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"Visual Learning"
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Hippocampal sharp-wave ripples linked to visual episodic recollection in humans
What are the brain mechanisms responsible for episodic memory retrieval? Norman
et al.
investigated epilepsy patients who had electrodes implanted in the hippocampus and a variety of cortical areas. Using a visual learning paradigm, they examined the temporal relationship between the incidence of hippocampal sharp-wave ripples and recall. Effective encoding of visual information was associated with higher incidence of ripples. Successful recall was preceded by an increased probability of ripples, which were also associated with transient reemergence of activation patterns in higher visual cortical areas. Hippocampal ripples may thus boost recollections during episodic memory retrieval.
Science
, this issue p.
eaax1030
Ripples reinstate human memory during free recall.
Hippocampal sharp-wave ripples (SWRs) constitute one of the most synchronized activation events in the brain and play a critical role in offline memory consolidation. Yet their cognitive content and function during awake, conscious behavior remains unclear. We directly examined this question using intracranial recordings in human patients engaged in episodic free recall of previously viewed photographs. Our results reveal a content-selective increase in hippocampal ripple rate emerging 1 to 2 seconds prior to recall events. During recollection, high-order visual areas showed pronounced SWR-coupled reemergence of activation patterns associated with recalled content. Finally, the SWR rate during encoding predicted subsequent free-recall performance. These results point to a role for hippocampal SWRs in triggering spontaneous recollections and orchestrating the reinstatement of cortical representations during free episodic memory retrieval.
Journal Article
Visual culture
\"This is a book about how to read visual images: from fine art to photography, film, television, and new media. The third edition of this lively and popular book contains over fifty illustrations, for the first time in colour, as well as new sections and material\"-- Provided by publisher.
Book
Complementary contributions of non-REM and REM sleep to visual learning
Sleep is beneficial for learning. However, it remains unclear whether learning is facilitated by non-rapid eye movement (NREM) sleep or by REM sleep, whether it results from plasticity increases or stabilization, and whether facilitation results from learning-specific processing. Here, we trained volunteers on a visual task and measured the excitatory and inhibitory (E/I) balance in early visual areas during subsequent sleep as an index of plasticity. The E/I balance increased during NREM sleep irrespective of whether pre-sleep learning occurred, but it was associated with post-sleep performance gains relative to pre-sleep performance. In contrast, the E/I balance decreased during REM sleep but only after pre-sleep training, and the decrease was associated with stabilization of pre-sleep learning. These findings indicate that NREM sleep promotes plasticity, leading to performance gains independent of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.Tamaki et al. measured MRS changes in sleeping humans trained on a visual task. During NREM sleep, learning gains were associated with enhanced visual cortical plasticity that was also seen independent of learning. REM sleep stabilized plasticity only after pre-sleep learning.
Journal Article
What in the world? : look again
Offers a series of diverse types of picture puzzles intended to strengthen visual and cognitive skills.
Book
The underestimated giants: operant conditioning, visual discrimination and long-term memory in giant tortoises
Relatively little is known about cognition in turtles, and most studies have focused on aquatic animals. Almost nothing is known about the giant land tortoises. These are visual animals that travel large distances in the wild, interact with each other and with their environment, and live extremely long lives. Here, we show that Galapagos and Seychelle tortoises, housed in a zoo environment, readily underwent operant conditioning and we provide evidence that they learned faster when trained in the presence of a group rather than individually. The animals readily learned to distinguish colors in a two-choice discrimination task. However, since each animal was assigned its own individual colour for this task, the presence of the group had no obvious effect on the speed of learning. When tested 95 days after the initial training, all animals remembered the operant task. When tested in the discrimination task, most animals relearned the task up to three times faster than naïve animals. Remarkably, animals that were tested 9 years after the initial training still retained the operant conditioning. As animals remembered the operant task, but needed to relearn the discrimination task constitutes the first evidence for a differentiation between implicit and explicit memory in tortoises. Our study is a first step towards a wider appreciation of the cognitive abilities of these unique animals.
Journal Article
The online interactive visual learning improves learning effectiveness and satisfaction of physicians with postgraduate year during the COVID-19 pandemic in Taiwan
Backgrounds
Medical education has shifted from passive forms of teaching to more active learning strategies, particularly in response to the COVID-19 pandemic. Research has discussed the challenges and disadvantages associated with online education, but there is limited documentation on physicians’ perceptions of this sudden and unexpected transformation in medical education. This study aimed to determine the effect of online interactive visual learning on physicians’ perceptions of the effectiveness and their satisfaction with this online learning experience.
Methods
We routinely recruited 64 unclassified physicians in the hospital’s postgraduate year (PGY) program between September 2021 and April 2022. PGY physicians received an online interactive visual learning course. Online (Google Form) testing and questionnaires before and after this course evaluated learning performance, learning attitude and satisfaction of these physicians.
Results
The interactive online learning tools facilitated the physicians’ active learning processes by reducing their learning burden (burden vs. no burden: 4.69% vs. 68.75%) and increasing their learning interest (interest vs. no interest: 84.38% vs. 3.12%) in the online format. Post-test scores were significantly improved compared with pretest scores (post-test vs. pre-test: 5 vs. 4; p < 0.05) and their imaging recognition was markedly improved from baseline (post-test vs. pre-test: 85.19% vs. 61.11%). Levels of satisfaction correlated positively with the physicians’ learning burden (
r
s
= 0.541), learning interest (
r
s
= 0.562), and perceived benefits of imaging recognition (post-course:
r
s
= 0.508; future:
r
s
= 0.563) (all p < 0.05).
Conclusions
Our online course with interactive visual learning facilitated PGY physicians’ learning performance, levels of satisfaction, interest, and perceived benefits of online learning. Hospitals and policymakers need to be aware that this learning approach can markedly enhance physicians’ academic outcomes and levels of clinical practice.
Journal Article
Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images
Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs provide a viable model of human vision when tested with challenging noisy images of objects, sometimes presented at the very limits of visibility. We show that popular state-of-the-art DNNs perform in a qualitatively different manner than humans—they are unusually susceptible to spatially uncorrelated white noise and less impaired by spatially correlated noise. We implemented a noise training procedure to determine whether noise-trained DNNs exhibit more robust responses that better match human behavioral and neural performance. We found that noise-trained DNNs provide a better qualitative match to human performance; moreover, they reliably predict human recognition thresholds on an image-by-image basis. Functional neuroimaging revealed that noise-trained DNNs provide a better correspondence to the pattern-specific neural representations found in both early visual areas and high-level object areas. A layer-specific analysis of the DNNs indicated that noise training led to broad-ranging modifications throughout the network, with greater benefits of noise robustness accruing in progressively higher layers. Our findings demonstrate that noise-trained DNNs provide a viable model to account for human behavioral and neural responses to objects in challenging noisy viewing conditions. Further, they suggest that robustness to noise may be acquired through a process of visual learning.
Journal Article