Open design of a reproducible videogame controller for MRI and MEG.

Videogames are emerging as a promising experimental paradigm in neuroimaging. Acquiring gameplay in a scanner remains challenging due to the lack of a scanner-compatible videogame controller that provides a similar experience to standard, commercial devices. In this paper, we introduce a videogame controller designed for use in the functional magnetic resonance imaging as well as magnetoencephalography. The controller is made exclusively of 3D-printed and commercially available parts. We evaluated the quality of our controller by comparing it to a non-MRI compatible controller that was kept outside the scanner. The comparison of response latencies showed reliable button press accuracies of adequate precision. Comparison of the subjects' motion during fMRI recordings of various tasks showed that the use of our controller did not increase the amount of motion produced compared to a regular MR compatible button press box. Motion levels during an ecological videogame task were of moderate amplitude. In addition, we found that the controller only had marginal effect on temporal SNR in fMRI, as well as on covariance between sensors in MEG, as expected due to the use of non-magnetic building materials. Finally, the reproducibility of the controller was demonstrated by having team members who were not involved in the design build a reproduction using only the documentation. This new videogame controller opens new avenues for ecological tasks in fMRI, including challenging videogames and more generally tasks with complex responses. The detailed controller documentation and build instructions are released under an Open Source Hardware license to increase accessibility, and reproducibility and enable the neuroimaging research community to improve or modify the controller for future experiments.

Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots.

This paper proposes an artificial spiking neural network (SNN) sustaining the cognitive abstract process of spatial concept learning, embedded in virtual and real robots. Based on an operant conditioning procedure, the robots learn the relationship of horizontal/vertical and left/right visual stimuli, regardless of their specific pattern composition or their location on the images. Tests with novel patterns and locations were successfully completed after the acquisition learning phase. Results show that the SNN can adapt its behavior in real time when the rewarding rule changes.

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context.

Visual motion detection is essential for the survival of many species. The phenomenon includes several spatial properties, not fully understood at the level of a neural circuit. This paper proposes a computational model of a visual motion detector that integrates direction and orientation selectivity features. A recent experiment in the Drosophila model highlights that stimulus orientation influences the neural response of direction cells. However, this interaction and the significance at the behavioral level are currently unknown. As such, another objective of this article is to study the effect of merging these two visual processes when contextualized in a neuro-robotic model and an operant conditioning procedure. In this work, the learning task was solved using an artificial spiking neural network, acting as the brain controller for virtual and physical robots, showing a behavior modulation from the integration of both visual processes.

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation.

This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information.

Ontogeny of 5-HT neurons in the brainstem of the lamprey, Petromyzon marinus.

This study examined the spatial and temporal distribution of serotonin-immunoreactive (5-HT-ir) neurons in the brainstem of Petromyzon marinus at three developmental stages, larval, postmetamorphic, and reproductive. Computer-assisted 3-D reconstructions were made of the three main 5-HT-ir neuron groups. The rostralmost brainstem group was located near the posterior commissure, the second group at the isthmus, and the third group in the bulbar area. For each of those groups, the distribution of the 5-HT-ir neurons was very similar in the three developmental stages examined, suggesting that the 5-HT system is relatively mature early in larval animals. The soma of 5-HT-ir neurons increased in size and their dendritic fields increased in complexity with development. Furthermore, the number of 5-HT-ir neurons in each group increased significantly from the larval to the reproductive stage. To determine whether this was due to the genesis of 5-HT neurons, bromodeoxyuridine (BrdU) was injected into larval, metamorphosing, and postmetamorphic lampreys. These experiments revealed a few neurons colocalizing BrdU and 5-HT in metamorphosing animals. Taken together, the present results suggest that 5-HT neurons increase in number during maturation and that neurogenesis could, at least partially, contribute to the appearance of new 5-HT cells at different developmental stages.

Vacuum-assisted venous drainage does not increase the neurological risk.

BACKGROUND: Vacuum-assisted venous drainage (VAVD) with negative pressure applied to integral sealed-hardshell venous reservoir facilitates valvular surgery through minimally invasive approaches. Despite concerns regarding air entrainment from the right atrium, cerebral microemboli of air and neurological complications, VAVD was used in patients who underwent valvular surgery throughout the last two years in our institution. METHODS: We compared the rate of neurological complications in patients who underwent surgery with and without VAVD from June 1997 to July 2001. VAVD was added to solid venous reservoirs with membrane oxygenators and arterial filters. Clinical results were prospectively entered in our valve database and were used for the analysis. RESULTS: Eight hundred twenty-two consecutive patients averaging 65 +/- 11 years of age underwent aortic, mitral and tricuspid valve replacements including 40 redos (40/822, 5%) and 265 associated CABG (265/822, 32%) with VAVD in 1999 to 2001 compared to 723 patients averaging 63 +/- 11 years of age (p = 0.01) who underwent the same procedures with 79 redos (79/723, 11%) and 177 CABG (177/723, 24%) without VAVD in 1997 to 1999. CPB time averaged 117 +/- 50 minutes in VAVD patients compared to 108 +/- 43 minutes in those without VAVD (p = 0.001). Thirty-day mortality averaged 5% (39/822) in patients with VAVD and 4% (30/723) in those without VAVD (p = 0.6). Seven patients of the VAVD group (7/822, 1%) and 11 patients without VAVD (11/723, 1.5%, p = 0.2) suffered from temporary or permanent neurological deficit. CONCLUSION: VAVD is a useful adjunct to modern cardiopulmonary bypass systems. When used with appropriate care, VAVD does not appear to significantly increase air microemboli and is not associated with an increased neurological risk following valvular surgery.