The Neural Representation of Prospective Choice during Spatial Planning and Decisions

We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point. Furthermore, we identified hippocampal responses during planning that correlated with subsequent choice accuracy and response time, particularly in mazes affording sequential choices. Psychophysiological interaction (PPI) analyses showed that coupling between the hippocampus and rd-mPFC increases during sequential (deep versus shallow) planning and is higher before correct versus incorrect choices. In short, using a naturalistic spatial planning paradigm, we reveal how the human brain represents sequential choices during planning without extensive training. Our data highlight a network centred on the cortical midline and hippocampus that allows us to make prospective choices while maintaining initial choices during planning in novel environments

Locomotor speed control circuits in the caudal brainstem

Locomotion is a universal behaviour that provides animals with the ability to move between places. Classical experiments have used electrical microstimulation to identify brain regions that promote locomotion, but the identity of neurons that act as key intermediaries between higher motor planning centres and executive circuits in the spinal cord has remained controversial. Here we show that the mouse caudal brainstem encompasses functionally heterogeneous neuronal subpopulations that have differential effects on locomotion. These subpopulations are distinguishable by location, neurotransmitter identity and connectivity. Notably, glutamatergic neurons within the lateral paragigantocellular nucleus (LPGi), a small subregion in the caudal brainstem, are essential to support high-speed locomotion, and can positively tune locomotor speed through inputs from glutamatergic neurons of the upstream midbrain locomotor region. By contrast, glycinergic inhibitory neurons can induce different forms of behavioural arrest mapping onto distinct caudal brainstem regions. Anatomically, descending pathways of glutamatergic and glycinergic LPGi subpopulations communicate with distinct effector circuits in the spinal cord. Our results reveal that behaviourally opposing locomotor functions in the caudal brainstem were historically masked by the unexposed diversity of intermingled neuronal subpopulations. We demonstrate how specific brainstem neuron populations represent essential substrates to implement key parameters in the execution of motor programs

Opportunity- and Necessity-Driven Self-Employment Among Older People in Finland

To date, few empirical studies have attempted to highlight the impact of the socio-economic characteristics of older entrepreneurs according to whether they are driven by necessity or opportunity. Tervo and Haapanen contribute to the economics of ageing by showing that opportunity- and necessity-driven senior entrepreneurs differ in terms of socio-economic characteristics. This chapter utilizes a longitudinal data set from Finland. Individuals aged between 55 and 70 entering self-employment are grouped in terms of pull and push motivations. Profiles of entrepreneurs are developed using personal, family, and environmental characteristics. The results show that opportunity-driven older self-employed workers are more likely to be highly educated males, whereas necessity-driven older self-employed workers are often less educated females and individuals who live in rural areas.peerReviewe

Characteristic of entire corneal topography and tomography for the detection of sub-clinical keratoconus with Zernike polynomials using Pentacam

Abstract The study aimed to characterize the entire corneal topography and tomography for the detection of sub-clinical keratoconus (KC) with a Zernike application method. Normal subjects (n = 147; 147 eyes), sub-clinical KC patients (n = 77; 77 eyes), and KC patients (n = 139; 139 eyes) were imaged with the Pentacam HR system. The entire corneal data of pachymetry and elevation of both the anterior and posterior surfaces were exported from the Pentacam HR software. Zernike polynomials fitting was used to quantify the 3D distribution of the corneal thickness and surface elevation. The root mean square (RMS) values for each order and the total high-order irregularity were calculated. Multimeric discriminant functions combined with individual indices were built using linear step discriminant analysis. Receiver operating characteristic curves determined the diagnostic accuracy (area under the curve, AUC). The 3rd-order RMS of the posterior surface (AUC: 0.928) obtained the highest discriminating capability in sub-clinical KC eyes. The multimeric function, which consisted of the Zernike fitting indices of corneal posterior elevation, showed the highest discriminant ability (AUC: 0.951). Indices generated from the elevation of posterior surface and thickness measurements over the entire cornea using the Zernike method based on the Pentacam HR system were able to identify very early KC