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We are capable of storing a virtually infinite amount of visual information in visual long-term memory (VLTM) storage. At the same time, the amount of visual information we can encode and maintain in visual short-term memory (VSTM) at a given time is severely limited. How do these two memory systems interact to accumulate vast amount of VLTM? In this series of experiments, we exploited interindividual and intraindividual differences VSTM capacity to examine the direct involvement of VSTM in determining the encoding rate (or “bandwidth”) of VLTM. Here, we found that the amount of visual information encoded into VSTM at a given moment (i.e., VSTM capacity), but neither the maintenance duration nor the test process, predicts the effective encoding “bandwidth” of VLTM.

Human memory is thought to consist of long-term storage and short-term storage mechanisms, the latter known as working memory. Although it has long been assumed that information retrieved from long-term memory is represented in working memory, we lack neural evidence for this and need neural measures that allow us to watch this retrieval into working memory unfold with high temporal resolution. Here, we show that human electrophysiology can be used to track information as it is brought back into working memory during retrieval from long-term memory. Specifically, we found that the retrieval of information from long-term memory was limited to just a few simple objects’ worth of information at once, and elicited a pattern of neurophysiological activity similar to that observed when people encode new information into working memory. Our findings suggest that working memory is where information is buffered when being retrieved from long-term memory and reconcile current theories of memory retrieval with classic notions about the memory mechanisms involved.

Working memory capacity reflects a core ability of the individual that affects performance on many cognitive tasks. Recent work has suggested that an important covariate of memory capacity is attentional control, and specifically that low-capacity individuals are more susceptible to attentional capture by distractors than high-capacity individuals are, with the latter being able to resist capture. Here, we tested an alternative account according to which all individuals are equally susceptible to attentional capture, but high-capacity individuals recover more quickly than low-capacity individuals. Using psychophysical and electrophysiological methods, we measured recovery time from attentional capture. In two experiments, we found that high- and low-capacity individuals showed equivalent attentional capture effects in the initial moments following capture, but that low-capacity individuals took much longer to recover than high-capacity individuals did. These results suggest that the poor attentional control associated with low capacity is due to slow disengagement from distractors.

Noninvasive brain stimulation methods are becoming increasingly common tools in the kit of the cognitive scientist. In particular, transcranial direct-current stimulation (tDCS) is showing great promise as a tool to causally manipulate the brain and understand how information is processed. The popularity of this method of brain stimulation is based on the fact that it is safe, inexpensive, its effects are long lasting, and you can increase the likelihood that neurons will fire near one electrode and decrease the likelihood that neurons will fire near another. However, this method of manipulating the brain to draw causal inferences is not without complication. Because tDCS methods continue to be refined and are not yet standardized, there are reports in the literature that show some striking inconsistencies. Primary among the complications of the technique is that the tDCS method uses two or more electrodes to pass current and all of these electrodes will have effects on the tissue underneath them. In this tutorial, we will share what we have learned about using tDCS to manipulate how the brain perceives, attends, remembers, and responds to information from our environment. Our goal is to provide a starting point for new users of tDCS and spur discussion of the standardization of methods to enhance replicability.

Background: Endovascular therapy for acute lower limb ischemia (ALLI) has developed and demonstrated safety and efficacy. The purpose of this study was to assess clinical outcomes in patients treated for ALLI with conventional endovascular or surgical revascularization. Method: This study was a retrospective single-center review. Consecutive patients with ALLI treated with conventional endovascular revascularization (ER) without thrombolytic agent or surgical revascularization (SR) between 2008 and 2014 were investigated. The 1 year and 3 year amputation rate and mortality rate were assessed by time-to-event methods, including Kaplan–Meier estimation. Result: A total of 64 limbs in 62 patients with ALLI due to thromboembolism or thrombosis of a native artery, bypass graft, or previous stented vessel were included. The majority of limbs (90.9%) presented with Rutherford clinical categories 1 to 2 ischemia. Technical success rate was 95.5% in ER and 92.9% in SR group (p = 0.547). Overall amputation rates were 9.1% in ER versus 9.5% in SR after 1 year (p = 0.971) and 9.1% in ER versus 11.9% in SR after 3 year (p = 0.742). Overall mortality rates were 15% in ER versus 7.1% in SR after 1 year (p = 0.491) and 15% in ER versus 11.2% in SR after 3 year (p = 0.878). Conclusion: Endovascular or surgical revascularization of ALLI resulted in comparable outcomes in limb salvage and mortality rate at 1 year and 3 year. Conventional endovascular therapy without thrombolytic agent such as stenting, balloon angioplasty, or catheter-directed thrombosuction may be considered as a treatment option for ALLI.

A simple, low-cost, and non-vacuum epitaxial growth method to realize large-area semiconductors on crystalline silicon will become the game-changer for various applications. For example, we can expect the disruptive effect on the cost of large-scale III–V multi-junction solar cells if we could replace the high-cost germanium substrate with silicon–germanium (SiGe) on Si. For SiGe epitaxial growth, we attempted to develop a process using original Al–Ge pastes for screen printing and subsequent annealing. We compare two pastes including Al–Ge alloyed pastes with compositional uniformity in each particle and Al–Ge mixed pastes. We revealed that Al–Ge alloyed paste could form flatter SiGe film with much less residual pastes, supported by in-situ observations. The uniform and sufficient dissolution of the alloyed paste is responsible for these and led to higher average Ge-composition by annealing at 500 °C. The composition in SiGe was vertically graded up to ~ 90% at the topmost surface. These results show that printing and firing of Al–Ge alloyed paste on Si is the desirable, simple, and high-speed process for epitaxial growth of SiGe, which could be potentially used as the lattice-matched virtual substrate with III–V semiconductors.

Photoacoustic tomography (PAT), also known as optoacoustic tomography, has been emerging as a biomedical imaging modality that can provide cross-sectional or three-dimensional (3D) visualization of biological tissues such as blood vessels and lymphatic vessels in vivo at high resolution. The principle behind the visualization involves the light being absorbed by the tissues which results in the generation of ultrasound. Depending on the strength of ultrasound and its decay rate, it could be used to visualize the absorber location. In general, pulsed lasers such as the Q-switched Nd-YAG and OPO lasers that provide high-energy widths in the range of a few nanoseconds operating at low repetition rates are commonly used as a light source in photoacoustic imaging. However, such lasers are expensive and occupy ample space. Therefore, PAT systems that use LED as the source instead of lasers, which have the advantage of being obtainable at low cost and portable, are gaining attention. However, LED light sources have significantly low energy, and the photoacoustic signals generated have a low signal-to-noise ratio (SNR). Therefore, in LED-based systems, one way to strengthen the signal and improve the SNR is to significantly increase the repetition rate of LED pulses and use signal processing, which can be achieved using a high-power LED along M-sequence signal decoding. M-sequence signal decoding is effective, especially under high repetition rates, thus improving the SNR. However, power supplies for high-power LEDs have a circuit jitter, resulting in random temporal fluctuations in the emitted light. Such jitters, in turn, would affect the M-sequence-based signal decoding. Therefore, we propose a new decoding algorithm which compensates for LED jitter in the M-sequence signal processing. We show that the proposed new signal processing method can significantly improve the SNR of the photoacoustic signals.

Humans are often tasked to remember new faces so that they can recognize the faces later in time. Previous studies found that memory reports for basic visual features (e.g., colors and shapes) are susceptible to systematic distortions as a result of comparison with new visual input, especially when the input is perceived as similar to the memory. The current study tested whether this similarity-induced memory bias (SIMB) would also occur with more complex face stimuli. The results showed that faces that are just perceptually encoded into visual working memory as well as retrieved from visual long-term memory are also susceptible to SIMB. Furthermore, once induced, SIMB persisted over time across cues through which the face memory was accessed for memory report. These results demonstrate the generalizability of SIMB to more complex and practically relevant stimuli, and thus, suggest potential real-world implications.

Past studies of emotion and mood on memory have mostly focused on the learning of emotional material in the laboratory or on the consequences of a punctate catastrophic event. However, the influence of a long-lasting global condition on memory and learning has not been studied. The COVID-19 pandemic unfortunately offered a unique situation to observe the effects of prolonged, negative events on human memory for visual information. One thousand online subjects were asked to remember the details of real-world photographs of objects to enable fine-grained visual discriminations from novel within-category foils. Visual memory performance was invariant across time, regardless of the infection rate in the local or national population, or the subjects’ self-reported affective state using the Positive and Negative Affect Schedule (PANAS). Thus, visual memory provides the human brain with storage that is particularly resilient to changes in emotional state, even when those changes are experienced for months longer than any imaginable laboratory procedure.

Although impairments in working memory (WM) are well documented in schizophrenia, the specific factors that cause these deficits are poorly understood. In this study, we hypothesized that a heightened susceptibility to attentional capture at an early stage of visual processing would result in working memory encoding problems. 30 patients with schizophrenia and 28 demographically matched healthy participants were presented with a search array and asked to report the orientation of the target stimulus. In some of the trials, a flanker stimulus preceded the search array that either matched the color of the target (relevant-flanker capture) or appeared in a different color (irrelevant-flanker capture). Working memory capacity was determined in each individual using the visual change detection paradigm. Patients needed considerably more time to find the target in the no-flanker condition. After adjusting the individual exposure time, both groups showed equivalent capture costs in the irrelevant-flanker condition. However, in the relevant-flanker condition, capture costs were increased in patients compared to controls when the stimulus onset asynchrony between the flanker and the search array was high. Moreover, the increase in relevant capture costs correlated negatively with working memory capacity. This study demonstrates preserved stimulus-driven attentional capture but impaired contingent attentional capture associated with low working memory capacity in schizophrenia. These findings suggest a selective impairment of top-down attentional control in schizophrenia, which may impair working memory encoding.