118 research outputs found

    Tensegrity and Recurrent Neural Networks: Towards an Ecological Model of Postural Coordination

    Get PDF
    Tensegrity systems have been proposed as both the medium of haptic perception and the functional architecture of motor coordination in animals. However, a full working model integrating those two aspects with some form of neural implementation is still lacking. A basic two-dimensional cross-tensegrity plant is designed and its mechanics simulated. The plant is coupled to a Recurrent Neural Network (RNN). The model’s task is to maintain postural balance against gravity despite the intrinsically unstable configuration of the plant. The RNN takes only proprioceptive input about the springs’ lengths and rate of length change and outputs minimum lengths for each spring which modulates their interaction with the plant’s inertial kinetics. Four artificial agents are evolved to coordinate the patterns of spring contractions in order to maintain dynamic equilibrium. A first study assesses quiet standing performance and reveals coordinative patterns between the tensegrity rods akin to humans’ strategy of anti-phase hip-ankle relative phase. The agents show a mixture of periodic and aperiodic trajectories of their Center of Mass. Moreover, the agents seem to tune to the anticipatory “time-to-balance” quantity in order to maintain their movements within a region of reversibility. A second study perturbs the systems with mechanical platform shifts and sensorimotor degradation. The agents’ response to the mechanical perturbation is robust. Dimensionality analysis of the RNNs’ unit activations reveals a pattern of degree of freedom recruitment after perturbation. In the degradation sub-study, different levels of noise are added to the RNN inputs and different levels of weakening gain are applied to the forces generated by the springs to mimic haptic degradation and muscular weakening in elderly humans. As expected, the systems perform less well, falling earlier than without the insults. However, the same systems re-evolved again under the degraded conditions see significant functional recovery. Overall, the dissertation supports the plausibility of RNN cum tensegrity models of haptics-guided postural coordination in humans

    Dynamics and network structure in neuroimaging data

    Get PDF

    Making a stronger case for comparative research to investigate the behavioral and neurological bases of three-dimensional navigation

    Get PDF
    The rich diversity of avian natural history provides exciting possibilities for comparative research aimed at understanding three-dimensional navigation. We propose some hypotheses relating differences in natural history to potential behavioral and neurological adaptations possessed by contrasting bird species. This comparative approach may offer unique insights into some of the important questions raised by Jeffery et al

    Direct and indirect cholinergic septo-hippocampal pathways cooperate to structure spiking activity in the hippocampus

    Get PDF
    The medial septum/vertical diagonal band of Broca complex (MSvDB) is a key structure that modulates hippocampal rhythmogenesis. Cholinergic neurons of the MSvDB play a central role in generating and pacing theta-band oscillations in the hippocampal formation during exploration, novelty detection, and memory encoding. However, how precisely cholinergic neurons affect hippocampal oscillatory activity and spiking rates of hippocampal neurons in vivo, has remained elusive. I therefore used silicon probe recordings of local field potentials and unit activity in the dorsal hippocampus in combination with cell type specific optogenetic activation of cholinergic MSvDB neurons to study the effects of synaptically released acetylcholine on hippocampal network activity in urethane-anesthetized mice.In vivo optogenetic activation of cholinergic MSvDB neurons induced hippocampal rhythmogenesis at the theta (3-6 Hz) and slow gamma (26-48 Hz) frequency range with a suppression of peri-theta frequencies. Interestingly, this effect was independent from the stimulation frequency. In addition, stimulation of cholinergic MSvDB neurons resulted in a net increase of interneuron firing with a concomitant net decrease of principal cell firing in the hippocampal CA3 subfield. I used focal injections of cholinergic blockers either into the MSvDB or the hippocampus to demonstrate that cholinergic MSvDB neurons modulate hippocampal network activity via two distinct pathways. Focal injection of a cholinergic blocker cocktail into the hippocampus strongly diminished the cholinergic stimulation-induced spiking rate modulation of hippocampal interneurons and principal cells. This demonstrates that modulation of neuronal activity in hippocampal subfield CA3 by cholinergic MSvDB neurons is mediated via direct septo-hippocampal projections. In contrast, focal injection of atropine, a blocker of the muscarinic type of acetylcholine receptors, into the MSvDB had no effect on spiking rate modulation in CA3, but abolished hippocampal theta synchronization. This strongly suggests that activity of an indirect septo-hippocampal pathway induces hippocampal theta oscillations via an intraseptal relay. Furthermore, cholinergic neurons depolarized parvalbumin-positive (PV+) GABAergic neurons within the MSvDB in vitro, and optogenetic activation of these fast spiking neurons in vivo induced hippocampal rhythmic activity precisely at the stimulation frequency. Taken together, these data suggest an intraseptal relay with a strong contribution of PV+ GABAergic MSvDB neurons in pacing hippocampal theta oscillations. Activation of both the direct and indirect pathways causes a reduction in CA3 pyramidal neuron firing and a more precise coupling to theta oscillatory phase with CA3 interneurons preferentially firing at the descending phase and CA3 principal neurons preferentially firing near the trough of the ongoing theta oscillation recorded at the pyramidal cell layer. The two identified anatomically and functionally distinct pathways are likely relevant for cholinergic control of encoding vs. retrieval modes in the hippocampus

    A neural network-based trajectory planner for redundant systems using direct inverse modeling

    Get PDF
    Redundant (i.e., under-determined) systems can not be trained effectively using direct inverse modeling with supervised learning, for reasons well out-lined by Michael Jordan at MIT. There is a loop-hole , however, in Jordan\u27s preconditions, which seems to allow just such an architecture. A robot path planner implementing a cerebellar inspired habituation paradigm with such an architecture will be introduced. The system, called ARTFORMS, for Adaptive Redundant Trajectory Formation System uses on-line training of multiple CMACS. CMACs are locally generalizing networks, and have an a priori deterministic geometric input space mapping. These properties together with on-line learning and rapid convergence satisfy the loop-hole conditions. Issues of stability/plasticity, presentation order and generalization, computational complexity, and subsumptive fusion of multiple networks are discussed. Two implementations are described. The first is shown not to be goal directed enough for ultimate success. The second, which is highly successful, is made more goal directed by the addition of secondary training, which reduces the dimensionality of the problem by using a set of constraint equations. Running open loop with respect to posture (the system metric which reduces dimensionality) is seen to be the root cause of the first system\u27s failure, not the use of the direct inverse method. In fact, several nice properties of direct inverse modeling contribute to the system\u27s convergence speed, robustness and compliance. The central problem used to demonstrate this method is the control of trajectory formation for a planar kinematic chain with a variable number of joints. Finally, this method is extended to implement adaptive obstacle avoidance

    Mediated Cognition: Information Technologies and the Sciences of Mind

    Get PDF
    This dissertation investigates the interconnections between minds, media, and the cognitive sciences. It asks what it means for media to have effects upon the mind: do our tools influence the ways that we think? It considers what scientific evidence can be brought to bear on the question: how can we know and measure these effects? Ultimately, it looks to the looping pathways by which science employs technological media in understanding the mind, and the public comes to understand and respond to these scientific discourses. I contend that like human cognition itself, the enterprise of cognitive science is a deeply and distinctively mediated phenomenon. This casts a different light on contemporary debates about whether television, computers, or the Internet are changing our brains, for better or for worse. Rather than imagining media effects as befalling a fictive natural mind, I draw on multiple disciplines to situate mind and the sciences thereof as shaped from their origins through interaction with technology. Our task is then to interrogate the forms of cognition and attention fostered by different media, alongside their attendant costs and benefits. The first chapter positions this dissertation between the fields of media studies and STS, developing a case for the reality of media effects without the implication of technological determinism. The second considers the history of technological metaphor in scientific characterizations of the mind. The third section consists of three separate chapters on the history of cognitive science, presenting the core of my case for its uniquely mediated character. Across three distinct eras, what unifies cognitive science is the quest to understand the mind using computational systems, operating by turns as generative metaphors and tangible models. I then evaluate the contemporary cognitive-scientific research on the question of media effects, and the growing role of electronic media in science. My fifth and final section develops a content analysis: what is said in the media about the popular theory that media themselves, in one way or another, are causing attention deficit disorders? The work concludes with a summary and some reflections on mind, culture, technoscience and markets as recursively interwoven causal systems

    Tätigkeitsbericht 2017-2019/20

    Get PDF

    Programming the cerebellum

    Get PDF
    It is argued that large-scale neural network simulations of cerebellar cortex and nuclei, based on realistic compartmental models of me major cell populations, are necessary before the problem of motor learning in the cerebellum can be solved, [HOUK et al.; SIMPSON et al.
    • …
    corecore