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Sensitivity minimization, biological homeostasis and information theory Biol. Cybern. (IF 1.111) Pub Date : 2021-01-21 Debojyoti Biswas, Pablo A. Iglesias
All organisms must be able to adapt to changes in the environment. To this end, they have developed sophisticated regulatory mechanisms to ensure homeostasis. Control engineers, who must design similar regulatory systems, have developed a number of general principles that govern feedback regulation. These lead to constraints which impose trade-offs that arise when developing controllers to minimize
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Bayesian mechanics of perceptual inference and motor control in the brain Biol. Cybern. (IF 1.111) Pub Date : 2021-01-20 Chang Sub Kim
The free energy principle (FEP) in the neurosciences stipulates that all viable agents induce and minimize informational free energy in the brain to fit their environmental niche. In this study, we continue our effort to make the FEP a more physically principled formalism by implementing free energy minimization based on the principle of least action. We build a Bayesian mechanics (BM) by casting the
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Catastrophe theory in work from heartbeats to eye movements Biol. Cybern. (IF 1.111) Pub Date : 2021-01-16 Syed Hussain Ather
In "Slow-fast control of eye movements: an instance of Zeeman’s model for an action," Clement and Akman extended Zeeman's model for the heartbeat to describe eye movement control of different species using aspects of catastrophe theory. The scientists created a model that gives an example of how the techniques of catastrophe theory can be used to understand information processing by biological organisms
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Multifrequency Hebbian plasticity in coupled neural oscillators Biol. Cybern. (IF 1.111) Pub Date : 2021-01-05 Ji Chul Kim, Edward W. Large
We study multifrequency Hebbian plasticity by analyzing phenomenological models of weakly connected neural networks. We start with an analysis of a model for single-frequency networks previously shown to learn and memorize phase differences between component oscillators. We then study a model for gradient frequency neural networks (GrFNNs) which extends the single-frequency model by introducing frequency
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Control for multifunctionality: bioinspired control based on feeding in Aplysia californica Biol. Cybern. (IF 1.111) Pub Date : 2020-12-10 Victoria A. Webster-Wood, Jeffrey P. Gill, Peter J. Thomas, Hillel J. Chiel
Animals exhibit remarkable feats of behavioral flexibility and multifunctional control that remain challenging for robotic systems. The neural and morphological basis of multifunctionality in animals can provide a source of bioinspiration for robotic controllers. However, many existing approaches to modeling biological neural networks rely on computationally expensive models and tend to focus solely
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Analysis of neural clusters due to deep brain stimulation pulses Biol. Cybern. (IF 1.111) Pub Date : 2020-12-09 Daniel Kuelbs, Jacob Dunefsky, Bharat Monga, Jeff Moehlis
Deep brain stimulation (DBS) is an established method for treating pathological conditions such as Parkinson’s disease, dystonia, Tourette syndrome, and essential tremor. While the precise mechanisms which underly the effectiveness of DBS are not fully understood, several theoretical studies of populations of neural oscillators stimulated by periodic pulses have suggested that this may be related to
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The roles of ascending sensory signals and top-down central control in the entrainment of a locomotor CPG Biol. Cybern. (IF 1.111) Pub Date : 2020-12-08 Marcello G. Codianni, Silvia Daun, Jonathan E. Rubin
Previous authors have proposed two basic hypotheses about the factors that form the basis of locomotor rhythms in walking insects: sensory feedback only or sensory feedback together with rhythmic activity of small neural circuits called central pattern generators (CPGs). Here we focus on the latter. Following this concept, to generate functional outputs, locomotor control must feature both rhythm generation
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On the rate coding response of peripheral sensory neurons Biol. Cybern. (IF 1.111) Pub Date : 2020-12-08 Willy Wong
The rate coding response of a single peripheral sensory neuron in the asymptotic, near-equilibrium limit can be derived using information theory, asymptotic Bayesian statistics and a theory of complex systems. Almost no biological knowledge is required. The theoretical expression shows good agreement with spike-frequency adaptation data across different sensory modalities and animal species. The approach
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A feedback information-theoretic transmission scheme (FITTS) for modeling trajectory variability in aimed movements Biol. Cybern. (IF 1.111) Pub Date : 2020-12-08 Julien Gori, Olivier Rioul
Trajectories in human aimed movements are inherently variable. Using the concept of positional variance profiles, such trajectories are shown to be decomposable into two phases: In a first phase, the variance of the limb position over many trajectories increases rapidly; in a second phase, it then decreases steadily. A new theoretical model, where the aiming task is seen as a Shannon-like communication
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Importance of self-connections for brain connectivity and spectral connectomics Biol. Cybern. (IF 1.111) Pub Date : 2020-11-26 Xiao Gao, P. A. Robinson
Spectral analysis and neural field theory are used to investigate the role of local connections in brain connectivity matrices (CMs) that quantify connectivity between pairs of discretized brain regions. This work investigates how the common procedure of omitting such self-connections (i.e., the diagonal elements of CMs) in published studies of brain connectivity affects the properties of functional
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Optimizing enzymatic catalysts for rapid turnover of substrates with low enzyme sequestration Biol. Cybern. (IF 1.111) Pub Date : 2020-10-12 Abhishek Deshpande, Thomas E. Ouldridge
Enzymes are central to both metabolism and information processing in cells. In both cases, an enzyme’s ability to accelerate a reaction without being consumed in the reaction is crucial. Nevertheless, enzymes are transiently sequestered when they bind to their substrates; this sequestration limits activity and potentially compromises information processing and signal transduction. In this article,
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Slow–fast control of eye movements: an instance of Zeeman’s model for an action Biol. Cybern. (IF 1.111) Pub Date : 2020-09-30 Richard A. Clement, Ozgur E. Akman
The rapid eye movements (saccades) used to transfer gaze between targets are examples of an action. The behaviour of saccades matches that of the slow–fast model of actions originally proposed by Zeeman. Here, we extend Zeeman’s model by incorporating an accumulator that represents the increase in certainty of the presence of a target, together with an integrator that converts a velocity command to
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Nonstationary shot noise modeling of neuron membrane potentials by closed-form moments and Gram-Charlier expansions. Biol. Cybern. (IF 1.111) Pub Date : 2020-09-21 Nicolas Privault
We present exact analytical expressions of moments of all orders for neuronal membrane potentials in the multiplicative nonstationary Poisson shot noise model. As an application, we derive closed-form Gram–Charlier density expansions that show how the probability density functions of potentials in such models differ from their Gaussian diffusion approximations. This approach extends the results of
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Mechanical aspects of the semicircular ducts in the vestibular system. Biol. Cybern. (IF 1.111) Pub Date : 2020-09-05 Mees Muller
The semicircular ducts (SCDs) of the vestibular system play an instrumental role in equilibration and rotation perception of vertebrates. The present paper is a review of quantitative approaches and shows how SCDs function. It consists of three parts. First, the biophysical mechanisms of an SCD system composed of three mutually connected ducts, allowing endolymph to flow from one duct into another
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Optimal time-varying postural control in a single-link neuromechanical model with feedback latencies. Biol. Cybern. (IF 1.111) Pub Date : 2020-08-31 Kamran Iqbal
Maintaining balance during quiet standing is a challenging task for the neural control mechanisms due to the inherent instabilities involved in the task. The feedback latencies and the lowpass characteristics of skeletal muscle add to the difficulty of regulating postural dynamics in real-time. Inverted-pendulum (IP) type robotic models have served as a popular paradigm to investigate control of postural
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Beetle-robot hybrid interaction: sex, lateralization and mating experience modulate behavioural responses to robotic cues in the larger grain borer Prostephanus truncatus (Horn). Biol. Cybern. (IF 1.111) Pub Date : 2020-07-31 Donato Romano,Giovanni Benelli,Nickolas G Kavallieratos,Christos G Athanassiou,Angelo Canale,Cesare Stefanini
Ethorobotics, a new fascinating field of biorobotics, proposes the use of robotic replicas as an advanced method for investigating animal behaviour. This novel research approach can also encourage the development of advanced bioinspired robots. In the present study, we investigated the pushing behaviour, a particular display occurring in several beetle species, such as the larger grain borer, Prostephanus
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Time- and frequency-resolved covariance analysis for detection and characterization of seizures from intracraneal EEG recordings. Biol. Cybern. (IF 1.111) Pub Date : 2020-07-12 Melisa Maidana Capitán,Nuria Cámpora,Claudio Sebastián Sigvard,Silvia Kochen,Inés Samengo
The amount of power in different frequency bands of the electroencephalogram (EEG) carries information about the behavioral state of a subject. Hence, neurologists treating epileptic patients monitor the temporal evolution of the different bands. We propose a covariance-based method to detect and characterize epileptic seizures operating on the band-filtered EEG signal. The algorithm is unsupervised
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Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds. Biol. Cybern. (IF 1.111) Pub Date : 2020-07-04 Qinbing Fu,Shigang Yue
Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly
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Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system. Biol. Cybern. (IF 1.111) Pub Date : 2020-06-24 Žiga Bostner,Gregory Knoll,Benjamin Lindner
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
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In Memoriam: Erol Başar and the General Systems Theory-a personal reminiscence. Biol. Cybern. (IF 1.111) Pub Date : 2020-06-01 Vasil Kolev
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Elbow angle generation during activities of daily living using a submovement prediction model. Biol. Cybern. (IF 1.111) Pub Date : 2020-06-09 Seyedeh Somayeh Naghibi,Ali Fallah,Ali Maleki,Farnaz Ghassemi
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
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A Renewed Vision for Biological Cybernetics. Biol. Cybern. (IF 1.111) Pub Date : 2020-06-01 Lindner Benjamin,Peter J Thomas,Jean-Marc Fellous
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Bio-inspired multi-scale fusion. Biol. Cybern. (IF 1.111) Pub Date : 2020-04-22 Stephen Hausler,Zetao Chen,Michael E Hasselmo,Michael Milford
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
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A model of path integration and representation of spatial context in the retrosplenial cortex. Biol. Cybern. (IF 1.111) Pub Date : 2020-04-18 Mingda Ju,Philippe Gaussier
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
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From spatial navigation via visual construction to episodic memory and imagination. Biol. Cybern. (IF 1.111) Pub Date : 2020-04-13 Michael A Arbib
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
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Conjunctive reward-place coding properties of dorsal distal CA1 hippocampus cells. Biol. Cybern. (IF 1.111) Pub Date : 2020-04-07 Zhuocheng Xiao,Kevin Lin,Jean-Marc Fellous
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. https://doi.org/10.1016/j.neuron.2018.06.008) have identified a subpopulation of hippocampal cells selectively
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Cognitive swarming in complex environments with attractor dynamics and oscillatory computing. Biol. Cybern. (IF 1.111) Pub Date : 2020-03-31 Joseph D Monaco,Grace M Hwang,Kevin M Schultz,Kechen Zhang
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
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EO-MTRNN: evolutionary optimization of hyperparameters for a neuro-inspired computational model of spatiotemporal learning. Biol. Cybern. (IF 1.111) Pub Date : 2020-03-17 Erhard Wieser,Gordon Cheng
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
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Simulating Small Neural Circuits with a Discrete Computational Model. Biol. Cybern. (IF 1.111) Pub Date : 2020-03-13 Nikolay I Bazenkov,Boris A Boldyshev,Varvara Dyakonova,Oleg P Kuznetsov
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. A neuron has several states, and the state transitions follow endogenous patterns which roughly correspond to firing behavior observed
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The effects of within-neuron degree correlations in networks of spiking neurons. Biol. Cybern. (IF 1.111) Pub Date : 2020-03-02 Carlo R Laing,Christian Bläsche
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
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Modeling of the neural mechanism underlying the terrestrial turning of the salamander. Biol. Cybern. (IF 1.111) Pub Date : 2020-02-27 Qiang Liu,Yongshuo Zhang,Jingzhuo Wang,Huizhen Yang,Lu Hong
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
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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. (IF 1.111) Pub Date : 2020-02-24 Nicolas Cazin,Pablo Scleidorovich,Alfredo Weitzenfeld,Peter Ford Dominey
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
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Modeling awake hippocampal reactivations with model-based bidirectional search. Biol. Cybern. (IF 1.111) Pub Date : 2020-02-17 Mehdi Khamassi,Benoît Girard
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
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An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks Biol. Cybern. (IF 1.111) Pub Date : 2020-01-06 Kunpeng Yao, Aude Billard
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. We studied the acquisition of bimanual fine manipulation skills in watchmaking tasks, which
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Establishing metrics and control laws for the learning process: ball and beam balancing. Biol. Cybern. (IF 1.111) Pub Date : 2020-01-18 Gergely Buza,John Milton,Laszlo Bencsik,Tamas Insperger
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
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Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation. Biol. Cybern. (IF 1.111) Pub Date : 2020-02-04 Anne Beuter,Anne Balossier,François Vassal,Simone Hemm,Vitaly Volpert
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
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Spiking time-dependent plasticity leads to efficient coding of predictions Biol. Cybern. (IF 1.111) Pub Date : 2019-12-24 Pau Vilimelis Aceituno, Masud Ehsani, Jürgen Jost
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
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Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability. Biol. Cybern. (IF 1.111) Pub Date : 2020-01-20 Chunjiang Fu,Yasuyuki Suzuki,Pietro Morasso,Taishin Nomura
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. We aimed
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A neuromechanical model exploring the role of the common inhibitor motor neuron in insect locomotion. Biol. Cybern. (IF 1.111) Pub Date : 2019-12-02 Mantas Naris,Nicholas S Szczecinski,Roger D Quinn
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
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Unstructured network topology begets order-based representation by privileged neurons. Biol. Cybern. (IF 1.111) Pub Date : 2020-02-27 Christoph Bauermeister,Hanna Keren,Jochen Braun
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
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Complex spatial navigation in animals, computational models and neuro-inspired robots. Biol. Cybern. (IF 1.111) Pub Date : 2020-04-01 Jean-Marc Fellous,Peter Dominey,Alfredo Weitzenfeld
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A computational model for spatial cognition combining dorsal and ventral hippocampal place field maps: multiscale navigation. Biol. Cybern. (IF 1.111) Pub Date : 2020-01-09 Pablo Scleidorovich,Martin Llofriu,Jean-Marc Fellous,Alfredo Weitzenfeld
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
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A neural model of schemas and memory encoding. Biol. Cybern. (IF 1.111) Pub Date : 2019-11-04 Tiffany Hwu,Jeffrey L Krichmar
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. (Science 316(5821):76-82, 2007) showed that new information matching a preexisting schema is learned rapidly. To better understand the neurobiological mechanisms for creating and maintaining schemas
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Investigating the role of gap junctions in seizure wave propagation. Biol. Cybern. (IF 1.111) Pub Date : 2019-11-06 Laura R González-Ramírez,Ava J Mauro
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
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The case for emulating insect brains using anatomical "wiring diagrams" equipped with biophysical models of neuronal activity. Biol. Cybern. (IF 1.111) Pub Date : 2019-11-06 Logan T Collins
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
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Comparative study of forced oscillators for the adaptive generation of rhythmic movements in robot controllers. Biol. Cybern. (IF 1.111) Pub Date : 2019-10-01 Melanie Jouaiti,Patrick Hénaff
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
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NeuroSLAM: a brain-inspired SLAM system for 3D environments. Biol. Cybern. (IF 1.111) Pub Date : 2019-09-30 Fangwen Yu,Jianga Shang,Youjian Hu,Michael Milford
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
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Generalised free energy and active inference. Biol. Cybern. (IF 1.111) Pub Date : 2019-09-27 Thomas Parr,Karl J Friston
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.e. perceptual inference). Alternatively, by acting on the world, it could change
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A generic deviance detection principle for cortical On/Off responses, omission response, and mismatch negativity. Biol. Cybern. (IF 1.111) Pub Date : 2019-08-21 Vincent S C Chien,Burkhard Maess,Thomas R Knösche
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.g
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A theory of consciousness: computation, algorithm, and neurobiological realization. Biol. Cybern. (IF 1.111) Pub Date : 2019-07-09 J H van Hateren
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. It is assumed that the brain makes an internal estimate of an individual's own evolutionary
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Frequency-dependent responses of neuronal models to oscillatory inputs in current versus voltage clamp. Biol. Cybern. (IF 1.111) Pub Date : 2019-07-08 Horacio G Rotstein,Farzan Nadim
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
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Information processing in the LGN: a comparison of neural codes and cell types. Biol. Cybern. (IF 1.111) Pub Date : 2019-06-26 Agnieszka Pregowska,Alex Casti,Ehud Kaplan,Eligiusz Wajnryb,Janusz Szczepanski
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
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An insect-inspired model for acquiring views for homing. Biol. Cybern. (IF 1.111) Pub Date : 2019-05-10 Patrick Schulte,Jochen Zeil,Wolfgang Stürzl
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
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Modeling of spike trains in auditory nerves with self-exciting point processes of the von Mises type. Biol. Cybern. (IF 1.111) Pub Date : 2019-04-19 Hiroyuki Mino
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
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Tutorial and simulations with ADAM: an adaptation and anticipation model of sensorimotor synchronization. Biol. Cybern. (IF 1.111) Pub Date : 2019-04-08 Bronson Harry,Peter E Keller
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
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An unsupervised neuromorphic clustering algorithm. Biol. Cybern. (IF 1.111) Pub Date : 2019-04-03 Alan Diamond,Michael Schmuker,Thomas Nowotny
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. Here we develop
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Explaining event-related fields by a mechanistic model encapsulating the anatomical structure of auditory cortex. Biol. Cybern. (IF 1.111) Pub Date : 2019-02-28 Aida Hajizadeh,Artur Matysiak,Patrick J C May,Reinhard König
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
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Evaluation of connectivity estimates using spiking neuronal network models. Biol. Cybern. (IF 1.111) Pub Date : 2019-02-19 Ronaldo V Nunes,Marcelo B Reyes,Raphael Y de Camargo
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
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A process account of the uncontrolled manifold structure of joint space variance in pointing movements. Biol. Cybern. (IF 1.111) Pub Date : 2019-02-15 Valère Martin,Hendrik Reimann,Gregor Schöner
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
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Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models. Biol. Cybern. (IF 1.111) Pub Date : 2019-02-14 Tim Kunze,Jens Haueisen,Thomas R Knösche
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
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