The link between learning performance, immobility in the forced swim test, and hippocampal glia

Aim: To obtain maximal translational insights from animal models of depression, we need to know the meaning of behavioral parameters of animal models. The extent of construct and face validities of behavioral despair in the form of behavioral immobility in forced swim test (FST) is disputed. In this study, learning performance in a dual solution T-Maze and immobility on the 2nd day of FST was compared to shed light on this debate. Furthermore, we aimed to inspect the relationship between hippocampal glial densities and behaviors observed. Method: Twelve adult male Sprague Dawley rats were tested in the dual-solution T-Maze and in FST. Subsequently, hippocampal slices were obtained, astrocyte and microglia cells were stained, and the densities were calculated for each subject. Results: The rats utilized different learning strategies to solve the T-Maze. But irrespective of strategy, the rats that exhibited an overall efficiency in their learning performance, remained immobile for longer durations on the 2nd day of the FST. No significant relationship was detected between hippocampal microglia and behavioral indices in T-Maze and FST. However, we detected a significant positive correlation with CA1 astrocyte density and T-Maze learning and dentate gyrus CA1 astrocyte density and headshake behavior in FST. Conclusions: The subjects showing a better cognitive performance in the T-Maze were immobile longer in the FST. This observation raises doubts about immobility as depression index and posits that it might reflect better learning. Our results also suggest that hippocampal glia cell types are differentially involved in cognition and affect

Aeroelastic Analysis of a Flapping Blow Fly Wing

In this study, a 3D model of the bio-inspired blowfly wing Callphere Erytrocephala is created and aeroelastic analysis is performed to calculate its aerodynamical characteristics by use of numerical methods. To perform the flapping motion, a sinusoidal input function is created. The scope of this study is to perform aeroelastic analysis by synchronizing computational fluid dynamics (CFD) and structural dynamic analysis models and to investigate the unsteady lift formation on the aeroelastic flapping wing for different angles of attack

Identification of linear handling models for road vehicles

This study reports the identification of linear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system, and ending with the estimation of parameters using the collected data. The model structure originates from the well-known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimisation phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. The identified model is shown to track the system response successfully

Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method

Aggregation in swarm robotics is referred to as the gathering of spatially distributed robots into a single aggregate. Aggregation can be classified as cue-based or self-organized. In cue-based aggregation, there is a cue in the environment that points to the aggregation area, whereas in self-organized aggregation no cue is present. In this paper, we proposed a novel fuzzy-based method for cue-based aggregation based on the state-of-the-art BEECLUST algorithm. In particular, we proposed three different methods: naïve, that uses a deterministic decision-making mechanism; vector-averaging, using a vectorial summation of all perceived inputs; and fuzzy, that uses a fuzzy logic controller. We used different experiment settings: one-source and two-source environments with static and dynamic conditions to compare all the methods. We observed that the fuzzy method outperformed all the other methods and it is the most robust method against noise

Analysis of mirror neuron system activation during action observation alone and action observation with motor imagery tasks

This study aimed to explore the relationship between action observation (AO)-related corticomotor excitability changes and phases of observed action and to explore the effects of pure AO and concurrent AO and motor imagery (MI) state on corticomotor excitability using TMS. It was also investigated whether the mirror neuron system activity is muscle-specific. Fourteen healthy volunteers were enrolled in the study. EMG recordings were taken from the right first dorsal interosseous and the abductor digiti minimi muscles. There was a significant main effect of TMS timing (after the beginning of the movement, at the beginning of motor output state, and during black screen) on the mean motor evoked potential (MEP) amplitude. Mean MEP amplitudes for AO combined with MI were significantly higher than pure AO session. There was a significant interaction between session and TMS timing. There was no significant main effect of muscle on MEP amplitude. The results indicate that corticomotor excitability is modulated by different phases of the observed motor movement and this modulation is not muscle-specific. Simultaneous MI and AO enhance corticomotor excitability significantly compared to pure AO

Technology-assisted exercise and physical activity interventions for older adults in clinical and laboratory settings: protocol for a scoping review of technology and sample characteristics

This registration describes a protocol for a scoping review that will attempt to address two key questions: 1) What types of technology are being used in clinical and laboratory settings to deliver exercise and physical activity interventions to older people and how do these relate to the type of intervention applied?; 2) In what (sub)populations of older adults are these technology-assisted interventions being applied