3,169 results match your criteria Biological Cybernetics[Journal]


A Renewed Vision for Biological Cybernetics.

Biol Cybern 2020 Jun;114(3):315-316

Departments of Psychology and Biomedical Engineering, University of Arizona, 1503 E. University bld, Tucson, AZ, 85721, USA.

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http://dx.doi.org/10.1007/s00422-020-00837-7DOI Listing

Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system.

Biol Cybern 2020 Jun 24;114(3):403-418. Epub 2020 Jun 24.

Physics Department, Humboldt University Berlin, Newtonstr. 15, 12489, Berlin, Germany.

Information about time-dependent sensory stimuli is encoded in the activity of neural populations; distinct aspects of the stimulus are read out by different types of neurons: while overall information is perceived by integrator cells, so-called coincidence detector cells are driven mainly by the synchronous activity in the population that encodes predominantly high-frequency content of the input signal (high-pass information filtering). Previously, an analytically accessible statistic called the partial synchronous output was introduced as a proxy for the coincidence detector cell's output in order to approximate its information transmission. In the first part of the current paper, we compare the information filtering properties (specifically, the coherence function) of this proxy to those of a simple coincidence detector neuron. Read More

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http://dx.doi.org/10.1007/s00422-020-00838-6DOI Listing

In Memoriam: Erol Başar and the General Systems Theory-a personal reminiscence.

Authors:
Vasil Kolev

Biol Cybern 2020 Jun;114(3):419-420

Institute of Neurobiology, Bulgarian Academy of Sciences, Sofia, Bulgaria.

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http://dx.doi.org/10.1007/s00422-020-00836-8DOI Listing

Elbow angle generation during activities of daily living using a submovement prediction model.

Biol Cybern 2020 Jun 9;114(3):389-402. Epub 2020 Jun 9.

Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran.

The present study aimed to develop a realistic model for the generation of human activities of daily living (ADL) movements. The angular profiles of the elbow joint during functional ADL tasks such as eating and drinking were generated by a submovement-based closed-loop model. First, the ADL movements recorded from three human participants were broken down into logical phases, and each phase was decomposed into submovement components. Read More

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http://dx.doi.org/10.1007/s00422-020-00834-wDOI Listing

Bio-inspired multi-scale fusion.

Biol Cybern 2020 Apr 22;114(2):209-229. Epub 2020 Apr 22.

Queensland University of Technology, Brisbane, Australia.

We reveal how implementing the homogeneous, multi-scale mapping frameworks observed in the mammalian brain's mapping systems radically improves the performance of a range of current robotic localization techniques. Roboticists have developed a range of predominantly single- or dual-scale heterogeneous mapping approaches (typically locally metric and globally topological) that starkly contrast with neural encoding of space in mammalian brains: a multi-scale map underpinned by spatially responsive cells like the grid cells found in the rodent entorhinal cortex. Yet the full benefits of a homogeneous multi-scale mapping framework remain unknown in both robotics and biology: in robotics because of the focus on single- or two-scale systems and limits in the scalability and open-field nature of current test environments and benchmark datasets; in biology because of technical limitations when recording from rodents during movement over large areas. Read More

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http://dx.doi.org/10.1007/s00422-020-00831-zDOI Listing

A model of path integration and representation of spatial context in the retrosplenial cortex.

Biol Cybern 2020 Apr 18;114(2):303-313. Epub 2020 Apr 18.

ETIS UMR8051, CY Cergy Paris University, ENSEA, CNRS, 95000, Cergy, France.

Inspired by recent biological experiments, we simulate animals moving in different environments (open space, spiral mazes and on a treadmill) to test the performances of a simple model of the retrosplenial cortex (RSC) acting as a path integration (PI) and as a categorization mechanism. The connection between the hippocampus, RSC and the entorhinal cortex is revealed through a novel perspective. We suppose that the path integration is performed by the information coming from RSC. Read More

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http://dx.doi.org/10.1007/s00422-020-00833-xDOI Listing

Complex spatial navigation in animals, computational models and neuro-inspired robots.

Biol Cybern 2020 Apr;114(2):137-138

Department of Computer Science and Engineering, University of South Florida, Tampa, FL, USA.

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http://dx.doi.org/10.1007/s00422-020-00832-yDOI Listing

From spatial navigation via visual construction to episodic memory and imagination.

Authors:
Michael A Arbib

Biol Cybern 2020 Apr 13;114(2):139-167. Epub 2020 Apr 13.

University of California San Diego, San Diego, USA.

This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affordance Model and the World Graph model of spatial navigation. The key here is to reject approaches in which memory is restricted to unanalyzed views from familiar places, and their later recall. Read More

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http://dx.doi.org/10.1007/s00422-020-00829-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152744PMC

Conjunctive reward-place coding properties of dorsal distal CA1 hippocampus cells.

Biol Cybern 2020 Apr 7;114(2):285-301. Epub 2020 Apr 7.

Program in Applied Mathematics, University of Arizona, Tucson, AZ, 85721, USA.

Autonomous motivated spatial navigation in animals or robots requires the association between spatial location and value. Hippocampal place cells are involved in goal-directed spatial navigation and the consolidation of spatial memories. Recently, Gauthier and Tank (Neuron 99(1):179-193, 2018. Read More

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http://dx.doi.org/10.1007/s00422-020-00830-0DOI Listing

Cognitive swarming in complex environments with attractor dynamics and oscillatory computing.

Biol Cybern 2020 Apr 31;114(2):269-284. Epub 2020 Mar 31.

Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.

Neurobiological theories of spatial cognition developed with respect to recording data from relatively small and/or simplistic environments compared to animals' natural habitats. It has been unclear how to extend theoretical models to large or complex spaces. Complementarily, in autonomous systems technology, applications have been growing for distributed control methods that scale to large numbers of low-footprint mobile platforms. Read More

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http://dx.doi.org/10.1007/s00422-020-00823-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7183509PMC

EO-MTRNN: evolutionary optimization of hyperparameters for a neuro-inspired computational model of spatiotemporal learning.

Biol Cybern 2020 Jun 17;114(3):363-387. Epub 2020 Mar 17.

Institute for Cognitive Systems (ICS), Technical University of Munich, Munich, Germany.

For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn spatiotemporal data. However, this implies a cumbersome trial-and-error process until suitable parameters are found and it reduces the long-term autonomy of artificial agents, such as robots that are controlled by multiple timescale networks. Read More

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http://dx.doi.org/10.1007/s00422-020-00828-8DOI Listing

Simulating Small Neural Circuits with a Discrete Computational Model.

Biol Cybern 2020 Jun 13;114(3):349-362. Epub 2020 Mar 13.

V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia.

Simulations of neural activity are commonly based on differential equations. We address the question what can be achieved with a simplified discrete model. The proposed model resembles artificial neural networks enriched with additional biologically inspired features. Read More

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http://dx.doi.org/10.1007/s00422-020-00826-wDOI Listing

The effects of within-neuron degree correlations in networks of spiking neurons.

Biol Cybern 2020 Jun 2;114(3):337-347. Epub 2020 Mar 2.

School of Natural and Computational Sciences, Massey University, NSMC, Private Bag 102-904, Auckland, New Zealand.

We consider the effects of correlations between the in- and out-degrees of individual neurons on the dynamics of a network of neurons. By using theta neurons, we can derive a set of coupled differential equations for the expected dynamics of neurons with the same in-degree. A Gaussian copula is used to introduce correlations between a neuron's in- and out-degree, and numerical bifurcation analysis is used determine the effects of these correlations on the network's dynamics. Read More

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http://dx.doi.org/10.1007/s00422-020-00822-0DOI Listing

Modeling of the neural mechanism underlying the terrestrial turning of the salamander.

Biol Cybern 2020 Jun 27;114(3):317-336. Epub 2020 Feb 27.

School of Electric Engineering, Jiangsu Ocean University, Lianyungang, 222005, China.

In order to explore the neural mechanism underlying salamander terrestrial turning, an improved biomechanical model is proposed by modifying the forelimb structure of the existing biomechanical model. Based on the proposed improved biomechanical model, a new spinal locomotor network model is constructed which contains the interneuron networks and motoneuron pool. Control methods are also developed for the new model which increase its transient response speed, control the initial swing order of the forelimbs, and generate different walking turning gait and turning on the spot (turning without moving forward). Read More

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http://dx.doi.org/10.1007/s00422-020-00821-1DOI Listing

Unstructured network topology begets order-based representation by privileged neurons.

Biol Cybern 2020 02 27;114(1):113-135. Epub 2020 Feb 27.

Institute of Biology, Otto-von-Guericke University, Leipziger Str. 44, Haus 91, 39120, Magdeburg, Germany.

How spiking activity reverberates through neuronal networks, how evoked and spontaneous activity interacts and blends, and how the combined activities represent external stimulation are pivotal questions in neuroscience. We simulated minimal models of unstructured spiking networks in silico, asking whether and how gentle external stimulation might be subsequently reflected in spontaneous activity fluctuations. Consistent with earlier findings in silico and in vitro, we observe a privileged subpopulation of 'pioneer neurons' that, by their firing order, reliably encode previous external stimulation. Read More

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http://dx.doi.org/10.1007/s00422-020-00819-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062672PMC
February 2020
1.713 Impact Factor

Real-time sensory-motor integration of hippocampal place cell replay and prefrontal sequence learning in simulated and physical rat robots for novel path optimization.

Biol Cybern 2020 Apr 24;114(2):249-268. Epub 2020 Feb 24.

INSERM UMR1093-CAPS, Université Bourgogne Franche-Comté, UFR des Sciences du Sport, 21000, Dijon, France.

An open problem in the cognitive dimensions of navigation concerns how previous exploratory experience is reorganized in order to allow the creation of novel efficient navigation trajectories. This behavior is revealed in the "traveling salesrat problem" (TSP) when rats discover the shortest path linking baited food wells after a few exploratory traversals. We have recently published a model of navigation sequence learning, where sharp wave ripple replay of hippocampal place cells transmit "snippets" of the recent trajectories that the animal has explored to the prefrontal cortex (PFC) (Cazin et al. Read More

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http://dx.doi.org/10.1007/s00422-020-00820-2DOI Listing

Modeling awake hippocampal reactivations with model-based bidirectional search.

Biol Cybern 2020 Apr 17;114(2):231-248. Epub 2020 Feb 17.

Institute of Intelligent Systems and Robotics (ISIR), Sorbonne Université and CNRS (Centre National de la Recherche Scientifique), 75005, Paris, France.

Hippocampal offline reactivations during reward-based learning, usually categorized as replay events, have been found to be important for performance improvement over time and for memory consolidation. Recent computational work has linked these phenomena to the need to transform reward information into state-action values for decision making and to propagate it to all relevant states of the environment. Nevertheless, it is still unclear whether an integrated reinforcement learning mechanism could account for the variety of awake hippocampal reactivations, including variety in order (forward and reverse reactivated trajectories) and variety in the location where they occur (reward site or decision-point). Read More

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http://dx.doi.org/10.1007/s00422-020-00817-xDOI Listing

Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation.

Biol Cybern 2020 02 4;114(1):5-21. Epub 2020 Feb 4.

Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622, Villeurbanne, France.

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. Read More

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http://dx.doi.org/10.1007/s00422-020-00818-wDOI Listing
February 2020

Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability.

Biol Cybern 2020 02 20;114(1):95-111. Epub 2020 Jan 20.

Graduate School of Engineering Science, Osaka University, Osaka, 5608531, Japan.

The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. Read More

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http://dx.doi.org/10.1007/s00422-020-00816-yDOI Listing
February 2020

Establishing metrics and control laws for the learning process: ball and beam balancing.

Biol Cybern 2020 02 18;114(1):83-93. Epub 2020 Jan 18.

Department of Applied Mechanics, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary.

Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the beam. Stabilizability analysis of different biomechanical models for the ball and beam task with time-delayed proportional-derivative feedback identified the angular position of the beam as the manipulated variable. Read More

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http://dx.doi.org/10.1007/s00422-020-00815-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062859PMC
February 2020

A computational model for spatial cognition combining dorsal and ventral hippocampal place field maps: multiscale navigation.

Biol Cybern 2020 Apr 9;114(2):187-207. Epub 2020 Jan 9.

Department of Computer Science and Engineering, University of South Florida, Tampa, FL, USA.

Classic studies have shown that place cells are organized along the dorsoventral axis of the hippocampus according to their field size, with dorsal hippocampal place cells having smaller field sizes than ventral place cells. Studies have also suggested that dorsal place cells are primarily involved in spatial navigation, while ventral place cells are primarily involved in context and emotional encoding. Additionally, recent work has shown that the entire longitudinal axis of the hippocampus may be involved in navigation. Read More

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http://dx.doi.org/10.1007/s00422-019-00812-xDOI Listing

An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks.

Biol Cybern 2020 02 6;114(1):63-82. Epub 2020 Jan 6.

Learning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Tasks that require the cooperation of both hands and arms are common in human everyday life. Coordination helps to synchronize in space and temporally motion of the upper limbs. In fine bimanual tasks, coordination enables also to achieve higher degrees of precision that could be obtained from a single hand. Read More

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http://dx.doi.org/10.1007/s00422-019-00814-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062861PMC
February 2020

Spiking time-dependent plasticity leads to efficient coding of predictions.

Biol Cybern 2020 02 24;114(1):43-61. Epub 2019 Dec 24.

Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103, Leipzig, Germany.

Latency reduction in postsynaptic spikes is a well-known effect of spiking time-dependent plasticity. We expand this notion for long postsynaptic spike trains on single neurons, showing that, for a fixed input spike train, STDP reduces the number of postsynaptic spikes and concentrates the remaining ones. Then, we study the consequences of this phenomena in terms of coding, finding that this mechanism improves the neural code by increasing the signal-to-noise ratio and lowering the metabolic costs of frequent stimuli. Read More

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http://dx.doi.org/10.1007/s00422-019-00813-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062862PMC
February 2020

A neuromechanical model exploring the role of the common inhibitor motor neuron in insect locomotion.

Biol Cybern 2020 02 2;114(1):23-41. Epub 2019 Dec 2.

Biologically Inspired Robotics Laboratory, Case Western Reserve University, Glennan 418 10900 Euclid Avenue, Cleveland, OH, 44106, USA.

In this work, we analyze a simplified, dynamical, closed-loop, neuromechanical simulation of insect joint control. We are specifically interested in two elements: (1) how slow muscle fibers may serve as temporal integrators of sensory feedback and (2) the role of common inhibitory (CI) motor neurons in resetting this integration when the commanded position changes, particularly during steady-state walking. Despite the simplicity of the model, we show that slow muscle fibers increase the accuracy of limb positioning, even for motions much shorter than the relaxation time of the fiber; this increase in accuracy is due to the slow dynamics of the fibers; the CI motor neuron plays a critical role in accelerating muscle relaxation when the limb moves to a new position; as in the animal, this architecture enables the control of the stance phase speed, independent of swing phase amplitude or duration, by changing the gain of sensory feedback to the stance phase muscles. Read More

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http://dx.doi.org/10.1007/s00422-019-00811-yDOI Listing
February 2020

Investigating the role of gap junctions in seizure wave propagation.

Biol Cybern 2019 12 6;113(5-6):561-577. Epub 2019 Nov 6.

Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA.

The effect of gap junctions as well as the biological mechanisms behind seizure wave propagation is not completely understood. In this work, we use a simple neural field model to study the possible influence of gap junctions specifically on cortical wave propagation that has been observed in vivo preceding seizure termination. We consider a voltage-based neural field model consisting of an excitatory and an inhibitory population as well as both chemical and gap junction-like synapses. Read More

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http://dx.doi.org/10.1007/s00422-019-00809-6DOI Listing
December 2019
1 Read

The case for emulating insect brains using anatomical "wiring diagrams" equipped with biophysical models of neuronal activity.

Authors:
Logan T Collins

Biol Cybern 2019 12 6;113(5-6):465-474. Epub 2019 Nov 6.

Department of Psychology and Neuroscience, University of Colorado, Boulder, 2860 Wilderness Place, Boulder, CO, 80301, USA.

Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). Read More

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http://dx.doi.org/10.1007/s00422-019-00810-zDOI Listing
December 2019

A neural model of schemas and memory encoding.

Biol Cybern 2020 Apr 4;114(2):169-186. Epub 2019 Nov 4.

Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, USA.

The ability to rapidly assimilate new information is essential for survival in a dynamic environment. This requires experiences to be encoded alongside the contextual schemas in which they occur. Tse et al. Read More

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http://dx.doi.org/10.1007/s00422-019-00808-7DOI Listing

Comparative study of forced oscillators for the adaptive generation of rhythmic movements in robot controllers.

Biol Cybern 2019 12 1;113(5-6):547-560. Epub 2019 Oct 1.

Université de Lorraine, CNRS, LORIA, 54000, Nancy, France.

The interest of central pattern generators in robot motor coordination is universally recognized so much so that a lot of possibilities on different scales of modeling are nowadays available. While each method obviously has its advantages and drawbacks, some could be more suitable for human-robot interactions. In this paper, we compare three oscillator models: Matsuoka, Hopf and Rowat-Selverston models. Read More

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http://dx.doi.org/10.1007/s00422-019-00807-8DOI Listing
December 2019

NeuroSLAM: a brain-inspired SLAM system for 3D environments.

Biol Cybern 2019 12 30;113(5-6):515-545. Epub 2019 Sep 30.

Science and Engineering Faculty, Queensland University of Technology and Australian Centre for Robotic Vision, Brisbane, QLD, 4000, Australia.

Roboticists have long drawn inspiration from nature to develop navigation and simultaneous localization and mapping (SLAM) systems such as RatSLAM. Animals such as birds and bats possess superlative navigation capabilities, robustly navigating over large, three-dimensional environments, leveraging an internal neural representation of space combined with external sensory cues and self-motion cues. This paper presents a novel neuro-inspired 4DoF (degrees of freedom) SLAM system named NeuroSLAM, based upon computational models of 3D grid cells and multilayered head direction cells, integrated with a vision system that provides external visual cues and self-motion cues. Read More

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http://dx.doi.org/10.1007/s00422-019-00806-9DOI Listing
December 2019
1 Read

Generalised free energy and active inference.

Biol Cybern 2019 12 27;113(5-6):495-513. Epub 2019 Sep 27.

Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3BG, UK.

Active inference is an approach to understanding behaviour that rests upon the idea that the brain uses an internal generative model to predict incoming sensory data. The fit between this model and data may be improved in two ways. The brain could optimise probabilistic beliefs about the variables in the generative model (i. Read More

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http://dx.doi.org/10.1007/s00422-019-00805-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848054PMC
December 2019

A generic deviance detection principle for cortical On/Off responses, omission response, and mismatch negativity.

Biol Cybern 2019 12 19;113(5-6):475-494. Epub 2019 Aug 19.

Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, Leipzig, Germany.

Neural responses to sudden changes can be observed in many parts of the sensory pathways at different organizational levels. For example, deviants that violate regularity at various levels of abstraction can be observed as simple On/Off responses of individual neurons or as cumulative responses of neural populations. The cortical deviance-related responses supporting different functionalities (e. Read More

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http://dx.doi.org/10.1007/s00422-019-00804-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848254PMC
December 2019

A theory of consciousness: computation, algorithm, and neurobiological realization.

Authors:
J H van Hateren

Biol Cybern 2019 08 9;113(4):357-372. Epub 2019 Jul 9.

Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK, Groningen, The Netherlands.

The most enigmatic aspect of consciousness is the fact that it is felt, as a subjective sensation. The theory proposed here aims to explain this particular aspect. The theory encompasses both the computation that is presumably involved and the way in which that computation may be realized in the brain's neurobiology. Read More

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http://dx.doi.org/10.1007/s00422-019-00803-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658579PMC

Frequency-dependent responses of neuronal models to oscillatory inputs in current versus voltage clamp.

Biol Cybern 2019 08 8;113(4):373-395. Epub 2019 Jul 8.

Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, NJ, 07102, USA.

Action potential generation in neurons depends on a membrane potential threshold and therefore on how subthreshold inputs influence this voltage. In oscillatory networks, for example, many neuron types have been shown to produce membrane potential ([Formula: see text]) resonance: a maximum subthreshold response to oscillatory inputs at a nonzero frequency. Resonance is usually measured by recording [Formula: see text] in response to a sinusoidal current ([Formula: see text]), applied at different frequencies (f), an experimental setting known as current clamp (I-clamp). Read More

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http://dx.doi.org/10.1007/s00422-019-00802-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689413PMC

Information processing in the LGN: a comparison of neural codes and cell types.

Biol Cybern 2019 08 26;113(4):453-464. Epub 2019 Jun 26.

Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-106, Warsaw, Poland.

To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. Read More

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http://dx.doi.org/10.1007/s00422-019-00801-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658673PMC
August 2019
1 Read

An insect-inspired model for acquiring views for homing.

Biol Cybern 2019 08 10;113(4):439-451. Epub 2019 May 10.

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Wessling, Germany.

Wasps and bees perform learning flights when leaving their nest or food locations for the first time during which they acquire visual information that enables them to return successfully. Here we present and test a set of simple control rules underlying the execution of learning flights that closely mimic those performed by ground-nesting wasps. In the simplest model, we assume that the angle between flight direction and the nest direction as seen from the position of the insect is constant and only flips sign when pivoting direction around the nest is changed, resulting in a concatenation of piecewise defined logarithmic spirals. Read More

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http://dx.doi.org/10.1007/s00422-019-00800-1DOI Listing
August 2019
2 Reads

Modeling of spike trains in auditory nerves with self-exciting point processes of the von Mises type.

Authors:
Hiroyuki Mino

Biol Cybern 2019 06 19;113(3):347-356. Epub 2019 Apr 19.

Department of Electrical Engineering, Kanto Gakuin University, 1-50-1 Mutsuura E., Kanazawa-ku, Yokohama, 236-8501, Japan.

This article presents the modeling of spike trains in auditory nerve fiber (ANF) models with a one-memory self-exciting point process (SEPP) of the von Mises type. The ANF models were acoustically stimulated by a synaptic current of inner hair cells, or electrically stimulated by sinusoidally amplitude-modulated pulsatile waveforms. It has been shown that the parameters of one-memory SEPP of the von Mises type could be estimated by numerically maximizing the likelihood function from sample realizations of the spike trains in response to acoustic or electric stimulus. Read More

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http://dx.doi.org/10.1007/s00422-019-00799-5DOI Listing
June 2019
1 Read

Tutorial and simulations with ADAM: an adaptation and anticipation model of sensorimotor synchronization.

Biol Cybern 2019 08 8;113(4):397-421. Epub 2019 Apr 8.

Music, Cognition and Action Group, The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia.

Interpersonal coordination of movements often involves precise synchronization of action timing, particularly in expert domains such as ensemble music performance. According to the adaptation and anticipation model (ADAM) of sensorimotor synchronization, precise yet flexible interpersonal coordination is supported by reactive error correction mechanisms and anticipatory mechanisms that exploit systematic patterns in stimulus timing to plan future actions. Here, we provide a tutorial introduction to the computational architecture of ADAM and present a series of single- and dual-virtual agent simulations that examine the model parameters that produce ideal synchronization performance in different tempo conditions. Read More

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http://dx.doi.org/10.1007/s00422-019-00798-6DOI Listing
August 2019
1 Read

An unsupervised neuromorphic clustering algorithm.

Biol Cybern 2019 08 3;113(4):423-437. Epub 2019 Apr 3.

School of Engineering and Informatics, University of Sussex, Falmer, Brighton, BN1 9QJ, UK.

Brains perform complex tasks using a fraction of the power that would be required to do the same on a conventional computer. New neuromorphic hardware systems are now becoming widely available that are intended to emulate the more power efficient, highly parallel operation of brains. However, to use these systems in applications, we need "neuromorphic algorithms" that can run on them. Read More

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http://dx.doi.org/10.1007/s00422-019-00797-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658584PMC
August 2019
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Explaining event-related fields by a mechanistic model encapsulating the anatomical structure of auditory cortex.

Biol Cybern 2019 06 28;113(3):321-345. Epub 2019 Feb 28.

Special Lab Non-invasive Brain Imaging, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118, Magdeburg, Germany.

Event-related fields of the magnetoencephalogram are triggered by sensory stimuli and appear as a series of waves extending hundreds of milliseconds after stimulus onset. They reflect the processing of the stimulus in cortex and have a highly subject-specific morphology. However, we still have an incomplete picture of how event-related fields are generated, what the various waves signify, and why they are so subject-specific. Read More

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http://dx.doi.org/10.1007/s00422-019-00795-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510841PMC
June 2019
2 Reads

Evaluation of connectivity estimates using spiking neuronal network models.

Biol Cybern 2019 06 19;113(3):309-320. Epub 2019 Feb 19.

Center for Mathematics, Computing and Cognition, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.

The flow of information between different regions of the cortex is fundamental for brain function. Researchers use causality detection techniques, such as Granger causality, to infer connectivity among brain areas from time series. Generalized partial directed coherence (GPDC) is a frequency domain linear method based on vector autoregressive model, which has been applied in electroencephalography, local field potential, and blood oxygenation level-dependent signals. Read More

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http://dx.doi.org/10.1007/s00422-019-00796-8DOI Listing
June 2019
5 Reads

A process account of the uncontrolled manifold structure of joint space variance in pointing movements.

Biol Cybern 2019 06 15;113(3):293-307. Epub 2019 Feb 15.

Institute for Neural Computation, Ruhr-University, Bochum, Germany.

In many situations, the human movement system has more degrees of freedom than needed to achieve a given movement task. Martin et al. (Neural Comput 21(5):1371-1414, 2009) accounted for signatures of such redundancy like self-motion and motor equivalence in a process model in which a neural oscillator generated timed end-effector virtual trajectories that a neural dynamics transformed into joint virtual trajectories while decoupling task-relevant and task-irrelevant combinations of joint angles. Read More

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http://dx.doi.org/10.1007/s00422-019-00794-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510836PMC
June 2019
10 Reads

Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models.

Biol Cybern 2019 06 14;113(3):273-291. Epub 2019 Feb 14.

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

The concept of connectionism states that higher cognitive functions emerge from the interaction of many simple elements. Accordingly, research on canonical microcircuits conceptualizes findings on fundamental neuroanatomical circuits as well as recurrent organizational principles of the cerebral cortex and examines the link between architectures and their associated functionality. In this study, we establish minimal canonical microcircuit models as elements of hierarchical processing networks. Read More

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http://dx.doi.org/10.1007/s00422-019-00792-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510829PMC
June 2019
1 Read

Extracellular GABA assisting in organizing dynamic cell assemblies to shorten reaction time to sensory stimulation.

Biol Cybern 2019 06 12;113(3):257-271. Epub 2019 Feb 12.

Department of Intelligent Systems Engineering, Ibaraki University, 4-12-1 Nakanarusawa, Hitachi, Ibaraki, 316-8511, Japan.

Until recently, glia, which exceeds the number of neurons, was considered to only have supportive roles in the central nervous system, providing homeostatic controls and metabolic supports. However, recent studies suggest that glia interacts with neurons and plays active roles in information processing within neuronal circuits. To elucidate how glia contributes to neuronal information processing, we simulated a sensory neuron-glia (neuron-astrocyte) network model. Read More

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http://dx.doi.org/10.1007/s00422-019-00793-xDOI Listing
June 2019
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Control theory in biology and medicine : Introduction to the special issue.

Biol Cybern 2019 04;113(1-2):1-6

Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, Ohio, USA.

From September-December 2017, the Mathematical Biosciences Institute at Ohio State University hosted a series of workshops on control theory in biology and medicine, including workshops on control and modulation of neuronal and motor systems, control of cellular and molecular systems, control of disease / personalized medicine across heterogeneous populations, and sensorimotor control of animals and robots. This special issue presents tutorials and research articles by several of the participants in the MBI workshops. Read More

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http://dx.doi.org/10.1007/s00422-018-00791-5DOI Listing
April 2019
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Representation of object's shape by multiple electric images in electrolocation.

Biol Cybern 2019 06 10;113(3):239-255. Epub 2019 Jan 10.

Department of Engineering Science, University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, Japan.

Weakly electric fish generate an electric field by discharging an electric organ located on the tail region. An object near the fish modulates the self-generated electric field. The modulated field enables the fish to perceive objects even in complete darkness. Read More

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http://dx.doi.org/10.1007/s00422-018-00790-6DOI Listing
June 2019
4 Reads

A review on animal-robot interaction: from bio-hybrid organisms to mixed societies.

Biol Cybern 2019 06 14;113(3):201-225. Epub 2018 Nov 14.

The BioRobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, PI, Italy.

Living organisms are far superior to state-of-the-art robots as they have evolved a wide number of capabilities that far encompass our most advanced technologies. The merging of biological and artificial world, both physically and cognitively, represents a new trend in robotics that provides promising prospects to revolutionize the paradigms of conventional bio-inspired design as well as biological research. In this review, a comprehensive definition of animal-robot interactive technologies is given. Read More

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http://link.springer.com/10.1007/s00422-018-0787-5
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http://dx.doi.org/10.1007/s00422-018-0787-5DOI Listing
June 2019
30 Reads

An optimal control approach for blood pressure regulation during head-up tilt.

Biol Cybern 2019 04 30;113(1-2):149-159. Epub 2018 Oct 30.

NC State University, Raleigh, NC, USA.

This paper presents an optimal control approach to modeling effects of cardiovascular regulation during head-up tilt (HUT). Many patients who suffer from dizziness or light-headedness are administered a head-up tilt test to explore potential deficits within the autonomic control system, which maintains the cardiovascular system at homeostasis. This system is complex and difficult to study in vivo, and thus we propose to use mathematical modeling to achieve a better understanding of cardiovascular regulation during HUT. Read More

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http://link.springer.com/10.1007/s00422-018-0783-9
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http://dx.doi.org/10.1007/s00422-018-0783-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417936PMC
April 2019
2 Reads

Parameter subset selection techniques for problems in mathematical biology.

Biol Cybern 2019 04 30;113(1-2):121-138. Epub 2018 Oct 30.

Department of Mathematics, NC State University, Raleigh, NC, 27695, USA.

Patient-specific models for diagnostics and treatment planning require reliable parameter estimation and model predictions. Mathematical models of physiological systems are often formulated as systems of nonlinear ordinary differential equations with many parameters and few options for measuring all state variables. Consequently, it can be difficult to determine which parameters can reliably be estimated from available data. Read More

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http://dx.doi.org/10.1007/s00422-018-0784-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417952PMC
April 2019
1 Read

Human-like hopping in machines : Feedback- versus feed-forward-controlled motions.

Biol Cybern 2019 06 28;113(3):227-238. Epub 2018 Oct 28.

Lauflabor Locomotion Laboratory, Institute of Sport Science, TU Darmstadt, Magdalenenstr. 27, 64289, Darmstadt, Germany.

Template models of legged locomotion are powerful tools for gait analysis, but can also inspire robot design and control. In this paper, a spring-loaded inverted pendulum (SLIP) model is employed to control vertical hopping of a 2-segmented legged robot. Feed-forward and bio-inspired virtual model control using the SLIP model are compared. Read More

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http://dx.doi.org/10.1007/s00422-018-0788-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510817PMC
June 2019
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Deep active inference.

Authors:
Kai Ueltzhöffer

Biol Cybern 2018 12 22;112(6):547-573. Epub 2018 Oct 22.

, Heidelberg, Germany.

This work combines the free energy principle and the ensuing active inference dynamics with recent advances in variational inference in deep generative models, and evolution strategies to introduce the "deep active inference" agent. This agent minimises a variational free energy bound on the average surprise of its sensations, which is motivated by a homeostatic argument. It does so by optimising the parameters of a generative latent variable model of its sensory inputs, together with a variational density approximating the posterior distribution over the latent variables, given its observations, and by acting on its environment to actively sample input that is likely under this generative model. Read More

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http://dx.doi.org/10.1007/s00422-018-0785-7DOI Listing
December 2018
1 Read