Institut des Maladies Neurodégénératives

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

BACKGROUND: PSP is a neuropathologically defined disease entity. Clinical diagnostic criteria, published in 1996 by the National Institute of Neurological Disorders and Stroke/Society for PSP, have excellent specificity, but their sensitivity is limited for variant PSP syndromes with presentations other than Richardson's syndrome. OBJECTIVE: We aimed to provide an evidence- and consensus-based revision of the clinical diagnostic criteria for PSP. METHODS: We searched the PubMed, Cochrane, Medline, and PSYCInfo databases for articles published in English since 1996, using postmortem diagnosis or highly specific clinical criteria as the diagnostic standard. Second, we generated retrospective standardized clinical data from patients with autopsy-confirmed PSP and control diseases. On this basis, diagnostic criteria were drafted, optimized in two modified Delphi evaluations, submitted to structured discussions with consensus procedures during a 2-day meeting, and refined in three further Delphi rounds. RESULTS: Defined clinical, imaging, laboratory, and genetic findings serve as mandatory basic features, mandatory exclusion criteria, or context-dependent exclusion criteria. We identified four functional domains (ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction) as clinical predictors of PSP. Within each of these domains, we propose three clinical features that contribute different levels of diagnostic certainty. Specific combinations of these features define the diagnostic criteria, stratified by three degrees of diagnostic certainty (probable PSP, possible PSP, and suggestive of PSP). Clinical clues and imaging findings represent supportive features. CONCLUSIONS: Here, we present new criteria aimed to optimize early, sensitive, and specific clinical diagnosis of PSP on the basis of currently available evidence. © 2017 International Parkinson and Movement Disorder Society.

Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron.

Abstract Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

This article reviews and summarizes 200 years of Parkinson's disease. It comprises a relevant history of Dr. James Parkinson's himself and what he described accurately and what he missed from today's perspective. Parkinson's disease today is understood as a multietiological condition with uncertain etiopathogenesis. Many advances have occurred regarding pathophysiology and symptomatic treatments, but critically important issues are still pending resolution. Among the latter, the need to modify disease progression is undoubtedly a priority. In sum, this multiple-author article, prepared to commemorate the bicentenary of the shaking palsy, provides a historical state-of-the-art account of what has been achieved, the current situation, and how to progress toward resolving Parkinson's disease. © 2017 International Parkinson and Movement Disorder Society.

BACKGROUND: The second consensus criteria for the diagnosis of multiple system atrophy (MSA) are widely recognized as the reference standard for clinical research, but lack sensitivity to diagnose the disease at early stages. OBJECTIVE: To develop novel Movement Disorder Society (MDS) criteria for MSA diagnosis using an evidence-based and consensus-based methodology. METHODS: We identified shortcomings of the second consensus criteria for MSA diagnosis and conducted a systematic literature review to answer predefined questions on clinical presentation and diagnostic tools relevant for MSA diagnosis. The criteria were developed and later optimized using two Delphi rounds within the MSA Criteria Revision Task Force, a survey for MDS membership, and a virtual Consensus Conference. RESULTS: The criteria for neuropathologically established MSA remain unchanged. For a clinical MSA diagnosis a new category of clinically established MSA is introduced, aiming for maximum specificity with acceptable sensitivity. A category of clinically probable MSA is defined to enhance sensitivity while maintaining specificity. A research category of possible prodromal MSA is designed to capture patients in the earliest stages when symptoms and signs are present, but do not meet the threshold for clinically established or clinically probable MSA. Brain magnetic resonance imaging markers suggestive of MSA are required for the diagnosis of clinically established MSA. The number of research biomarkers that support all clinical diagnostic categories will likely grow. CONCLUSIONS: This set of MDS MSA diagnostic criteria aims at improving the diagnostic accuracy, particularly in early disease stages. It requires validation in a prospective clinical and a clinicopathological study. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

OBJECTIVE: Mounting evidence suggests that α-synuclein, a major protein component of Lewy bodies (LB), may be responsible for initiating and spreading the pathological process in Parkinson disease (PD). Supporting this concept, intracerebral inoculation of synthetic recombinant α-synuclein fibrils can trigger α-synuclein pathology in mice. However, it remains uncertain whether the pathogenic effects of recombinant synthetic α-synuclein may apply to PD-linked pathological α-synuclein and occur in species closer to humans. METHODS: Nigral LB-enriched fractions containing pathological α-synuclein were purified from postmortem PD brains by sucrose gradient fractionation and subsequently inoculated into the substantia nigra or striatum of wild-type mice and macaque monkeys. Control animals received non-LB fractions containing soluble α-synuclein derived from the same nigral PD tissue. RESULTS: In both mice and monkeys, intranigral or intrastriatal inoculations of PD-derived LB extracts resulted in progressive nigrostriatal neurodegeneration starting at striatal dopaminergic terminals. No neurodegeneration was observed in animals receiving non-LB fractions from the same patients. In LB-injected animals, exogenous human α-synuclein was quickly internalized within host neurons and triggered the pathological conversion of endogenous α-synuclein. At the onset of LB-induced degeneration, host pathological α-synuclein diffusely accumulated within nigral neurons and anatomically interconnected regions, both anterogradely and retrogradely. LB-induced pathogenic effects required both human α-synuclein present in LB extracts and host expression of α-synuclein. INTERPRETATION: α-Synuclein species contained in PD-derived LB are pathogenic and have the capacity to initiate a PD-like pathological process, including intracellular and presynaptic accumulations of pathological α-synuclein in different brain areas and slowly progressive axon-initiated dopaminergic nigrostriatal neurodegeneration.

Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/mL, in plasma diluted 1 to 10) of IFN-α and/or -ω are found in about 10% of patients with critical COVID-19 pneumonia, but not in subjects with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or -ω (100 pg/mL, in 1/10 dilutions of plasma) in 13.6% of 3,595 patients with critical COVID-19, including 21% of 374 patients > 80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1,124 deceased patients (aged 20 days-99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected subjects from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or -ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of subjects carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals <70 years, 2.3% between 70 and 80 years, and 6.3% >80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over-80s, and total fatal COVID-19 cases.

Abstract Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry 1,2 . Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated ( P &lt; 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis 3 , and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN ) and variants (such as at GRK5 and NOS3 ). Using a three-pronged approach 4 , we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry 5 . Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

BACKGROUND: Multiple system atrophy (MSA) is a fatal and still poorly understood degenerative movement disorder that is characterised by autonomic failure, cerebellar ataxia, and parkinsonism in various combinations. Here we present the final analysis of a prospective multicentre study by the European MSA Study Group to investigate the natural history of MSA. METHODS: Patients with a clinical diagnosis of MSA were recruited and followed up clinically for 2 years. Vital status was ascertained 2 years after study completion. Disease progression was assessed using the unified MSA rating scale (UMSARS), a disease-specific questionnaire that enables the semiquantitative rating of autonomic and motor impairment in patients with MSA. Additional rating methods were applied to grade global disease severity, autonomic symptoms, and quality of life. Survival was calculated using a Kaplan-Meier analysis and predictors were identified in a Cox regression model. Group differences were analysed by parametric tests and non-parametric tests as appropriate. Sample size estimates were calculated using a paired two-group t test. FINDINGS: 141 patients with moderately severe disease fulfilled the consensus criteria for MSA. Mean age at symptom onset was 56·2 (SD 8·4) years. Median survival from symptom onset as determined by Kaplan-Meier analysis was 9·8 years (95% CI 8·1-11·4). The parkinsonian variant of MSA (hazard ratio [HR] 2·08, 95% CI 1·09-3·97; p=0·026) and incomplete bladder emptying (HR 2·10, 1·02-4·30; p=0·044) predicted shorter survival. 24-month progression rates of UMSARS activities of daily living, motor examination, and total scores were 49% (9·4 [SD 5·9]), 74% (12·9 [8·5]), and 57% (21·9 [11·9]), respectively, relative to baseline scores. Autonomic symptom scores progressed throughout the follow-up. Shorter symptom duration at baseline (OR 0·68, 0·5-0·9; p=0·006) and absent levodopa response (OR 3·4, 1·1-10·2; p=0·03) predicted rapid UMSARS progression. Sample size estimation showed that an interventional trial with 258 patients (129 per group) would be able to detect a 30% effect size in 1-year UMSARS motor examination decline rates at 80% power. INTERPRETATION: Our prospective dataset provides new insights into the evolution of MSA based on a follow-up period that exceeds that of previous studies. It also represents a useful resource for patient counselling and planning of multicentre trials.

Significance Left–right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population and how biological factors such as age, sex, and genetic variation affect these asymmetries. Here, we describe by far the largest-ever study of cerebral cortical asymmetry, based on data from 17,141 participants. We found a global anterior–posterior “torque” pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an online resource that will serve future studies of human brain anatomy in health and disease.

There is more to brain connections than the mere transfer of signals between brain regions. Behavior and cognition emerge through cortical area interaction. This requires integration between local and distant areas orchestrated by densely connected networks. Brain connections determine the brain's functional organization. The imaging of connections in the living brain has provided an opportunity to identify the driving factors behind the neurobiology of cognition. Connectivity differences between species and among humans have furthered the understanding of brain evolution and of diverging cognitive profiles. Brain pathologies amplify this variability through disconnections and, consequently, the disintegration of cognitive functions. The prediction of long-term symptoms is now preferentially based on brain disconnections. This paradigm shift will reshape our brain maps and challenge current brain models.

Acquisition and performance of instrumental actions are assumed to require both action-outcome and stimulus-response (S-R) habit processes. Over the course of extended training, control over instrumental performance shifts from goal-directed action-outcome associations to S-R associations that progressively gain domination over behavior. Lesions of the lateral part of the dorsal striatum disrupt this process, and rats with lesions to the lateral striatum showed selective sensitivity to devaluation of the instrumental outcome (Yin et al., 2004), indicating that this area is necessary for habit formation. The present experiment further explored the basis of this dysfunction by examining the ability of rats subjected to bilateral 6-hydroxydopamine lesions of the nigrostriatal dopaminergic pathway to develop behavioral autonomy with overtraining. Rats were given extended training on two cued instrumental tasks associating a stimulus (a tone or a light) with an instrumental action (lever press or chain pull) and a food reward (pellets or sucrose). Both tasks were run daily in separate sessions. Overtraining was followed by a test of goal sensitivity by satiety-specific devaluation of the reward. In control animals, one action (lever press) was insensitive to reward devaluation, indicating that it became a habit, whereas the second action (chain pull) was still sensitive to goal devaluation. This result provides evidence that the development of habit learning may depend on the characteristics of the response. In dopamine-depleted rats, lever press and chain pull remained sensitive to reward devaluation, evidencing a role of striatal dopamine transmission in habit formation.

Although formation and stabilization of long-lasting associative memories are thought to require time-dependent coordinated hippocampal-cortical interactions, the underlying mechanisms remain unclear. Here, we present evidence that neurons in the rat cortex must undergo a "tagging process" upon encoding to ensure the progressive hippocampal-driven rewiring of cortical networks that support remote memory storage. This process was AMPA- and N-methyl-D-aspartate receptor-dependent, information-specific, and capable of modulating remote memory persistence by affecting the temporal dynamics of hippocampal-cortical interactions. Post-learning reinforcement of the tagging process via time-limited epigenetic modifications resulted in improved remote memory retrieval. Thus, early tagging of cortical networks is a crucial neurobiological process for remote memory formation whose functional properties fit the requirements imposed by the extended time scale of systems-level memory consolidation.

An improved understanding of how the brain allocates mental resources as a function of task difficulty is critical for enhancing human performance. Functional near infrared spectroscopy (fNIRS) is a field-deployable optical brain monitoring technology that provides a direct measure of cerebral blood flow in response to cognitive activity. We found that fNIRS was sensitive to variations in task difficulty in both real-life (flight simulator) and laboratory settings (tests measuring executive functions), showing increased concentration of oxygenated hemoglobin (HbO2) and decreased concentration of deoxygenated hemoglobin (HHb) in the prefrontal cortex as the tasks became more complex. Intensity of prefrontal activation (HbO2 concentration) was not clearly correlated to task performance. Rather, activation intensity shed insight on the level of mental effort, i.e., how hard an individual was working to accomplish a task. When combined with performance, fNIRS provided an estimate of the participants' neural efficiency, and this efficiency was consistent across levels of difficulty of the same task. Overall, our data support the suitability of fNIRS to assess the mental effort related to human operations and represents a promising tool for the measurement of neural efficiency in other contexts such as training programs or the clinical setting.