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Federmeier, K. D.

Publications and source records attributed to Federmeier, K. D..

4 recordsLinked to original sources

Parallel and dynamic attention allocation during natural reading

During natural reading, attention constantly shifts across words, yet how linguistic properties (e.g., lexical frequency) impact the allocation of attention remains unclear. In this study, we co-registered MEG data and eye movements while participants read one-line sentences containing target words of either low or high lexical frequency. Using rapid invisible frequency tagging (RIFT), we simultaneously tracked attention to target and post-target words by flickering them at different frequencies. First, we provide neural evidence that attention was allocated simultaneously to both foveal target and parafoveal post-target words. Second, we found an early parafoveal lexical effect, whereby lower frequency targets demanded more attention prior to fixation, and, additionally, a foveal load effect whereby lower frequency targets reduced the amount of attention allocated to post-targets. Furthermore, flexibility in attention shifts between foveal and parafoveal processing correlated with individual reading speed. These results suggest attention is distributed across multiple words and is flexibly adjusted during reading.

neuroscience↗

Parafoveal semantic integration in natural reading

Humans can read and comprehend text rapidly, implying that readers might process multiple words per fixation. However, the extent to which parafoveal words are previewed and integrated into the evolving sentence context remains disputed. We investigated parafoveal processing during natural reading by recording brain activity and eye movements using MEG and an eye tracker while participants silently read one-line sentences. The sentences contained an unpredictable target word that was either congruent or incongruent with the sentence context. To measure parafoveal processing, we flickered the target words at 60 Hz and measured the resulting brain responses (i.e., Rapid Invisible Frequency Tagging, RIFT) during fixations on the pre-target words. Our results revealed a significantly weaker tagging response for target words that were incongruent with the previous context compared to congruent ones, even within 100 ms of fixating the word immediately preceding the target. This reduction in the RIFT response was also found to be predictive of individual reading speed. We conclude that semantic information is not only extracted from the parafovea but can also be integrated with the previous context before the word is fixated. This early and extensive parafoveal processing supports the rapid word processing required for natural reading. Our study suggests that theoretical frameworks of natural reading should incorporate the concept of deep parafoveal processing.

neuroscience↗

The N300: An Index For Predictive Coding Of Complex Visual Objects and Scenes

Predictive coding models can simulate known perceptual or neuronal phenomena, but there have been fewer attempts to identify a reliable neural signature of predictive coding for complex stimuli. In a pair of studies, we test whether the N300 component of the event-related potential, occurring 250-350 ms post-stimulus-onset, has the response properties expected for such a signature of perceptual hypothesis testing at the level of whole objects and scenes. We show that N300 amplitudes are smaller to representative ("good exemplars") compared to less representative ("bad exemplars") items from natural scene categories. Integrating these results with patterns observed for objects, we establish that, across a variety of visual stimuli, the N300 is responsive to statistical regularity, or the degree to which the input is "expected" (either explicitly or implicitly) based on prior knowledge, with statistically regular images evoking a reduced response. Moreover, we show that the measure exhibits context-dependency; that is, we find the N300 sensitivity to category representativeness when stimuli are congruent with, but not when they are incongruent with, a category pre-cue. Thus, we argue that the N300 is the best candidate to date for an index of perceptual hypotheses testing for complex visual objects and scenes.

neuroscience↗

Representational pattern similarity of electrical brain activity reveals rapid and specific prediction during language comprehension

Predicting upcoming stimuli and events is a critical function of the brain, and understanding the mechanisms of prediction has thus become a central topic in neuroscientific research. Language provides a fertile testing ground for examining predictive mechanisms, as comprehenders use context to predict different features of upcoming words. Although there is a substantive body of research on prediction in language, many aspects of the mechanisms of prediction remain elusive, in part due to a lack of methodological tools to probe prediction formation in the moment. To elucidate what features are neurally pre-activated and when, we used representational similarity analysis (RSA) on data from a sentence reading task (Federmeier et al., 2007). We compared EEG activity patterns elicited by expected and unexpected sentence final words to patterns from the preceding words of the sentence, in both strongly and weakly constraining sentences. Pattern similarity with the final word was increased in an early time window (suggestive of visual feature activation) following the presentation of the pre-final word, and this increase was modulated by both expectancy and constraint (greatest for strongly constrained expected words). This was not seen at earlier words, suggesting that predictions are precisely timed. Additionally, pre-final word activity - the predicted representation - had negative similarity with later final word activity, but only for strongly expected words. Together, these findings shed light on the mechanisms of prediction in the brain: features of upcoming stimuli are rapidly pre-activated following related cues, but the predicted information may receive reduced subsequent processing upon confirmation.

neuroscience↗