Visual information representation and rapid-scene categorization are simultaneous across cortex: An MEG study

نویسندگان

  • Pavan Ramkumar
  • Bruce C. Hansen
  • Sebastian Pannasch
  • Lester C. Loschky
چکیده

Perceiving the visual world around us requires the brain to represent the features of stimuli and to categorize the stimulus based on these features. Incorrect categorization can result either from errors in visual representation or from errors in processes that lead to categorical choice. To understand the temporal relationship between the neural signatures of such systematic errors, we recorded whole-scalp magnetoencephalography (MEG) data from human subjects performing a rapid-scene categorization task. We built scene category decoders based on (1) spatiotemporally resolved neural activity, (2) spatial envelope (SpEn) image features, and (3) behavioral responses. Using confusion matrices, we tracked how well the pattern of errors from neural decoders could be explained by SpEn decoders and behavioral errors, over time and across cortical areas. Across the visual cortex and the medial temporal lobe, we found that both SpEn and behavioral errors explained unique variance in the errors of neural decoders. Critically, these effects were nearly simultaneous, and most prominent between 100 and 250ms after stimulus onset. Thus, during rapid-scene categorization, neural processes that ultimately result in behavioral categorization are simultaneous and co-localized with neural processes underlying visual information representation.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study

How are visual scenes represented in the brain during categorization? We acquired magnetoencephalography (MEG) data from nine healthy subjects who participated in a rapid natural scene categorization task. Scenes were presented in two different perspectives (aerial vs. terrestrial) and two different orientations (upright vs. inverted). We applied multivariate pattern classification to categoriz...

متن کامل

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or "brain decoding", methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, obje...

متن کامل

Image phase or amplitude? Rapid scene categorization is an amplitude-based process.

Models of the visual cortex are based on image decomposition according to the Fourier spectrum (amplitude and phase). On one hand, it is commonly believed that phase information is necessary to identify a scene. On the other hand, it is known that complex cells of the visual cortex, the most numerous ones, code only the amplitude spectrum. This raises the question of knowing if these cells carr...

متن کامل

To Err Is Human: Correlating Fmri Decoding and Behavioral Errors to Probe the Neural Representation of Natural Scene Categories

New multivariate methods for the analysis of functional magnetic resonance imaging (fMRI) data have enabled us to decode neural representations of visual information with unprecedented fidelity. But how do we know if humans make use of the information that we decode from the fMRI data for their behavioral response? In this chapter we propose a method for correlating the errors from fMRI decodin...

متن کامل

A state-space model of cross-region dynamic connectivity in MEG/EEG

Cross-region dynamic connectivity, which describes the spatio-temporal dependence of neural activity among multiple brain regions of interest (ROIs), can provide important information for understanding cognition. For estimating such connectivity, magnetoencephalography (MEG) and electroencephalography (EEG) are well-suited tools because of their millisecond temporal resolution. However, localiz...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • NeuroImage

دوره 134  شماره 

صفحات  -

تاریخ انتشار 2016