The cerebellum acts as the analog to the medial temporal lobe for sensorimotor memory.

The cerebellum is critical for sensorimotor learning. The specific contribution that it makes, however, remains unclear. Inspired by the classic finding that, for declarative memories, medial temporal lobe structures provide a gateway to the formation of long-term memory but are not required for short-term memory, we hypothesized that, for sensorimotor memories, the cerebellum may play an analogous role. Here we studied the sensorimotor learning of individuals with severe ataxia from cerebellar degeneration. We dissected the memories they formed during sensorimotor learning into a short-term temporally-volatile component, that decays rapidly with a time constant of just 15-20sec and thus cannot lead to long-term retention, and a longer-term temporally-persistent component that is stable for 60 sec or more and leads to long-term retention. Remarkably, we find that these individuals display dramatically reduced levels of temporally-persistent sensorimotor memory, despite spared and even elevated levels of temporally-volatile sensorimotor memory. In particular, we find both impairment that systematically increases with memory window duration over shorter memory windows (<12 sec) and near-complete impairment of memory maintenance over longer memory windows (>25 sec). This dissociation uncovers a new role for the cerebellum as a gateway for the formation of long-term but not short-term sensorimotor memories, mirroring the role of the medial temporal lobe for declarative memories. It thus reveals the existence of distinct neural substrates for short-term and long-term sensorimotor memory, and it explains both newly-identified trial-to-trial differences and long-standing study-to-study differences in the effects of cerebellar damage on sensorimotor learning ability. Significance Statement: A key discovery about the neural underpinnings of memory, made more than half a century ago, is that long-term, but not short-term, memory formation depends on neural structures in the brain's medial temporal lobe (MTL). However, this dichotomy holds only for declarative memories - memories for explicit facts such as names and dates - as long-term procedural memories - memories for implicit knowledge such as sensorimotor skills - are largely unaffected even with substantial MTL damage. Here we demonstrate that the formation of long-term, but not short-term, sensorimotor memory depends on a neural structure known as the cerebellum, and we show that this finding explains the variability previously reported in the extent to which cerebellar damage affects sensorimotor learning.

Subtle Visual Latency Can Profoundly Impair Implicit Sensorimotor Learning.

Short sub-100ms visual feedback latencies are common in many types of human-computer interactions yet are known to markedly reduce performance in a wide variety of motor tasks from simple pointing to operating surgical robotics. These latencies are also present in the computer-based experiments used to study the sensorimotor learning that underlies the acquisition of motor performance. Inspired by neurophysiological findings showing that cerebellar LTD and cortical LTP would both be disrupted by sub-100ms latencies, we hypothesized that implicit sensorimotor learning may be particularly sensitive to these short latencies. Remarkably, we find that improving latency by just 60ms, from 85 to 25ms in latency-optimized experiments, increases implicit learning by 50% and proportionally decreases explicit learning, resulting in a dramatic reorganization of sensorimotor memory. We go on to show that implicit sensorimotor learning is considerably more sensitive to latencies in the sub-100ms range than at higher latencies, in line with the latency-specific neural plasticity that has been observed. This suggests a clear benefit for latency reduction in computer-based training that involves implicit sensorimotor learning and that across-study differences in implicit motor learning might often be explained by disparities in feedback latency.

A double dissociation between savings and long-term memory in motor learning.

Memories are easier to relearn than learn from scratch. This advantage, known as savings, has been widely assumed to result from the reemergence of stable long-term memories. In fact, the presence of savings has often been used as a marker for whether a memory has been consolidated. However, recent findings have demonstrated that motor learning rates can be systematically controlled, providing a mechanistic alternative to the reemergence of a stable long-term memory. Moreover, recent work has reported conflicting results about whether implicit contributions to savings in motor learning are present, absent, or inverted, suggesting a limited understanding of the underlying mechanisms. To elucidate these mechanisms, we investigate the relationship between savings and long-term memory by experimentally dissecting the underlying memories based on short-term (60-s) temporal persistence. Components of motor memory that are temporally-persistent at 60 s might go on to contribute to stable, consolidated long-term memory, whereas temporally-volatile components that have already decayed away by 60 s cannot. Surprisingly, we find that temporally-volatile implicit learning leads to savings, whereas temporally-persistent learning does not, but that temporally-persistent learning leads to long-term memory at 24 h, whereas temporally-volatile learning does not. This double dissociation between the mechanisms for savings and long-term memory formation challenges widespread assumptions about the connection between savings and memory consolidation. Moreover, we find that temporally-persistent implicit learning not only fails to contribute to savings, but also that it produces an opposite, anti-savings effect, and that the interplay between this temporally-persistent anti-savings and temporally-volatile savings provides an explanation for several seemingly conflicting recent reports about whether implicit contributions to savings are present, absent, or inverted. Finally, the learning curves we observed for the acquisition of temporally-volatile and temporally-persistent implicit memories demonstrate the coexistence of implicit memories with distinct time courses, challenging the assertion that models of context-based learning and estimation should supplant models of adaptive processes with different learning rates. Together, these findings provide new insight into the mechanisms for savings and long-term memory formation.

Trusted research environments are definitely about trust.

In their highly topical paper, Graham et al argued that Trusted Research Environments (TREs) are not actually about trust because they reduce or remove '…the need for trust in the use and sharing of patient health data'. We believe this is fundamentally mistaken. TREs mitigate or remove some risks, but they do not address all public concerns. In this regard, TREs provide evidence for people to decide whether the bodies holding and using their data can be trusted. TREs may make it easier for people to trust but there is still a need for that trust.

Longitudinal symptom changes and association with home time in people with schizophrenia: An observational digital phenotyping study.

BACKGROUND: Smartphone assessments and sensors offer the ability to easily assess symptoms across environments in a naturalistic and longitudinal manner. However, the value of this new data to make inferences about personal vs population health and the role of environment in moderating symptoms in schizophrenia has not been fully explored in a scalable and reproducible manner. METHODS: Eighty-six adults with a diagnosis of schizophrenia were recruited from the Greater Boston Area between August 2019 and May 2021. Using the open-source mindLAMP app in an observational manner, smartphone surveys and sensors (GPS, accelerometer, screen on/off and call and text logs) were collected for up to six months. RESULTS: Sixty-three participants were analyzed, who had at least completed one survey in the app. App-based self-reported symptom surveys were highly correlated with scores on gold standard clinical assessments (r = 0.80, p = 10-11 for mood and r = 0.78, p = 10-12 for anxiety). For these app-based assessments, inter-individual differences account for a larger proportion of the correlations in longitudinal symptoms as compared to intra-individual differences. Mood, sleep, and psychosis symptoms reported on app surveys were more severe when taken at home as determined by the smartphone's GPS sensor. DISCUSSION: The intra-individual symptom correlations and the stratification of symptoms by home-time highlight the utility of digital phenotyping methods as a diagnostic tool, as well as the potential for personalized psychiatric treatment building on this data.

Models for COVID-19 Early Cardiac Pathology Following SARS-CoV-2 Infection.

OBJECTIVES: The clinical manifestations of COVID-19 associated cardiac complications are heterogeneous, ranging from asymptomatic to severe symptoms, including arrhythmias and cardiogenic shock. For COVID-19 patients with cardiac sequela, only a small subset of patients have myocarditis; the pathogenesis of cardiac sequela caused by SARS-CoV-2 other than microthrombi associated sequela remains to be determined. METHODS: Retrospective analysis of 71 heart autopsy specimens from COVID-19 and putative COVID-19 in the NIH COVID Digital Pathology Repository. RESULTS: The most consistent observation was localized myocardial cell death not associated with either myocarditis or microthrombi. Red blood cells were typically absent from capillaries but, when observed, were predominately in linear clusters (stacks) of adjacent cells. CONCLUSIONS: Based on our retrospective analysis, we propose that localized ischemia and subsequent cell death by anoxia contributes to the cardiac pathogenesis in some COVID-19 patients. We propose two new models predicting vasoconstriction of cardiac pericyte cells induced by elevated histamine from hyper-activated mast cells or direct infection. We propose that impeded blood flow and cell death by anoxia are initial steps in the development of SARS-CoV-2 induced cardiac injury in COVID-19 patients independent of microthrombi or myocarditis.

Motor planning under uncertainty.

Actions often require the selection of a specific goal amongst a range of possibilities, like when a softball player must precisely position her glove to field a fast-approaching ground ball. Previous studies have suggested that during goal uncertainty the brain prepares for all potential goals in parallel and averages the corresponding motor plans to command an intermediate movement that is progressively refined as additional information becomes available. Although intermediate movements are widely observed, they could instead reflect a neural decision about the single best action choice given the uncertainty present. Here we systematically dissociate these possibilities using novel experimental manipulations and find that when confronted with uncertainty, humans generate a motor plan that optimizes task performance rather than averaging potential motor plans. In addition to accurate predictions of population-averaged changes in motor output, a novel computational model based on this performance-optimization theory accounted for a majority of the variance in individual differences between participants. Our findings resolve a long-standing question about how the brain selects an action to execute during goal uncertainty, providing fundamental insight into motor planning in the nervous system.

Implicit adaptation compensates for erratic explicit strategy in human motor learning.

Sports are replete with strategies, yet coaching lore often emphasizes 'quieting the mind', 'trusting the body' and 'avoiding overthinking' in referring to the importance of relying less on high-level explicit strategies in favor of low-level implicit motor learning. We investigated the interactions between explicit strategy and implicit motor adaptation by designing a sensorimotor learning paradigm that drives adaptive changes in some dimensions but not others. We find that strategy and implicit adaptation synergize in driven dimensions, but effectively cancel each other in undriven dimensions. Independent analyses-based on time lags, the correlational structure in the data and computational modeling-demonstrate that this cancellation occurs because implicit adaptation effectively compensates for noise in explicit strategy rather than the converse, acting to clean up the motor noise resulting from low-fidelity explicit strategy during motor learning. These results provide new insight into why implicit learning increasingly takes over from explicit strategy as skill learning proceeds.

Postoperative delirium: the findings from a multidisciplinary survey.

BACKGROUND: Delirium is a common postoperative neurocognitive complication in the older population and can lead to significant morbidity and mortality, as well as cognitive and functional impairment. Hypoactive delirium is characterised by drowsiness and inactivity, and expert opinions suggest that it is more likely to be missed and can lead to more complications. Current guidelines and literature evidence both support the use of non-pharmacological management of delirium. METHODS: To investigate the recognition of hyperactive and hypoactive delirium by the surgical multidisciplinary team, and to investigate staff understanding regarding the management and prognosis of postoperative delirium. We conducted a single-centre, multidisciplinary survey on the diagnosis, management and complication of postoperative delirium. RESULTS: We found that hypoactive delirium is significantly less likely to be identified. In contrast, acute psychosis is likely to be misdiagnosed as delirium. Only a small proportion of the respondents had knowledge of the supportive management options for delirium; and the medical complications and higher mortality risk associated with postoperative delirium. DISCUSSION: The finding of the survey demonstrates a need for delirium education. Surveys such as this may be conducted in other centres to identify areas of focus on staff delirium education.

Adaptive Regulation of Motor Variability.

Trial-to-trial movement variability can both drive motor learning and interfere with expert performance, suggesting benefits of regulating it in context-specific ways. Here we address whether and how the brain regulates motor variability as a function of performance by training rats to execute ballistic forelimb movements for reward. Behavioral datasets comprising millions of trials revealed that motor variability is regulated by two distinct processes. A fast process modulates variability as a function of recent trial outcomes, increasing it when performance is poor and vice versa. A slower process tunes the gain of the fast process based on the uncertainty in the task's reward landscape. Simulations demonstrated that this regulation strategy optimizes reward accumulation over a wide range of time horizons, while also promoting learning. Our results uncover a sophisticated algorithm implemented by the brain to adaptively regulate motor variability to improve task performance. VIDEO ABSTRACT.

Dissociating effects of error size, training duration, and amount of adaptation on the ability to retain motor memories.

Extensive computational and neurobiological work has focused on how the training schedule, i.e., the duration and rate at which an environmental disturbance is presented, shapes the formation of motor memories. If long-lasting benefits are to be derived from motor training, however, retention of the performance improvements gained during practice is essential. Thus a better understanding of mechanisms that promote retention could lead to the design of more effective training procedures. The few studies that have investigated how retention depends on the training schedule have suggested that the gradual exposure of a perturbation leads to improved retention of motor memory compared with an abrupt exposure. However, several of these previous studies showed small effects, and although some controlled the training duration and others the level of learning, none have controlled both. In the present study we disambiguated both of these effects from exposure rate by systematically varying the duration of training, type of trained dynamics, and exposure rate for these dynamics in human force-field adaptation. After controlling for both training duration and the amount of learning, we found essentially identical retention when comparing gradual and abrupt training for two different types of force-field dynamics. By contrast, we found that retention was markedly higher for long-duration compared with short-duration training for both types of dynamics. These results demonstrate that the duration of training has a far greater effect on the retention of motor memory than the exposure rate during training. We show that a multirate learning model provides a computational mechanism for these findings.NEW & NOTEWORTHY Previous studies have suggested that a gradual, incremental introduction of a novel environment is helpful for improving retention. However, we used experimental and computational approaches to demonstrate that previously reported improvements in retention associated with gradual introductions fail to persist when other factors, including the duration of training and the degree of initial learning, are accounted for.

Retrospective observational study of the impact on emergency admission of telehealth at scale delivered in community care in Liverpool, UK.

OBJECTIVE: To assess the effect of a real world, ongoing telehealth service on the use of secondary healthcare. DESIGN: A retrospective observational study with anonymous matched controls. SETTING: Primary and community healthcare. Patients were recruited over 4 years in 89 general practices in Liverpool, UK and remotely managed by a dedicated clinical team in Liverpool Community Health. PARTICIPANTS: 5154 patients with chronic obstructive pulmonary disease, heart failure or diabetes were enrolled in the programme, of whom 3562 satisfied the inclusion criteria of this study. INTERVENTION: At least 9 weeks of telehealth including vital sign collection, questionnaires, education, support and informal coaching by clinical staff. PRIMARY OUTCOME: Reduction in the number of emergency admissions in the 12 months after start, compared with the year before start. Secondary subgroup analysis to improve future targeting and personalisation of the service. RESULT: The average number of emergency admissions for the intervention group at baseline is 0.35, 95% CI 0.32 to 0.38. The differential decrease in emergency admissions in the intervention group in comparison with the control group, the average treatment effect, is 0.08, 95 CI 0.05 to 0.11, corresponding to an average percentage decrease of 22.7%. In subgroup analysis, a score is calculated that can be used prospectively to predict individual benefit from the intervention. Patients with an above median score (37%) are predicted average reduction in emergency admissions of 0.15, 95% CI 0.09 to 0.2, corresponding to a percentage decrease in admissions of 25.3%. CONCLUSION: The telehealth intervention has a positive impact across a wide cohort of patients with different diseases. Prospective scoring of patients and allocation to targeted telehealth interventions is likely to improve the effectiveness and efficiency of the service.

Temporal specificity of the initial adaptive response in motor adaptation.

Repeated exposure to a novel physical environment eventually leads to a mature adaptive response whereby feedforward changes in motor output mirror both the amplitude and temporal structure of the environmental perturbations. However, adaptive responses at the earliest stages of learning have been found to be not only smaller, but systematically less specific in their temporal structure compared to later stages of learning. This observation has spawned a lively debate as to whether the temporal structure of the initial adaptive response is, in fact, stereotyped and non-specific. To settle this debate, we directly measured the adaptive responses to velocity-dependent and position-dependent force-field perturbations (vFFs and pFFs) at the earliest possible stage of motor learning in humans-after just a single-movement exposure. In line with previous work, we found these earliest stage adaptive responses to be more similar than the perturbations that induced them. However, the single-trial adaptive responses for vFF and pFF perturbations were clearly distinct, and the disparity between them reflected the difference between the temporal structure of the perturbations that drove them. Critically, we observed these differences between single-trial adaptive responses when vFF and pFF perturbations were randomly intermingled from one trial to the next within the same block, indicating perturbation response specificity at the single trial level. These findings demonstrate that the initial adaptive responses to physical perturbations are not stereotyped. Instead, the neural plasticity in sensorimotor areas is sensitive to the temporal structure of a movement perturbation even at the earliest stage in learning. This insight has direct implications for the development of computational models of early-stage motor adaptation and the evolution of this adaptive response with continued training.

The Role of Variability in Motor Learning.

Trial-to-trial variability in the execution of movements and motor skills is ubiquitous and widely considered to be the unwanted consequence of a noisy nervous system. However, recent studies have suggested that motor variability may also be a feature of how sensorimotor systems operate and learn. This view, rooted in reinforcement learning theory, equates motor variability with purposeful exploration of motor space that, when coupled with reinforcement, can drive motor learning. Here we review studies that explore the relationship between motor variability and motor learning in both humans and animal models. We discuss neural circuit mechanisms that underlie the generation and regulation of motor variability and consider the implications that this work has for our understanding of motor learning.

Robot-induced perturbations of human walking reveal a selective generation of motor adaptation.

The processes underlying the generation of motor adaptation in response to mechanical perturbations during human walking have been subject to debate. We used a robotic system to apply mechanical perturbations to step length and step height over consecutive gait cycles. Specifically, we studied perturbations affecting only step length, only step height, and step length and height in combination. Both step-length and step-height perturbations disrupt normal walking patterns, but step-length perturbations have a far greater impact on locomotor stability. We found a selective process of motor adaptation in that participants failed to adapt to step-height perturbations but strongly adapted to step-length perturbations, even when these adaptations increased metabolic cost. These results indicate that motor adaptation during human walking is primarily driven by locomotor stability, and only secondarily by energy expenditure and walking pattern preservation. These findings have substantial implications for the design of protocols for robot-assisted gait rehabilitation.

Evaluation of the Tobacco Heating System 2.2. Part 1: Description of the system and the scientific assessment program.

This publication introduces a series of eight other publications describing the non-clinical assessment and initial clinical study of a candidate modified risk tobacco product (MRTP) - the Tobacco Heating System 2.2 (THS2.2). This paper presents background information on tobacco harm reduction, to complement the approaches aimed at increasing smoking cessation and reducing smoking initiation to reduce the morbidity and mortality caused by cigarette smoking. THS2.2 heats tobacco without combustion, and the resulting formation of harmful and potentially harmful constituents (HPHC) is greatly reduced compared with cigarette smoke. Assessment of the THS2.2 aerosol in vitro and in vivo reveals reduced toxicity and no new hazards. Additional mechanistic endpoints, measured as part of in vivo studies, confirmed reduced impact on smoking-related disease networks. The clinical study confirmed the reduced exposure to HPHCs in smokers switching to THS2.2, and the associated transcriptomic study confirmed the utility of a gene expression signature, consisting of only 11 genes tested in the blood transcriptome of subjects enrolled in the clinical study, as a complementary measure of exposure response. The potential of THS2.2 as an MRTP is demonstrated by the assessment and additional publications cited in this series.

The Decay of Motor Memories Is Independent of Context Change Detection.

When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected; and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection.

Flexible Control of Safety Margins for Action Based on Environmental Variability.

To reduce the risk of slip, grip force (GF) control includes a safety margin above the force level ordinarily sufficient for the expected load force (LF) dynamics. The current view is that this safety margin is based on the expected LF dynamics, amounting to a static safety factor like that often used in engineering design. More efficient control could be achieved, however, if the motor system reduces the safety margin when LF variability is low and increases it when this variability is high. Here we show that this is indeed the case by demonstrating that the human motor system sizes the GF safety margin in proportion to an internal estimate of LF variability to maintain a fixed statistical confidence against slip. In contrast to current models of GF control that neglect the variability of LF dynamics, we demonstrate that GF is threefold more sensitive to the SD than the expected value of LF dynamics, in line with the maintenance of a 3-sigma confidence level. We then show that a computational model of GF control that includes a variability-driven safety margin predicts highly asymmetric GF adaptation between increases versus decreases in load. We find clear experimental evidence for this asymmetry and show that it explains previously reported differences in how rapidly GFs and manipulatory forces adapt. This model further predicts bizarre nonmonotonic shapes for GF learning curves, which are faithfully borne out in our experimental data. Our findings establish a new role for environmental variability in the control of action.