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AbstractAll life must solve how to allocate limited energy resources to maximise benefits from scarce opportunities. Economic theory posits decision makers optimise choice by maximising the subjective benefit (utility) of reward minus the subjective cost (disutility) of the required effort. While successful in many settings, this model does not fully account for how experience can alter reward-effort trade-offs. Here we test how well the subtractive model of effort disutility explains the behavior of two non-human primates (Macaca mulatta) in a binary choice task in which reward quantity and physical effort to obtain were varied.Applying random utility modelling to independently estimate reward utility and effort disutility, we show the subtractive effort model better explains out-of-sample choice behavior when compared to parabolic and exponential effort discounting. Furthermore, we demonstrate that effort disutility is dependent on previous experience of effort: in analogy to work from behavioral labour economics, we develop a model of reference-dependent effort disutility to explain the increased willingness to expend effort following previous experience of effortful options in a session. The result of this analysis suggests that monkeys discount reward by an effort cost that is measured relative to an expected effort learned from previous trials. When this subjective cost of effort, a function of context and experience, is accounted for, trial-by-trial choice behavior can be explained by the subtractive cost model of effort.Therefore, in searching for net utility signals that may underpin effort-based decision-making in the brain, careful measurement of subjective effort costs is an essential first step.SignificanceAll decision-makers need to consider how much effort they need to expend when evaluating potential options. Economic theories suggest that the optimal way to choose is by cost-benefit analysis of reward against effort. To be able to do this efficiently over many decision contexts, this needs to be done flexibly, with appropriate adaptation to context and experience. Therefore, in aiming to understand how this might be achieved in the brain, it is important to first carefully measure the subjective cost of effort. Here we show monkeys make reward-effort cost-benefit decisions, subtracting the subjective cost of effort from the subjective value of rewards. Moreover, the subjective cost of effort is dependent on the monkeys’ experience of effort in previous trials.

BackgroundFollowing spinal cord injury (SCI), disease processes spread gradually along the spinal cord forming a spatial gradient with most pronounced changes located at the lesion site. However, the dynamics of this gradient in sub-acute SCI patients is not established.ObjectiveThis study tracks the spatiotemporal dynamics of remote anterograde and retrograde spinal tract degeneration in the upper cervical cord following SCI over two years utilizing quantitative MRI.MethodsTwenty-three acute SCI patients (11 paraplegics, 12 tetraplegics) and 21 healthy controls were scanned with a T1-weighted sequence for volumetry and a FLASH sequence for myelin-sensitive magnetization transfer saturation (MTsat) map of the upper cervical cord. We estimated myelin content from MTsat maps within the corticospinal tracts (CST) and dorsal columns (DC) and measured spinal cord atrophy by means of left-right width (LRW) and anterior-posterior width (APW) on the T1-weighted images across cervical levels C1-C3. MTsat in the CST and LRW were considered proxies for retrograde degeneration, while MTsat in the DC and APW provided evidence for anterograde degeneration, respectively. Using regression models, we compared the temporal and spatial trajectories of these MRI readouts between tetraplegics, paraplegics, and controls over a 2-year period and assessed their associations with clinical improvement.ResultsLinear rates and absolute differences in myelin-sensitive MTsat indicated retrograde and anterograde neurodegeneration in the CST and DC, respectively. Changes in MTsat within the CST (change per cervical level: -0.247 p.u./level, p=0.034) and LRW (change per level: -0.323 mm/level, p=0.024) progressively developed over time with a strong gradient towards lower cervical segments specifically in tetraplegics. Within the DC, MTsat was already decreased at all cervical levels at baseline and linear rates in APW were similar across all cervical levels showing no spatial gradient in para- and tetraplegics. The relative improvement in light touch score was correlated with MTsat within the DC at baseline (1.5 months) (rs=0.575, p=0.014).ConclusionRostral and remote to the injury, the CST and DC showed ongoing structural changes, indicative of myelin reductions and atrophy within 2 years after SCI. While anterograde degeneration in the DC was already detectable uniformly at C1-C3 early following SCI, retrograde degeneration in the CST developed over time revealing specific spatial and temporal neurodegenerative gradients. Disentangling and quantifying such dynamic pathological processes may provide biomarkers for regenerative and remyelinating therapies, where antero- and retrograde spinal pathways become specifically affected.

PURPOSE: Measuring longitudinal changes in amyloid load in the asymptomatic stage of Alzheimer's disease is of high relevance for clinical research and progress towards more efficacious, timely treatments. Apolipoprotein E ε4 (APOE4) has a well-established effect on the rate of amyloid accumulation. Here we investigated which region of interest and which reference region perform best at detecting the effect of APOE4 on longitudinal amyloid load in individuals participating in the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK). METHODS: Ninety cognitively intact F-PACK participants (baseline age: 68 (52-80) years, 46 males, 42 APOE4 carriers) received structural MRI and 18F-Flutemetamol PET scans at baseline and follow-up (6.2 (3.4-10.9) year interval). Standardised uptake value ratios (SUVRs) and Centiloids (CLs) were calculated in a composite cortical volume of interest (SUVRcomp/CL) and in the precuneus (SUVRprec), and amyloid rate of change derived: (follow-up amyloid load - baseline amyloid load) / time interval (years). Four reference regions were used to derive amyloid load: whole cerebellum, cerebellar grey matter, eroded subcortical white matter, and pons. RESULTS: When using whole cerebellum or cerebellar grey matter as reference region, APOE4 carriers had a significantly higher SUVRcomp amyloid rate of change than non-carriers (pcorr = 0.004, t = 3.40 (CI 0.005-0.018); pcorr = 0.036, t = 2.66 (CI 0.003-0.018), respectively). Significance was not observed for eroded subcortical white matter or pons (pcorr = 0.144, t = 2.13 (CI 0.0003-0.008); pcorr = 0.116, t = 2.22 (CI 0.005-0.010), respectively). When using CLs as the amyloid measurement, and whole cerebellum, APOE4 carriers had a higher amyloid rate of change than non-carriers (pcorr = 0.012, t = 3.05 (CI 0.499-2.359)). Significance was not observed for the other reference regions. No significance was observed with any of the reference regions and amyloid rate of change in the precuneus (SUVRprec). CONCLUSION: In this cognitively intact cohort, a composite neocortical volume of interest together with whole cerebellum or cerebellar grey matter as reference region are the methods of choice for detecting APOE4-dependent differences in amyloid rate of change. ispartof: NEUROIMAGE-CLINICAL vol:37 ispartof: location:Netherlands status: published

Background: Pre- and intra-operative language mapping in neurosurgery patients frequently involves an object naming task. The choice of the optimal object naming paradigm remains challenging due to lack of normative data and standardization in mapping practices. The aim of this study was to identify object naming paradigms that robustly and consistently activate classical language regions and could therefore be used to improve the sensitivity of language mapping in brain tumor and epilepsy patients.Methods: Functional magnetic resonance imaging (fMRI) data from two independent groups of healthy controls (total = 79) were used to generate threshold-weighted voxel-based consistency maps. This novel approach allowed us to compare inter-subject consistency of activation for naming single objects in the visual and auditory modality and naming two objects in a phrase or a sentence.Results: We found that the consistency of activation in language regions was greater for naming two objects per picture than one object per picture, even when controlling for the number of names produced in 5 s.Conclusion: More consistent activation in language areas for naming two objects compared to one object suggests that two-object naming tasks may be more suitable for delimiting language eloquent regions with pre- and intra-operative language testing. More broadly, we propose that the functional specificity of brain mapping paradigms for a whole range of different linguistic and non-linguistic functions could be enhanced by referring to databased models of inter-subject consistency and variability in typical and atypical brain responses.

While parents have long received guidance on how to raise children, a relatively new element of this involves explicit references to infant brain development, drawing on brain scans and neuroscientific knowledge. Sometimes called ‘brain-based parenting’, this has been criticised from within sociological and policy circles alike. However, the engagement of parents themselves with neuroscientific concepts is far less researched. Drawing on 22 interviews with parents/carers of children (mostly aged 0–7) living in Scotland, this article examines how they account for their (non-)use of concepts and understandings relating to neuroscience. Three normative tropes were salient: information about children’s processing speed, evidence about deprived Romanian orphans in the 1990s, and ideas relating to whether or not children should ‘self-settle’ when falling asleep. We interrogate how parents reflexively weigh and judge such understandings and ideas. In some cases, neuroscientific knowledge was enrolled by parents in ways that supported biologically reductionist models of childhood agency. This reductionism commonly had generative effects, enjoining new care practices and producing particular parent and infant subjectivities. Notably, parents do not uncritically adopt or accept (sometimes reductionist) neurobiological and/or psychological knowledge; rather, they reflect on whether and when it is applicable to and relevant for raising their children. Thus, our respondents draw on everyday epistemologies of parenting to negotiate brain-based understandings of infant development and behaviour, and invest meaning in these in ways that cannot be fully anticipated (or appreciated) within straightforward celebrations or critiques of the content of parenting programmes drawing on neuropsychological ideas.

Background: White matter hyperintensities (WMH), of presumed vascular origin, are visible and quantifiable neuroradiological markers of brain parenchymal change. These changes may range from damage secondary to inflammation and other neurological conditions, through to healthy ageing. Fully automatic WMH quantification methods are promising, but still, traditional semi-automatic methods seem to be preferred in clinical research. We systematically reviewed the literature for fully automatic methods developed in the last five years, to assess what are considered state-of-the-art techniques, as well as trends in the analysis of WMH of presumed vascular origin. Method: We registered the systematic review protocol with the International Prospective Register of Systematic Reviews (PROSPERO), registration number - CRD42019132200. We conducted the search for fully automatic methods developed from 2015 to July 2020 on Medline, Science direct, IEE Explore, and Web of Science. We assessed risk of bias and applicability of the studies using QUADAS 2. Results: The search yielded 2327 papers after removing 104 duplicates. After screening titles, abstracts and full text, 37 were selected for detailed analysis. Of these, 16 proposed a supervised segmentation method, 10 proposed an unsupervised segmentation method, and 11 proposed a deep learning segmentation method. Average DSC values ranged from 0.538 to 0.93, being the highest value obtained from a deep learning segmentation method. Only four studies validated their method in longitudinal samples, and eight performed an additional validation using clinical parameters. Only 8/37 studies made available their method in public repositories. Conclusions: Although deep learning methods reported highly accurate results, we found no evidence that favours them over the more established k-NN, linear regression and unsupervised methods in this task. Data and code availability, bias in study design and ground truth generation influence the wider validation and applicability of these methods in clinical research.