What are the neural mechanisms and physiological functions of dreams?

Dreams are mental experiences, including perceptions, thoughts, and emotions, that occur during sleep. In dreams, hallucinatory perceptions, particularly visual and motoric, are often accompanied by negative emotions. When people dream, they perceive them as real even though they are bizarre and distorted in time and space. People often cannot recall their dreams, even though people dream every night. Dreaming is a strange physiological phenomenon. Research has demonstrated that dreaming is closely associated with rapid eye movement (REM) sleep. It is known that dreaming also occurs during non-REM (NREM) sleep, but the content appears to be different. Dreams during REM sleep tend to be longer, more vivid, more story-like, and more bizarre than those during NREM sleep. In this review, the neural circuits underlying dreaming and the physiological functions associated with it are summarized. Two major theories have been proposed regarding the neural circuits involved in dreaming. One is that dreams are generated by the activation of neural activity in the brainstem and its signal transmission to the cortex. The other is that dreams are caused by forebrain activation by dopamine. Whereas the physiological function of dreams remains unclear, several hypotheses have been proposed that are associated with memory and emotions.

Memories of motor adaptation do not necessarily decay with behavioral unlearning

Motor adaptation reshapes behaviors to habituate novel predictable demands caused by dramatic changes in our body (or environment). In the absence of error signals, behaviors rapidly return to the manner before adaptation. It is still in debate whether this behavioral unlearning is due to memory decay. Recent studies suggested that unlearning may be related to the detection of a context change between adaptation phase and error-absent phase. This context-dependent idea is extended in the present study, which examined the motor adaptation in a ball-tossing task. To facilitate the manipulation of the task and the measurement of the behavior, this tossing task was conducted in a virtual environment. Experiment 1 found that unlearning was more likely to occur when the context in the adaptation phase was less similar to that in the error-absent phase. Experiment 2 further demonstrated that the memory of motor adaptation can bias behavior even after behavioral unlearning. Experiment 3 confirmed that the results in Experiment 1 and 2 were not artifacts. These findings indicate that memories of adaptation are independent of behavioral unlearning, and the contextual similarity between adaptation and error-absent phase determines the unlearning rate.

Is post-transplant cyclophosphamide a true game-changer in allogeneic transplantation: The struggle to unlearn

Close HLA matching of donors and recipients has been the dogma for successful allogeneic blood or marrow transplantation (BMT), to limit the complications of graft rejection and graft-versus-host disease (GVHD). However, many patients in need, especially those in certain racial and ethnic groups such as African-Americans and Hispanics, are unable to find matches despite increased availability of unrelated donors. Unfortunately, despite many early attempts to develop safe, related haploidentical allogenic BMT, mortality rates exceeding 50% from severe GVHD led most centers to steer away from such transplants by the mid-1990s. However, recent advances based largely on the development of high-dose post-transplant cyclophosphamide GVHD prophylaxis, now yield results with haploidentical related donors that approach those with matched donors. With emerging data that younger donor age may be the most important donor selection criterion, HLA-mismatched donors may even have advantages over matched donors in certain situations. Although the exact role that haploidentical donors should play in donor selection strategies is still being defined, the lack of an HLA-matched donor should no longer ever be an exclusion for allogeneic BMT. Unfortunately, this progress in donor availability has not yet been fully recognized by the medical community. Such a discordance between new advances and their clinical translation highlights that changing standard practice is difficult and takes longer than it should, at least in part because it requires "unlearning" long-standing behaviors.

Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones

The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symmetric networks, i.e. α=1. Inspired by sleeping and dreaming mechanisms in mammal brains, we propose an extension of this model displaying the standard on-line (awake) learning mechanism (that allows the storage of external information in terms of patterns) and an off-line (sleep) unlearning&consolidating mechanism (that allows spurious-pattern removal and pure-pattern reinforcement): this obtained daily prescription is able to saturate the theoretical bound α=1, remaining also extremely robust against thermal noise. The emergent neural and synaptic features are analyzed both analytically and numerically. In particular, beyond obtaining a phase diagram for neural dynamics, we focus on synaptic plasticity and we give explicit prescriptions on the temporal evolution of the synaptic matrix. We analytically prove that our algorithm makes the Hebbian kernel converge with high probability to the projection matrix built over the pure stored patterns. Furthermore, we obtain a sharp and explicit estimate for the "sleep rate" in order to ensure such a convergence. Finally, we run extensive numerical simulations (mainly Monte Carlo sampling) to check the approximations underlying the analytical investigations (e.g., we developed the whole theory at the so called replica-symmetric level, as standard in the Amit-Gutfreund-Sompolinsky reference framework) and possible finite-size effects, finding overall full agreement with the theory.

Empirical and conceptual investigation of de-implementation of low-value care from professional and health care system perspectives: a study protocol

Background

A considerable proportion of interventions provided to patients lacks evidence of their effectiveness. This implies that patients may receive ineffective, unnecessary, or even harmful care. Thus, in addition to implementing evidence-based practices, there is also a need to abandon interventions that are not based on best evidence, i.e., low-value care. However, research on de-implementation is limited, and there is a lack of knowledge about how effective de-implementation processes should be carried out. The aim of this project is to explore the phenomenon of the de-implementation of low-value health care practices from the perspective of professionals and the health care system.

Methods

Theories of habits and developmental learning in combination with theories of organizational alignment will be used. The project’s work will be conducted in five steps. Step 1 is a scoping review of the literature, and Step 2 has an explorative design involving interviews with health care stakeholders. Step 3 has a prospective design in which workplaces and professionals are shadowed during an ongoing de-implementation. In Step 4, a conceptual framework for de-implementation will be developed based on the previous steps. In Step 5, strategies for de-implementation are identified using a co-design approach.

Discussion

This project contributes new knowledge to implementation science consisting of empirical data, a conceptual framework, and strategy suggestions on de-implementation of low-value care. The professionals’ perspectives will be highlighted, including insights into how they make decisions, handle de-implementation in daily practice, and what consequences it has on their work. Furthermore, the health care system perspective will be considered and new knowledge on how de-implementation can be understood across health care system levels will be obtained. The theories of habits and developmental learning can also offer insights into how context triggers and reinforces certain behaviors and how factors at the individual and the organizational levels interact. The project employs a solution-oriented perspective by developing a framework for de-implementation of low-value practices and suggesting practical strategies to improve de-implementation processes at all levels of the health care system. The framework and the strategies can thereafter be evaluated for their validity and impact in future studies.

Putting into practice error management theory: Unlearning and learning to manage action errors in construction

Error management theory is drawn upon to examine how a project-based organization, which took the form of a program alliance, was able to change its established error prevention mindset to one that enacted a learning mindfulness that provided an avenue to curtail its action errors. The program alliance was required to unlearn its existing routines and beliefs to accommodate the practices required to embrace error management. As a result of establishing an error management culture the program alliance was able to create a collective mindfulness that nurtured learning and supported innovation. The findings provide a much-needed context to demonstrate the relevance of error management theory to effectively address rework and safety problems in construction projects. The robust theoretical underpinning that is grounded in practice and presented in this paper provides a mechanism to engender learning from errors, which can be utilized by construction organizations to improve the productivity and performance of their projects.

Working smarter not harder: Coupling implementation to de-implementation

In this paper, we discuss de-implementation as an implicit part of implementation and organizational change, and consider its underlying processes of unlearning to discontinue or deviate from ineffective practice and learning to applying newer, more effective practices. We describe a typology of de-implementation that represents four types of change: partial reduction, complete reversal, substitution with related replacement and substitution with unrelated replacement of existing practice. We also explicate how learning and unlearning needed for effective change vary in these four types of de-implementation. Last, we propose coupling de-implementation and implementation efforts, which serve conceptual and logistical goals of organizational change.

Mental challenges of nurses in the face of unlearning situations in hospitals: A qualitative study

BACKGROUND

The unlearning process is complex and sometimes painful in nature. This process usually occurs in social interactions and is very dependent on social contexts and the work environment.

OBJECTIVE

To explore the concerns and mental challenges in facing unlearning situations in nurses.

METHODS

This qualitative study using content analysis was conducted in 2013-2015. Participants were 25 people, and research environment was hospitals in Mashhad and Gonabad. The method of data collection was unstructured interview, and sampling was continued until data saturation. First, the recorded interviews were transcribed and reviewed several times. Then open codes were extracted and after reviewing several times, were classified into subcategories based on semantic similarity. Finally, the similar subcategories were put into the main categories semantically.

RESULTS

Data analysis led to the emergence of 1,180 initial codes and 8 categories and 3 themes. Our themes were discouraging/encouraging situation, double-edged sword colleagues, and organizational policies paradox, that the central theme of progressive and suppressor organizational climate paradox were derived from them.

CONCLUSION

Exposure to unlearning situations is a complex process of which its adoption and implementation is difficult and challenging. This suggests that supporting nurses and attention to their mental concerns and providing favorable learning conditions is required.

The physician's experience of changing clinical practice: a struggle to unlearn

BACKGROUND

Changing clinical practice is a difficult process, best illustrated by the time lag between evidence and use in practice and the extensive use of low-value care. Existing models mostly focus on the barriers to learning and implementing new knowledge. Changing clinical practice, however, includes not only the learning of new practices but also unlearning old and outmoded knowledge. There exists sparse literature regarding the unlearning that takes place at a physician level. Our research objective was to elucidate the experience of trying to abandon an outmoded clinical practice and its relation to learning a new one.

METHODS

We used a grounded theory-based qualitative approach to conduct our study. We conducted 30-min in-person interviews with 15 primary care physicians at the Cleveland VA Medical Center and its clinics. We used a semi-structured interview guide to standardize the interviews.

RESULTS

Our two findings include (1) practice change disturbs the status quo equilibrium. Establishing a new equilibrium that incorporates the change may be a struggle; and (2) part of the struggle to establish a new equilibrium incorporating a practice change involves both the "evidence" itself and tensions between evidence and context.

CONCLUSIONS

Our findings provide evidence-based support for many of the empirical unlearning models that have been adapted to healthcare. Our findings differ from these empirical models in that they refute the static and unidirectional nature of change that previous models imply. Rather, our findings suggest that clinical practice is in a constant flux of change; each instance of unlearning and learning is merely a punctuation mark in this spectrum of change. We suggest that physician unlearning models be modified to reflect the constantly changing nature of clinical practice and demonstrate that change is a multi-directional process.