An Infomax algorithm can perform both familiarity discrimination and feature extraction in a single network.

Psychological experiments have shown that the capacity of the brain for discriminating visual stimuli as novel or familiar is almost limitless. Neurobiological studies have established that the perirhinal cortex is critically involved in both familiarity discrimination and feature extraction. However, opinion is divided as to whether these two processes are performed by the same neurons. Previously proposed models have been unable to simultaneously extract features and discriminate familiarity for large numbers of stimuli. We show that a well-known model of visual feature extraction, Infomax, can simultaneously perform familiarity discrimination and feature extraction efficiently. This model has a significantly larger capacity than previously proposed models combining these two processes, particularly when correlation exists between inputs, as is the case in the perirhinal cortex. Furthermore, we show that once the model fully extracts features, its ability to perform familiarity discrimination increases markedly.

A high visibility Talbot-Lau neutron grating interferometer to investigate stress-induced magnetic degradation in electrical steel.

Neutron grating interferometry (nGI) is a unique technique allowing to probe magnetic and nuclear properties of materials not accessible in standard neutron imaging. The signal-to-noise ratio of an nGI setup is strongly dependent on the achievable visibility. Hence, for analysis of weak signals or short measurement times a high visibility is desired. We developed a new Talbot-Lau interferometer using the third Talbot order with an unprecedented visibility (0.74) over a large field of view. Using the third Talbot order and the resulting decreased asymmetry allows to access a wide correlation length range. Moreover, we have used a novel technique for the production of the absorption gratings which provides nearly binary gratings even for thermal neutrons. The performance of the new interferometer is demonstrated by visualizing the local magnetic domain wall density in electrical steel sheets when influenced by residual stress induced by embossing. We demonstrate that it is possible to affect the density of the magnetic domain walls by embossing and therefore to engineer the guiding of magnetic fields in electrical steel sheets. The excellent performance of our new setup will also facilitate future studies of dynamic effects in electric steels and other systems.

Computer- and robot-assisted stereotaxy for high-precision small animal brain exploration.

This contribution introduces a computer- and robot-assisted framework for stereotactic neurosurgery on small animals. Two major elements of this framework are presented in detail: a robotic stereotactic assistant and the software framework for placement of probes into the brain. The latter integrates modules for registration, insertion control, and preoperative path planning. Two options for path planning are addressed: (a) atlas-based planning and (b) image-based planning based on computed tomography data. The framework is tested performing robot-assisted insertion of microelectrodes and acquisition of electrophysiological recordings in vivo. Concepts for data analysis pointing towards a mapping of position and neural structure to functional data are introduced. Results show that the presented framework allows precise small animal stereotaxy and therefore offers new options for brain research.

Physical Activity, Nutrition, Cognition, Neurophysiology, and Short-Time Synaptic Plasticity in Healthy Older Adults: A Cross-Sectional Study.

The aging brain undergoes remodeling processes because of biological and environmental factors. To counteract brain aging, neuronal plasticity should be preserved. The aim of this study was to test if the capacity of generating short-time synaptic plasticity in older adults may be related to either physical activity, nutritional status, cognition, or neurophysiological activity. Thirty-six participants (mean age 73.3 ± 5.9 years) received transcranial magnetic stimulation in combination with peripheral nerve stimulation to experimentally induce short-time synaptic plasticity by paired associative stimulation (PAS). Adaptations in neuronal excitability were assessed by motor-evoked potential (MEP) in the right m. tibialis anterior before and after PAS. The Physical Activity Questionnaire 50+ and the StepWatchTM captured physical activity levels. Nutritional status was assessed by the Mini Nutritional Assessment. Cognition was assessed by reaction time for a divided attention test and with the Montreal Cognitive Assessment. Neurophysiological activity was assessed by electroencephalography during the divided attention test. MEPs of the highest stimulation intensity resulted significantly different comparing before, 5 min, or 30 min after PAS (p < 0.05). Data-driven automatic hierarchical classification of the individual recruitment curve slopes over the three-time points indicated four different response types, however, response groups did not significantly differ based on physical activity, nutritional status, cognition, or neurophysiological activity. In a second-level analysis, participants having an increased slope showed a significant higher energy expenditure (z = -2.165, p = 0.030, r = 0.36) and revealed a significant higher power activity in the alpha frequency band (z = -2.008, p = 0.046, r = 0.37) at the prefrontal-located EEG electrodes, compared to the participants having a decreased slope. This study hints toward older adults differing in their neuronal excitability which is strongly associated to their short-time synaptic plasticity levels. Furthermore, a physically active lifestyle and higher EEG power in the alpha frequency band seem to be connected to the capacity of generating long-term potentiation-like synaptic plasticity in older adults. Future studies should consider more sensitive assessments and bigger sample sizes to get a broad scope of the older adults' population.

Neuromodulation of STDP through short-term changes in firing causality.

Spike timing dependent plasticity (STDP) likely plays an important role in forming and changing connectivity patterns between neurons in our brain. In a unidirectional synaptic connection between two neurons, it uses the causal relation between spiking activity of a presynaptic input neuron and a postsynaptic output neuron to change the strength of this connection. While the nature of STDP benefits unsupervised learning of correlated inputs, any incorporation of value into the learning process needs some form of reinforcement. Chemical neuromodulators such as Dopamine or Acetylcholine are thought to signal changes between external reward and internal expectation to many brain regions, including the basal ganglia. This effect is often modelled through a direct inclusion of the level of Dopamine as a third factor into the STDP rule. While this gives the benefit of direct control over synaptic modification, it does not account for observed instantaneous effects in neuronal activity on application of Dopamine agonists. Specifically, an instant facilitation of neuronal excitability in the striatum can not be explained by the only indirect effect that dopamine-modulated STDP has on a neuron's firing pattern. We therefore propose a model for synaptic transmission where the level of neuromodulator does not directly influence synaptic plasticity, but instead alters the relative firing causality between pre- and postsynaptic neurons. Through the direct effect on postsynaptic activity, our rule allows indirect modulation of the learning outcome even with unmodulated, two-factor STDP. However, it also does not prohibit joint operation together with three-factor STDP rules.