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Identifying factors that influence age-related cognitive decline is crucial, given its severe personal and societal impacts. However, studying aging in human or animal models is challenging due to the significant variability in aging processes among individuals. Additionally, longitudinal and cross-sectional studies often produce differing results. In this context, home-cage-based behavioral analysis over lifespans has emerged as a significant method in recent years. This study aimed to explore how prior experience affects cognitive performance in mice of various age groups (4, 12, and 22 months) using a home-cage-based touchscreen test battery. In this automated system, group-housed, ID-chipped mice primarily obtain their food during task performance throughout the day, motivated by their own initiative, without being subjected to food deprivation. Spatial working memory and attention were evaluated using the trial unique non-matching to location (TUNL) and the five-choice serial reaction time task (5-CSRTT), respectively. The same set of mice learned both of these demanding tasks. While signs of cognitive decline were already apparent in middle-aged mice, older mice exhibited poorer performance in both tasks. Mice at both 12 and 22 months displayed an increase in perseverance and a decrease in the percentage of correct responses in the TUNL test compared to the 4-month-old mice. Furthermore, during the 5-CSRTT, they exhibited higher rates of omissions and premature responses compared to their younger counterparts. Additionally, the correct response rate in 22-month-old mice was lower than that of the 4-month-old ones. However, mice that had undergone cognitive training at 4 months maintained high-performance levels when re-tested at 12 months, showing an increase in correct responses during TUNL testing compared to their untrained controls. In the 5-CSRTT, previously trained mice demonstrated higher correct response rates, fewer omissions, and reduced premature responses compared to naive control mice. Notably, even when assessed on a visual discrimination and behavioral flexibility task at 22 months, experienced mice outperformed naive 4-month-old mice. These findings highlight the advantages of early-life cognitive training and suggest that its benefits extend beyond the cognitive domains primarily targeted during early training. The success of this study was significantly aided by the fully automated home-cage-based testing system, which allows for high throughput with minimal human intervention.

Single-board computers such as the Raspberry Pi make it easy to control hardware setups for laboratory experiments. GPIOs and expansion boards (HATs) give access to a whole range of sensor and control hardware. However, controlling such hardware can be challenging, when many experimental setups run in parallel and the time component is critical. LabNet is a C++ optimized control layer software to give access to the Raspberry Pi connected hardware over a simple network protocol. LabNet was developed to be suitable for time-critical operations, and to be simple to expand. It leverages the actor model to simplify multithreading programming and to increase modularity. The message protocol is implemented in Protobuf and offers performance, small message size, and supports a large number of programming languages on the client side. It shows good performance compared to locally executed tools like Bpod, pyControl, or Autopilot and reaches sub-millisecond range in network communication latencies. LabNet can monitor and react simultaneously to up to 14 pairs of digital inputs, without increasing latencies. LabNet itself does not provide support for the design of experimental tasks. This is left to the client. LabNet can be used for general automation in experimental laboratories with its control PC located at some distance. LabNet is open source and under continuing development.

UnlabelledCurrent assessment of visual neglect involves paper-and-pencil tests or computer-based tasks. Both have been criticised because of their lack of ecological validity as target stimuli can only be presented in a restricted visual range. This study examined the user-friendliness and diagnostic strength of a new "Circle-Monitor" (CM), which enlarges the range of the peripersonal space, in comparison to a standard paper-and-pencil test (Neglect-Test, NET).MethodsTen stroke patients with neglect and ten age-matched healthy controls were examined by the NET and the CM test comprising of four subtests (Star Cancellation, Line Bisection, Dice Task, and Puzzle Test).ResultsThe acceptance of the CM in elderly controls and neglect patients was high. Participants rated the examination by CM as clear, safe and more enjoyable than NET. Healthy controls performed at ceiling on all subtests, without any systematic differences between the visual fields. Both NET and CM revealed significant differences between controls and patients in Line Bisection, Star Cancellation and visuo-constructive tasks (NET: Figure Copying, CM: Puzzle Test). Discriminant analyses revealed cross-validated assignment of patients and controls to groups was more precise when based on the CM (hit rate 90%) as compared to the NET (hit rate 70%).ConclusionThe CM proved to be a sensitive novel tool to diagnose visual neglect symptoms quickly and accurately with superior diagnostic validity compared to a standard neglect test while being well accepted by patients. Due to its upgradable functions the system may also be a valuable tool not only to test for non-visual neglect symptoms, but also to provide treatment and assess its outcome.