Simulating a neural cross-talk model for between-hand interference during bimanual circle drawing

Studies on drawing circles with both hands in the horizontal plane have shown that this task is easy to perform across a wide range of movement frequencies under the symmetrical mode of coordination, whereas under the asymmetrical mode (both limbs moving clockwise or counterclockwise) increases in movement frequency have a disruptive effect on trajectory control and hand coordination. To account for these interference effects, we propose a simplified computer model for bimanual circle drawing based on the assumptions that (1) circular trajectories are generated from two orthogonal oscillations coupled with a phase delay, (2) the trajectories are organized on two levels, “intention” and “motor execution”, and (3) the motor systems controlling each hand are prone to neural cross-talk. The neural cross-talk consists in dispatching some fraction of any force command sent to one limb as a mirror image to the other limb. Assuming predominating coupling influences from the dominant to the nondominant limb, the simulations successfully reproduced the main characteristics of performance during asymmetrical bimanual circle drawing with increasing movement frequencies, including disruption of the circular form drawn with the nondominant hand, increasing dephasing of the hand movements, increasing variability of the phase difference, and occasional reversals of the movement direction in the nondominant limb. The implications of these results for current theories of bimanual coordination are discussed. Received: 23 June 1998 / Accepted in revised form: 20 April 1999     

On reinforcement and interference between stimuli

It is shown that the current “two-factor” theory of nerve excitation can account for sustained inhibition or enhancement by a sequence of stimulus pulses, and for the decrease in the reinforcement period with each successive pulse of the train.     

A new model for simple neural nets and its application in the design of a neural oscillator

The results of a previous theoretical study of a class of systems are applied for the design of neural nets which try to simulate biological behavior. Besides the models for single aperiodic and periodic neurons, a “neural oscillator” is developed which consists of two cross-excited neurons. Its response is similar to the firing pattern of certain biological neural oscillators, like the flying system of the locust. Also, by proper change of its parameters, it can be made highly irregular, providing a deterministic model for the spontaneous neural activity.     

Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise

We developed a theory of human stance control that predicted (1) how subjects re-weight their utilization of proprioceptive and graviceptive orientation information in experiments where eyes closed stance was perturbed by surface-tilt stimuli with different amplitudes, (2) the experimentally observed increase in body sway variability (i.e. the “remnant” body sway that could not be attributed to the stimulus) with increasing surface-tilt amplitude, (3) neural controller feedback gains that determine the amount of corrective torque generated in relation to sensory cues signaling body orientation, and (4) the magnitude and structure of spontaneous body sway. Responses to surface-tilt perturbations with different amplitudes were interpreted using a feedback control model to determine control parameters and changes in these parameters with stimulus amplitude. Different combinations of internal sensory and/or motor noise sources were added to the model to identify the properties of noise sources that were able to account for the experimental remnant sway characteristics. Various behavioral criteria were investigated to determine if optimization of these criteria could predict the identified model parameters and amplitude-dependent parameter changes. Robust findings were that remnant sway characteristics were best predicted by models that included both sensory and motor noise, the graviceptive noise magnitude was about ten times larger than the proprioceptive noise, and noise sources with signal-dependent properties provided better explanations of remnant sway. Overall results indicate that humans dynamically weight sensory system contributions to stance control and tune their corrective responses to minimize the energetic effects of sensory noise and external stimuli.     

Neural field model of binocular rivalry waves

We present a neural field model of binocular rivalry waves in visual cortex. For each eye we consider a one-dimensional network of neurons that respond maximally to a particular feature of the corresponding image such as the orientation of a grating stimulus. Recurrent connections within each one-dimensional network are assumed to be excitatory, whereas connections between the two networks are inhibitory (cross-inhibition). Slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We derive an analytical expression for the speed of a binocular rivalry wave as a function of various neurophysiological parameters, and show how properties of the wave are consistent with the wave-like propagation of perceptual dominance observed in recent psychophysical experiments. In addition to providing an analytical framework for studying binocular rivalry waves, we show how neural field methods provide insights into the mechanisms underlying the generation of the waves. In particular, we highlight the important role of slow adaptation in providing a “symmetry breaking mechanism” that allows waves to propagate.     

Interaction of cycles

We discuss under the McCulloch and Pitts assumptions for neural nets a circuit consisting ofk cycles such that one cycle is activated by an outside stimulus and sends an impulse to a second cycle which in its turn sends an impulse to the next cycle, etc., up to thekth cycle, which sends an impulse to a response. We thus have a “series” ofk cycles “interacting”. We give several theorems regarding the response patterns of such circuits under the additional constraint that the stimulus acts but once, and at the time it acts the circuit is at rest.     

Neural adaptation to tone sequences in the songbird forebrain: patterns, determinants, and relation to the build-up of auditory streaming

Neural responses to tones in the mammalian primary auditory cortex (A1) exhibit adaptation over the course of several seconds. Important questions remain about the taxonomic distribution of multi-second adaptation and its possible roles in hearing. It has been hypothesized that neural adaptation could explain the gradual “build-up” of auditory stream segregation. We investigated the influence of several stimulus-related factors on neural adaptation in the avian homologue of mammalian A1 (field L2) in starlings (Sturnus vulgaris). We presented awake birds with sequences of repeated triplets of two interleaved tones (ABA–ABA–…) in which we varied the frequency separation between the A and B tones (ΔF), the stimulus onset asynchrony (time from tone onset to onset within a triplet), and tone duration. We found that stimulus onset asynchrony generally had larger effects on adaptation compared with ΔF and tone duration over the parameter range tested. Using a simple model, we show how time-dependent changes in neural responses can be transformed into neurometric functions that make testable predictions about the dependence of the build-up of stream segregation on various spectral and temporal stimulus properties.     

A theory of steady-state activity in nerve-fiber networks II: The simple circuit

It is found that for a simple circuit of neurons, if this contains an odd number of inhibitory fibers, or none at all, or if the product of the activity parameters is less than unity, then the stimulus pattern always determines uniquely the steady-state activity. For circuits not of one of these types, it is possible to classify exclusively and exhaustively all possible activity patterns into three types, here called “odd”, “even”, and “mixed”. For any pattern of odd type and any pattern of even type there always exists a stimulus pattern consistent with both, but in no other way can such an association of activity patterns be made.     

On looking for neural networks and “cell assemblies” that underlie behavior: I. A mathematical model

A list of important features of animal behavior related primarily to learning has suggested to many investigators that an important aspect of brain function is the establishment or modification of functional connections between neural elements. In this paper a considerably, more inclusive list of behavioral features suggests that another important aspect may be the utilization of patterns of activity constituting the resonant responses of linear networks in the brain. To account for the longer list on the basis of connections requires additional assumptions, while both lists follow immediately from the second mechanism. An input locus may become functionally connected to a particular response mode by firing at a frequency which comes to approach the resonant frequency of that mode. The information in a complicated “cell assembly” of the type considered could be transmitted through a nerve tract by a very simple frequency code. One neurological guess is that frequency-coded inputs excite the transients in dedritic networks. It the amplititude of the pattern becomes large, as it would near, resonance, the all-or-none axonal response would become excited. This axonal response would tend to augment resonant patterns and disrupt other patterns, for a reasonal inherent in any linear network. It is shown how the mechanism might be related to the list of important behavioral features, and a numerical illustration is provided. Since this mechanism is automatically present in any linear network, unless special processes suppress it, it must have led to overt hehavior in any animal, possessing such networks. Evolution either suppressed this feature or exploited it. Since its properties resemble those of animal behavior, the latter might be suspected. This research was supported by the Office of Naval Research under Contract No. Nonr 2121(17) NR 049-148. Reproduction in whole or in part is permitted for any purpose of the United States Government.     

Tuned solutions in dynamic neural fields as building blocks for extended EEG models

The most prominent functional property of cortical neurons in sensory areas are their tuned receptive fields which provide specific responses of the neurons to external stimuli. Tuned neural firing indeed reflects the most basic and best worked out level of cognitive representations. Tuning properties can be dynamic on a short time-scale of fractions of a second. Such dynamic effects have been modeled by localised solutions (also called “bumps” or “peaks”) in dynamic neural fields. In the present work we develop an approximation method to reduce the dynamics of localised activation peaks in systems of n coupled nonlinear d-dimensional neural fields with transmission delays to a small set of delay differential equations for the peak amplitudes and widths only. The method considerably simplifies the analysis of peaked solutions as demonstrated for a two-dimensional example model of neural feature selectivity in the brain. The reduced equations describe the effective interaction between pools of local neurons of several (n) classes that participate in shaping the dynamic receptive field responses. To lowest order they resemble neural mass models as they often form the base of EEG-models. Thereby they provide a link between functional small-scale receptive field models and more coarse-grained EEG-models. More specifically, they connect the dynamics in feature-selective cortical microcircuits to the more abstract local elements used in coarse-grained models. However, beside amplitudes the reduced equations also reflect the sharpness of tuning of the activity in a d-dimensional feature space in response to localised stimuli.     

Energy efficiency of electron plasma emitters

Electron emission influence from gas-discharge plasma on plasma emitter energy parameters is considered. It is shown, that electron emission from plasma is accompanied by energy contribution redistribution in the gas-discharge from plasma emitter supplies sources—the gas-discharge power supply and the accelerating voltage power supply. Some modes of electron emission as a result can be realized: “a probe measurements mode,” “a transitive mode,” and “a full switching mode.”     

Slow Potentials in the Rhinal Region of the Cat Brain Cortex Related to Visual Recognition Memory

We examined correlation between the development of slow potentials in the rhinal cortical region of cats and results of behavioral testing of visual recognition memory of these animals in the “delayed nonmatching-to-sample” (DNMS) selection version. Among different types of cognitive memory, the recognition memory occupies a special position because the process of taking off (retrieval) of a memory trace from the “stores” can be completely and effectively controlled by the experimenter (this process is initiated only after repetitive presentation of a stimulus identical to that whose trace should be subjected to retrieval or after presentation of an absolutely new stimulus whose trace had not been formed earlier). Recording of the field potentials was performed from the surface of the rhinal cortex using stereotaxically implanted mono- or bipolar Ag-AgCl electrodes after the experimental animals reached a sufficiently high level of successful performance of the test for recognition memory. Analysis of relations between negative slow potentials in the rhinal cortex and the correctness of performance (according to Spearman’s nonparametric test) demonstrated the existence of significant correlation between the electrophysiological and behavioral indices of visual recognition memory only within a late portion (final 10 sec but not initial 10 ones) of the retention interval for memorizing the trace of single presentation of a visual stimulus. The data obtained are interpreted as a confirmation of the existence of correlation between generation of negative slow potentials in the rhinal cortical region and the process of retrieval of the sample from the visual memory stores.     

A stochastic model for head lice infections

We investigate the dynamics of head lice infections in schools, by consideringa model for endemic infection based on a stochastic SIS (susceptible-infected-susceptible) epidemic model, with the addition of an external source of infection. We deduce a range of properties of our model, including the length of a single outbreak of infection. We use the stationary distribution of the number of infected individuals, in conjunction with data from a recent study carried out in Welsh schools on the prevalence of head lice infections, and employ maximum likelihood methods to obtain estimates of the model parameters. A complication is that, for each school, only a sample of the pupils was checked for infection. Our likelihood function takes account of the missing data by incorporating a hypergeometric sampling element. We arrive at estimates of the ratios of the “within school” and “external source” transmission rates to the recovery rate and use these to obtain estimates for various quantities of interest.      

Mechanisms of Neural and Behavioral Dysfunction in Alzheimer’s Disease

This review critically examines progress in understanding the link between Alzheimer’s disease (AD) molecular pathogenesis and behavior, with an emphasis on the impact of amyloid-β. We present the argument that the AD research field requires more multifaceted analyses into the impacts of Alzheimer’s pathogenesis which combine simultaneous molecular-, circuit-, and behavior-level approaches. Supporting this argument is a review of particular research utilizing similar, “systems-level” methods in mouse models of AD. Related to this, a critique of common physiological and behavioral models is made—highlighting the likely usefulness of more refined and specific tools in understanding the relationship between candidate molecular pathologies and behavioral dysfunction. Finally, we propose challenges for future research which, if met, may greatly extend our current understanding of how AD molecular pathology impacts neural network function and behavior and possibly may lead to refinements in disease therapeutics.     

Behavioral modification in choice process of<Emphasis Type="Italic">Drosophila</Emphasis>

In visual operant conditioning ofDrosophila at the flight simulator, only motor output of flies—yaw torque—is recorded, which is involved in the conditioning process. The current study used a newly-designed data analysis method to study the torque distribution ofDrosophila. Modification of torque distribution represents the effects of operant conditioning on flies’ behavioral mode. Earlier works^[10] showed that, when facing contradictory visual cues, flies could make choices based upon the relative weightiness of different cues, and it was demonstrated that mushroom bodies might play an important role in such choice behavior. The new “torque-position map” method was used to explore the CS-US associative learning and choice behavior inDrosophila from the aspect of its behavioral mode. Finally, this work also discussed various possible neural bases involved in visual associative learning, choice processing and modification processing of the behavioral mode in the visual operant conditioning ofDrosophila.     

Source-sink landscape theory and its ecological significance

Exploring the relationships between landscape pattern and ecological processes is the key topic of landscape ecology, for which, a large number of indices as well as landscape pattern analysis model were developed. However, one problem faced by landscape ecologists is that it is hard to link the landscape indices with a specific ecological process. Linking landscape pattern and ecological processes has become a challenge for landscape ecologists. “Source” and “sink” are common concepts used in air pollution research, by which the movement direction and pattern of different pollutants in air can be clearly identified. In fact, for any ecological process, the research can be considered as a balance between the source and the sink in space. Thus, the concepts of “source” and “sink” could be implemented to the research of landscape pattern and ecological processes. In this paper, a theory of sourcesink landscape was proposed, which include: (1) In the research of landscape pattern and ecological process, all landscape types can be divided into two groups, “source” landscape and “sink” landscape. “Source” landscape contributes positively to the ecological process, while “sink” landscape is unhelpful to the ecological process. (2) Both landscapes are recognized with regard to the specific ecological process. “Source” landscape in a target ecological process may change into a “sink” landscape as in another ecological process. Therefore, the ecological process should be determined before “source” or “sink” landscape were defined. (3) The key point to distinguish “source” landscape from “sink” landscape is to quantify the effect of landscape on ecological process. The positive effect is made by “source” landscape, and the negative effect by “sink” landscape. (4) For the same ecological process, the contribution of “source” landscapes may vary, and it is the same to the “sink” landscapes. It is required to determine the weight of each landscape type on ecological processes. (5) The sourcesink principle can be applied to non-point source pollution control, biologic diversity protection, urban heat island effect mitigation, etc. However, the landscape evaluation models need to be calibrated respectively, because different ecological processes correspond with different source-sink landscapes and evaluation models for the different study areas. This theory is helpful to further study landscape pattern and ecological process, and offers a basis for new landscape index design. __________ Translated from Acta Ecologica Sinica, 2006, 26(5): 1444–1449 [译自: 生态学报]     

Modeling of the actomyosin ATPase activity

In the rapid “quench” kientics of myosin, the “initial phosphate burst” is the excess inorganic phosphate that is produced during the early time-course of ATP hydrolysis by myosin subfragment-1 (S-1) or HMM. In general, the existence of a Pi burst implies a rapid (i.e., generally an order of magnitude faster than the steady-state hydrolysis rate) lysis of the phospho-anhydride bond within the ATP molecule, followed by one or more slower steps that are rate limiting for the process. Thus, the presence of a Pi burst can provide an important clue to the mechanism of the reaction. However, in the case of actomyosin, this clue as long been the subject of controversy and misunderstanding. To measure the (initial) Pi burst, myosin S-1 (or HMM) is rapidly mixed with ATP and then the mixture is acid quenched after a specific time period. The medium produced contains free Pi generated from hydrolysis of the ATP. The quantitative measure of the phosphate generated in this way has always been significantly greater than that expected by steady-state “release” of Pi alone, and it is that very difference between this measured Pi after the quench and that amount of Pi expected to be released by steady-state considerations in that same time period that has been referred to as the “initial Pi burst”. Recent investigations of the kinetics of Pi release have used an entirely new method that directly measures the release of Pi from the enzyme-product complex. These studies have made reference to the properties of the “initial Pi burst” in the presence of actin, as well as to a new kinetic entity: the “burst of Pi release”, and have been often vague concerning the true nature of the initial Pi burst, as well as the properties of Pi release as predicted by the current models of the actin activation of the myosin ATPase activity. The purpose of the current article is to correct this oversight, to discuss the “burst” in some detail, and to display the kinetics predicted by the current models for the actin activation of myosin. Furthermore, predictions for the kinetics of the new “burst of Pi release” are discussed in terms of its ability to discriminate between the two current competing models for actin activation of the myosin ATPase activity.     

Acquisition and transfer of visual Go/No-go discrimination by a chimpanzee

An adolescent female chimpanzee was trained to press a key in the presence of a computer-graphic geometric figure (“Go” stimulus) within 5 sec and not to press the key during 5-sec presentations of another figure (“No-go” stimulus) with food reinforcement. In the acquisition training, the accuracy of performance increased primarily as a result of learning to inhibit key presses in No-go trials. The chimpanzee acquired this “Go/No-go” visual discrimination task in 1,260 trials. She was then given 14 successive transfer problems. The results for these problems suggested that learning-set formation and repeated use of the same discriminative stimuli both influenced transfer to new problems.     

From “Lists of Traits” to “Open-Mindedness”: Emerging Issues in Cultural Competence Education

The incorporation of “culture” into U.S. biomedicine has been increasing at a rapid pace over the last several decades. Advocates for “cultural competence” point to changing patient demographics and growing health disparities as they call for improved educational efforts that train health providers to care for patients from a variety of backgrounds. Medical anthropologists have long been critical of the approach to “culture” that emerges in cultural competence efforts, identifying an essentialized, static notion of culture that is conflated with racial and ethnic categories and seen to exist primarily among exotic “Others.” With this approach, culture can become a “list of traits” associated with various racial and ethnic groups that must be mastered by health providers and applied to patients as necessary. This article uses an ethnographic examination of cultural competence training to highlight recent efforts to develop more nuanced approaches to teaching culture. I argue that much of contemporary cultural competence education has rejected the “list of traits” approach and instead aims to produce a new kind of health provider who is “open-minded,” willing to learn about difference, and treats each patient as an individual. This shift, however, can ultimately reinforce behavioral understandings of culture and draw attention away from the social conditions and power differentials that underlie health inequalities.     

A neural model for conditioned avoidance learning

A mathematical model for learning of a conditioned avoidance behavior is presented. An identification of the net excitation of a neural model (Rashevsky, N., 1960.Mathematical Biophysics. Vol. II. New York: Dover Publications, Inc.) with the instantaneous probability of response is introduced and its usefulness in discussing block-trial learning performances in the conditioned avoidance situation is outlined for normal and brain-operated animals, using experimental data collected by the author. Later, the model is applied to consecutive trial learning and connection is made with the approach of H. D. Landahl (1964. “An Avoidance Learning Situation. A Neural Net Model.”Bull. Math. Biophysics,26, 83–89; and 1965, “A Neural Net Model for Escape Learning.”Bull. Math. Biophysics,27, Special Edition, 317–328) wherein lie further data with which the model can be compared.