Rapid Formation and Flexible Expression of Memories of Subliminal Word Pairs

Our daily experiences are incidentally and rapidly encoded as episodic memories. Episodic memories consist of numerous associations (e.g., who gave what to whom where and when) that can be expressed flexibly in new situations. Key features of episodic memory are speed of encoding, its associative nature, and its representational flexibility. Another defining feature of human episodic memory has been consciousness of encoding/retrieval. Here, we show that humans can rapidly form associations between subliminal words and minutes later retrieve these associations even if retrieval words were conceptually related to, but different from encoding words. Because encoding words were presented subliminally, associative encoding, and retrieval were unconscious. Unconscious association formation and retrieval were dependent on a preceding understanding of task principles. We conclude that key computations underlying episodic memory – rapid encoding and flexible expression of associations – can operate outside consciousness

B- and C-type low molecular weight glutenin subunits in tetraploid wheat germplasm

General knowledge acquisition entails the extraction of statistical regularities from the environment. At high levels of complexity, this may involve the extraction, and consolidation, of associative regularities across event memories. The underlying neural mechanisms would likely involve a hippocampo-neocortical dialog, as proposed previously for system-level consolidation. To test these hypotheses, we assessed possible differences in consolidation between associative memories containing cross-episodic regularities and unique associative memories. Subjects learned face-location associations, half of which responded to complex regularities regarding the combination of facial features and locations, whereas the other half did not. Importantly, regularities could only be extracted over hippocampus-encoded, associative aspects of the items. Memory was assessed both immediately after encoding and 48 h later, under fMRI acquisition. Our results suggest that processes related to system-level reorganization occur preferentially for regular associations across episodes. Moreover, the build-up of general knowledge regarding regular associations appears to involve the coordinated activity of the hippocampus and mediofrontal regions. The putative cross-talk between these two regions might support a mechanism for regularity extraction. These findings suggest that the consolidation of cross-episodic regularities may be a key mechanism underlying general knowledge acquisition

Sleep Deprivation Induces Fragmented Memory Loss

Sleep deprivation increases rates of forgetting in episodic memory. Yet, whether an extended lack of sleep alters the qualitative nature of forgetting is unknown. We compared forgetting of episodic memories across intervals of overnight sleep, daytime wakefulness and overnight sleep deprivation. Item-level forgetting was amplified across daytime wakefulness and overnight sleep deprivation, as compared to sleep. Importantly, however, overnight sleep deprivation led to a further deficit in associative memory that was not observed after daytime wakefulness. These findings suggest that sleep deprivation induces fragmentation among item memories and their associations, altering the qualitative nature of episodic forgetting

Episodic associative memories taught by evolutionary algorithm

The paper analyses possibilities of episodic multi-winner multi-directional associative memory taught by evolutionary algorithm. This kind of memory allows to store and recall more complex associations, like episode-to-episode

A Cognitive Science Based Machine Learning Architecture

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:\ud 1) perceptual learning, the learning of new objects, categories, relations, etc.,\ud 2) episodic learning of events, the what, where, and when,\ud 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence

LIDA: A Working Model of Cognition

In this paper we present the LIDA architecture as a working model of cognition. We argue that such working models are broad in scope and address real world problems in comparison to experimentally based models which focus on specific pieces of cognition. While experimentally based models are useful, we need a working model of cognition that integrates what we know from neuroscience, cognitive science and AI. The LIDA architecture provides such a working model. A LIDA based cognitive robot or software agent will be capable of multiple learning mechanisms. With artificial feelings and emotions as primary motivators and learning facilitators, such systems will ‘live’ through a developmental period during which they will learn in multiple ways to act in an effective, human-like manner in complex, dynamic, and unpredictable environments. We discuss the integration of the learning mechanisms into the existing IDA architecture as a working model of cognition

Manipulating Memory Associations Changes Decision-making Preferences in a Preconditioning Task

Memories of past experiences can guide our decisions. Thus, if memories are undermined or distorted, decision making should be affected. Nevertheless, little empirical research has been done to examine the role of memory in reinforcement decision-making . We hypothesized that if memories guide choices in a conditioning decision-making task, then manipulating these memories would result in a change of decision preferences to gain reward. We manipulated participants’ memories by providing false feedback that their memory associations were wrong before they made decisions that could lead them to win money . Participants’ memory ratings decreased significantly after receiving false feedback. More importantly, we found that false feedback led participants’ decision bias to disappear after their memory associations were undermined . Our results suggest that reinforcement decision-making can be altered by fasle feedback on memories . The results are discussed using memory mechanisms such as spreading activation theories

Reduced Memory Coherence for Negative Events and Its Relationship to Posttraumatic Stress Disorder

Posttraumatic stress disorder (PTSD) is characterized by disruptions in memory, including vivid sensory images of the trauma that are involuntarily reexperienced. However, the extent and nature of disruptions to deliberate memory for trauma remain controversial. A unitary account posits that all aspects of memory for a traumatic event are strengthened. In contrast, a dual-representation account proposes up-modulation of sensory and affective representations of the negative content and down-modulation of hippocampal representations of the context in which the event occurred. We take a neuroscientific approach and review the literature concerning the mechanisms required to produce coherent episodic memories and how they are affected in experiments involving negative content. We find, in healthy volunteers, that negative content can reduce associative binding and the coherence of episodic memories. Finally, we bring these findings together with the literature on PTSD to highlight how similar associative mechanisms are affected in patients, consistent with hippocampal impairment, supporting a dual-representation view of disrupted memory coherence