention is fundamental to cognitive activity and can be deployed in 2 different ways. Non-human primate data suggests that spatial and feature-based 3 visual attention have qualitatively different effects on neural tuning, but this has 4 been challenging to assess in humans. Using multivariate decoding of MEG data, 5we tracked the effects of spatial and feature-selective attention on population-level 6 coding of novel objects. We found that spatial and feature-selective attention 7 interacted multiplicatively to enhance object representation. Moreover, the two 8 types of attention induced qualitatively different patterns of enhancement in 9 occipital cortex, and these differences were accounted for by the principles of 10 response-gain and tuning curve sharpening derived from single-unit work. A novel 11 information flow analysis further showed that stimulus representations in occipital 12 cortex were Granger-caused by coding in frontal cortices earlier in time. We find 13 that human spatial and feature-selective attention rely on qualitatively different, 14interacting, neural mechanisms. 15At any moment, there is far more information available from our senses than we can 16 possibly process at once. Accordingly, only a subset of the available information is 17 processed to a high level, making it crucial that brain can dynamically devote greatest 18 processing resources to the most relevant information. Our ability to selectively attend 19 to relevant information is remarkably flexible. For instance, we can adapt our 20 attentional state by directing our attention in space (spatial attention, e.g. attend left), 21 to a specific feature dimension (feature-selective attention, e.g. detect changes in color 22 across a scene) or based on a particular feature value along that feature dimension 23 (feature-based attention, e.g. find all the red objects), using the definitions of Chen et 24 al. (2012). Each of these types of attention can change behavior, improving 25 performance related to the attended location or feature-dimension, while decreasing 26 performance on the ignored dimension/location (Pestilli and Carrasco, 2005; Rossi and

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Section: What Regions Drive the E↵ects Of Attention On The Occipital mentioning

confidence: 82%

Section: Frontal Influence On the Occipital Representation Of Object mentioning

confidence: 99%

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Spatial and feature-selective attention have distinct effects on population-level tuning

Goddard

Woolgar

2019

Preprint

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“…In object detection, which refers to the recognition of a target/cued object among a set of simultaneously or sequentially presented objects, the target-related information has been previously shown to exert its effect on object-selective cortical areas such as the lateral occipital cortex (LOC;Kaiser et al, 2016;Soon et al, 2013;Stokes et al, 2009) and anterior inferior temporal cortex (Bansal et al, 2014), prior to (Soon et al, 2013;Battistoni et al, 2017;Milton and Pleydell-Pearce, 2016) and during (Kaiser et al, 2016;Goddard et al, 2016) the presentation of the object. A magnetoencephalography (MEG) study showed that the presence of target object in a scene could be significantly decoded as early as 160 ms post-stimulus whereas the decoding of non-target stimuli could not provide significant results until after 200 ms post-stimulus (Kaiser et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Fortunately, however, the recently-developed causality-based method of multi-variate representational similarity analysis (RSA; Goddard et al, 2016), when combined with the temporally high-resolution electroencephalography (EEG) and MEG, can allow the evaluation of target-related information flow across different brain regions. As a support for the performance of the method, a recent study, which first proposed this method, used it to reappraise the results reported by Bar et al (2006) about the above-mentioned parallel visual processing pathways, and observed a totally different temporal dynamics of information flow across the frontal and visual brain areas (Goddard et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis of Category and Target-related Information Processing in the Brain during Object Detection

Karimi-Rouzbahani

Vahab

Ebrahimpour

et al. 2018

Preprint

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to recognize a target object, brain implements strategies which involved a combination of externally sensory-driven and internally task-driven mechanisms. While previous studies have suggested the role of frontal brain areas in sending task-related information to visual cortices, especially the lateral-occipital cortex, they failed to provide quantitative evidence supporting the transaction of taskrelated information between those areas. However, recently developed representational Granger causality analysis, could allow us to track the movement of any desired information in the brain. Therefore, we designed an EEG object detection experiment and evaluated the spatiotemporal dynamics of category-and target-related information transaction across the brain using the mentioned method. Results showed that prefrontal area was the first region to process the target-related information, even before the appearance of the stimulus. This information was transferred to posterior brain areas during the stimulus presentation probably to facilitate object recognition and to direct the decision-making procedure. We also observed that, as compared to category-related information, the target-related information could predict the behavioral detection outcomes more precisely, suggesting the dominant representation of the internal compared to external information. These results provided new insights into the role of prefrontal cortex and the representation of task in the brain during object detection.

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Visual Object Recognition

Behrmann

Vida

2018

Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience

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Humans have the remarkable ability to encode and remember thousands of familiar objects in great detail, and yet the psychological and neural mechanisms that contribute to this facility remain elusive. This review considers the recent progress made on this topic, with consideration given to the data gleaned from a host of relevant methodologies. The results of psychophysical and neuroimaging investigations are considered alongside findings that examine object recognition in individuals with deficits in this domain. We also consider the emergence of object recognition skills through behavioral and imaging studies with children. Theoretical accounts and new techniques, including representational (dis)similarity analysis and deep convolution networks, are also considered. As is often the case in such reviews, more questions are raised than answers provided, and the comprehensive understanding of the mechanisms giving rise to visual object recognition remains an alluring challenge to cognitive science.

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Representational dynamics of object recognition: Feedforward and feedback information flows

Cited by 77 publications

References 37 publications

Spatial and feature-selective attention have distinct effects on population-level tuning

Spatial and feature-selective attention have distinct effects on population-level tuning

Spatiotemporal Analysis of Category and Target-related Information Processing in the Brain during Object Detection

Visual Object Recognition

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