Spatial orientation during gondola centrifugation with subjects upright versus supine: Evidence for Gestalt psychological mechanisms in vestibular perception

BACKGROUND: Recent theories suggest that perception of complex self-motion is governed by familiarity of the motion pattern as a whole in 3D. OBJECTIVE: To explore how familiarity determines the perceived angular displacement with respect to the Earth during a simulated coordinated turn in a gondola centrifuge. METHOD: The centrifuge was accelerated to 2G (gondola displacement 60°) within 12.5 s. Using visual indicators in darkness, responses to the gondola displacement were recorded with subjects (n = 10) in two positions: sitting-upright, facing-forward versus lying-supine, feet-forwards. Each subject underwent 2×2 6-minute runs. RESULT: When upright, subjects indicated a tilt of initially 18.8±11.3°, declining with T = 66±37 s. In the supine position (subject’s yaw plane coinciding with the plane of gondola displacement) the indicated displacement was negligible (–0.3±4.8°). CONCLUSION: Since the canal system is most responsive to stimuli in yaw, these findings are difficult to explain by bottom-up models. Rather, the motion pattern during acceleration would be recognized as a familiar or meaningful whole (entering a co-ordinated turn) only when the subject is upright. Presumably, the degree of familiarity is reflected in the subject’s ability to discern and estimate a single stimulus component. Findings are discussed in connection with human factors in aviation and the principles of Gestalt psychology.

Estimating the Parameters of Fitzhugh–Nagumo Neurons from Neural Spiking Data

A theoretical and computational study on the estimation of the parameters of a single Fitzhugh–Nagumo model is presented. The difference of this work from a conventional system identification is that the measured data only consist of discrete and noisy neural spiking (spike times) data, which contain no amplitude information. The goal can be achieved by applying a maximum likelihood estimation approach where the likelihood function is derived from point process statistics. The firing rate of the neuron was assumed as a nonlinear map (logistic sigmoid) relating it to the membrane potential variable. The stimulus data were generated by a phased cosine Fourier series having fixed amplitude and frequency but a randomly shot phase (shot at each repeated trial). Various values of amplitude, stimulus component size, and sample size were applied to examine the effect of stimulus to the identification process. Results are presented in tabular and graphical forms, which also include statistical analysis (mean and standard deviation of the estimates). We also tested our model using realistic data from a previous research (H1 neurons of blowflies) and found that the estimates have a tendency to converge.

Spatial arrangement drastically changes the neural representation of multiple visual stimuli that compete in more than one feature domain

ABSTRACTNatural scenes often contain multiple objects and surfaces. However, how neurons in the visual cortex represent multiple visual stimuli is not well understood. Previous studies have shown that, when multiple stimuli compete in one feature domain, the evoked neuronal response is biased toward the stimulus that has a stronger signal strength. Here we investigate how neurons in the middle temporal (MT) cortex of macaques represent multiple stimuli that compete in more than one feature domain. Visual stimuli were two random-dot patches moving in different directions. One stimulus had low luminance contrast and moved with high coherence, whereas the other had high contrast and moved with low coherence. We found that how MT neurons represent multiple stimuli depended on the spatial arrangement of the stimuli. When two stimuli were overlapping, MT responses were dominated by the stimulus component that had high contrast. When two stimuli were spatially separated within the receptive fields, the contrast dominance was abolished. We found the same results when using contrast to compete with motion speed. Our neural data and computer simulations using a V1-MT model suggest that the contrast dominance found with overlapping stimuli is due to normalization occurring at an input stage fed to MT, and MT neurons cannot overturn this bias based on their own feature selectivity. The interaction between spatially separated stimuli can largely be explained by normalization within MT. Our results revealed new rules on stimulus competition and highlighted the impact of hierarchical processing on representing multiple stimuli in the visual cortex.SIGNIFICANCE STATEMENTPrevious studies have shown that the neural representation of multiple visual stimuli can be accounted for by a divisive normalization model. By using multiple stimuli that compete in more than one feature domain, we found that luminance contrast has a dominant effect in determining competition between multiple stimuli when they were overlapping but not spatially separated. Our results revealed that neuronal responses to multiple stimuli in a given cortical area cannot be simply predicted by the population neural responses elicited in that area by the individual stimulus components. To understand the neural representation of multiple stimuli, rather than considering response normalization only within the area of interest, one must consider the computations including normalization occurring along the hierarchical visual pathway.

An attempt to fit all parameters of a dynamical recurrent neural network from sensory neural spiking data

A simulation based study on model fitting for sensory neurons from stimulus/response data is presented. The employed model is a continuous time recurrent neural network (CTRNN) which is a member of models with known universal approximation features. This feature of the recurrent dynamical neuron network models allow us to describe excitatory-inhibitory characteristics of an actual sensory neural network with any desired number of neurons. This work will be a continuation of a previous study where the parameters associated with the sigmoidal gain functions are not taken into account. In this work, we will construct a similar framework but all parameters associated with the model are estimated. The stimulus data is generated by a Phased Cosine Fourier series having fixed amplitude and frequency but a randomly shot phase. Various values of amplitude, stimulus component size and sample size are applied in order to examine the effect of stimulus to the identification process. Results are presented in tabular and graphical forms at the end of this text. In addition a comparison of the results with previous researches including will be presented.

An attempt to fit all parameters of a dynamical recurrent neural network from sensory neural spiking data

A simulation based study on model fitting for sensory neurons from stimulus/response data is presented. The employed model is a continuous time recurrent neural network (CTRNN) which is a member of models with known universal approximation features. This feature of the recurrent dynamical neuron network models allow us to describe excitatory-inhibitory characteristics of an actual sensory neural network with any desired number of neurons. This work will be a continuation of a previous study where the parameters associated with the sigmoidal gain functions are not taken into account. In this work, we will construct a similar framework but all parameters associated with the model are estimated. The stimulus data is generated by a Phased Cosine Fourier series having fixed amplitude and frequency but a randomly shot phase. Various values of amplitude, stimulus component size and sample size are applied in order to examine the effect of stimulus to the identification process. Results are presented in tabular and graphical forms at the end of this text. In addition a comparison of the results with previous researches including will be presented.

Lateralized Human Cortical Activity for Shifting Visuospatial Attention and Initiating Saccades

Wauschkuhn, Bernd, Rolf Verleger, Edmund Wascher, Wolfgang Klostermann, Marcel Burk, Wolfgang Heide, and Detlef Kömpf. Lateralized human cortical activity for shifting visuospatial attention and initiating saccades. J. Neurophysiol. 80: 2900–2910, 1998. The relation between shifts of visual attention and saccade preparation was investigated by studying their electrophysiological correlates in human scalp-recorded electroencephalogram (EEG). Participants had to make saccades either to a saliently colored or to a gray circle, simultaneously presented in opposite visual hemifields, under different task instructions. EEG was measured within the short interval between stimulus onset and saccade, focusing on lateralized activity, contralateral either to the side of the relevant stimulus or to the direction of the saccade. Three components of lateralization were found: 1) activity contralateral to the relevant stimulus irrespective of saccade direction, peaking 250 ms after stimulus onset, largest above lateral parietal sites, 2) activity contralateral to the relevant stimulus if the stimulus was also the target of the saccade, largest 330–480 ms after stimulus onset, widespread over the scalp but with a focus again above lateral parietal sites, and 3) activity contralateral to saccade direction, beginning about 100 ms before the saccade, largest above mesial parietal sites, with some task-dependent fronto–central contribution. Because of their sensitivity to task variables, component 1 is interpreted as the shifting of attention to the relevant stimulus, component 2 is interpreted as reflecting the enhancement of the attentional shift if the relevant stimulus is also the saccade target, and component 3 is interpreted as the triggering signal for saccade execution. Thus human neurophysiological data provided evidence both for independent and interdependent processes of saccade preparation and shifts of visual attention.

Temporal asynchrony interferes with vernier acuity

Two dots may be aligned vertically with a precision much higher than that expected from two-point resolution provided they are separated by a visual angle of 3–5 min of arc. This precision suffers when the two dots are not exposed synchronously. Neither onset nor offset asynchronies can be tolerated; exposure differences of the two components of the vernier task as low as 30 ms can lead to a reduction in performance when the total exposure is below 90 ms. This effect cannot be compensated for by synchronizing the onset of one stimulus component with the offset of the other, even when the two are of opposite contrast. The data suggest that vernier acuity may be subserved by a dynamical linking of cortical excitation generated by the synchronous arrival of signals within a range of locations in the cortex whose spatial separation is critical for optimal hyperacuity performance. The evidence presented in this paper must be taken into account when a physiological substrate for hyperacuity is considered.

The Effectiveness of Internally-Generated Feedback with an Instructional Expert System

An expert system was developed and included as a feedback stimulus component of an instructional unit that taught the production of graphics instructional materials. The expert system was used to help students generate their own feedback about the quality of their production projects. Implementation of the expert system raised questions about its effects on processing activities and learning. To investigate these questions, a total of forty-three students were assigned to either an internal (provided by expert system) or external (provided by an instructor) feedback condition. Internally-generated feedback, stimulated by the expert system, proved as effective as externally provided feedback in the learning of the production tasks and improved both the learning and application of evaluation criteria in a complex evaluation task. The internal feedback group were also more creative in their evaluations. Students who used the expert system held positive opinions about its use.

Auditory nerve representation of vowels in background noise

Responses of auditory nerve fibers to steady-state vowels presented alone and in the presence of background noise were obtained from anesthetized cats. Representation of vowels based on average discharge rate and representation based primarily on phase-locked properties of responses are considered. Profiles of average discharge rate versus characteristic frequency (CF) ("rate-place" representation) can show peaks of discharge rate in the vicinity of formant frequencies when vowels are presented alone. These profiles change drastically in the presence of background noise, however. At moderate vowel and noise levels and signal/noise ratios of +9 dB, there are not peaks of rate near the second and third formant frequencies. In fact, because of two-tone suppression, rate to vowels plus noise is less than rate to noise alone for fibers with CFs above the first formant. Rate profiles measured over 5-ms intervals near stimulus onset show clear formant-related peaks at higher sound levels than do profiles measured over intervals later in the stimulus (i.e., in the steady state). However, in background noise, rate profiles at onset are similar to those in the steady state. Specifically, for fibers with CFs above the first formant, response rates to the noise are suppressed by the addition of the vowel at both vowel onset and steady state. When rate profiles are plotted for low spontaneous rate fibers, formant-related peaks appear at stimulus levels higher than those at which peaks disappear for high spontaneous fibers. In the presence of background noise, however, the low spontaneous fibers do not preserve formant peaks better than do the high spontaneous fibers. In fact, the suppression of noise-evoked rate mentioned above is greater for the low spontaneous fibers than for high. Representations that reflect phase-locked properties as well as discharge rate ("temporal-place" representations) are much less affected by background noise. We have used synchronized discharge rate averaged over fibers with CFs near (+/- 0.25 octave) a stimulus component as a measure of the population temporal response to that component. Plots of this average localized synchronized rate (ALSR) versus frequency show clear first and second formant peaks at all vowel and noise levels used. Except at the highest level (vowel at 85 dB sound pressure level (SPL), signal/noise = +9 dB), there is also a clear third formant peak. At signal-to-noise ratios where there are no second formant peaks in rate profiles, human observers are able to discriminate second formant shifts of less than 112 Hz. ALSR plots show clear second formant peaks at these signal/noise ratios.

Additive Structures in Multidimensional Scaling

The formal complexity underlying a group of objects may be partitioned into two components, one of which is due to the total number of attributes involved (the between-attribute component) and the other of which is due to complexity within the individual attributes themselves (the within-attribute component). This notion of multidimensional structure is discussed within the framework of an additive component model of multidimensional scaling, where a configuration is considered to be composed of disjoint subspaces, each one of which reflects variation due to a specific stimulus component. A number of empirical examples are given to demonstrate the applicability of the additive component model to multidimensional scaling.