Spontaneous α oscillations (∼10 Hz) have been associated with various cognitive functions, including perception. Their phase and amplitude independently predict cortical excitability and subsequent perceptual performance. However, the causal role of α phase-amplitude tradeoffs on visual perception remains ill-defined. We aimed to fill this gap and tested two clear predictions from the pulsed inhibition theory according to which α oscillations are associated with periodic functional inhibition. (1) High-α amplitude induces cortical inhibition at specific phases, associated with low perceptual performance, while at opposite phases, inhibition decreases  and perceptual performance increases. (2) Low-α amplitude is less susceptible to these phasic (periodic) pulses of inhibition, leading to overall higher perceptual performance. Here, cortical excitability was assessed in humans using phosphene (illusory) perception induced by single pulses of transcranial magnetic stimulation (TMS) applied over visual cortex at perceptual threshold, and its postpulse evoked activity recorded with simultaneous electroencephalography (EEG). We observed that prepulse α phase modulates the probability to perceive a phosphene, predominantly for high-α amplitude, with a nonoptimal phase for phosphene perception between –π/2 and –π/4. The prepulse nonoptimal phase further leads to an increase in postpulse-evoked activity [event-related potential (ERP)], in phosphene-perceived trials specifically. Together, these results show that α oscillations create periodic inhibitory moments when α amplitude is high, leading to periodic decrease of perceptual performance. This study provides strong causal evidence in favor of the pulsed inhibition theory. The pulsed inhibition theory predicts that the functional inhibition induced by high-α oscillations’ amplitude is periodic, with specific phases decreasing neural firing and perceptual performance. In turn, low-α oscillations’ amplitude is less susceptible to phasic moments of pulsed inhibition leading to overall higher perceptual performance. Using transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) recordings in humans, we found that specific phases of spontaneous α oscillations (∼10 Hz) decrease cortical excitability and the subsequent perceptual outcomes predominantly when α amplitude is high. Our results provide strong causal evidence in favor of the pulsed inhibition theory.α Brain oscillations (8–12 Hz) play a role in various cognitive functions, including visual perception , and areα Oscillations’ amplitude and phase further seem to predict cortical excitability. Spiking activity recorded in macaques is higher at the trough of the α cycle, and for lower α amplitude . MoreoveHere, we address this question in the framework of the pulsed inhibition theory , which mWe investigated the causal effect of spontaneous α phase-amplitude tradeoffs on cortical excitability and subsequent perceptual performance in the visual modality, and tested the predictions made by the pulsed inhibition theory using TMS and electroencephalography (EEG) in human. Cortical excitability was assessed using phosphene perception induced by single-pulse TMS applied over V1/V2 at perceptual threshold (∼50% detection), and its postpulse evoked activity. Our results validate both predictions, demonstrating that α oscillations create periodic inhibitory moments when α amplitude is high, leading to lower perceptual performance. Critically, both simulations and ERP analyses confirmed that the obtained results were not a mere analysis confound in which the quality of the phase estimation covaries with the amplitude.This study is a reappraisal of an early study from As in the original study, the data from nine participants  were analyzed . EEG was acquired simultaneously with a 64-channels Active Two Biosemi system, with DC recording at a sampling rate of 1024 Hz. Additional electrodes, Common Mode Sense (CMS) and Driven Right Leg (DRL), were placed 2 cm under the eyes of the participants and were used as reference and ground, respectively, to minimize TMS-induced EEG artifact. Finally, horizontal, and vertical electro-oculograms were recorded using three additional electrodes placed around the eyes.Participants seated in a dark room, 57 cm from a computer screen . Their head was maintained using a chinrest and a headrest. A 70-mm figure-of-eight coil was placed over the right occipital pole . The handle of the coil was oriented vertically, with the handle of the coil positioned dorsally to the coil itself, resulting in a ventral to dorsal electric current in the brain tissue. Biphasic TMS pulses were applied with a Magstim RapidParticipants were selected based on their ability to perceive TMS-induced phosphenes in the left visual field. A train of seven pulses at 20 Hz and 70% of the TMS machine output intensity, i.e., suprathreshold, was applied over the right occipital pole . In the test trials, single-pulse TMS was applied at the perception threshold, on average across participants, phosphenes were perceived in 45.96 ± 7.68% of trials. In the catch trials, the stimulation intensity was kept the same, but instead of applying single pulses, double pulses  were administered to monitor the validity of participants’ responses (91.66 ± 8.81% of phosphene perceived). In other words, participants were presumably not pressing the button randomly; the selected cortical location did in fact lead to phosphene perception when stimulated. Adding a second pulse of TMS with a short delay between the two pulses has a cumulative effect on neural activity, leading to suprathreshold stimulation . The lonEEG analyses were performed with EEGLAB 13.6.5  were detected. No electrode was rejected from the analysis.A time-frequency transform (morlet wavelets) was computed on single trials with the timefreq function from EEGLAB. The “cycles” parameter was set to , the length of the filter increasing logarithmically from 1 to 15 cycles. The “freqs” parameter was set to , producing frequencies that increase from 2 to 100 Hz.We then sorted the trials according to the amplitude of prepulse, spontaneous, α oscillations. The amplitude at each time-frequency point and for each trial, participant, and electrode was thus calculated. It corresponds to the absolute of the complex vector obtained from the time-frequency decomposition. For each trial and participant, we then averaged the amplitude across all electrodes (we had no a priori hypothesis regarding the electrode location of the effect) and time-frequency points selected based on the previous publication , i.e., tWe calculated the phase-locking values , separately for low-α and high-α amplitude trials, and perceived-phosphene and unperceived-phosphene trials. The phase-locking value was obtained by, first, dividing the complex vectors obtained from the time-frequency decomposition by their length  thus normalizing for amplitude and keeping only the instantaneous phase . Second, the mean across trials of the normalized vectors was computed. The length of the average vector is now a measure of phase distribution, i.e., phase-locking across trials. For each amplitude condition, we subsampled the number of trials in the phosphene condition with the most trials to match the phosphene condition with the least trials. This subsampling procedure was repeated 100 times with a different subset of selected trials, and then we averaged the iterations. For each participant, phase-locking values were then summed across perceived-phosphene and unperceived-phosphene trials to obtain phase-opposition sums (POSs). POSs were then averaged across all electrodes, separately for low-α and high-α amplitude trials.This measure of phase opposition is designed to give a low value when summing over two conditions both with uniform (random) phase distributions. On the other hand, POS is high when summing over two conditions both with strong phase-locked distributions across trials, as would happen when two conditions are associated with opposite phases. Since POS is computed on spontaneous (prepulse) activity, i.e., the phase distribution across all trials can be assumed to be uniform (see below for further statistics), if the phase is locked across trials for one specific condition  then the phase of the other condition  would logically be locked in the opposite direction, leading to a high POS value.Z-scores were computed by comparing the experimentally obtained POS to the mean and SEM of the surrogate POS: Z-scores = (POS – surrogate POS mean)/surrogate POS SEM.This average was then compared with a surrogate distribution obtained with a permutation procedure  consistip-values. A topographical analysis on the z-scores revealed two regions of interest (ROIs) involved in the phase-opposition effect . We repeated the previous analyses for these regions.False discovery rate (FDR) correction for multiple comparisons was further applied to Specific time-frequency points were then selected for further analyses. We selected the time points separately for occipital and frontal electrodes/ROIs for which http://www.jstatsoft.org/v31/i10, p = 0.081657, κ = 0.1883; high-α amplitude trials: p = 0.22 314, κ = 0.13 517) and electrode AFz , the tests did not reveal a significant effect suggesting that the phase was uniformly distributed across trials.We further ensured, at these selected time-frequency points, that the prepulse phase-opposition effect was not because of a contamination by the wavelet decomposition from the postpulse activity, separately for electrode PO3 and AFz. We thus tested whether the phase was uniformly distributed for both low-α and high-α amplitude trials. For each trial, phases were extracted and averaged across participants, separately for perceived-phosphene and unperceived-phosphene conditions, and the uniformity of the distribution across all trials was tested with a Rayleigh test from the Circular Statistics Toolbox . On average across the nine participants, phosphene-conditions, and α-amplitude conditions, there were 167.94 ± 36.01 trials per bin in the two-bin version, 111.96 ± 24.29 trials in the three-bin version, 83.97 ± 18.41 trials in the four-bin version, and 67.18 ± 15.39 trials in the five-bin version.Finally, t tests were used to compare individual 10.24-Hz peaks to their corresponding 1/f aperiodic component. The 10.24-Hz peaks were further compared between low-α and high-α amplitude conditions with one-tailed t tests. To ensure that the significant difference between the two conditions did not come from a difference in their aperiodic 1/f component, we also fitted the amplitude spectra to the 1/f component for each participant and compared the 1/f component at 10.24 Hz between low-α and high-α amplitude conditions with two-tailed t tests.To confirm further that the high-α as well as the low-α amplitude conditions both contained α oscillations, EEG time series from −600 to −1 ms were analyzed with an FFT (500 points zero padding), independently for the occipital and frontal ROI, for each α-amplitude condition, trial and participant. The resulting amplitude spectra were then averaged across trials and participants and plotted from 2 to 40 Hz. One-tailed z-score of phase-opposition  at –77 ms prepulse, and averaged across electrodes within the occipital ROI, (E–H) at –40 ms prepulse, and averaged across the electrodes within the frontal ROI. Dots, POS for individual participants. Circles, POS averaged across the nine participants. All following analyses were performed on the three-bin condition , i.e., trials were binned in low-α, medium-α (med), and high-α amplitude trials, discarding the medium-α amplitude bin. Download Figure 2-1, TIF file.The phase effect on phosphene perception is higher for high-α compared to low-α amplitude trials. POS computed for several binning versions of α amplitude trials, at 10.7 Hz and  and the frontal (right panel) ROI. Red color, high-α amplitude condition; blue color, low-α amplitude condition. Colored solid lines, amplitude spectra averaged across the nine participants between 2 and 40 Hz. Colored shaded areas, SEM. *, significant difference at 10.24 Hz between low-α and high-α amplitude conditions. Download t tests (from 350 to 800 ms). Correction for multiple comparisons was applied following a cluster procedure. For each participant, surrogate ERPs were obtained by shuffling the perceived and unperceived phosphene labels (500 repetitions). t tests were recomputed similarly as before, and the number of consecutive significant time points (surrogate cluster size) for each repetition was stored. The p-value for each empirical cluster was then computed as the proportion of surrogate clusters that were larger than the empirical cluster. Using an α level of 0.05, we considered an empirical cluster significant if its size was larger than at least 95% of the surrogate clusters.Previously preprocessed EEG data were further cleaned from the power line noise by applying a notch filter at 50 Hz (band-stop at 47–53 Hz) before epoching. ERPs, centered on the pulse onset, were computed as the average of trials for each α-amplitude condition, phosphene-perception condition, and participant. The difference of ERPs between perceived-phosphene and unperceived-phosphene conditions was computed, separately for low-α and high-α amplitude conditions. The ERP differences were then compared against zero with repeated measures one-tailed t test. To ensure that the obtained significant difference between low-α and high-α amplitude conditions was not because of a difference in their 1/f aperiodic components, we fitted the amplitude spectra to their 1/f component and computed the area under the curve, for each participant, separately for low-α and high-α amplitude conditions, for both electrodes PO3 and AFz. The area under the curve of the low-α amplitude condition was compared with the one of the high-α amplitude condition with a two-tailed t test.The use of TMS to induce phosphene perception rather than an external stimulation allows for direct access to the instantaneous state of the spontaneous brain oscillations. In other words, one can directly compute the prepulse ERP differences (time before pulse onset) between perceived-phosphene and unperceived-phosphene conditions, to assess spontaneous oscillatory activity. In this case, when comparing ERP differences between perceived-phosphene and unperceived-phosphene conditions, separately for low-α and high-α (presorted) amplitude trials, there is no analysis confound coming from a less accurate phase estimation when α amplitude is low. ERP differences from −400 to 0 ms were then analyzed with an FFT (500 points zero padding), independently for electrodes PO3 and AFz, for each α-amplitude condition and for each participant. The resulting amplitude spectra were then averaged across participants and plotted from 2 to 40 Hz (a peak at 10.24 Hz was observed for both electrodes and for each α-amplitude condition). We then performed the following steps to test for a difference between high-α and low-α amplitude trials in the resulting amplitude spectra: (1) difference of the averaged amplitude spectra between high-α and low-α amplitude trials; (2) fit of this difference to the 1/f component; (3) removing of the 1/f component; (4) Gaussian fit of the resulting amplitude spectra to extract the frequency window showing a difference between high-α and low-α amplitude trials; (5) statistical comparison of the amplitude spectra (uncorrected for 1/f) between high-α and low-α amplitude trials conditions with a one-tailed P-values were estimated by comparing these POSs to the mean and SEM of the surrogate distribution obtained by shuffling the perceived-phosphene and unperceived-phosphene labels (repeated 500 times), for low-α and high-α amplitude trials separately, before replicating the previous analysis on the surrogate ERPs.Finally, an FFT (500 points zero padding) was performed separately for the ERP of perceived-phosphene and unperceived-phosphene conditions on each participant. We then computed phase-locking values across participants to assess the interindividual variability at 10.24 Hz for low-α and high-α amplitude trials separately (frequency at which a peak of amplitude was observed in the amplitude spectra of the ERP difference between phosphene perceived and unperceived conditions). The sum of phase-locking values across participants of perceived-phosphene and unperceived-phosphene conditions was computed, for low-α and high-α amplitude trials separately, and evaluated statistically with a permutation procedure. t tests against the aperiodic 1/f activity were used to test the significance of the 10.24-Hz peak.As mentioned above, the advantage of the present TMS procedure is that it allows for direct access to the instantaneous state of the spontaneous brain oscillations. In other words, prepulse spontaneous activity is readily observable on the ERP. To ensure that postpulse ERPs were not contaminated by spontaneous α oscillations , an FFT (500 points zero padding) was performed on the ERPs of the perceived-phosphene and unperceived-phosphene conditions, from 400 to 800 ms, for electrodes PO3 and AFz separately, and for each α-amplitude condition and participant. One-tailed Low-α and high-α amplitude trials were sorted in nine phase bins at the selected time-frequency points , separately for the occipital ROI, as well as the specific electrode PO3 , and the frontal ROI, as well as the specific electrode AFz . The percentage of perceived-phosphene was computed for each phase bin, α-amplitude condition, electrode, and participant, and further averaged across participants and electrodes. The values were finally normalized by dividing the percentage of perceived-phosphene averaged across phase bins, separately for each α-amplitude condition. A two-way repeated-measures ANOVA was performed to test for the main effect of phase bin. The percentage of variance explained was computed as the difference between the optimal phase (maximum percentage of phosphene perceived) and the opposite one.t test for each time point from 350 to 800 ms . A two-way repeated-measures ANOVA was performed to test for a main effect of phase bin and interaction between phase bin and α-amplitude (results regarding the main effect of α-amplitude were not interpreted). Specifically, we tested the hypotheses that (1) the ERP difference between perceived-phosphene and unperceived-phosphene conditions depended on the phase of spontaneous α oscillation, and (2) that this phase effect is stronger for high-α amplitude trials. Finally, we calculated the maximum ERP amplitude of the perceived-phosphene and unperceived-phosphene conditions separately, independently for phase bin centered on –π/4 and π/2, corresponding, respectively, to the maximum and the minimum ERP difference, and low-α and high-α amplitude trials. For each α-amplitude condition, we fitted the data to a linear mixed-effect model with phase bins and phosphene conditions as fixed effects, and participants as random effects. Post hoc analyses were done with one-tailed t tests.Bin sorting was applied as described in the previous section. Then, the ERP difference between perceived-phosphene and unperceived-phosphene conditions for each phase bin and α-amplitude condition was computed. The maximum perceived-unperceived ERP difference was selected in the time window in which an ERP difference between low-α and high-α amplitude was detected, according to repeated measures two-tailed p = 0.0553, Cohen’s d (effect size) = 0.88). Note that the earlier study  in nine healthy participants, at threshold intensity (45.96 ± 7.68% of phosphene perceived across participants) while simultaneously recording EEG. Previous analysis of this dataset  revealeder study  was not er study . In the z-score threshold of 4.27, a p-value threshold of 1.96 × 10−5, and a Cohen’s d threshold approaching infinity). The corresponding topography revealed that the phase-opposition effect was maximal over occipital and frontal electrodes , and showed a less informative topography of the effect. A post hoc analysis revealed that POS values, averaged across electrodes, separately for the occipital and frontal ROIs at the respective selected time-frequency points , were significantly higher for high-α compared with low-α amplitude trials at  for the occipital ROI . However, increasing the number of bins decreases the number of trials in each bin. Consequently, all main analyses were performed on the three-bin version (excluding the middle bin) to clearly separate low-α and high-α amplitude trials while maximizing the number of trials per condition.To investigate the potential joint effect of the amplitude and the phase of spontaneous α oscillations on phosphene perception, we calculated POS , separately for low-α and high-α amplitude conditions. Specifically, this analysis assesses whether phosphene perception is modulated by significantly different phases of the α cycle by computing the sum of phase-locking values  over the perceived-phosphene and unperceived-phosphene conditions . Spontanectrodes B,C. The t test against the 1/f aperiodic activity: p = 0.0354, Cohen’s d = 0.7371, CI = ) and high-α  amplitude trials, and in the frontal ROI for both low-α  and high-α  amplitude trials. This analysis confirms that estimating the phase in low-α amplitude trials is indeed neurophysiologically relevant. Additionally, the peak at 10.24 Hz was significantly higher for high-α compared with low-α amplitude trials, for both the occipital  and the frontal  ROI. This difference was unlikely because of a difference in the 1/f aperiodic activity between low-α and high-α amplitude conditions, i.e., there was no significant difference in the 1/f component at 10.24 Hz between low-α and high-α amplitude conditions for the occipital  and the frontal  ROI.To ensure that the difference in phase effect observed between low-α and high-α amplitude trials does not depend on a poor estimation of the phase when α amplitude is low, we performed a control analysis based on simulations , and from 7.16 to 10.24 Hz for AFz . This difference was unlikely because of a difference in the 1/f aperiodic activity between low-α and high-α amplitude conditions as their aperiodic activity did not differ significantly, neither for electrode PO3  nor AFz . To further assess the interindividual variability, we calculated the sum of phase-locking values across participants at 10.24 Hz for perceived-phosphene and unperceived-phosphene conditions, separately for low-α and high-α amplitude trials, and for PO3 and AFz electrodes. In other words, we ask whether the prepulse ERP for each condition oscillates in-phase across all participants, and are in phase-opposition between perceived-phosphene and unperceived-phosphene conditions. We found that there is a phase-opposition between perceived-phosphene and unperceived-phosphene conditions for the electrode PO3, for high-α amplitude trials , but not for low-α amplitude trials , nor for AFz low-α  and high-α  amplitude. Phosphene perception depends on an optimal phase of α oscillation at the occipital electrode PO3, when α amplitude is high. Together, these analyses suggest that phosphene perception alternates between optimal and nonoptimal phases of the α (10.24 Hz) oscillations in the 400-ms window before the pulse, with all participants sharing a similar optimal phase. This phase effect is predominant in the occipital region, and stronger when the α amplitude is high.To further understand the link between prepulse spontaneous α oscillatory phase and amplitude, cortical excitability and phosphene perception, and address further a possible confound coming from a less accurate phase estimation when α amplitude is low , we analyzed the ERP difference between perceived-phosphene and unperceived-phosphene conditions. Critically, the use of TMS to induce phosphene perception allows for direct access to the instantaneous state of the spontaneous brain oscillations. In other words, the prepulse ERP differences (time before pulse onset) between perceived-phosphene and unperceived-phosphene conditions, allows to assess spontaneous oscillatory activity. Thus, if there is an optimal phase for perception and an opposite, nonoptimal one, then for each participant the prepulse ERP for perceived-phosphene and for unperceived-phosphene should each oscillate in α, and so would the ERP difference. Additionally, if all participants share the same optimal phase, then the prepulse ERP difference averaged across participants should oscillate in α as well. We analyzed the ERP difference between perceived-phosphene and unperceived-phosphene conditions for electrodes PO3 and AFz  = 2.117, p = 0.0467, η2 (effect size) = 20.93, square sum (SS) = 0.345) and frontal  = 3.360, p = 0.0028, η2 = 29.58, SS = 0.472) ROIs. There was no main effect of amplitude in either the occipital  = 1.818, p = 0.2145, η2 = 18.51, SS = 0.001) or the frontal  = 0.225, p = 0.6476, η2 = 2.74, SS < 0.001) ROIs, nor interaction in either the occipital  = 0.249, p = 0.9794, SS = 0.048) or the frontal  = 0.462, p = 0.8781, SS = 0.076) ROIs. Critically, the results show that the optimal phase for phosphene perception is centered on π/2 while the opposite phase, between –π/2 and –π/4, is nonoptimal. Finally, we observe that the percentage of variance explained by the phase is more important for high-α  compared with low-α  amplitude of spontaneous oscillations. We repeated this analysis for the individual electrodes PO3 and AFz and observed similar effects. A two-way repeated-measures ANOVA showed a significant effect of the phase for both electrodes PO3  = 2.113, p = 0.0472, η2 = 20.89, SS = 0.937) and AFz  = 2.106, p = 0.0479, η2 = 20.84, SS = 0.908), no significant main effect of the amplitude for either electrode PO3  = 0.461, p = 0.5164, η2 = 5.45, SS = 0.002) or AFz  = 0.002, p = 0.9633, η2 = 0.03, SS < 0.001), and no interaction for either electrode PO3  = 0.612, p = 0.7648, SS = 0.294) or AFz  = 0.389, p = 0.9224, SS = 0.2).Next, for each participant, we sorted low-α and high-α amplitude trials in nine bins according to the prepulse EEG phase, for the selected time-frequency points . Then, the percentage of phosphene perceived was calculated for each bin and averaged across participants . A two-wt tests against the 1/f aperiodic component: low-α amplitude, perceived: p = 0.9244, Cohen’s d = −0.4967, CI = ; unperceived: p = 0.6837, Cohen’s d = −0.1176, CI = ; high-α amplitude, perceived: p = 0.4279, Cohen’s d = 0.0643, CI = ; unperceived: p = 0.0971, Cohen’s d = 0.3345, CI = ) and AFz . Thus, the postpulse signal likely does not contain sufficient prepulse information to translate into a contamination of the postpulse ERP.To understand the role of spontaneous α oscillations phase-amplitude tradeoffs on cortical excitability and subsequent perceptual performance, we then focused on the postpulse evoked activity. F = 2.338, p = 0.0286, η2 = 22.62, SS = 430.66) and α-amplitude  = 13.623, p = 0.0061, η2 = 63, SS = 137.62; this is coherent with the selection of the ERP time window of interest and will not be further interpreted; see Materials and Methods), but no significant interaction  = 0.377, p = 0.9289, SS = 61.76). The two-way repeated-measures ANOVA on electrode AFz  = 12.749, p = 0.0073, η2 = 61.44, SS = 102.97; this is coherent with the selection of the ERP time window of interest and will not be further interpreted; see Materials and Methods), no significant effect of the phase  = 0.393, p = 0.9206, η2 = 4.68, SS = 161.37), and no interaction  = 0.376, p = 0.9297, SS = 158.75). In other words, for both low-α and high-α amplitude, the phase of prepulse spontaneous α oscillations predicts the ERP difference exclusively for the occipital electrode PO3. Specifically, we observed a higher ERP difference at –π/4, i.e., around the nonoptimal phase for phosphene perception (see t(32) = −3.1, p = 0.004, estimate = −12.201 ± 3.935, SE) and high-α (t(32) = −3.252, p = 0.003, estimate = −12.188 ± 3.748, SE) amplitude conditions, a significant effect of the phase for low-α (t(32) = −2.551, p = 0.0157, estimate = −10.161 ± 3.983, SE) and high-α (t(32) = −2.313, p = 0.0273, estimate = −8.833 ± 3.82, SE) amplitude conditions, and a significant interaction between the phosphene condition and the phase for both low-α (t(32) = 2.468, p = 0.0191, estimate = 6.142 ± 2.489, SE) and high-α (t(32) = 2.237, p = 0.033, estimate = 5.292 ± 2.369, SE) amplitude conditions. A post hoc analysis showed that the ERP difference at –π/4 for perceived-phosphene trials was significantly higher compared with unperceived-phosphene trials at –π/4 for both low-α  and high-α  amplitude conditions, and compared with unperceived-phosphene trials at π/2 for both low-α  and high-α  amplitude conditions. Thus, around –π/4 for both low-α and high-α amplitude, we observed a low percentage of perceived-phosphene  higAs previously described in the literature, we found that the phase of spontaneous oscillations in the α frequency range predicts whether a near-threshold stimulus would be successfully perceived , 2017. TWe observed that the phase and the amplitude of spontaneous α oscillations influence cortical excitability, only when there is subsequent perception. Indeed, a phase between –π/2 and –π/4 led to higher ERP exclusively for phosphene perception trials. Interestingly, this phase was also associated with lower perceptual performance. The nonoptimal phase of the α oscillations (between –π/2 and –π/4) tends to create periodic inhibitory cortical states favoring the absence of phosphene perception, which leads to a greater ERP response when a phosphene is in fact perceived. It is important to notice that the paradigm developed by Our results show a potential functional link between the occipital and the frontal lobes. Several authors have proposed that α carries feedback information  and thatIn conclusion, our study provides strong causal evidence in favor of tradeoffs between the phase and the amplitude of α oscillations to create periodic inhibitory moments leading to rhythms in perception. As predicted by the pulsed inhibition theory, the effect of the phase of spontaneous α oscillations on perception increases for larger α amplitude.


Fusobacterium nucleatum (F. nucleatum) to colorectal tumorigenesis, we aimed to produce preliminary data on the expression of F. nucleatum in both oral and colorectal body sites in cases diagnosed with colorectal neoplasms (CRN) and CRN-free controls. We conducted a pilot hospital-based case–control study among patients who underwent colonoscopy examination. Saliva samples and biopsies from healthy colon mucosa from CRN cases and CRN-free controls, and from tumors in cases, were collected, as well as data on periodontal condition and potential CRN risk factors. A total of 22 CRN cases and 21 CRN-free controls participated in this study, with a total of 135 biospecimens collected and analyzed by qPCR for detection and quantification of F. nucleatum. The detection rate of F. nucleatum was 95% in saliva samples and 18% in colorectal mucosa specimens. The median (95% CI) salivary F. nucleatum level was 0.35 (0.15–0.82) and 0.12 (0.05–0.65) in case and control groups, respectively, with a Spearman correlation of 0.64 (95% CI 0.2–0.94) between F. nucleatum level in saliva and healthy colorectal mucosa in controls. Our study results support the need for and the feasibility of further studies that aim to investigate the association between oral and colorectal levels of F. nucleatum in CRN cases and controls.As evidence has been linking the oral bacterium Clinical Relevance: Considering the current evidence linking F. nucleatum to colorectal carcinogenesis, investigating the role of oral F. nucleatum expression in its colorectal enrichment is crucial for colorectal cancer screening and prevention avenues. Most CRCs arise from adenomatous polyps, which can eventually degenerate into invasive carcinomas2. The potential for malignant progress depends on the histologic pattern of growth (with villous pattern being an adverse indicator), size, multiplicity of polyps, and high-grade dysplasia status3. A small proportion of CRCs develop under the alternative “serrated pathway”, from serrated polyps frequently located in the proximal colon, and are linked to the Microsatellite Instability phenotype, resulting from a deficiency of the DNA repair system2.Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second cause of death from cancer worldwide, with over 1,900,000 newly diagnosed cases and over 900,000 deaths in 2020Fusobacterium nucleatum (F. nucleatum) in colorectal tissues and stools collected from subjects diagnosed with cancerous and even precancerous colorectal lesions6. The involvement of F. nucleatum in early colorectal carcinogenesis stages has been suggested by studies that identified the bacterium in colorectal adenomas, with a gradual enrichment of the colon with F. nucleatum in parallel to the adenoma-carcinoma sequence9. Moreover, the bacterium was identified with two virulence factors promoting colorectal carcinogenesis. The first factor is FadA, an adhesin that allows F. nucleatum to invade human epithelial cells, activate β-catenin signaling, induce expression of the oncogenic gene, and promote the growth of colorectal tumor cells10. The second factor is a self-transporting protein Fap2, which inhibits the activity of immune cells and thus potentiates the progression of CRC11.Over the last decade, many studies have reported an enrichment of F. nucleatum is also among the dominant species of the oral cavity13 and plays an essential role in the formation of dental plaque. It also promotes the colonization and invasion of tooth surfaces by other pathogenic species, which in turn stimulates the recruitment and activation of local immune cells, resulting in destruction of tooth-supporting tissues and progression of periodontitis15. F. nucleatum is abundant in salivary samples from patients with gingivitis and chronic periodontitis16.F. nucleatum is sourced intra-individually from the oral cavity19, in the presence of periodontal sites, which may explain the association of periodontal disease (PD) with CRC and colorectal adenomas23. However, the hypothesis of an intra-individual oral source of gut enrichment with F. nucleatum still needs to be tested, which would require epidemiologic data on paired measures of both oral and gut F. nucleatum levels in subjects diagnosed with colorectal neoplasms (CRN) and in CRN-free controls. To date, few studies have investigated F. nucleatum in saliva from subjects with CRN and CRN-free controls29, only two studies have investigated paired saliva and colorectal specimens in these groups28, and none has explored the link between paired oral and colorectal levels of F. nucleatum in subjects with CRN and CRN-free controls  aged 40–80 years; (2) resident of Montreal metropolitan area; (3) speaking French and/or English; (4) no prior diagnosis of cancer; (5) no history of hereditary colorectal disease; (6) no history of inflammatory bowel disease; and (7) no history of treatment with antibiotics within the past 3 months.31. Patients whose colonoscopy did not result in the diagnosis of CRC, colorectal advanced adenoma, or inflammatory bowel disease were included in the ‘control’ group.Patients with histologically confirmed advanced colorectal adenoma or CRC were included in the “case” group of CRN. Advanced colorectal adenoma refers to adenomas with high risk of malignant transformation, which is defined by one or more of the following criteria being met: 3–10 adenomas; high-grade dysplasia; tubulovillous or villous appearance; adenoma > 1 cm in diameter; serrated sessile adenomasEligible patients who agreed to participate in the study were invited to complete a multi-item study questionnaire, provide a saliva sample, and provide consent for biopsy collection during colonoscopy examination. The study was approved by the University of Montreal Hospital Centre Research Ethics Committee under the number: 2017-7068, CE 16.375—MJB, and all study participants signed the study consent before undergoing their colonoscopy. Participants were confirmed for eligibility only after colonoscopy examination. Participant status (case or control) was confirmed by histological investigation.32. The questionnaire included different sections on sociodemographic and medical history information, cigarette smoking, anthropometric measures, non-steroidal anti-inflammatory drugs use, oral health, dietary habits, and total physical activity36. A life-course approach was used to document cumulative long-term history regarding cigarette smoking, specific dietary habits, and physical activity.Participants were administered a multi-item study-questionnaire that had been used by the research team in a previous population-based case–control study, COLDENT study, investigating the association between PD and sporadic CRC32.Thus, collected data enabled the description of study participants regarding sociodemographic characteristics, periodontal health status, as well as potential risk factors of CRN/CRC, namely age, gender, education attainment, income, body mass index, history of type II diabetes, history of CRC in first-degree relatives, history of regular use of non-steroidal anti-inflammatory drugs, lifetime cumulative cigarette smoking, consumption of red meats, processed meats, and total alcoholic drinks since early adulthood, as well as lifetime total physical activity score. Positive history of PD was defined as self-reported PD with bone loss, a previous professional diagnosis or treatment of PD, or history of clinical symptoms and complications of the disease, such as frequent gum bleeding, tooth mobility, or tooth loss because of PD or tooth mobility® and Dulcolax 5 mg®) in the day before colonoscopy. During colonoscopy, biopsies were taken from healthy mucosa in cases and controls, and from polyps (or tumors) in cases. Given the differences in gut microbial composition between proximal and distal colon sites, biopsies of healthy mucosa were separately collected from ascending and descending colon. Biopsies of polyps were taken from freshly excised polyps before they were sent for histopathology analysis. If a clinical decision was made during colonoscopy to delay a polyp removal and take biopsies for histopathology analysis , an extra-biopsy was then taken for the present study analysis. All biopsies were collected in physiological solution (Nacl 0.9%), then immediately transferred to empty sterile containers.In preparation to colonoscopy examination, all participants received the protocol for conventional bowel preparation, which consists of a diet restricted in residue for 2 days, followed by a strict liquid diet and laxatives (Bi-Peglyte®). Participants were warned not to eat, drink, smoke, or chew gum for 30 min before saliva collection. Mucosa and saliva specimens were immediately stored at − 80 °C until analysis.Unstimulated saliva was collected from participants the day of colonoscopy, or a few days later (at the time of interview), by spitting in a commercial collection kit for DNA stabilization . For human saliva, the MEFE gene  was used as reference gene. A total of 80 ng DNA was used in qPCR reaction and the total reaction volume was 10 ul. Amplification and detection of DNA was performed with the StepOnePlus Real-Time PCR Systems , using the following reaction conditions: 10 min at 95 °C, 40 cycles of 15 s at 95 °C, and 1 min at 60 °C. For quality control, DNA of F. nucleatum strain ATCC 25,586 was used as a positive control. No DNA loading and Diethyl pyrocarbonate (DEPC) treated water were used as negative controls. F. nucleatum positivity was defined as a detectable level of F. nucleatum DNA within 40 PCR cycles, and F. nucleatum negativity was defined as an undetectable level with a proper amplification of human reference gene SLCO2A1. The bacterium level relative quantification is automatically provided by StepOne Plus Realtime PCR Systems  as 2−ΔCq value, with ΔCq = average Cq value of F. nucleatum − average Cq value of total bacteria or of the reference gene.Genomic DNA was isolated from saliva and colon tissue samples using the QIAamp DNA Mini Kit  and procedures were done according to the manufacturer’s instructions. DNA content was quantified using the Bio-Rad SmartSpec 3000 Spectrophotometer . DNA sequences of TaqMan primer and probe used to detect 16S ribosomal RNA gene of Since this is a pilot study, the statistical analysis performed was purely exploratory, in order to help future studies in study-design decisions, including sample-size calculations., we calculated both frequencies of positive detection of F. nucleatum and medians of 2−ΔCq with their corresponding 95% confidence intervals (CI), in each group (cases and controls) and each specimen type . Also, coefficients of Spearman correlation between salivary and colorectal F. nucleatum levels, as well as between F. nucleatum levels in heathy mucosa of both the ascending and descending colon were presented with their corresponding 95% CIs. IBM SPSS Statistics version 26 was used for statistical analysis.The distributions of relevant characteristics concerning CRN risk factors in the case and control series were presented with mean and standard deviation, or median and inter-quartile range  for continuous variables, and percentage for categorical variables. Based on data from qPCR analysis of study specimensThe study was approved by the University of Montreal Hospital Centre Research Ethics Committee, and we certify that the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.All study participants have provided an informed consent to participate in the study.A total of 75 potentially eligible participants were solicited, of whom 20 did not meet the study eligibility criteria, and 12 refused to participate. Therefore 43 patients participated to this pilot study, including 22 cases of CRN and 21 CRN-free controls.All participants, except one case, completed the study questionnaire. Distributions of cases and controls according to sociodemographic and other relevant characteristics are presented in Table F. nucleatum levels.All cases had undergone polypectomy or endoscopic mucosal resection during colonoscopy, and one polyp was removed in each patient, except for two patients with two polyps removed during the same colonoscopy, bringing the total CRN specimens to 24. Characteristics of the CRN  are presented in Table F. nucleatum detection rate by biospecimen type , in case and control groups. F. nucleatum was detected in saliva specimens from almost all cases (21/22) and controls (20/21). F. nucleatum levels (measured by qPCR as 2−ΔCq) in saliva ranged from barely detectable (0.000004) to 3.17 and 2.65, in cases and controls respectively. The median (95% CI) of salivary F. nucleatum level was 0.345 (0.15–0.82) and 0.12 (0.05–0.65) in case and control groups respectively  within both healthy mucosa (from both ascending and descending colon specimens) and polyp, and in 9 controls’ healthy mucosa specimens (ascending and/or descending colon) (43%). The polyp where F. nucleatum was detected was a conventional adenoma, tubular subtype, located in the proximal colon.In colorectal mucosa, F. nucleatum in controls’ healthy mucosa specimens ranged from 0.116 to 2.02 in the ascending colon, and from 0.045 to 1.2 in the descending colon. F. nucleatum level in healthy mucosa from the case detected with F. nucleatum was higher than the maximum observed in controls: 2.574 in the ascending colon, 1.143 in the descending colon, and 1.952 in the polyp.The level of F. nucleatum levels in saliva and mucosa samples was 0.64 (95% CI: 0.2–094). This was calculated for controls only, as in cases only one subject had F. nucleatum detected in both saliva and colorectal mucosa specimens. We also explored if there was any correlation between levels of F. nucleatum in heathy mucosa of both ascending and descending colon, and the corresponding Spearman correlation coefficient was calculated as 0.68 (95 CI 0.25–0.96).The Spearman correlation coefficient between F. nucleatum in both saliva and colorectal mucosa from patients diagnosed with CRN and CRN-free controls.In this pilot study, we generated preliminary data on detection and quantification of We were able to collect and analyze a total of 135 biospecimens including saliva samples and healthy-colon mucosa biopsies from most cases and controls, and CRN biopsies from all cases.F. nucleatum in saliva from both case and control groups, consistent with previous studies29. F. nucleatum is in fact a commensal bacterium of the oral cavity, which explains its more common detection in saliva regardless of disease status. We also found a higher median level of F. nucleatum in saliva from the case group than from controls. A recent study in Turkey with a large number of participants (71 CRC cases and 77 controls)25, and also using qPCR for microbial saliva analysis, showed a higher mean amount of F. nucleatum in CRC group than in control group . However, two other studies that applied 16SrRNA gene sequencing found similar salivary levels of F. nucleatum relative abundance in cases and controls. The first study was conducted in the USA27, and saliva was collected by oral rinse with a commercial mouthwash, among 68 CRC cases and 122 controls. The second was conducted in Japan26, and included unstimulated saliva from 24 CRC cases (and other cancers of the digestive tract) and 118 controls. In both studies, Fusobacterium was not the dominant bacterium.Analysis with qPCR showed high detection rates of F. nucleatum in colorectal mucosa specimens in the controls, and it was even lower in the cases. At first, this finding might appear contradictory to previous reports finding F. nucleatum to be associated with CRN9. However, when considering the histologic type and the location of CRN in the patients in our study, our results can be seen to be consistent with those previous findings. Mima et al.38 analyzed 1,102 colorectal tumors with qPCR, in 13% of which F. nucleatum was detected. When analyzing by colorectal tumor site, F. nucleatum detection was 15% and 9% in proximal and distal-rectal sites, respectively. Also, in a previous study by Yu et al.39, where F. nucleatum was investigated in 280 CRNs and 20 healthy mucosa specimens from independent controls using FISH technique, that was further validated in 20 samples by F. nucleatum-specific PCR primers, F. nucleatum was prevalent in proximal serrated sessile adenomas, but rare in conventional adenomas39. According to that study, the frequency of F. nucleatum positivity  was 29% in proximal conventional adenomas, 24% in distal conventional adenomas, 79% in serrated sessile adenomas, 90% in proximal CRCs, 42% in distal CRCs, and 20% in healthy mucosa from independent controls. High abundance of invasive F. nucleatum  was present in 5.3% of proximal conventional adenomas, 2.4% of distal conventional adenomas, 49% of serrated sessile adenomas, 71% of proximal CRCs, 38% of distal CRCs, and none of the 20 healthy mucosa samples. We point out that the CRNs sampled in our study included 12 proximal conventional adenomas, 6 distal conventional adenomas, 2 serrated sessile adenomas and 2 distal CRCs, and that F. nucleatum was detected in a proximal conventional adenoma.We found a low global detection rate of F. nucleatum was usually either detected in both subject’s proximal and distal colon sites , or not detected at all in both colon sites. On the other hand, we noticed that F. nucleatum level in the ascending colon moderately correlated with level in the descending colon. This could probably be because some subjects naturally harbor F. nucleatum in their gut microbiome, whereas others do not, which can also explain the detection of F. nucleatum in healthy mucosa of some controls in many previous studies. We can also think F. nucleatum may be associated to the intestinal disorders that led patients in the control group to undergo colonoscopy, and that it may be particularly involved in the serrated neoplasia pathway (where sessile serrated adenomas are precursors to tumors with sporadic microsatellite instability), and less in the conventional adenoma-carcinoma sequence, as suggested by Yu et al.39.In this pilot study, we noticed that F. nucleatum in colorectal mucosa was much lower than in saliva, and few subjects had F. nucleatum detected in both sites. We found a moderate correlation between F. nucleatum level in saliva and healthy proximal colorectal mucosa in controls, but we could not explore this correlation in cases as F. nucleatum was detected in colorectal mucosa specimens of only one CRN case. The only data that could serve as comparison to our finding came from two previous studies that investigated F. nucleatum in a few samples of saliva and colorectal tumors in the same CRC cases, without control group and without bacterium quantification, as only conventional PCR (non-quantitative) was used28. F. nucleatum was detected less commonly in mucosa samples than in saliva in the first study 18, and in all specimens in the second one 28.Detection rate of F. nucleatum in both oral and colorectal body sites in patients diagnosed with CRN and CRN-free controls. Further studies that aim to assess the association between oral and colorectal levels of F. nucleatum in CRN cases are still needed and can draw from our methods and results in making study-design decisions, including the inclusion/exclusion criteria, selection of study participants, data collection instruments and analysis, and sample size calculation. They also should pay attention to both the histologic type and site of CRNs to be included, and optimally focus on proximal location and adenoma of sessile type. To quantify F. nucleatum in colorectal healthy mucosa, there may no longer be a need for collection and analysis of two different specimens from both proximal and distal colon sites, as one specimen  can be sufficiently informative, especially given that some patients may not consent to provide biopsies from healthy mucosa even if they agree to provide specimens of their tumor, which they know will be excised anyway. Finally, studies should generally plan a quantitative microbial analysis of F. nucleatum in saliva specimens: non-quantitative techniques  only assess the presence of the bacterium.In conclusion, concerning the objectives of the pilot study, our study findings provide potentially useful preliminary data on expression of F. nucleatum, in patients with precancerous lesions as well as cancerous lesions at different stages of colorectal malignant transformation, to overcome the difficulty of conducting prospective research on the causal role of the oral bacterium F. nucleatum in colorectal carcinogenesis. If the hypothesis of an intra-individual oral origin of the colorectal enrichment in F. nucleatum is confirmed, this may have potential impact on colorectal cancer prevention, diagnosis, and treatment. Thus, many studies are investigating the potential of candidate fecal bacteria as biomarkers for early detection of adenomatous polyps and colon cancer41. Under the same perspective, saliva can be a promising non-invasive screening tool for colorectal adenoma and cancer. Also, and more importantly, investigating the association between the oral and colorectal levels of F. nucleatum in colorectal neoplasms patients can advance the understanding of the mechanism(s) underlying the connection between periodontal disease and colorectal cancer, which may involve the translocation of periodontal pathogens to the gut and the release of their pro-oncogen and pro-inflammatory virulence products. Periodontal disease is suggested as a risk factor for periodontal disease42, but the mechanisms of the association have yet to be elucidated. Thus, a subsequent, larger epidemiological study on this topic is highly recommended.Our preliminary results encourage future research to investigate oral and colorectal enrichment in


Previous studies have associated visual working memory (VWM) capacity with the use of internal attention. Retrocues, which direct internal attention to a particular object or feature dimension, can improve VWM performance . However, so far, no study has investigated the relationship between VWM capacity and the magnitudes of RCBs obtained from object-based and dimension-based retrocues. The present study explored individual differences in the magnitudes of object- and dimension-based RCBs and their relationships with VWM capacity. Participants completed a VWM capacity measurement, an object-based cue task, and a dimension-based cue task. We confirmed that both object- and dimension-based retrocues could improve VWM performance. We also found a significant positive correlation between the magnitudes of object- and dimension-based RCB indexes, suggesting a partly overlapping mechanism between the use of object- and dimension-based retrocues. However, our results provided no evidence for a correlation between VWM capacity and the magnitudes of the object- or dimension-based RCBs. Although inadequate attention control is usually assumed to be associated with VWM capacity, the results suggest that the internal attention mechanism for using retrocues in VWM retention is independent of VWM capacity. Although VWM is flexible and goal-oriented, it can only retain limited information from the total sensory input. Using internal attention, which is the modulation and retention of internally generated information3, individuals can select or prioritize VWM content to facilitate efficient information storage. In the last two decades, many studies have examined internal attention’s influence on VWM5.Visual working memory (VWM) is an essential mental storage system that can briefly store visual information, integrating information from external inputs to create dynamic and continuous experiences. After forming VWM representations, individuals can mentally access and control them, even if the visual input disappears4. In a typical VWM task with retrocues, participants are asked to remember a memory array and complete a subsequent test. After the memory array disappears, a retroactive cue (retrocue) is presented to indicate which memory item is the most likely to be tested. Researchers found that, in a valid retrocue condition , VWM performance was better than that in a neutral cue condition7; thus, participants can benefit from retrocues in a VWM task. Improved VWM performance through the utilization of retrocues is called a retrocue benefit (RCB). The acquisition of RCB indicates that internal attention can improve the retention of VWM information.Internal attention’s effect on VWM representations has been extensively studied using retrocuesthe target item; e.g.16), exogenous cues , and feature cues . Dimension-based retrocues, by contrast, direct attention toward one visual dimension  of all the memory items30. Notably, feature-based cues and dimension-based cues differ: feature-based cues are used to direct attention to a specific object , while dimension-based cues are used to direct attention to a specific dimension of all objects instead of a specific object .Previous studies of retrocues in VWM tasks have mainly used two types of retrocues: object-based and dimension-based. Object-based retrocues direct attention to one or several items in the memory array, and such retrocues can be further divided into endogenous cues , thus reducing memory load. When using dimension-based retrocues, individuals cannot reduce the total number of VWM representations, but they can reduce the amount of information needed to retain in each representation. Since the influencing mechanisms of object-based and dimension-based internal attention for retaining VWM information may be different, it is necessary to investigate the effect of internal attention on VWM using separate object- and dimension-based retrocues.Early studies mostly investigated object-based retrocues’ influence on VWM representations4. Recent studies have also demonstrated improvement in VWM performance facilitated by dimension-based retrocues34 (but see a study by Maniglia and Souza33 that found no evidence for the dimension-based RCB). So far, however, there has been little discussion about what factors affect the magnitudes of object-based and dimension-based RCBs.A variety of studies have demonstrated that people can obtain benefit from object-based retrocues in VWM tasks37. Our recent study also found that, when memory stimuli were presented for a sufficiently long period, participants’ VWM capacity positively correlated with their ability to voluntarily “trade off” VWM numbers and precision . Since inadequate attention control is assumed to affect VWM capacity, inefficient use of object- or dimension-based internal attention to facilitate the retention of VWM information may also be associated with VWM capacity. However, no study has directly investigated the relationship between VWM capacity and the magnitudes of object-based and dimension-based RCBs.The magnitudes of object-based and dimension-based RCBs may be associated with other cognitive abilities . Many studies have found a correlation between individual differences in VWM capacity and attention control; for example, previous studies that used a change detection task to quantify VWM capacity found positive correlations between VWM capacity and the ability to filter distractors34, which found significant object- and dimension-based RCBs at a population level (using the mean performance of the sample). Namely, we expected to find that VWM performance under a valid cue condition would be better than that under a neutral cue condition for both dimension-based and object-based cue tasks. More importantly, since previous studies have found that VWM capacity is positively associated with attention control38, a tentative hypothesis is that there are positive correlations between VWM capacity and the magnitudes of RCBs. Lastly, the mechanisms of object-based and dimension-based RCBs may differ, but the utilization of object- and dimension-based retrocues can still involve overlapping  mechanisms of internal attention. We therefore predicted a positive correlation between the magnitudes of object-based and dimension-based RCBs.The present study aimed to explore the relationships between VWM capacity and the magnitudes of object-based and dimension-based RCBs. We used a change detection task to quantify VWM capacity, and then asked participants to conduct VWM recall tasks with object- and dimension-based retrocues. We expected to replicate the findings of previous studies regarding object- or dimension-based RCBsr = 0.30, with a statistical power of (1 − β) = 0.80 and α = 0.05 significance level39. The results indicated that 67 participants were required.Using G ∗ power 3.1.9.2, we calculated the minimum sample size to gain sufficient statistical power to detect a correlation strength of at least Declaration of Helsinki and approved by the Ethics Committee of Liaoning Normal University and the Ethics Committee of Sichuan Normal University. Sixty-eight volunteers , who were college students studying at the aforementioned universities, participated in this study in return for compensation. All participants reported having normal or corrected-to-normal vision, normal color vision, and no history of neurological problems. Participants provided written informed consent before participating in the study.Our study was conducted under the The experiment comprised three different tasks. First, participants completed a color change detection task, with which we measured their VWM capacity. Next, they completed two recall tasks . Half the participants completed the object-based task first, while the other half completed the dimension-based task first. The whole experiment was conducted in a dimly lit, soundproof room with 19-inch screens presenting the stimuli. The distance between participants and their screens was approximately 60 cm.In the color change detection task, six colored squares, each 0.65° × 0.65° , were displayed in a memory array in a 9.8° × 7.3° region surrounding a fixed central dot. The distance between any two colors had to be at least 3.5° (center-to-center).29. The memory stimuli were three colored bars , which were randomly presented at the four corners of an imaginary square with a diagonal of 6.0°. For both the dimension-based retrocue task and the object-based cue task, only endogenous cues were used, since the dimension-based cue task can only be applied with an endogenous cue. Specifically, in the dimension-based cue task, the dimension-based retrocues were the words “color and “orientation,” and the neutral retrocue was the word “random” . These retrocues were presented in black Simsun normal font (approximately 3.2° × 1.5°) at the center of the screen. In the object-based cue task, the object-based retrocue was a pair of central arrows (1.5° × 1.5°), both of which pointed to the location of one memory item. The neutral retrocue was a black cross (1.5° × 1.5°) at the center of the screen. For both object- and dimension-based cue tasks, the test array for the color recall trials comprised an outlined square and a color wheel , while that for the orientation task comprised an outlined square (1.2° × 1.2°) and a vertical white bar (1.1° × 0.4°). To reduce the similarity between memory items, the colors and orientations in the memory array were randomly selected from 360 possible colors  and 180 possible angles , with any two bars separated by at least 30 orientation degrees and 60 color steps.In the retrocue tasks, the stimuli were the same as the corresponding stimuli in our previous study40. As Fig. The conventional single-probed color change detection paradigm was used for the VWM capacity measurement29. Participants were asked to perform a dimension-based cue task with the trial structures depicted in Fig. The procedure for the dimension-based cue task was the same as the corresponding procedure in our previous study33) were conducted for each condition , with a total of 192 trials. Trials were fully randomized. The task lasted approximately 30 min. Instructions at the beginning of the task informed participants about the task, and participants completed at least 16 practice trials before completing the main task.Forty-eight trials , with a total of 192 trials. The trials were fully randomized. The task lasted approximately 30 min. Instructions at the beginning of the task informed participants about the task, and participants completed at least 16 practice trials before completing the main task.41, we quantified each participant’s VWM capacity based on their results in the color change detection task. Since our study used the single-probe change detection task42, the standard formula proposed by Cowan43 was applied: K = N × (H − F), where K is the VWM capacity, N is the set size of the memory array , H is the hit rate or proportion of correct responses when a change is present, and F is the false alarm rate or proportion of incorrect responses when no change is present.For the VWM capacity measurement, similar to studies that reported VWM capacity of participantsFor the object- and dimension-based cue tasks, we computed each participant’s response deviation for each experimental condition  by subtracting the target item’s value from the response. One main dependent variable used to represent the recall task performance was the deviation’s absolute value, which we called the “offset”. A larger offset signified worse memory performance.It is worth noting that the offset (VWM performance) depended on the defined color step or orientation degree. Because the response ranges of color (1–360 color steps) and orientation (1–180 orientation degree) differed, a larger offset in the color report trials than that in the orientation report trials did not mean that the color memory performance was worse than the orientation memory performance; thus, we did not directly compare the offset in the color report trials with the offset in the orientation report trials. Instead, we used the formula of the RCB index to standardize the magnitude of RCBs in the color and orientation report trials.The other main dependent variable used to represent RCB magnitude was the RCB index, which we defined as:To examine the existence of object- and dimension-based RCBs, we conducted repeated measures ANOVAs  for offsets with different cue types  and tasks (object-based cue task vs. dimension-based cue task) as within-subject factors. Two-tailed t-tests were conducted for follow-up comparisons of the object- and dimension-based cue tasks. Because the color and orientation reports in our recall tasks differed qualitatively, we conducted separate analyses for the offsets in the color and orientation report trials. To investigate the relationship between VWM capacity and the utilization of retrocues, we calculated the two-tailed Pearson’s correlation coefficients between VWM capacity and the RCB index (magnitude of RCB) for the different retrocues.44, we sorted participants into three groups on the basis of their VWM capacity  to visualize the relationship between VWM capacity and RCB indexes. Moreover, to analyze the effect of VWM capacity on RCB indexes at the population level, we conducted repeated measures ANOVAs for the RCB index with reported features (color vs. orientation) and tasks (object-based cue task vs. dimension-based cue task) as within-subject factors, and capacity group (high capacity vs. medium capacity vs. low capacity) as a between-subject factor.As in a previous study on VWM capacityp < 0.05 was used for all tests. All t-tests were conducted using a bootstrapping method , and Cohen’s d was used as an estimator of the effect size. Partial η2 was used as an estimator of the effect size for ANOVAs. A Bayes factor analysis (Bayesian t-test) was also used for reporting the t-test results45. The Bayes factor (BF10) provides an odds ratio for alternative/null hypotheses ; for example, a BF10 of 0.5 would indicate that the null hypothesis is two times more likely than the alternative hypothesis.A significance level of 2p = 0.712, of the task, F = 37.730, p < 0.001, η2p = 0.360, and a significant interaction between cue conditions and tasks, F = 69.336, p < 0.001, η2p = 0.510. Follow-up comparisons showed that the offset under the valid cue condition was significantly lower than that under the neutral cue condition for both the object-based cue task, t(67) = 13.742, p < 0.001, CI95% = , d = 1.84, BF10 > 10,000, and the dimension-based cue task, t(67) = 5.606, p < 0.001, CI95% = , d = 0.46, BF10 > 10,000.For the color report trials, Fig. 2p = 0.710, of the task, F = 47.859, p < 0.001, η2p = 0.417, and a significant interaction between cue conditions and tasks, F = 84.633, p < 0.001, η2p = 0.558. Follow-up comparisons showed that the offset under the valid cue condition was significantly lower than that under the neutral cue condition for both the object-based cue task, t(67) = 14.640, p < 0.001, CI95% = , d = 1.24, BF10 > 10,000, and the dimension-based cue task, t(67) = 2.652, p = 0.01, CI95% = , d = 0.19, BF10 = 3.345. We conducted a correlation analysis to explore the relationship between VWM capacity and offset (memory performance) under each condition for different tasks. Because the focus of the study was on the relationship between VWM capacity and the RCB index, the results and discussion of the relationship between VWM capacity and memory performance are reported and discussed in the Supplementary Material For the orientation report trials, Fig. These results of offsets showed that, for both the color and orientation report trials, participants were able to significantly improve their VWM performance using object- and dimension-based cues. These findings suggest that the object- and dimension-based RCBs in our study were significant.46. The correlation results showed no significant correlation between VWM capacity and the RCB indexes of the object- or dimension-based cue tasks ; that is, contrary to our expectations, we found no evidence for a correlation between VWM capacity and the magnitudes of RCBs.Table p < 0.01) while no significant correlation was found between the magnitudes of the RCBs for the object- and dimension-based cues in the orientation report trials  was 2.52 ± 0.94. Participants were sorted into three groups  on the basis of their VWM capacity. The one-third split on the K scores resulted in 22 participants  in the high VWM capacity group (M = 3.60 ± 0.64), 24 participants  in the medium VWM capacity group (M = 2.42 ± 0.20), and 22 participants  in the low VWM capacity group (M = 1.54 ± 0.36).p < 0.001, η2p = 0.306, of the task, F = 241.577, p < 0.001, η2p = 0.788. All the other main effects and interaction effects were non-significant . These results showed no impact of VWM capacity on object- or dimension-based RCB index. Again, the results provided no evidence for the difference in the object- or dimension-based RCB index between the different VWM capacity groups.Figure 34, our results at the population level showed that VWM performance could be improved by using both object- and dimension-based retrocues. Our findings for the existence of RCBs at the population level enabled us to further investigate correlations at the individual level; however, we found no evidence for correlations between the magnitudes of RCBs and VWM capacity. Our results did not support the idea that the efficient use of internal attention to facilitate the retention of VWM information is associated with VWM capacity. Previous studies have associated participants’ VWM capacity with the ability of attention control to filter distractors or “trade off” quantity and quality of VWM representations40. The current results implied that, besides attention control, participants can use another kind of attention  to affect VWM retention by using retrocues. Importantly, the mechanism for using retrocues to improve VWM differs from the mechanism for distractor filtering or trading off quantity and quality of VWM representations; thus, previous findings on the relationship between VWM capacity and attention control cannot explain the internal attention processing involved in the present study.The main purpose of the present study was to explore the relationship between VWM capacity and the magnitudes of RCBs. In line with previous findings supporting object- and dimension-based RCBs47. Participants who could retain information in the iconic memory for longer could have obtained greater RCB, because iconic memory assisted the allocation of internal attention; thus, the RCB indexes in our study may have been affected by individual differences in the duration of iconic memory retention. Using a longer ISI could prevent this potential problem. Moreover, in addition to iconic memory and VWM, recent studies have suggested that a third memory stage, termed fragile visual short-term memory (FM), exists between iconic memory and VWM. FM has a large capacity (more than eight items) and long duration50. FM can exist almost as long as VWM without interference from a new stimulus. Individuals can selectively transfer cued FM to VWM via internal attention to obtain RCB. Since the capacity of FM is independent of VWM capacity49, RCBs may be related to FM capacity rather than VWM capacity. Future research could examine the possible impacts of iconic memory and FM on RCBs.The magnitude of RCB may be affected by other memory factors besides VWM capacity. The interstimulus interval (ISI) between the memory array and retrocue was 500 ms in our study. It has been suggested that information can linger in iconic memory, which is a fast decaying store of visual information, for about 500 ms31 and, in line with our results, found moderate positive correlations between object- and dimension-based RCB indexes. Previous studies have demonstrated that orientation stimuli require a larger VWM consolidation bandwidth than color stimuli52. Participants had more difficulty completing orientation report trials under valid cue conditions (resulting in a larger guess rate) for the dimension-based cue task than for the object-based cue task. This could have weakened the correlation between the object- and dimension-based RCB indexes in the orientation report trials, resulting in the only positive correlation in color report trials observed in our study.Besides the relationship between VWM capacity and RCB indexes, we also examined the relationship between the RCB indexes for object-based retrocues and dimension-based retrocues. We found that in the color report trials, the participants who benefitted most from object-based retrocues also benefitted most from dimension-based retrocues, but there was no correlation between the object-based RCB and the dimension-based RCB in the orientation report trials. The results suggested that—at least for the color reports—the object-based and dimension-based RCBs may share an overlapping internal attention mechanism. A recently published study also examined the relationship between object-based and dimension-based RCBsIt is worth noting that there was an inherent difference in the memory load imposed by the object-based and dimension-based cue tasks in our study. Although the neutral cue conditions for the object- and dimension-based cue task were similar, the task difficulty (storage requirements) for the valid cue conditions of the two tasks differed. In the object-based cue task, after the retrocue was presented, participants only needed to retain two features (one color and one orientation) of one object, but in the dimension-based cue task, they needed to retain three features (three colors or three orientations) of three objects. This led to worse performance under valid cue conditions for dimension-based cue tasks than for object-based cue tasks. As a result, the magnitude of dimension-based RCB was expected to be smaller than that of object-based RCB, and our results showed that the average RCB index for all participants obtained via object-based retrocues (41.05% ± 0.13) was larger than the average RCB index obtained via dimension-based retrocues (9.45% ± 0.15). This indicated that participants did not obtain as many benefits from dimension-based retrocues as from object-based retrocues because of our experimental design. The correlation between the magnitudes of the object- and dimension-based RCBs could have been weakened by the set size of the memory arrays in our study.31’s study), because participants were expected to have near-perfect performance if they only needed to memorize two or fewer items1. The ceiling effect of VWM performance could have reduced the difference between the neutral cue condition and the valid cue condition for the retrocue task, resulting in a weakening of RCBs. Indeed, our previous study found that the dimension-based RCB index for remembering three double-feature items was larger than that for remembering two double-feature items29. Since the research on the dimension-based RCB is very limited, we designed the experiment to require participants to memorize three items instead of two items to maximize the dimension-based RCB.We should point out that the main purpose of our experimental design was to investigate the relationship between VWM capacity and the magnitude of RCBs, rather than directly compare object-based and dimension-based RCBs. We did not choose fewer items for the memory arrays  were larger than the RCB indexes for the orientation report trials . Due to the qualitative difference between the offsets of the color (color steps) and orientation report trials (orientation degrees), the latter may not have been inherently more difficult than the former. This difference between the RCB indexes for the color and orientation report trials could have been affected by factors other than the features; for example, the set size of memory array could have affected the difference in RCB indexes between the color and orientation report trials. By using a similar paradigm for the dimension-based cue task, our previous results showed that when participants needed to memorize three items, the dimension-based RCB index for color report trials was 56% larger than for orientation report trials. However, when the participants only needed to memorize two items, the dimension-based RCB index for color report trials was only 3% larger than for the orientation report trials4, only a handful of recent studies have investigated whether people can improve their VWM performance by using dimension-based retrocues34. The results of our study provide new evidence for the existence of dimension-based RCB. However, previous studies obtained contradictory results regarding dimension-based RCB. In addition to those studies supporting the existence of dimension-based RCB34, a recent study by Maniglia and Souza33 found no evidence for the existence of dimension-based RCB in a young adult group. Here, we propose two possible reasons for the null result in Maniglia and Souza33 study. Firstly, unlike object-based RCB, dimension-based RCB may be difficult to observe. In Maniglia and Souza33’s study, participants needed to remember six double-feature items in each trial That is, they still needed to retain six features after the dimension-based retrocues appeared. Since young adults’ VWM capacity is about three to four units53, the information that participants needed to retain exceeded their VWM capacity, which may cause the floor effect under both neutral cue and valid cue conditions, resulting in the null result for dimension-based RCB. Secondly, Maniglia and Souza33’s task was more complicated than other studies. Their trials using dimension-based retrocues were randomly dispersed among trials with dimension-based precues. Because the use of retrocues and precues involves different mechanisms, participants who are accustomed to using dimension-based precues may be less able to use dimension-based retrocues. Future studies on the dimension-based RCB should take these possibilities into account.Although extensive studies over the past decade have repeatedly supported the acquisition of RCBs through using object-based retrocues40, we found no support for the claim that participants with high VWM capacity can obtain greater RCB than low-capacity participants using either object- or dimension-based retrocues; hence, individual differences in the RCB indexes cannot be explained by limited VWM capacity. Since far too little attention has been paid to the factors that affect the magnitudes of RCBs , our study improves the understanding of RCBs as well as the internal attention mechanism in VWM retention.In conclusion, the current study provides new evidence for the existence of object- and dimension-based RCBs, suggesting that the influencing mechanisms of object- and dimension-based internal attention on VWM retention partly overlap. More importantly, although inefficient attention control is usually associated with VWM capacitySupplementary Information.


Disseminated mucormycosis presenting with multiple subcutaneous nodules is a rare condition with a poor prognosis, and delayed diagnosis and treatment is common.Acinetobacter baumannii pneumonia and respiratory failure. Following 10 days after her admission to the intensive care unit, she developed hospital-acquired pneumonia. Five days later, multiple subcutaneous nodules appeared on both arms and both legs. Bronchoalveolar lavage and skin biopsy cultures both grew Mucor spp. She was diagnosed with disseminated mucormycosis and was treated with liposomal amphotericin B at a dose of 5 mg/kg/day. Despite treatment, our patient succumbed to septic shock and multiorgan failure on the third day after definitive diagnosis.We report a case of 64-year-old Thai woman with colorectal cancer who initially presented with This case demonstrates that the subcutaneous nodules caused by hematogenously disseminated mucormycosis are unusual in a patient with a solid tumor. Clinicians should be aware of this atypical presentation of mucormycosis in patients with solid tumors. Rhizopus spp., Mucor spp. and Lichtheimia spp., are typically found in decaying organic material and in soil . PComparing the immediately aforementioned case report with our patient, both patients were critically ill, and both had some degree of immunosuppression. Nevertheless, our patient received hydrocortisone at dosage of 2000 mg, which is equivalent to prednisolone at dosage of 500 mg. A previous study demonstrated that high corticosteroid use (> 600 mg) was associated with mucormycosis . Recent Aspergillus colonization.Diagnosis of mucormycosis with cutaneous manifestation is quite difficult since most physicians are unfamiliar with the disease spectrum. Histopathology remains the standard diagnostic method. The biopsy specimen should be taken from the center of the lesion, and should include subcutaneous tissue because the fungi usually invade blood vessels in the deep cutaneous and subcutaneous layer . Fungal Treatment of mucormycosis consists of early antifungal treatment, adequate surgery, and reversal of immunosuppression . The recThe significance of the case described relates to an episode of disseminated mucor, including skin manifestations, in a patient with a history of solid tumor and recent prolonged steroid use. Thus, the presence of subcutaneous nodules with bleb or necrosis in a critically ill patient should prompt further investigation to exclude mucormycosis as the possible cause.Disseminated mucormycosis can occur in critically ill patients. Cutaneous involvement as a result of disseminated mucormycosis is a rare, but serious disease. Early diagnosis and appropriate antifungal therapy are needed to improve patient outcome.


This study aimed to clarify the variability in the independence profiles of specific activities of daily living (ADL) among older men and women. The research subjects were 5872 older adults (1143 men and 4729 women) certified as requiring nursing care or support (based on data obtained from the nursing care insurance certification survey database) who could be surveyed in both 2009 and 2018. Using item response theory, this study compared longitudinal data of difficulties faced by older adults during ADL. The results indicated that among the long-term care insurance-certified persons, in 2009, men had higher ADL difficulty than women in all ADL items, and in 2018, there was no significant difference in items other than dressing and excretion. Furthermore, the difference in the rate of ADL difficulty level over 9 years was significantly higher in women than in men. It was shown that the progression of ADL disability due to aging is faster in men on a yearly basis, but it increases in women with aging. Therefore, it was suggested that the rate of ADL difficulty varies depending on age and sex. In Japan, over the last few decades, the number of people eligible for long-term care has nearly tripled, from 2.18 million in 2000 to 6.08 million in 2015. . It is cJapanese people have a relatively long life expectancy, but the difference between average life expectancy and healthy life expectancy  is 9.13 years for men and 12.68 years for women . Women’sIn general, physical functionality, especially among dependent older adults, is determined by their ability to undertake ADL, which decreases with age . ADL conThis study aimed to (1) assess long-term changes in independence levels, (2) assess the activity-specific independence levels of older adults requiring physical assistance and supervision to perform ADL, and (3) investigate the differences in these matters between men and women. Generating knowledge regarding this progression pattern may aid in the identification of older adult groups at high risk of disability—an important process to ensure the well-informed creation of targeted interventions aimed at maintaining their independence. Clarifying which ADL abilities are maintained and which diminish with age also contributes significantly to long-term care prevention priorities and support priorities. If it is possible to clarify the mode of reduction of ADL disorder among older men and women, it may be possible to contribute to the extension of healthy life expectancy and new strategies for long-term care prevention.n = 576) were excluded from the analysis. This resulted in a follow-up rate of 91.1% (5872/6448). The LTCI system was implemented by the Japanese government in 2000 to address the accelerating rate of population aging and older adults’ increasing need for care [For this retrospective study, we used the 2009–2018 long-term care insurance (LTCI) certification data from City A, Japan. We identified 5872 subjects requiring long-term care who could be tracked for nine years . Subjects who could not be tracked in 2018 , Mobility, Eating, Urination, Defecation, Grooming , Upper-body dressing, and Lower-body dressing. Depending on the degree of assistance required, all items were scored from 1 to 4—except for Grooming, as its items were scored from 1 to 3. Higher scores indicated a lower daily functioning ability in that item and an increased need for assistance . Based ox is a log of the odds of endorsing each activity , reflecting participants’ disability level. β, which is the coefficient of IRT, is a parameter of the difficulty level and is based on 0. The difficulty level becomes lower in the negative direction and higher in the positive direction. Additionally, β is a curve that shifts from the left to the right as the value increases, reflecting the severity of the disability for each activity. The difference between β in 2009 and 2018 was calculated, and the difference between men and women was examined by a nonparametric test. All statistical analyses were performed using R 3.5.2 software .A chi-square test was performed with the ADL non-independence rate to determine if there were significant differences for this variable between 2009 and 2018 as well as between men and women. Furthermore, based on item reaction theory (IRT), the data of each item were approximated onto a logistic model, where long-term changes in participants’ independence level for each specific ADL were estimated. IRT can be used to rank items unequivocally along a hierarchy based on their difficulty, as follows:Saitama Prefectural University and municipal government signed the memorandum of data handling according to the local government regulation for privacy policy. Additionally, the Ethics Committee of Saitama Prefectural University approved the procedure of this study with anonymized database (No. 20019) in 17 June 2020.p < 0.0001 for all items). Contrarily, in 2018, the non-independent rate of Upper-body dressing, Lower-body dressing, Urination, and Defecation in men was significantly higher, and there was no difference between men and women in other specific ADL items.In the 2018 sample, Grooming (89.8%) still had the highest non-independence rate, which was followed by Bathing (85.1%), Upper-body dressing (68.4%), Urination (66.2%), Defecation (64.0%), Lower-body dressing (62.9%), Mobility (62.2%), Transfer (49.9%), and Eating (9.0%). Specifically, owing to aging, specific ADL non-independence rates were significantly higher in 2018 than in 2009 for all subjects, regardless of sex. The non-independence rate of all specific ADL among men was higher than that among women in 2009 . In terms of IRT, ADL difficulty was significantly higher in 2018 than in 2009 for all subjects, regardless of sex. In 2009, for the overall sample and for women, the difficulty level in descending order (highest to lowest) was as follows: Grooming, Bathing, Upper-body dressing, Lower-body dressing, Mobility, Urination, Defecation, Transfer, and Eating. For men, the same ranking was as follows: Grooming, Bathing, Upper-body dressing, Lower-body dressing, Urination, Mobility, Defecation, Transfer, and Eating. In 2018, nonetheless, this ranking for the overall sample was as follows: Grooming, Bathing, Lower-body dressing, Upper-body dressing, Urination, Defecation, Mobility, Transfer, and Eating. In other words, the rankings across the three groups were the same in the second assessment period. Furthermore, the difference in β between 2009 and 2018, that is, the rate of increase in difficulty level, was significantly higher in women than in men. In 2018, the curve of the model was displaced to the right in all items when compared to 2009, with the probability of independence having decreased (The IRT results are shown in ecreased .The X-axis denotes each person’s disability level. The Y-axis denotes the probability of independence for each activity. The dotted line represents the 2008 sample, and the solid line represents the 2018 sample. In 2018, the curve of the model shifted to the right, meaning that the difficulty increased for all items when compared to 2009.Similarly for men, in 2018, the curve of the model shifted to the right, meaning that the difficulty increased for all items when compared to 2009. Both years were generally shifted to the right, suggesting that ADL difficulty is high in men. The changes in 2009 and 2018 were particularly remarkable in grooming, bathing, urination, and defecation, but the changes in other items were relatively small.Similarly for women, in 2018, the curve of the model shifted to the right, meaning that the difficulty increased for all items when compared to 2009. Similar to men, the changes in 2009 and 2018 were particularly remarkable in grooming, bathing, urination, and defecation, but it was suggested that the changes in each item were larger than in men.This study corroborated that the proportion of people who had difficulty remaining independent in their ADL increased with age in both men and women. Past studies have shown that the pattern of ADL disabilities in geriatric populations follows a distinct progression ,21,22,28This study’s results suggest that the order of independence probabilities according to each activity item is generally the same, although the independence levels of various activities in ADL do decrease over the long term. Shinkai et al. reported that the number of people with disabilities increases with age, which corroborates the current study’s findings . This stThis study has some limitations. First, the findings were limited to residents within the LTCI system and therefore, they may reflect the idiosyncratic nature of those receiving treatment, nursing care, and functional assessments within one large healthcare system. In order to generalize this study’s findings, the survey should be expanded to general older adults and middle-aged people. Second, in this study, the factors of difficulty for each ADL item were not clarified. Further research is needed to clarify these factors in terms of the order of difficulty of each item.This study reveals that among the long-term care insurance certified persons, in 2009, men had higher ADL difficulty than women in all ADL items, and in 2018, there was no significant difference in items other than changing clothes and excretion. Furthermore, the difference in β over 9 years was significantly larger in women than in men. In other words, it was shown that the progression of ADL disability due to aging is faster in men on a yearly basis, but it increases in women with aging. It was suggested that men with ADL disorder had many other ADL disabilities from the beginning, and that once women had an ADL disorder, their ADL ability declined sharply with aging. This suggestion may indicate that we need comprehensive ADL support for men and local and staged interventions for women when providing interventions for older adults in need of care. Furthermore, the difficulty levels were relatively low for Eating and Transfer and were high for Grooming and Bathing. Therefore, our study results will assist healthcare practitioners in understanding and anticipating specific target areas for interventions aimed at older adults. In other words, the findings from this study provide useful information for the development of effective care prevention plans that aim to maintain the independence of older adults.