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The polyphenol resveratrol has been suggested to exert beneficial effects on memory and the aging hippocampus due to calorie-restriction mimicking effects. However, the evidence based on human interventional studies is scarce. We therefore aimed to determine the effects of resveratrol on memory performance, and to identify potential underlying mechanisms using a broad array of blood-based biomarkers as well as hippocampus connectivity and microstructure assessed with ultra-high field magnetic resonance imaging (UHF-MRI). In this double-blind, randomized controlled trial, 60 elderly participants (60–79 years) with a wide body-mass index (BMI) range of 21–37 kg/m2 were randomized to receive either resveratrol (200 mg/day) or placebo for 26 weeks (registered at ClinicalTrials.gov: NCT02621554). Baseline and follow-up assessments included the California Verbal Learning Task (CVLT, main outcome), the ModBent task, anthropometry, markers of glucose and lipid metabolism, inflammation and neurotrophins derived from fasting blood, multimodal neuroimaging at 3 and 7 T, and questionnaires to assess confounding factors. Multivariate repeated-measures ANOVA did not detect significant time by group effects for CVLT performance. There was a trend for preserved pattern recognition memory after resveratrol, while performance decreased in the placebo group (n.s., p = 0.07). Further exploratory analyses showed increases in both groups over time in body fat, cholesterol, fasting glucose, interleukin 6, high sensitive C-reactive protein, tumor necrosis factor alpha and in mean diffusivity of the subiculum and presubiculum, as well as decreases in physical activity, brain-derived neurotrophic factor and insulin-like growth factor 1 at follow-up, which were partly more pronounced after resveratrol. This interventional study failed to show significant improvements in verbal memory after 6 months of resveratrol in healthy elderly with a wide BMI range. A non-significant trend emerged for positive effects on pattern recognition memory, while possible confounding effects of unfavorable changes in lifestyle behavior, neurotrophins and inflammatory markers occurred. Our findings also indicate the feasibility to detect (un)healthy aging-related changes in measures of hippocampus microstructure after 6 months using 7T diffusion MRI. More studies incorporating a longer duration and larger sample size are needed to determine if resveratrol enhances memory performance in healthy older adults. •In this randomized clinical trial, 6 months resveratrol supplementation showed no significant effects on verbal memory compared to placebo.•Unfavorable changes in lifestyle factors at follow-up might have introduced confounding.•Secondary analyses showed a trend towards preserved pattern recognition.•We used multimodal ultra high field MRI to detect subtle changes in microstructure of hippocampus subfields.

Findings in the domain of spoken word recognition have indicated that lexical representations contain both abstract and episodic information. It has been proposed that processing time determines when each source of information is recruited, with increased processing time being required to access lower-frequency episodic instantiations. The time-course hypothesis of specificity effects has thus identified a strong role for retrieval mechanisms mediating the use of abstract versus episodic information. Here we conducted three recognition memory experiments to examine whether the findings previously attributed to retrieval mechanisms might instead reflect attention during encoding. The results from Experiment 1 showed that talker-specificity effects emerged when subjects attended to the individual speakers, but not when they attended to lexical characteristics, during encoding, even though processing times at retrieval were equivalent. The results from Experiment 2 showed that talker-specificity effects emerged when listeners attended to talker gender but not when they attended to syntactic characteristics, even though the processing times at retrieval were significantly longer in the latter condition. The results from Experiment 3 showed no talker-specificity effects when all listeners attended to lexical characteristics, even when processing at retrieval was slowed by the addition of background noise. Collectively, these results suggest that when processing time during retrieval is decoupled from encoding factors, it fails to predict the emergence of talker-specificity effects. Rather, attention during encoding appears to be the putative variable.

Visual adaptation is expected to improve visual performance in the new environment. This expectation has been contradicted by evidence that adaptation sometimes decreases sensitivity for the adapting stimuli, and sometimes it changes sensitivity for stimuli very different from the adapting ones. We hypothesize that this pattern of results can be explained by a process that optimizes sensitivity for many stimuli, rather than changing sensitivity only for those stimuli whose statistics have changed. To test this hypothesis, we measured visual sensitivity across a broad range of spatiotemporal modulations of luminance, while varying the distribution of stimulus speeds. The manipulation of stimulus statistics caused a large-scale reorganization of visual sensitivity, forming the orderly pattern of sensitivity gains and losses. This pattern is predicted by a theory of distribution of receptive field characteristics in the visual system.

Background Chronic pain can disrupt the cortical representation of a painful body part. This disruption may play a role in maintaining the individual’s pain. Tactile acuity training has been used to normalise cortical representation and reduce pain in certain pain conditions. However, there is little evidence for the effectiveness of this intervention for chronic low back pain (CLBP). The primary aim of this study was to inform the development of a fully powered randomised controlled trial (RCT) by providing preliminary data on the effect of tactile acuity training on pain and function in individuals with CLBP. The secondary aim was to obtain qualitative feedback about the intervention. Methods In this mixed-methods pilot RCT 15 individuals were randomised to either an intervention (tactile acuity training) or a placebo group (sham tactile acuity training). All participants received 3 sessions of acuity training (intervention or sham) from a physiotherapist and were requested to undertake daily acuity home training facilitated by an informal carer (friend/relative). All participants also received usual care physiotherapy. The primary outcome measures were pain (0-100visual analogue scale (VAS)) and function (Roland Morris Disability Questionnaire (RMDQ)). Participants and their informal carers were invited to a focus group to provide feedback on the intervention. Results The placebo group improved by the greatest magnitude for both outcome measures, but there was no statistically significant difference (Mean difference (95%CI), p-value) between groups for change in pain (25.6 (-0.7 to 51.9), p = 0.056) or function (2.2 (-1.6 to 6.0), p = 0.237). Comparing the number of individuals achieving a minimally clinically significant improvement, the placebo group had better outcomes for pain with all participants achieving ≥30% improvement compared to only a third of the intervention group (6/6 vs. 3/9, p = 0.036). Qualitatively, participants reported that needing an informal carer was a considerable barrier to the home training component of the study. Conclusions This pilot RCT found tactile acuity training to be no more effective than sham tactile acuity training for function and less effective for pain in individuals with CLBP. That the intervention could not be self-applied was a considerable barrier to its use. Trial registration ISRCTN: ISRCTN98118082

To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r = .97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r = .54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed.

Distinct scientific theories can make similar predictions. To adjudicate between theories, we must design experiments for which the theories make distinct predictions. Here we consider the problem of comparing deep neural networks as models of human visual recognition. To efficiently compare models’ ability to predict human responses, we synthesize controversial stimuli: images for which different models produce distinct responses.We applied this approach to two visual recognition tasks, handwritten digits (MNIST) and objects in small natural images (CIFAR-10). For each task, we synthesized controversial stimuli to maximize the disagreement among models which employed different architectures and recognition algorithms. Human subjects viewed hundreds of these stimuli, as well as natural examples, and judged the probability of presence of each digit/object category in each image. We quantified how accurately each model predicted the human judgments. The best-performing models were a generative analysis-by-synthesis model (based on variational autoencoders) for MNIST and a hybrid discriminative–generative joint energy model for CIFAR-10. These deep neural networks (DNNs), which model the distribution of images, performed better than purely discriminative DNNs, which learn only to map images to labels. None of the candidate models fully explained the human responses. Controversial stimuli generalize the concept of adversarial examples, obviating the need to assume a ground-truth model. Unlike natural images, controversial stimuli are not constrained to the stimulus distribution models are trained on, thus providing severe out-of-distribution tests that reveal the models’ inductive biases. Controversial stimuli therefore provide powerful probes of discrepancies between models and human perception.

Humans have a striking ability to infer meaning from even the sparsest and most abstract forms of narratives. At the same time, flexibility in the form of a narrative is matched by inherent ambiguity in its interpretation. How does the brain represent subtle, idiosyncratic differences in the interpretation of abstract and ambiguous narratives? In this fMRI study, subjects were scanned either watching a novel 7-min animation depicting a complex narrative through the movement of geometric shapes, or listening to a narration of the animation's social story. Using an intersubject representational similarity analysis that compared interpretation similarity and neural similarity across subjects, we found that the more similar two people's interpretations of the abstract shapes animation were, the more similar were their neural responses in regions of the default mode network (DMN) and fronto-parietal network. Moreover, these shared responses were modality invariant: the shapes movie and the verbal interpretation of the movie elicited shared responses in linguistic areas and a subset of the DMN when subjects shared interpretations. Together, these results suggest a network of high-level regions that are not only sensitive to subtle individual differences in narrative interpretation during naturalistic conditions, but also resilient to large differences in the modality of the narrative. •Shared narrative interpretation is correlated with neural similarity in DMN and FCPN.•Neural responses in DMN depend on shared interpretation, not stimulus modality.•Intersubject representation similarity analysis can detect individual differences.

How learning enhances neural representations for behaviorally relevant stimuli via activity changes of cortical cell types remains unclear. We simultaneously imaged responses of pyramidal cells (PYR) along with parvalbumin (PV), somatostatin (SOM), and vasoactive intestinal peptide (VIP) inhibitory interneurons in primary visual cortex while mice learned to discriminate visual patterns. Learning increased selectivity for task-relevant stimuli of PYR, PV and SOM subsets but not VIP cells. Strikingly, PV neurons became as selective as PYR cells, and their functional interactions reorganized, leading to the emergence of stimulus-selective PYR–PV ensembles. Conversely, SOM activity became strongly decorrelated from the network, and PYR–SOM coupling before learning predicted selectivity increases in individual PYR cells. Thus, learning differentially shapes the activity and interactions of multiple cell classes: while SOM inhibition may gate selectivity changes, PV interneurons become recruited into stimulus-specific ensembles and provide more selective inhibition as the network becomes better at discriminating behaviorally relevant stimuli.

Background Emotionally salient information in spoken language can be provided by variations in speech melody (prosody) or by emotional semantics. Emotional prosody is essential to convey feelings through speech. In sensori-neural hearing loss, impaired speech perception can be improved by cochlear implants (CIs). Aim of this study was to investigate the performance of normal-hearing (NH) participants on the perception of emotional prosody with vocoded stimuli. Semantically neutral sentences with emotional (happy, angry and neutral) prosody were used. Sentences were manipulated to simulate two CI speech-coding strategies: the Advance Combination Encoder (ACE) and the newly developed Psychoacoustic Advanced Combination Encoder (PACE). Twenty NH adults were asked to recognize emotional prosody from ACE and PACE simulations. Performance was assessed using behavioral tests and event-related potentials (ERPs). Results Behavioral data revealed superior performance with original stimuli compared to the simulations. For simulations, better recognition for happy and angry prosody was observed compared to the neutral. Irrespective of simulated or unsimulated stimulus type, a significantly larger P200 event-related potential was observed for happy prosody after sentence onset than the other two emotions. Further, the amplitude of P200 was significantly more positive for PACE strategy use compared to the ACE strategy. Conclusions Results suggested P200 peak as an indicator of active differentiation and recognition of emotional prosody. Larger P200 peak amplitude for happy prosody indicated importance of fundamental frequency (F0) cues in prosody processing. Advantage of PACE over ACE highlighted a privileged role of the psychoacoustic masking model in improving prosody perception. Taken together, the study emphasizes on the importance of vocoded simulation to better understand the prosodic cues which CI users may be utilizing.

Cultured neural networks in vitro have demonstrated the biocomputing capability to recognize patterns. However, the underlying mechanisms behind information processing and pattern recognition remain less understood. Here, we developed an in vitro neural network integrated with microelectrode arrays (MEAs) to explore the network’s classification capability and elucidate the mechanisms underlying this classification. After applying different stimulation patterns using MEAs, the network exhibited structural alterations and distinct electrical responses that recognized various stimulation patterns. Alongside the reshaping of network structures, repeated training increased recognition accuracy for each stimulation pattern. Additionally, it was reported for the first time that spontaneous networks after stimulation are more closely related to the structures of evoked networks. This work provides new insights into the structural changes underlying information processing and contributes to our understanding of how cultured neural networks respond to different patterns.