Promises, Pitfalls, and Basic Guidelines for Applying Machine Learning Classifiers to Psychiatric Imaging Data, with Autism as an Example

Most psychiatric disorders are associated with subtle alterations in brain function and are subject to large interindividual differences. Typically, the diagnosis of these disorders requires time-consuming behavioral assessments administered by a multidisciplinary team with extensive experience. While the application of Machine Learning classification methods (ML classifiers) to neuroimaging data has the potential to speed and simplify diagnosis of psychiatric disorders, the methods, assumptions, and analytical steps are currently opaque and not accessible to researchers and clinicians outside the field. In this paper, we describe potential classification pipelines for autism spectrum disorder, as an example of a psychiatric disorder. The analyses are based on resting-state fMRI data derived from a multisite data repository (ABIDE). We compare several popular ML classifiers such as support vector machines, neural networks, and regression approaches, among others. In a tutorial style, written to be equally accessible for researchers and clinicians, we explain the rationale of each classification approach, clarify the underlying assumptions, and discuss possible pitfalls and challenges. We also provide the data as well as the MATLAB code we used to achieve our results. We show that out-of-the-box ML classifiers can yield classification accuracies of about 60-70%. Finally, we discuss how classification accuracy can be further improved, and we mention methodological developments that are needed to pave the way for the use of ML classifiers in clinical practice.

Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity

Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc.

Quantitative Evaluation of Intensity Inhomogeneity Correction Methods for Structural MR Brain Images

The correction of intensity non-uniformity (INU) in magnetic resonance (MR) images is extremely important to ensure both within-subject and across-subject reliability. Here we tackled the problem of objectively comparing INU correction techniques for T1-weighted images, which are the most commonly used in structural brain imaging. We focused our investigations on the methods integrated in widely used software packages for MR data analysis: FreeSurfer, BrainVoyager, SPM and FSL. We used simulated data to assess the INU fields reconstructed by those methods for controlled inhomogeneity magnitudes and noise levels. For each method, we evaluated a wide range of input parameters and defined an enhanced configuration associated with best reconstruction performance. By comparing enhanced and default configurations, we found that the former often provide much more accurate results. Accordingly, we used enhanced configurations for a more objective comparison between methods. For different levels of INU magnitude and noise, SPM and FSL, which integrate INU correction with brain segmentation, generally outperformed FreeSurfer and BrainVoyager, whose methods are exclusively dedicated to INU correction. Nonetheless, accurate INU field reconstructions can be obtained with FreeSurfer on images with low noise and with BrainVoyager for slow and smooth inhomogeneity profiles. Our study may prove helpful for an accurate selection of the INU correction method to be used based on the characteristics of actual MR data.

Influence of oxytocin on emotion recognition from body language: A randomized placebo-controlled trial

The neuropeptide 'oxytocin' (OT) is known to play a pivotal role in a variety of complex social behaviors by promoting a prosocial attitude and interpersonal bonding. One mechanism by which OT is hypothesized to promote prosocial behavior is by enhancing the processing of socially relevant information from the environment. With the present study, we explored to what extent OT can alter the 'reading' of emotional body language as presented by impoverished biological motion point light displays (PLDs). To do so, a double-blind between-subjects randomized placebo-controlled trial was conducted, assessing performance on a bodily emotion recognition task in healthy adult males before and after a single-dose of intranasal OT (24 IU). Overall, a single-dose of OT administration had a significant effect of medium size on emotion recognition from body language. OT-induced improvements in emotion recognition were not differentially modulated by the emotional valence of the presented stimuli (positive versus negative) and also, the overall tendency to label an observed emotional state as 'happy' (positive) or 'angry' (negative) was not modified by the administration of OT. Albeit moderate, the present findings of OT-induced improvements in bodily emotion recognition from whole-body PLD provide further support for a link between OT and the processing of socio-communicative cues originating from the body of others.

Reconsolidation of Motor Memories Is a Time-Dependent Process

Reconsolidation is observed when a consolidated stable memory is recalled, which renders it transiently labile and requires re-stabilization. Motor memory reconsolidation has previously been demonstrated using a three-day design: on day 1 the memory is encoded, on day 2 it is reactivated and experimentally manipulated, and on day 3 memory strength is tested. The aim of the current study is to determine specific boundary conditions in order to consistently degrade motor memory through reconsolidation paradigms. We investigated a sequence tapping task (n = 48) with the typical three-day design and confirmed that reactivating the motor sequence briefly (10 times tapping the learned motor sequence) destabilizes the memory trace and makes it susceptible to behavioral interference. By systematically varying the time delay between memory reactivation and interference while keeping all other aspect constant we found that a short delay (i.e., 20 s) significantly decreased performance on day 3, whereas performance was maintained or small (but not significant) improvements were observed for longer delays (i.e., 60 s). We also tested a statistical model that assumed a linear effect of the different time delays (0 s, 20 s, 40 s, 60 s) on the performance changes from day 2 to day 3. This linear model revealed a significant effect consistent with the interpretation that increasing time delays caused a gradual change from performance degradation to performance conservation across groups. These findings indicate that re-stabilizing motor sequence memories during reconsolidation does not solely rely on additional motor practice but occurs with the passage of time. This study provides further support for the hypothesis that reconsolidation is a time-dependent process with a transition phase from destabilization to re-stabilization.

Revealing the quality of movement: A meta-analysis review to quantify the thresholds to pathological variability during standing and walking

Neuromotor processes are inherently noisy, which results in variability during movement and fluctuations in motor control. Although controversial, low levels of variability are traditionally considered healthy, while increased levels are thought to be pathological. This systematic review and meta-analysis of the literature investigates the thresholds between healthy and pathological task variability. After examining 13,195 publications, 109 studies were included. Results from over 3000 healthy subjects and 2775 patients revealed an overall positive effect size of pathology on variability of 0.59 for walking and 0.80 for sway. For the coefficient of variation of stride time (ST) and sway area (SA), upper thresholds of 2.6% and 265mm(2) discriminated pathological from asymptomatic performance, while 1.1% and 62mm(2) identified the lower thresholds for pathological variability. This window of healthy performance now provides science based evidence for the discrimination of both extremely low and extremely high levels of variability in the identification as well as standardised monitoring of functional status in neurological cases.

A Day Awake Attenuates Motor Learning-Induced Increases in Corticomotor Excitability

The "synaptic homeostasis hypothesis" proposes that the brain's capacity to exhibit synaptic plasticity is reduced during the day but restores when sleeping. While this prediction has been confirmed for declarative memories, it is currently unknown whether it is also the case for motor memories. We quantified practice-induced changes in corticomotor excitability in response to repetitive motor sequence training as an indirect marker of synaptic plasticity in the primary motor cortex (M1). Subjects either practiced a motor sequence in the morning and a new motor sequence in the evening, i.e., after a 12 h period of wakefulness (wake group); or they practiced a sequence in the evening and a new sequence in the morning, i.e., after a 12 h period including sleep (sleep group). In both wake and sleep groups motor training improved movement performance irrespective of the time of day. Learning a new sequence in the morning triggered a clear increase in corticomotor excitability suggesting that motor training triggered synaptic adaptation in the M1 that was absent when a new sequence was learned in the evening. Thus, the magnitude of the practice-induced increase in corticomotor excitability was significantly influenced by time of day while the magnitude of motor performance improvements were not. These results suggest that the motor cortex's potential to efficiently adapt to the environment by quickly adjusting synaptic strength in an activity-dependent manner is higher in the morning than in the evening.

Connectivity-based parcellation increases network detection sensitivity in resting state fMRI: An investigation into the cingulate cortex in autism

Although resting state fMRI (RS-fMRI) is increasingly used to generate biomarkers of psychiatric illnesses, analytical choices such as seed size and placement can lead to variable findings. Seed placement especially impacts on RS-fMRI studies of Autism Spectrum Disorder (ASD), because individuals with ASD are known to possess more variable network topographies. Here, we present a novel pipeline for analysing RS-fMRI in ASD using the cingulate cortex as an exemplar anatomical region of interest. Rather than using seeds based on previous literature, or gross morphology, we used a combination of structural information, task-independent (RS-fMRI) and task-dependent functional connectivity (Meta-Analytic Connectivity Modeling) to partition the cingulate cortex into six subregions with unique connectivity fingerprints and diverse behavioural profiles. This parcellation was consistent between groups and highly replicable across individuals (up to 93% detection) suggesting that the organisation of cortico-cingulo connections is highly similar between groups. However, our results showed an age-related increase in connectivity between the anterior middle cingulate cortex and right lateral prefrontal cortex in ASD, whilst this connectivity decreased in controls. There was also a Group × Grey Matter (GM) interaction, showing increased connectivity between the anterior cingulate cortex and the rectal gyrus in concert with increasing rectal gyrus GM in controls. By comparing our approach to previously established methods we revealed that our approach improves network detection in both groups, and that the ability to detect group differences using 4 mm radius spheres varies greatly with seed placement. Using our multi-modal approach we find disrupted cortico-cingulo circuits that, based on task-dependent information, may contribute to ASD deficits in attention and social interaction. Moreover, we highlight how more sensitive approaches to RS-fMRI are crucial for establishing robust and reproducible connectivity-based biomarkers in psychiatric disorders.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect 'neural masculinization', as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD.

Intensity Inhomogeneity Correction of Structural MR Images: A Data-Driven Approach to Define Input Algorithm Parameters

Intensity non-uniformity (INU) in magnetic resonance (MR) imaging is a major issue when conducting analyses of brain structural properties. An inaccurate INU correction may result in qualitative and quantitative misinterpretations. Several INU correction methods exist, whose performance largely depend on the specific parameter settings that need to be chosen by the user. Here we addressed the question of how to select the best input parameters for a specific INU correction algorithm. Our investigation was based on the INU correction algorithm implemented in SPM, but this can be in principle extended to any other algorithm requiring the selection of input parameters. We conducted a comprehensive comparison of indirect metrics for the assessment of INU correction performance, namely the coefficient of variation of white matter (CVWM), the coefficient of variation of gray matter (CVGM), and the coefficient of joint variation between white matter and gray matter (CJV). Using simulated MR data, we observed the CJV to be more accurate than CVWM and CVGM, provided that the noise level in the INU-corrected image was controlled by means of spatial smoothing. Based on the CJV, we developed a data-driven approach for selecting INU correction parameters, which could effectively work on actual MR images. To this end, we implemented an enhanced procedure for the definition of white and gray matter masks, based on which the CJV was calculated. Our approach was validated using actual T1-weighted images collected with 1.5 T, 3 T, and 7 T MR scanners. We found that our procedure can reliably assist the selection of valid INU correction algorithm parameters, thereby contributing to an enhanced inhomogeneity correction in MR images.

A technical guide to tDCS, and related non-invasive brain stimulation tools

Transcranial electrical stimulation (tES), including transcranial direct and alternating current stimulation (tDCS, tACS) are non-invasive brain stimulation techniques increasingly used for modulation of central nervous system excitability in humans. Here we address methodological issues required for tES application. This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches. It aims to help the reader to appropriately design and conduct studies involving these brain stimulation techniques, understand limitations and avoid shortcomings, which might hamper the scientific rigor and potential applications in the clinical domain.

High-intensity interval training evokes larger serum BDNF levels compared with intense continuous exercise

Exercise can have a positive effect on the brain by activating brain-derived neurotrophic factor (BDNF)-related processes. In healthy humans there appears to be a linear relationship between exercise intensity and the positive short-term effect of acute exercise on BDNF levels (i.e., the highest BDNF levels are reported after high-intensity exercise protocols). Here we performed two experiments to test the effectiveness of two high-intensity exercise protocols, both known to improve cardiovascular health, to determine whether they have a similar efficacy in affecting BDNF levels. Participants performed a continuous exercise (CON) protocol at 70% of maximal work rate and a high-intensity interval-training (HIT) protocol at 90% of maximal work rate for periods of 1 min alternating with 1 min of rest (both protocols lasted 20 min). We observed similar BDNF kinetics in both protocols, with maximal BDNF concentrations being reached toward the end of training (experiment 1). We then showed that both exercise protocols significantly increase BDNF levels compared with a rest condition (CON P = 0.04; HIT P < 0.001), with HIT reaching higher BDNF levels than CON (P = 0.035) (experiment 2). These results suggest that shorter bouts of high intensity exercise are slightly more effective than continuous high-intensity exercise for elevating serum BDNF. Additionally, 73% of the participants preferred the HIT protocol (P = 0.02). Therefore, we suggest that the HIT protocol might represent an effective and preferred intervention for elevating BDNF levels and potentially promoting brain health.

Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach

BACKGROUND

The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network.

METHOD

Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC).

RESULTS

Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD.

CONCLUSION

While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model

Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different re-referencing methods, among which linked-mastoid re-referencing (LMR), average re-referencing (AR) and reference electrode standardization technique (REST). In this study we quantitatively assessed the extent to which the use of a high-density montage and a realistic head model can impact on the optimal estimation of a neutral reference for EEG recordings. Approach. Using simulated recordings generated by projecting specific source activity over the sensors, we assessed to what extent AR, REST and LMR may distort the scalp topography. We examined the impact electrode coverage has on AR and REST, and how accurate the REST reconstruction is for realistic and less realistic (three-layer and single-layer spherical) head models, and with possible uncertainty in the electrode positions. We assessed LMR, AR and REST also in the presence of typical EEG artifacts that are mixed in the recordings. Finally, we applied them to real EEG data collected in a target detection experiment to corroborate our findings on simulated data. Main results. Both AR and REST have relatively low reconstruction errors compared to LMR, and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data. For both AR and REST, high electrode density yields low re-referencing reconstruction errors. A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models. With a low-density montage, REST shows a more reliable reconstruction than AR either with a realistic or a three-layer spherical head model. Conversely, with a high-density montage AR yields better results unless precise information on electrode positions is available. Significance. Our study is the first to quantitatively assess the performance of EEG re-referencing techniques in relation to the use of a high-density montage and a realistic head model. We hope our study will help researchers in the choice of the most effective re-referencing approach for their EEG studies.

Effects of Transcranial Direct Current Stimulation on the Recognition of Bodily Emotions from Point-Light Displays

Perceiving human motion, recognizing actions, and interpreting emotional body language are tasks we perform daily and which are supported by a network of brain areas including the human posterior superior temporal sulcus (pSTS). Here, we applied transcranial direct current stimulation (tDCS) with anodal (excitatory) or cathodal (inhibitory) electrodes mounted over right pSTS (target) and orbito-frontal cortex (reference) while healthy participants performed a bodily emotion recognition task using biological motion point-light displays (PLDs). Performance (accuracy and reaction times) was also assessed on a control task which was matched to the emotion recognition task in terms of cognitive and motor demands. Each subject participated in two experimental sessions, receiving either anodal or cathodal stimulation, which were separated by one week to avoid residual effects of previous stimulations. Overall, tDCS brain stimulation did not affect the recognition of emotional states from PLDs. However, when emotions with a negative or positive-neutral emotional valence were analyzed separately, effects of stimulation were shown for recognizing emotions with a negative emotional valence (sadness and anger), indicating increased recognition performance when receiving anodal (excitatory) stimulation compared to cathodal (inhibitory) stimulation over pSTS. No stimulation effects were shown for the recognition of emotions with positive-neutral emotional valences. These findings extend previous studies showing structure-function relationships between STS and biological motion processing from PLDs and provide indications that stimulation effects may be modulated by the emotional valence of the stimuli.

Anodal tDCS over the Primary Motor Cortex Facilitates Long-Term Memory Formation Reflecting Use-Dependent Plasticity

Previous research suggests that anodal transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) modulates NMDA receptor dependent processes that mediate synaptic plasticity. Here we test this proposal by applying anodal versus sham tDCS while subjects practiced to flex the thumb as fast as possible (ballistic movements). Repetitive practice of this task has been shown to result in performance improvements that reflect use-dependent plasticity resulting from NMDA receptor mediated, long-term potentiation (LTP)-like processes. Using a double-blind within-subject cross-over design, subjects (n=14) participated either in an anodal or a sham tDCS session which were at least 3 months apart. Sham or anodal tDCS (1 mA) was applied for 20 min during motor practice and retention was tested 30 min, 24 hours and one week later. All subjects improved performance during each of the two sessions (p < 0.001) and learning gains were similar. Our main result is that long term retention performance (i.e. 1 week after practice) was significantly better when practice was performed with anodal tDCS than with sham tDCS (p < 0.001). This effect was large (Cohen's d=1.01) and all but one subject followed the group trend. Our data strongly suggest that anodal tDCS facilitates long-term memory formation reflecting use-dependent plasticity. Our results support the notion that anodal tDCS facilitates synaptic plasticity mediated by an LTP-like mechanism, which is in accordance with previous research.

The Corticospinal Tract: A Biomarker to Categorize Upper Limb Functional Potential in Unilateral Cerebral Palsy

Children with unilateral cerebral palsy (CP) typically present with largely divergent upper limb sensorimotor deficits and individual differences in response to upper limb rehabilitation. This review summarizes how early brain damage can cause dramatic deviations from the normal anatomy of sensory and motor tracts, resulting in unique "wiring patterns" of the sensorimotor system in CP. Based on the existing literature, we suggest that corticospinal tract (CST) anatomy and integrity constrains sensorimotor function of the upper limb and potentially also the response to treatment. However, it is not possible to infer CST (re)organization from clinical presentation alone and conventional biomarkers, such as time of insult, location, and lesion extent seem to have limited clinical utility. Here, we propose a theoretical framework based on a detailed examination of the motor system using behavioral, neurophysiological, and magnetic resonance imaging measures, akin to those used to predict potential for upper limb recovery of adults after stroke. This theoretical framework might prove useful because it provides testable hypotheses for future research with the goal to develop and validate a clinical assessment flowchart to categorize children with unilateral CP.

Virtual water maze learning in human increases functional connectivity between posterior hippocampus and dorsal caudate

Recent work has demonstrated that functional connectivity between remote brain regions can be modulated by task learning or the performance of an already well-learned task. Here, we investigated the extent to which initial learning and stable performance of a spatial navigation task modulates functional connectivity between subregions of hippocampus and striatum. Subjects actively navigated through a virtual water maze environment and used visual cues to learn the position of a fixed spatial location. Resting-state functional magnetic resonance imaging scans were collected before and after virtual water maze navigation in two scan sessions conducted 1 week apart, with a behavior-only training session in between. There was a large significant reduction in the time taken to intercept the target location during scan session 1 and a small significant reduction during the behavior-only training session. No further reduction was observed during scan session 2. This indicates that scan session 1 represented initial learning and scan session 2 represented stable performance. We observed an increase in functional connectivity between left posterior hippocampus and left dorsal caudate that was specific to scan session 1. Importantly, the magnitude of the increase in functional connectivity was correlated with offline gains in task performance. Our findings suggest cooperative interaction occurs between posterior hippocampus and dorsal caudate during awake rest following the initial phase of spatial navigation learning. Furthermore, we speculate that the increase in functional connectivity observed during awake rest after initial learning might reflect consolidation-related processing.

Whole brain myelin mapping using T1- and T2-weighted MR imaging data

Despite recent advancements in MR imaging, non-invasive mapping of myelin in the brain still remains an open issue. Here we attempted to provide a potential solution. Specifically, we developed a processing workflow based on T1-w and T2-w MR data to generate an optimized myelin enhanced contrast image. The workflow allows whole brain mapping using the T1-w/T2-w technique, which was originally introduced as a non-invasive method for assessing cortical myelin content. The hallmark of our approach is a retrospective calibration algorithm, applied to bias-corrected T1-w and T2-w images, that relies on image intensities outside the brain. This permits standardizing the intensity histogram of the ratio image, thereby allowing for across-subject statistical analyses. Quantitative comparisons of image histograms within and across different datasets confirmed the effectiveness of our normalization procedure. Not only did the calibrated T1-w/T2-w images exhibit a comparable intensity range, but also the shape of the intensity histograms was largely corresponding. We also assessed the reliability and specificity of the ratio image compared to other MR-based techniques, such as magnetization transfer ratio (MTR), fractional anisotropy (FA), and fluid-attenuated inversion recovery (FLAIR). With respect to these other techniques, T1-w/T2-w had consistently high values, as well as low inter-subject variability, in brain structures where myelin is most abundant. Overall, our results suggested that the T1-w/T2-w technique may be a valid tool supporting the non-invasive mapping of myelin in the brain. Therefore, it might find important applications in the study of brain development, aging and disease.

Gone for 60 seconds: reactivation length determines motor memory degradation during reconsolidation

When a stable memory is reactivated it becomes transiently labile and requires restabilization, a process known as reconsolidation. Animal studies have convincingly demonstrated that during reconsolidation memories are modifiable and can be erased when reactivation is followed by an interfering intervention. Few studies have been conducted in humans, however, and results are inconsistent regarding the extent to which a memory can be degraded. We used a motor sequence learning paradigm to show that the length of reactivation constitutes a crucial boundary condition determining whether human motor memories can be degraded. In our first experiment, we found that a short reactivation (less than 60 sec) renders the memory labile and susceptible to degradation through interference, while a longer reactivation does not. In our second experiment, we reproduce these results and show a significant linear relationship between the length of memory reactivation and the detrimental effect of the interfering task performed afterwards, i.e., the longer the reactivation, the smaller the memory loss due to interference. Our data suggest that reactivation via motor execution activates a time-dependent process that initially destabilizes the memory, which is then followed by restabilization during further practice.

Functional Brain Activation Associated with Inhibitory Control Deficits in Older Adults

In young adults, canceling an initiated action depends on the right inferior frontal cortex (IFC), presupplementary motor area (preSMA), and the basal ganglia. Older adults show response inhibition deficits, but how this relates to functional brain activation remains unclear. Using event-related functional magnetic resonance imaging, we tested whether older adults (N = 20) exhibit overactivation during stop-signal inhibition as shown for attentional control tasks, or reduced activity compared with young adults (N = 20). We used a modified stop-signal task involving coupled bimanual responses and manipulated whether both or just one hand was cued to stop. Stop-task difficulty was matched across groups. We found a group by condition interaction in supramarginal gyrus, anterior insula, rIFC, and preSMA, with activation increasing for successful Stop versus Go trials in the young adults only. Comparing the groups on Stop trials revealed preSMA and striatum hypoactivity for older adults. White matter tracts connecting rIFC, preSMA, and the subthalamic nuclei were associated with stronger activation of preSMA in older adults, suggesting that maintenance of the brain's structure has positive implications for brain function.