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Hannula DE, Minor GN, Slabbekoorn D. Conscious awareness and memory systems in the brain. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2023; 14:e1648. [PMID: 37012615 DOI: 10.1002/wcs.1648] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/06/2023] [Accepted: 03/05/2023] [Indexed: 04/05/2023]
Abstract
The term "memory" typically refers to conscious retrieval of events and experiences from our past, but experience can also change our behaviour without corresponding awareness of the learning process or the associated outcome. Based primarily on early neuropsychological work, theoretical perspectives have distinguished between conscious memory, said to depend critically on structures in the medial temporal lobe (MTL), and a collection of performance-based memories that do not. The most influential of these memory systems perspectives, the declarative memory theory, continues to be a mainstay of scientific work today despite mounting evidence suggesting that contributions of MTL structures go beyond the kinds or types of memory that can be explicitly reported. Consistent with these reports, more recent perspectives have focused increasingly on the processing operations supported by particular brain regions and the qualities or characteristics of resulting representations whether memory is expressed with or without awareness. These alternatives to the standard model generally converge on two key points. First, the hippocampus is critical for relational memory binding and representation even without awareness and, second, there may be little difference between some types of priming and explicit, familiarity-based recognition. Here, we examine the evolution of memory systems perspectives and critically evaluate scientific evidence that has challenged the status quo. Along the way, we highlight some of the challenges that researchers encounter in the context of this work, which can be contentious, and describe innovative methods that have been used to examine unconscious memory in the lab. This article is categorized under: Psychology > Memory Psychology > Theory and Methods Philosophy > Consciousness.
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Zher-Wen, Yu R. Unconscious integration: Current evidence for integrative processing under subliminal conditions. Br J Psychol 2023; 114:430-456. [PMID: 36689339 DOI: 10.1111/bjop.12631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/05/2023] [Indexed: 01/24/2023]
Abstract
Integrative processing is traditionally believed to be dependent on consciousness. While earlier studies within the last decade reported many types of integration under subliminal conditions (i.e. without perceptual awareness), these findings are widely challenged recently. This review evaluates the current evidence for 10 types of subliminal integration that are widely studied: arithmetic processing, object-context integration, multi-word processing, same-different processing, multisensory integration and 5 different types of associative learning. Potential methodological issues concerning awareness measures are also taken into account. It is concluded that while there is currently no reliable evidence for subliminal integration, this does not necessarily refute 'unconscious' integration defined through non-subliminal (e.g. implicit) approaches.
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Affiliation(s)
- Zher-Wen
- Department of Management, Hong Kong Baptist University, Hong Kong, China.,Department of Psychology, National University of Singapore, Singapore City, Singapore
| | - Rongjun Yu
- Department of Management, Hong Kong Baptist University, Hong Kong, China
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Ruch S, Alain Züst M, Henke K. Sleep-learning impairs subsequent awake-learning. Neurobiol Learn Mem 2021; 187:107569. [PMID: 34863922 DOI: 10.1016/j.nlm.2021.107569] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 09/21/2021] [Accepted: 11/26/2021] [Indexed: 01/11/2023]
Abstract
Although we can learn new information while asleep, we usually cannot consciously remember the sleep-formed memories - presumably because learning occurred in an unconscious state. Here, we ask whether sleep-learning expedites the subsequent awake-learning of the same information. To answer this question, we reanalyzed data (Züst et al., 2019, Curr Biol) from napping participants, who learned new semantic associations between pseudowords and translation-words (guga-ship) while in slow-wave sleep. They retrieved sleep-formed associations unconsciously on an implicit memory test following awakening. Then, participants took five runs of paired-associative learning to probe carry-over effects of sleep-learning on awake-learning. Surprisingly, sleep-learning diminished awake-learning when participants learned semantic associations that were congruent to sleep-learned associations (guga-boat). Yet, learning associations that conflicted with sleep-learned associations (guga-coin) was unimpaired relative to learning new associations (resun-table; baseline). We speculate that the impeded wake-learning originated in a deficient synaptic downscaling and resulting synaptic saturation in neurons that were activated during both sleep-learning and awake-learning.
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Affiliation(s)
- Simon Ruch
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland.
| | - Marc Alain Züst
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Katharina Henke
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
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Schneider E, Züst MA, Wuethrich S, Schmidig F, Klöppel S, Wiest R, Ruch S, Henke K. Larger capacity for unconscious versus conscious episodic memory. Curr Biol 2021; 31:3551-3563.e9. [PMID: 34256016 DOI: 10.1016/j.cub.2021.06.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 01/29/2021] [Accepted: 06/03/2021] [Indexed: 11/28/2022]
Abstract
Episodic memory is the memory for experienced events. A peak competence of episodic memory is the mental combination of events to infer commonalities. Inferring commonalities may proceed with and without consciousness of events. Yet what distinguishes conscious from unconscious inference? This question inspired nine experiments that featured strongly and weakly masked cartoon clips presented for unconscious and conscious inference. Each clip featured a scene with a visually impenetrable hiding place. Five animals crossed the scene one-by-one consecutively. One animal trajectory represented one event. The animals moved through the hiding place, where they might linger or not. The participants' task was to observe the animals' entrances and exits to maintain a mental record of which animals hid simultaneously. We manipulated information load to explore capacity limits. Memory of inferences was tested immediately, 3.5 or 6 min following encoding. The participants retrieved inferences well when encoding was conscious. When encoding was unconscious, the participants needed to respond intuitively. Only habitually intuitive decision makers exhibited a significant delayed retrieval of inferences drawn unconsciously. Their unconscious retrieval performance did not drop significantly with increasing information load, while conscious retrieval performance dropped significantly. A working memory network, including hippocampus, was activated during both conscious and unconscious inference and correlated with retrieval success. An episodic retrieval network, including hippocampus, was activated during both conscious and unconscious retrieval of inferences and correlated with retrieval success. Only conscious encoding/retrieval recruited additional brain regions outside these networks. Hence, levels of consciousness influenced the memories' behavioral impact, memory capacity, and the neural representational code.
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Affiliation(s)
- Else Schneider
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Marc Alain Züst
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland; University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bolligenstraße 111, 3000 Bern, Switzerland
| | - Sergej Wuethrich
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Flavio Schmidig
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bolligenstraße 111, 3000 Bern, Switzerland
| | - Roland Wiest
- Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
| | - Simon Ruch
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Katharina Henke
- Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland.
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Lin Y, Duan L, Xu P, Li X, Gu R, Luo Y. Electrophysiological indexes of option characteristic processing. Psychophysiology 2019; 56:e13403. [PMID: 31134663 DOI: 10.1111/psyp.13403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 05/07/2019] [Accepted: 05/08/2019] [Indexed: 12/29/2022]
Abstract
Decision making is vital to human behavior and can be divided into multiple stages including option assessment, behavioral output, and feedback evaluation. Studying how people evaluate option characteristics in the option assessment stage would provide important knowledge on human decision making. Using the event-related potential (ERP) method, the present study investigated the neural mechanism of evaluating two types of option characteristics (i.e., reward magnitude and degree of uncertainty) in the temporal dimension. Thirty-five volunteers participated in a monetary gambling task, where they either accepted or rejected gambles. The ERP results showed a double dissociation pattern, with the early P1 component being sensitive to magnitude but insensitive to degree of uncertainty, while both the N2 and P3 components showed the opposite pattern. The results suggest that these two fundamental option features are assessed rapidly and separately in the human brain. Specifically, small magnitude elicited a larger P1 than did large magnitude, indicating that the perceptual and attentional processing of options is modulated by magnitude. Both the N2 and P3 amplitudes evoked by the risky context were larger than those evoked by the ambiguous one, reflecting that more cognitive conflicts and resources are involved in the former condition. Furthermore, the P1, but not the N2 or P3, amplitude was sensitive to decisions, suggesting that early attentional processes may contribute to human decision making. These findings may provide insight into the temporal mechanisms of option characteristic processing.
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Affiliation(s)
- Yongling Lin
- Center for Brain Disorder and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
| | - Lian Duan
- Center for Brain Disorder and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
| | - Pengfei Xu
- Center for Brain Disorder and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
| | - Xinying Li
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ruolei Gu
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Yuejia Luo
- Center for Brain Disorder and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
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