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Hodapp, A.

Publications and source records attributed to Hodapp, A..

2 recordsLinked to original sources

The N400 ERP component reflects a learning signal during language comprehension

The functional significance of the N400 ERP component is still actively debated. Based on neural network modeling it was recently proposed that the N400 component can be interpreted as the change in a probabilistic representation corresponding to an internal temporal-difference prediction error at the level of meaning that drives adaptation in language processing. These computational modeling results imply that increased N400 amplitudes should correspond to greater adaptation. To investigate this model derived hypothesis, the current study manipulated expectancy in a sentence reading task, which influenced N400 amplitudes, and critically also later implicit memory for the manipulated word: reaction times in a perceptual identification task were significantly faster for previously unexpected words. Additionally, it could be demonstrated that this adaptation seems to specifically depend on the process underlying N400 amplitudes, as participants with larger N400 differences also exhibited a larger implicit memory benefit. These findings support the interpretation of the N400 as an implicit learning signal in language processing.

neuroscience↗

Opposing signatures of neural excitability and sensory input in initial cortical responses differentially predict intensity perception

Perception of sensory information is determined by stimulus features (e.g., intensity) and instantaneous neural states (e.g., excitability). Commonly, it is assumed that both are reflected similarly in evoked brain potentials, that is, higher evoked activity leads to a stronger percept of a stimulus. We tested this assumption in a somatosensory discrimination task in humans, simultaneously assessing (i) single-trial excitatory post-synaptic currents inferred from short-latency somatosensory evoked potentials (SEP), (ii) pre-stimulus alpha oscillations (8-13 Hz), and (iii) peripheral nerve measures. Fluctuations of neural excitability shaped the perceived stimulus intensity already during the very first cortical response (at [~]20 ms) yet demonstrating opposite neural signatures as compared to the effect of presented stimulus intensity. We reconcile this discrepancy via a common framework based on modulations of electro-chemical membrane gradients linking neural states and responses, which calls for reconsidering conventional interpretations of brain potential magnitudes in stimulus intensity encoding.

neuroscience↗