The preferred direction

2021 ◽  
Author(s):  
Benjamin E. Feldman
Keyword(s):  
Preferred Direction

scholarly journals Run-and-Tumble Motion: The Role of Reversibility

2021 ◽  
Vol 183 (3) ◽  
Author(s):  
Bart van Ginkel ◽  
Bart van Gisbergen ◽  
Frank Redig
Keyword(s):  
Free Energy ◽  
Diffusion Coefficient ◽  
Large Deviations ◽  
Energy Function ◽  
Internal State ◽  
Rate Function ◽  
Free Energy Function ◽  
Large Deviations Principle ◽  
Preferred Direction ◽  
State Process

AbstractWe study a model of active particles that perform a simple random walk and on top of that have a preferred direction determined by an internal state which is modelled by a stationary Markov process. First we calculate the limiting diffusion coefficient. Then we show that the ‘active part’ of the diffusion coefficient is in some sense maximal for reversible state processes. Further, we obtain a large deviations principle for the active particle in terms of the large deviations rate function of the empirical process corresponding to the state process. Again we show that the rate function and free energy function are (pointwise) optimal for reversible state processes. Finally, we show that in the case with two states, the Fourier–Laplace transform of the distribution, the moment generating function and the free energy function can be computed explicitly. Along the way we provide several examples.

scholarly journals Symmetry aspects in the macroscopic dynamics of magnetorheological gels and general liquid crystalline magnetic elastomers

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Harald Pleiner ◽  
Helmut R. Brand
Keyword(s):  
Electric Fields ◽  
Time Reversal ◽  
Liquid Crystalline ◽  
Second Law Of Thermodynamics ◽  
Time Reversal Symmetry ◽  
Local Conservation ◽  
Continuous Symmetry ◽  
Polar Order ◽  
Preferred Direction ◽  
Symmetry Properties

Abstract We investigate theoretically the macroscopic dynamics of various types of ordered magnetic fluid, gel, and elastomeric phases. We take a symmetry point of view and emphasize its importance for a macroscopic description. The interactions and couplings among the relevant variables are based on their individual symmetry behavior, irrespective of the detailed nature of the microscopic interactions involved. Concerning the variables we discriminate between conserved variables related to a local conservation law, symmetry variables describing a (spontaneously) broken continuous symmetry (e.g., due to a preferred direction) and slowly relaxing ones that arise from special conditions of the system are considered. Among the relevant symmetries, we consider the behavior under spatial rotations (e.g., discriminating scalars, vectors or tensors), under spatial inversion (discriminating e.g., polar and axial vectors), and under time reversal symmetry (discriminating e.g., velocities from polarizations, or electric fields from magnetic ones). Those symmetries are crucial not only to find the possible cross-couplings correctly but also to get a description of the macroscopic dynamics that is compatible with thermodynamics. In particular, time reversal symmetry is decisive to get the second law of thermodynamics right. We discuss (conventional quadrupolar) nematic order, polar order, active polar order, as well as ferromagnetic order and tetrahedral (octupolar) order. In a second step, we show some of the consequences of the symmetry properties for the various systems that we have worked on within the SPP1681, including magnetic nematic (and cholesteric) elastomers, ferromagnetic nematics (also with tetrahedral order), ferromagnetic elastomers with tetrahedral order, gels and elastomers with polar or active polar order, and finally magnetorheological fluids and gels in a one- and two-fluid description.

Measures of preferred direction for environmental and ecological circular data

2006 ◽  
Vol 13 (3) ◽  
pp. 311-324 ◽  
Author(s):  
B. Sango Otieno ◽  
Christine M. Anderson-Cook
Keyword(s):  
Circular Data ◽  
Preferred Direction

Energy Harvesting Using the Rattleback: Theoretical Analysis and Simulations of Spin Resonance

2015 ◽  
Author(s):  
Aditya Nanda ◽  
M. Amin Karami ◽  
Puneet Singla
Keyword(s):  
Energy Harvesting ◽  
Closed Form Expression ◽  
Longitudinal Vibrations ◽  
Form Expression ◽  
Preferred Direction ◽  
Spin Resonance ◽  
Vibration Sensing ◽  
Inertia Parameters ◽  
Set Up ◽  
Linearized Model

This paper investigates the spin resonance of a rattleback subjected to base oscillations. The phenomenon of Spin resonance can transduce vibrations to rotations. The rattleback is an ellipsoidal top with a preferred direction of spin. If rotated anti to it, longitudinal vibrations are set up and spin direction is reversed. Simulations and results are presented which show that the rattleback has a mono-peak spin resonance with respect to base vibrations. Two frequencies that appear in the response are identified — the Coupled and Uncoupled frequencies. Spin resonance, it is deduced, occurs when the base frequency is twice the coupled frequency of the rattleback. A linearized model is developed and a closed form expression for the Resonant frequency in terms of the inertia parameters of the rattleback is derived. Novel ideas for applications in Energy harvesting and Vibration sensing that utilize the phenomenon of spin resonance are also included.

Motor intention activity in the macaque's lateral intraparietal area. I. Dissociation of motor plan from sensory memory

1996 ◽  
Vol 76 (3) ◽  
pp. 1439-1456 ◽  
Author(s):  
P. Mazzoni ◽  
R. M. Bracewell ◽  
S. Barash ◽  
R. A. Andersen
Keyword(s):  
Eye Movements ◽  
Visual Stimulus ◽  
Visual Stimuli ◽  
Saccadic Eye Movements ◽  
Stimulus Location ◽  
Sensory Memory ◽  
Lateral Intraparietal Area ◽  
Preferred Direction ◽  
Motor Plan ◽  
Stimulation Of

1. The lateral intraparietal area (area LIP) of the monkey's posterior parietal cortex (PPC) contains neurons that are active during saccadic eye movements. These neurons' activity includes visual and saccade-related components. These responses are spatially tuned and the location of a neuron's visual receptive field (RF) relative to the fovea generally overlaps its preferred saccade amplitude and direction (i.e., its motor field, MF). When a delay is imposed between the presentation of a visual stimulus and a saccade made to its location (memory saccade task), many LIP neurons maintain elevated activity during the delay (memory activity, M), which appears to encode the metrics of the next intended saccadic eye movements. Recent studies have alternatively suggested that LIP neurons encode the locations of visual stimuli regardless of where the animal intends to look. We examined whether the M activity of LIP neurons specifically encodes movement intention or the locations of recent visual stimuli, or a combination of both. In the accompanying study, we investigated whether the intended-movement activity reflects changes in motor plan. 2. We trained monkeys (Macaca mulatta) to memorize the locations of two visual stimuli and plan a sequence of two saccades, one to each remembered target, as we recorded the activity of single LIP neurons. Two targets were flashed briefly while the monkey maintained fixation; after a delay the fixation point was extinguished, and the monkey made two saccades in sequence to each target's remembered location, in the order in which the targets were presented. This "delayed double saccade" (DDS) paradigm allowed us to dissociate the location of visual stimulation from the direction of the planned saccade and thus distinguish neuronal activity related to the target's location from activity related to the saccade plan. By imposing a delay, we eliminated the confounding effect of any phasic responses coincident with the appearance of the stimulus and with the saccade. 3. We arranged the two visual stimuli so that in one set of conditions at least the first one was in the neuron's visual RF, and thus the first saccade was in the neuron's motor field (MF). M activity should be high in these conditions according to both the sensory memory and motor plan hypotheses. In another set of conditions, the second stimulus appeared in the RF but the first one was presented outside the RF, instructing the monkey to plan the first saccade away from the neuron's MF. If the M activity encodes the motor plan, it should be low in these conditions, reflecting the plan for the first saccade (away from the MF). If it is a sensory trace of the stimulus' location, it should be high, reflecting stimulation of the RF by the second target. 4. We tested 49 LIP neurons (in 3 hemispheres of 2 monkeys) with M activity on the DDS task. Of these, 38 (77%) had M activity related to the next intended saccade. They were active in the delay period, as expected, if the first saccade was in their preferred direction. They were less active or silent if the next saccade was not in their preferred direction, even when the second stimulus appeared in their RF. 5. The M activity of 8 (16%) of the remaining neurons specifically encoded the location of the most recent visual stimulus. Their firing rate during the delay reflected stimulation of the RF independently of the saccade being planned. The remaining 3 neurons had M activity that did not consistently encode either the next saccade or the stimulus' location. 6. We also recorded the activity of a subset of neurons (n = 38) in a condition in which no stimulus appeared in a neuron's RF, but the second saccade was in the neuron's MF. In this case the majority of neurons tested (23/38, 60%) became active in the period between the first and second saccade, even if neither stimulus had appeared in their RF. Moreover, this activity appeared only after the first saccade had started in all but two of

Receptive-field properties of neurons in middle temporal visual area (MT) of owl monkeys

1984 ◽  
Vol 52 (3) ◽  
pp. 488-513 ◽  
Author(s):  
D. J. Felleman ◽  
J. H. Kaas
Keyword(s):  
Receptive Field ◽  
Stimulus Onset ◽  
Visual Area ◽  
Area Mt ◽  
Stimulus Movement ◽  
Middle Temporal ◽  
Preferred Direction ◽  
Direction Of Movement ◽  
Owl Monkeys ◽  
Visual Area Mt

Response properties of single neurons in the middle temporal visual area (MT) of anesthetized owl monkeys were determined and quantified for flashed and moving bars of light under computer control for position, orientation, direction of movement, and speed. Receptive-field sizes, ranging from 4 to 25 degrees in width, were considerably larger than receptive fields with corresponding eccentricities in the striate cortex. Neurons were highly binocular with most cells equally or nearly equally activated by either eye. Neurons varied in selectivity for axis and direction of moving bars. Some neurons demonstrated little or no selectivity, others were bidirectional on a single axis, while the largest group was highly selective for direction with little or no response to bar movement opposite to the preferred direction. Over 70% of neurons were classified as highly selective and 90% showed some preference for direction and/or axis of stimulus movement. Neurons typically responded to bar movement only over a restricted range of velocities. The majority of neurons responded best to a particular velocity within the 5-60 degrees/s range, with marked attenuation of the response for velocities greater or less than the preferred. Some neurons failed to show significant response attenuation even at the lowest tested velocity, while other neurons preferred velocities of 100 degrees/s or more and failed to attenuate to the highest velocities. Response magnitude varied with stimulus dimensions. Increasing the length of the moving bar typically increased the magnitude of the response slightly until the stimulus exceeded the receptive-field borders. Other neurons responded less to increases in bar length within the excitatory receptive field. Neurons preferred narrow bars less than 1 degree in width, and marked reductions in responses characteristically occurred with wider stimuli. Moving patterns of randomly placed small dots were often as effective as or more effective than single bars in activating neurons. Selectivity for direction of movement remained for the dot pattern. for the dot pattern. Poststimulus time (PST) histograms of responses to bars flashed at a series of 21 different positions across the receptive field, in the "response-plane" format, indicated a spatially and temporally homogeneous receptive-field structure for nearly all neurons. Cells characteristically showed transient excitation at both stimulus onset and offset for all effective stimulus locations. Some cells responded mainly at bright stimulus onset or offset.

scholarly journals Modeling simple-cell direction selectivity with normalized, half-squared, linear operators

1993 ◽  
Vol 70 (5) ◽  
pp. 1885-1898 ◽  
Author(s):  
D. J. Heeger
Keyword(s):  
Linear Prediction ◽  
Direction Selectivity ◽  
Linear Operators ◽  
Simple Cell ◽  
Physiological Data ◽  
Simple Cells ◽  
Cell Responses ◽  
Preferred Direction ◽  
Model Cell ◽  
Actual Response

1. A longstanding view of simple cells is that they sum their inputs linearly. However, the linear model falls short of a complete account of simple-cell direction selectivity. We have developed a nonlinear model of simple-cell responses (hereafter referred to as the normalization model) to explain a larger body of physiological data. 2. The normalization model consists of an underlying linear stage along with two additional nonlinear stages. The first is a half-squaring nonlinearity; half-squaring is half-wave rectification followed by squaring. The second is a divisive normalization non-linearity in which each model cell is suppressed by the pooled activity of a large number of cells. 3. By comparing responses with counterphase (flickering) gratings and drifting gratings, researchers have demonstrated that there is a nonlinear contribution to simple-cell responses. Specifically they found 1) that the linear prediction from counterphase grating responses underestimates a direction index computed from drifting grating responses, 2) that the linear prediction correctly estimates responses to gratings drifting in the preferred direction, and 3) that the linear prediction overestimates responses to gratings drifting in the nonpreferred direction. 4. We have simulated model cell responses and derived mathematical expressions to demonstrate that the normalization model accounts for this empirical data. Specifically the model behaves as follows. 1) The linear prediction from counterphase data underestimates the direction index computed from drifting grating responses. 2) The linear prediction from counterphase data overestimates the response to gratings drifting in the nonpreferred direction. The discrepancy between the linear prediction and the actual response is greater when using higher contrast stimuli. 3) For an appropriate choice of contrast, the linear prediction from counterphase data correctly estimates the response to gratings drifting in the preferred direction. For higher contrasts the linear prediction overestimates the actual response, and for lower contrasts the linear prediction underestimates the actual response. 5. In addition, the normalization model is qualitatively consistent with data on the dynamics of simple-cell responses. Tolhurst et al. found that simple cells respond with an initial transient burst of activity when a stimulus first appears. The normalization model behaves similarly; it takes some time after a stimulus first appears before the model cells are fully normalized. We derived the dynamics of the model and found that the transient burst of activity in model cells depends in a particular way on stimulus contrast. The burst is short for high-contrast stimuli and longer for low-contrast stimuli.(ABSTRACT TRUNCATED AT 400 WORDS)

Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex

1991 ◽  
Vol 66 (2) ◽  
pp. 505-529 ◽  
Author(s):  
R. C. Reid ◽  
R. E. Soodak ◽  
R. M. Shapley
Keyword(s):  
Time Course ◽  
Linear Prediction ◽  
Striate Cortex ◽  
Receptive Fields ◽  
Quantitative Measure ◽  
Direction Selectivity ◽  
Simple Cells ◽  
Preferred Direction ◽  
Orientation Contrast ◽  
Cat Striate Cortex

1. Simple cells in cat striate cortex were studied with a number of stimulation paradigms to explore the extent to which linear mechanisms determine direction selectivity. For each paradigm, our aim was to predict the selectivity for the direction of moving stimuli given only the responses to stationary stimuli. We have found that the prediction robustly determines the direction and magnitude of the preferred response but overestimates the nonpreferred response. 2. The main paradigm consisted of comparing the responses of simple cells to contrast reversal sinusoidal gratings with their responses to drifting gratings (of the same orientation, contrast, and spatial and temporal frequencies) in both directions of motion. Although it is known that simple cells display spatiotemporally inseparable responses to contrast reversal gratings, this spatiotemporal inseparability is demonstrated here to predict a certain amount of direction selectivity under the assumption that simple cells sum their inputs linearly. 3. The linear prediction of the directional index (DI), a quantitative measure of the degree of direction selectivity, was compared with the measured DI obtained from the responses to drifting gratings. The median value of the ratio of the two was 0.30, indicating that there is a significant nonlinear component to direction selectivity. 4. The absolute magnitudes of the responses to gratings moving in both directions of motion were compared with the linear predictions as well. Whereas the preferred direction response showed only a slight amount of facilitation compared with the linear prediction, there was a significant amount of nonlinear suppression in the nonpreferred direction. 5. Spatiotemporal inseparability was demonstrated also with stationary temporally modulated bars. The time course of response to these bars was different for different positions in the receptive field. The degree of spatiotemporal inseparability measured with sinusoidally modulated bars agreed quantitatively with that measured in experiments with stationary gratings. 6. A linear prediction of the responses to drifting luminance borders was compared with the actual responses. As with the grating experiments, the prediction was qualitatively accurate, giving the correct preferred direction but underestimating the magnitude of direction selectivity observed.(ABSTRACT TRUNCATED AT 400 WORDS)

Neuronal Responses Related to Smooth Pursuit Eye Movements in the Periarcuate Cortical Area of Monkeys

1998 ◽  
Vol 80 (1) ◽  
pp. 28-47 ◽  
Author(s):  
Masaki Tanaka ◽  
Kikuro Fukushima
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Cortical Area ◽  
Eye Position ◽  
Smooth Pursuit Eye Movements ◽  
Neuronal Responses ◽  
Stationary Target ◽  
Pursuit Eye Movements ◽  
Preferred Direction ◽  
Eye Velocity

Tanaka, Masaki and Kikuro Fukushima. Neuronal responses related to smooth pursuit eye movements in the periarcuate cortical area of monkeys. J. Neurophysiol. 80: 28–47, 1998. To examine how the periarcuate area is involved in the control of smooth pursuit eye movements, we recorded 177 single neurons while monkeys pursued a moving target in the dark. The majority (52%, 92/177) of task-related neurons responded to pursuit but had little or no response to saccades. Histological reconstructions showed that these neurons were located mainly in the posterior bank of the arcuate sulcus near the sulcal spur. Twenty-seven percent (48/177) changed their activity at the onset of saccades. Of these, 36 (75%) showed presaccadic burst activity with strong preference for contraversive saccades. Eighteen (10%, 18/177) were classified as eye-position–related neurons, and 11% (19/177) were related to other aspects of the stimuli or response. Among the 92 neurons that responded to pursuit, 85 (92%) were strongly directional with uniformly distributed preferred directions. Further analyses were performed in these directionally sensitive pursuit-related neurons. For 59 neurons that showed distinct changes in activity around the initiation of pursuit, the median latency from target motion was 96 ms and that preceding pursuit was −12 ms, indicating that these neuron can influence the initiation of pursuit. We tested some neurons by briefly extinguishing the tracking target ( n = 39) or controlling its movement with the eye position signal ( n = 24). The distribution of the change in pursuit-related activity was similar to previous data for the dorsomedial part of the medial superior temporal neurons ( Newsome et al. 1988) , indicating that pursuit-related neurons in the periarcuate area also carry extraretinal signals. For 22 neurons, we examined the responses when the animals reversed pursuit direction to distinguish the effects of eye acceleration in the preferred direction from oppositely directed eye velocity. Almost all neurons discharged before eye velocity reached zero, however, only nine neurons discharged before the eyes were accelerated in the preferred direction. The delay in neuronal responses relative to the onset of eye acceleration in these trials might be caused by suppression from oppositely directed pursuit velocity. The results suggest that the periarcuate neurons do not participate in the earliest stage of eye acceleration during the change in pursuit direction, although most of them may participate in the early stages of pursuit initiation in the ordinary step-ramp pursuit trials. Some neurons changed their activity when the animals fixated a stationary target, and this activity could be distinguished easily from the strong pursuit-related responses. Our results suggest that the periarcuate pursuit area carries extraretinal signals and affects the premotor circuitry for smooth pursuit.

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