Visual narratives like comics involve a range of complex cognitive operations in order to be understood. The Parallel Interfacing Narrative‐Semantics (PINS) Model integrates an emerging literature showing that comprehension of wordless image sequences balances two representational levels of semantic and narrative structure. The neurocognitive mechanisms that guide these processes are argued to overlap with other domains, such as language and music.

The experienced qualities of memories of factual and fictional events have been little researched previously. The few studies that exist find no or few differences. However, one reason to expect differences in memory qualities is that processing of fact and fiction seem to involve activation of different brain areas. The present study expands earlier research by including a wider range of memory qualities, using positive and negative events, and three time-points: immediately after, after a ten-minute delay and after a five-week (...) delay. Participants (N = 52) read four short stories in English, labelled either fact or fiction, and rated memory qualities on 7-point scales. Results show no differences; however, an interaction was found between fictionality and story emotional valence, in that memories of negative fictional stories are rated as more clear. The higher clarity can be explained by previous findings that negative events from stories are in general remembered in more detail, in combination with the idea that fiction entails simulation to a higher degree than fact. The conclusion is that although a difference in memory qualities between fact and fiction was found in one case, memory qualities seem not to play an operative role when the memory system distinguishes fact from fiction. (shrink)

The regional brain networks and the underlying neurophysiological mechanisms subserving the cognition of visual narrative in humans have largely been studied with non-invasive brain recording. In this study, we specifically investigated how regional and cross-regional cortical activities support visual narrative interpretation using intracranial stereotactic electroencephalograms recordings from thirteen human subjects (6 females, and 7 males). Widely distributed recording sites across the brain were sampled while subjects were explicitly instructed to observe images from fables presented in “sequential” order, and a set (...) of images drawn from multiple fables presented in “scrambled” order. Broadband activity mainly within the frontal and temporal lobes were found to encode if a presented image is part of a visual narrative (sequential) or random image set (scrambled). Moreover, the temporal lobe exhibits strong activation in response to visual narratives while the frontal lobe is more engaged when contextually novel stimuli are presented. We also investigated the dynamics of interregional interactions between visual narratives and contextually novel series of images. Interestingly, the interregional connectivity is also altered between sequential and scrambled sequences. Together, these results suggest that both changes in regional neuronal activity and cross-regional interactions subserve visual narrative and contextual novelty processing. (shrink)

Drawn sequences of images, like those in comics and picture stories, are a pervasive and fundamental way that humans have communicated for millennia. Yet, the study of visual narratives has only recently gained traction in Cognitive Science. Here we explore what has held back the study of the cognition of visual narratives, and why researchers should join in scholarship of this ubiquitous aspect of expression.

Acquiring expertise in a task is often thought of as an automatic process that follows inevitably with practice according to the log‐log law (aka: power law) of learning. However, as Ericsson, Chase, and Faloon (1980) showed, this is not true for digit‐span experts and, as we show, it is certainly not true for Tetris players at any level of expertise. Although some people may simply “twitch” faster than others, the limit to Tetris expertise is not raw keypress time but the (...) techniques acquired by players that allow them to use the tools provided by the hardware and software to compensate for the game's relentlessly increasing drop speed. Unfortunately, these increases in drop speed between Tetris levels make performance plateaus very short and quickly followed by game death. Hence, a player's success at discovering, exploring, and practicing new techniques for the tasks of board preparation, board maintenance, optimal placement discovery, zoid rotation, lateral movement of zoids, and other tasks important to expertise in Tetris is limited. In this paper, we analyze data collected from 492 Tetris players to reveal the challenges they confronted while constructing expertise via the discovery of new techniques for gameplay at increasingly difficult levels of Tetris. (shrink)

Cognitive Science, Volume 46, Issue 5, May 2022.

Acquiring expertise in a task is often thought of as an automatic process that follows inevitably with practice according to the log‐log law (aka: power law) of learning. However, as Ericsson, Chase, and Faloon (1980) showed, this is not true for digit‐span experts and, as we show, it is certainly not true for Tetris players at any level of expertise. Although some people may simply “twitch” faster than others, the limit to Tetris expertise is not raw keypress time but the (...) techniques acquired by players that allow them to use the tools provided by the hardware and software to compensate for the game's relentlessly increasing drop speed. Unfortunately, these increases in drop speed between Tetris levels make performance plateaus very short and quickly followed by game death. Hence, a player's success at discovering, exploring, and practicing new techniques for the tasks of board preparation, board maintenance, optimal placement discovery, zoid rotation, lateral movement of zoids, and other tasks important to expertise in Tetris is limited. In this paper, we analyze data collected from 492 Tetris players to reveal the challenges they confronted while constructing expertise via the discovery of new techniques for gameplay at increasingly difficult levels of Tetris. (shrink)

Categorization is fundamental for spatial and motion representation in both the domain of artificial intelligence and human cognition. In this paper, we investigated whether motion categorizations designed in artificial intelligence can inform human cognition. More concretely, we investigated if such categorizations (also known as qualitative representations) can inform the psychological understanding of human perception and memory of motion scenes. To this end, we took two motion categorizations in artificial intelligence, Motion‐RCC and Motion‐OPRA1, and conducted four experiments on human perception and (...) memory. Participants viewed simple motion scenes and judged the similarity of transformed scenes with this reference scene. Those transformed scenes differed in none, one, or both Motion‐RCC and Motion‐OPRA1 categories. Importantly, we applied an equal absolute metric change to those transformed scenes, so that differences in the similarity judgments should be due only to differing categories. In Experiments 1a and 1b, where the reference stimulus and transformed stimuli were visible at the same time (perception), both Motion‐OPRA1 and Motion‐RCC influenced the similarity judgments, with a stronger influence of Motion‐OPRA1. In Experiments 2a and 2b, where participants first memorized the reference stimulus and viewed the transformed stimuli after a short blank (memory), only Motion‐OPRA1 had marked influences on the similarity judgments. Our findings demonstrate a link between human cognition and these motion categorizations developed in artificial intelligence. We argue for a continued and close multidisciplinary approach to investigating the representation of motion scenes. (shrink)