Sarah Laszlo

The N400 as a snapshot of interactive processing: Evidence from regression analyses of orthographic neighbor and lexical associate effects.

Linking print with meaning tends to be divided into subprocesses, such as recognition of an inputs lexical entry and subsequent access of semantics. However, recent results suggest that the set of semantic features activated by an input is broader than implied by a view wherein access serially follows recognition. EEG was collected from participants who viewed items varying in number and frequency of both orthographic neighbors and lexical associates. Regression analysis of single item ERPs replicated past findings, showing that N400 amplitudes are greater for items with more neighbors, and further revealed that N400 amplitudes increase for items with more lexical associates and with higher frequency neighbors or associates. Together, the data suggest that in the N400 time window semantic features of items broadly related to inputs are active, consistent with models in which semantic access takes place in parallel with stimulus recognition.

Chapter 1 Time for Meaning: Electrophysiology Provides Insights into the Dynamics of Representation and Processing in Semantic Memory

Abstract At least since the time of Aristotle, humans have been fascinated with trying to understand how meaning is represented in what, in modern terms, has come to be known as semantic memory. Behavioral science, computational modeling, neuropsychology, hemodynamic imaging, and electrophysiological techniques have all been applied to the task of delineating how semantic memory is instantiated in the brain. As reviewed in this chapter, the collective data from these methods are providing an increasingly detailed picture of the functional and neural organization of semantic memory. What remains less clear are the dynamics of how meaning is accessed and used. Those dynamics, however, are beginning to be revealed by data from temporally sensitive measures, such as electrophysiology. In particular, studies of the N400 event-related potential (ERP) component suggest that considerations of time may hold the key to understanding how information represented in disparate areas of the brain comes to be bound in the structured-yet-flexible manner that is the hallmark of human semantic processing.

Better the DVL You Know Acronyms Reveal the Contribution of Familiarity to Single-Word Reading

Current theories of reading are divided between dual-route accounts, which propose that separable processes subserve word recognition for orthographically regular and irregular strings, and connectionist models, which propose a single mechanism mapping form to meaning. These theories make distinct predictions about the processing of acronyms, which can be orthographically illegal and yet familiar, as compared with the processing of pseudowords, which are regular but unfamiliar. This study examined whether acronyms are processed like pseudowords and words. Event-related potentials (ERPs) were recorded as subjects viewed familiar and unfamiliar acronyms, words, pseudowords, illegal strings, and—as the targets of the substantive behavioral task—proper names. Familiar acronyms elicited repetition effects on the N400 component, a functionally specific index of semantic activation processes; repetition effects for familiar acronyms were similar in magnitude, timing, and scalp distribution to those for words and pseudowords. The similarity of the brain response to familiar-but-illegal and unfamiliar-but-legal classes of stimuli is inconsistent with predictions of dual-route models of reading.

A Neurally Plausible Parallel Distributed Processing Model of Event-Related Potential Word Reading Data

The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between explicit, computational models and physiological data collected during the performance of cognitive tasks, we developed a PDP model of visual word recognition which simulates key results from the ERP reading literature, while simultaneously being able to successfully perform lexical decision-a benchmark task for reading models. Simulations reveal that the models success depends on the implementation of several neurally plausible features in its architecture which are sufficiently domain-general to be relevant to cognitive modeling more generally.

Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics

Abstract The human brain continually generates electrical potentials representing neural communication. These potentials can be measured at the scalp, and constitute the electroencephalogram (EEG). When the EEG is time-locked to stimulation – such as the presentation of a word – and averaged over many such presentations, the Event-Related Potential (ERP) is obtained. The functional characteristics of components of the ERP are well understood, and some components represent processing that may differ uniquely from individual to individual—such as the N400 component, which represents access to the semantic network. We applied several pattern classifiers to ERPs representing the response of individuals to a stream of text designed to be idiosyncratically familiar to different individuals. Results indicate that there are robustly identifiable features of the ERP that enable labeling of ERPs as belonging to individuals with accuracy reliably above chance (in the range of 82–97%). Further, these features are stable over time, as indicated by continued accurate identification of individuals from ERPs after a lag of up to six months. Even better, the high degree of labeling accuracy achieved in all cases was achieved with the use of only 3 electrodes on the scalp—the minimal possible number that can acquire clean data.

Minding the PS, queues, and PXQs: Uniformity of semantic processing across multiple stimulus types

An assumption in the reading literature is that access to semantics is gated by stimulus properties such as orthographic regularity or familiarity. In the electrophysiological domain, this assumption has led to a debate about the features necessary to initiate semantic processing as indexed by the N400 event-related potential (ERP) component. To examine this, we recorded ERPs to sentences with endings that were familiar and legal (words), familiar and illegal (acronyms), or unfamiliar and illegal (consonant or vowel strings). N400 congruency effects (reduced negativity to expected relative to unexpected endings) were observed for words and acronyms; these were identical in size, timing, and scalp distribution. Notably, clear N400 potentials were also elicited by unfamiliar, illegal strings, suggesting that, at least in a verbal context, semantic access may be attempted for any letter string, regardless of familiarity or regularity.

Never seem to find the time: evaluating the physiological time course of visual word recognition with regression analysis of single-item event-related potentials

Visual word recognition is a process that, both hierarchically and in parallel, draws on different types of information ranging from perceptual to orthographic to semantic. A central question concerns when and how these different types of information come online and interact after a word form is initially perceived. Numerous studies addressing aspects of this question have been conducted with a variety of techniques [e.g., behaviour, eye-tracking, event-related potentials (ERPs)], and divergent theoretical models, suggesting different overall speeds of word processing, have coalesced around clusters of mostly method-specific results. Here, we examine the time course of influence of variables ranging from relatively perceptual (e.g., bigram frequency) to relatively semantic (e.g., the number of lexical associates) on ERP responses, analysed at the single-item level. Our results, in combination with a critical review of the literature, suggest methodological, analytic and theoretical factors that may have led to inconsistency in results of past studies; we will argue that consideration of these factors may lead to a reconciliation between divergent views of the speed of word recognition.

The acronym superiority effect.

The visual world is replete with noisy, continuous, perceptually variant linguistic information, which fluent readers rapidly translate from percept to meaning. What are the properties the language comprehension system uses as cues to initiate lexical/semantic access in response to some, but not all, orthographic strings? In the behavioral, electromagnetic, and neuropsychological literatures, orthographic regularity and familiarity have been identified as critical factors. Here, we present a study in the Reicher—Wheeler tradition that manipulates these two properties independently through the use of four stimulus categories: familiar and orthographically regular words, unfamiliar but regular pseudowords, unfamiliar illegal strings, and familiar but orthographically illegal acronyms. We find that, like letters in words and pseudowords, letters in acronyms enjoy an identification benefit relative to similarly illegal, but unfamiliar strings. This supports theories of visual word recognition in which familiarity, rather than orthographic regularity, plays a critical role in gating processing.

Won't get fooled again: An event-related potential study of task and repetition effects on the semantic processing of items without semantics

A growing body of evidence suggests that semantic access is obligatory. Several studies have demonstrated that brain activity associated with semantic processing, measured in the N400 component of the event-related brain potential (ERP), is elicited even by meaningless, orthographically illegal strings, suggesting that semantic access is not gated by lexicality. However, the downstream consequences of that activity vary by item type, exemplified by the typical finding that N400 activity is reduced by repetition for words and pronounceable nonwords but not for illegal strings. We propose that this lack of repetition effect for illegal strings is caused not by lack of contact with semantics, but by the unrefined nature of that contact under conditions in which illegal strings can be readily categorised as task-irrelevant. To test this, we collected ERPs from participants performing a modified Lexical Decision Task, in which the presence of orthographically illegal acronyms rendered meaningless illegal strings more difficult lures than normal. Confirming our hypothesis, under these conditions illegal strings elicited robust N400 repetition effects, quantitatively and qualitatively similar to those elicited by words, pseudowords, and acronyms.

CEREBRE: A Novel Method for Very High Accuracy Event-Related Potential Biometric Identification

The vast majority of existing work on brain biometrics has been conducted on the ongoing electroencephalogram. Here, we argue that the averaged event-related potential (ERP) may provide the potential for more accurate biometric identification, as its elicitation allows for some control over the cognitive state of the user to be obtained through the design of the challenge protocol. We describe the Cognitive Event-RElated Biometric REcognition (CEREBRE) protocol, an ERP biometric protocol designed to elicit individually unique responses from multiple functional brain systems (e.g., the primary visual, facial recognition, and gustatory/appetitive systems). Results indicate that there are multiple configurations of data collected with the CEREBRE protocol that all allow 100% identification accuracy in a pool of 50 users. We take this result as the evidence that ERP biometrics are a feasible method of user identification and worthy of further research.