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Effective knowledge communication presupposes common ground (Clark & Brennan, 1991) that needs to be established and maintained. This is particularly difficult in remote communication as well as in non-interactive settings, because the speaker cannot use gestures or mimic and has to tailor his utterances to the addressee without receiving feedback. In these situations, the speaker may achieve mutual understanding for example by adopting the addressee’s perspective. We present a study conducted to test the impact of instructions that support and hinder individual problem solving and knowledge communication. We used a picture-sorting task requiring individual cognitive processes of feature search (Treisman & Gelade, 1980) in addition to referential communication. As our study focused on the design of utterances, all participants assumed the role of speaker. Participants were told that their descriptions would be recorded and then listened to later on by a participant in the role of addressee. Eight sets of pictures were used, which varied on two dimensions: the individual cognitive demands of detecting the relevant features (varied as between-subject factor) and the communicative demands (varied as within-subject factor). A further between-subject factor was the type of instructions: The participants received either a collaboration script as supporting instructions, or time pressure was applied to induce stress, or else they were given no additional instructions (control group). We used the speakers’ verbal utterances to examine the quality of the speakers’ descriptions. For both dimensions of difficulty, we found the expected effects. In the conditions with a collaboration script, there were fewer irrelevant features mentioned and fewer features were described with delay. In the conditions with time pressure, there were fewer irrelevant features described, but the number of correctly described pictures was impaired through the fact that relevant features were also neglected. Under time pressure, speakers tended to provide ambiguous descriptions regarding the frame of reference.
We propose a framework of individual problem-solving and communicative demands (IproCo) that bridges the gap between models from cognitive psychology and communication pragmatics. Furthermore, we present two experiments conducted to identify factors influencing the demands and to test possibilities for support. The experiments employed a remote collaborative picture-sorting task with concrete and abstract pictures and applied non-interactive conditions compared to interactive conditions. In a first experiment, the influence of the postulated demands on collaboration process and outcome was analysed, and the impact of shared applications was tested. In a second experiment, we evaluated instructional support measures consisting of model collaboration and a collaboration script. The collaboration process showed benefits of the support but the outcome did not. However, the support measures fostered the collaboration process even in the particularly difficult conditions with non-interactive communication. We discuss the impact of the IproCo framework and apply it to other tasks.
Metacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We aimed at identifying the brain systems that underlie the developmental emergence of this ability in a preschool sample.
Twenty-four children aged between five and six years answered questions under three conditions of a meta-ignorance task twice. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box behind a screen, out of sight from the child. The experimenter then asked the child whether or not she knew which toy was in the box.
Children who answered correctly both times to the metacognitive question in the partial knowledge condition (n=9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n=15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.
This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.
Precise slow oscillation-spindle coupling promotes memory consolidation in younger and older adults
(2018)
Memory consolidation during sleep relies on the precisely timed interaction of rhythmic neural events. Here, we investigate differences in slow oscillations (SO) and sleep spindles (SP) and their coupling across the adult human lifespan and ask whether observed alterations relate to the ability to retain associative memories across sleep. We demonstrate that the fine-tuned SO–SP coupling that is present in younger adults diffuses with advanced age and shifts both in time and frequency. Crucially, we show that the tight precision of SO–SP coupling promotes memory consolidation in younger and older adults, and that brain integrity in source regions for the generation of SOs and SPs reinforces this beneficial SO–SP coupling in old age. Our results reveal age-related differences in SO–SP coupling in healthy elderly individuals. Furthermore, they broaden our understanding of the conditions and the functional significance of SO–SP coupling across the entire adult lifespan.
The outstanding speed of language comprehension necessitates a highly efficient implementation of cognitive-linguistic processes. The domain-general theory of Predictive Coding suggests that our brain solves this problem by continuously forming linguistic predictions about expected upcoming input. The neurophysiological implementation of these predictive linguistic processes, however, is not yet understood. Here, we use EEG (human participants, both sexes) to investigate the existence and nature of online-generated, category-level semantic representations during sentence processing. We conducted two experiments in which some nouns – embedded in a predictive spoken sentence context – were unexpectedly delayed by 1 second. Target nouns were either abstract/concrete (Experiment 1) or animate/inanimate (Experiment 2). We hypothesized that if neural prediction error signals following (temporary) omissions carry specific information about the stimulus, the semantic category of the upcoming target word is encoded in brain activity prior to its presentation. Using time-generalized multivariate pattern analysis, we demonstrate significant decoding of word category from silent periods directly preceding the target word, in both experiments. This provides direct evidence for predictive coding during sentence processing, i.e., that information about a word can be encoded in brain activity before it is perceived. While the same semantic contrast could also be decoded from EEG activity elicited by isolated words (Experiment 1), the identified neural patterns did not generalize to pre-stimulus delay period activity in sentences. Our results not only indicate that the brain processes language predictively, but also demonstrate the nature and sentence-specificity of category-level semantic predictions preactivated during sentence comprehension.
We tested 6–7-year-olds, 18–22-year-olds, and 67–74-year-olds on an associative memory task that consisted of knowledge-congruent and knowledge-incongruent object–scene pairs that were highly familiar to all age groups. We compared the three age groups on their memory congruency effect (i.e., better memory for knowledge-congruent associations) and on a schema bias score, which measures the participants’ tendency to commit knowledge-congruent memory errors. We found that prior knowledge similarly benefited memory for items encoded in a congruent context in all age groups. However, for associative memory, older adults and, to a lesser extent, children overrelied on their prior knowledge, as indicated by both an enhanced congruency effect and schema bias. Functional Magnetic Resonance Imaging (fMRI) performed during memory encoding revealed an age-independent memory x congruency interaction in the ventromedial prefrontal cortex (vmPFC). Furthermore, the magnitude of vmPFC recruitment correlated positively with the schema bias. These findings suggest that older adults are most prone to rely on their prior knowledge for episodic memory decisions, but that children can also rely heavily on prior knowledge that they are well acquainted with. Furthermore, the fMRI results suggest that the vmPFC plays a key role in the assimilation of new information into existing knowledge structures across the entire lifespan. vmPFC recruitment leads to better memory for knowledge-congruent information but also to a heightened susceptibility to commit knowledge-congruent memory errors, in particular in children and older adults.
We studied oscillatory mechanisms of memory formation in 48 younger and 51 older adults in an intentional associative memory task with cued recall. While older adults showed lower memory performance than young adults, we found subsequent memory effects (SME) in alpha/beta and theta frequency bands in both age groups. Using logistic mixed effect models, we investigated whether interindividual differences in structural integrity of key memory regions could account for interindividual differences in the strength of the SME. Structural integrity of inferior frontal gyrus (IFG) and hippocampus was reduced in older adults. SME in the alpha/beta band were modulated by the cortical thickness of IFG, in line with its hypothesized role for deep semantic elaboration. Importantly, this structure–function relationship did not differ by age group. However, older adults were more frequently represented among the participants with low cortical thickness and consequently weaker SME in the alpha band. Thus, our results suggest that differences in the structural integrity of the IFG contribute not only to interindividual, but also to age differences in memory formation.
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scientists argue for vectorial representations of concepts, where the meaning of a word is represented as its position in a high-dimensional neural state space. At the intersection of natural language processing and artificial intelligence, a class of very successful distributional word vector models has developed that can account for classic EEG findings of language, i.e., the ease vs. difficulty of integrating a word with its sentence context. However, models of semantics have to account not only for context-based word processing, but should also describe how word meaning is represented. Here, we investigate whether distributional vector representations of word meaning can model brain activity induced by words presented without context. Using EEG activity (event-related brain potentials) collected while participants in two experiments (English, German) read isolated words, we encode and decode word vectors taken from the family of prediction-based word2vec algorithms. We find that, first, the position of a word in vector space allows the prediction of the pattern of corresponding neural activity over time, in particular during a time window of 300 to 500 ms after word onset. Second, distributional models perform better than a human-created taxonomic baseline model (WordNet), and this holds for several distinct vector-based models. Third, multiple latent semantic dimensions of word meaning can be decoded from brain activity. Combined, these results suggest that empiricist, prediction-based vectorial representations of meaning are a viable candidate for the representational architecture of human semantic knowledge.
Successful consolidation of associative memories relies on the coordinated interplay of slow oscillations and sleep spindles during non-rapid eye movement (NREM) sleep, enabling the transfer of labile information from the hippocampus to permanent memory stores in the neocortex. During senescence, the decline of the structural and functional integrity of the hippocampus and neocortical regions is paralleled by changes of the physiological events that stabilize and enhance associative memories during NREM sleep. However, the currently available evidence is inconclusive if and under which circumstances aging impacts memory consolidation. By tracing the encoding quality of single memories in individual participants, we demonstrate that previous learning determines the extent of age-related impairments in memory consolidation. Specifically, the detrimental effects of aging on memory maintenance were greatest for mnemonic contents of medium encoding quality, whereas memory gain of weakly encoded memories did not differ by age. Using multivariate techniques, we identified profiles of alterations in sleep physiology and brain structure characteristic for increasing age. Importantly, while both ‘aged’ sleep and ‘aged’ brain structure profiles were associated with reduced memory maintenance, inter-individual differences in neither sleep nor structural brain integrity qualified as the driving force behind age differences in sleep-dependent consolidation in the present study.
Word familiarity and predictive context facilitate visual word processing, leading to faster recognition times and reduced neuronal responses. Previously, models with and without top-down connections, including lexical-semantic, pre-lexical (e.g., orthographic/ phonological), and visual processing levels were successful in accounting for these facilitation effects. Here we systematically assessed context-based facilitation with a repetition priming task and explicitly dissociated pre-lexical and lexical processing levels using a pseudoword familiarization procedure. Experiment 1 investigated the temporal dynamics of neuronal facilitation effects with magnetoencephalography (MEG; N=38 human participants) while Experiment 2 assessed behavioral facilitation effects (N=24 human participants). Across all stimulus conditions, MEG demonstrated context-based facilitation across multiple time windows starting at 100 ms, in occipital brain areas. This finding indicates context based-facilitation at an early visual processing level. In both experiments, we furthermore found an interaction of context and lexical familiarity, such that stimuli with associated meaning showed the strongest context-dependent facilitation in brain activation and behavior. Using MEG, this facilitation effect could be localized to the left anterior temporal lobe at around 400 ms, indicating within-level (i.e., exclusively lexical-semantic) facilitation but no top-down effects on earlier processing stages. Increased pre-lexical familiarity (in pseudowords familiarized utilizing training) did not enhance or reduce context effects significantly. We conclude that context based-facilitation is achieved within visual and lexical processing levels. Finally, by testing alternative hypotheses derived from mechanistic accounts of repetition suppression, we suggest that the facilitatory context effects found here are implemented using a predictive coding mechanism.