Direction-selective Mechanisms Research Articles

A spatiotemporal energy model based on spiking neurons for human motion perception.

Inspired by the motion processing pathway, this paper proposes a bio-inspired feedforward spiking network model based on Hodgkin-Huxley neurons for human motion perception. The proposed network mimics the mechanisms of direction selectivity found in simple and complex cells of the primary visual cortex. Simple cells' receptive fields are modeled using Gabor energy filters, while complex cells' receptive fields are constructed by integrating the responses of simple cells in an energy model. To generate the motion map, the spiking output of the network integrates motion information encoded by the responses of complex cells with various preferred directions. Simulation results demonstrate that the spiking neuron-based network effectively replicates the directional selectivity operation of the visual cortex when presented with a sequence of time-varying images. We evaluate the proposed model against state-of-the-art spiking neuron-based motion detection models using publicly available datasets. The results highlight the model's capability to extract motion energy from diverse video sequences, akin to human visual motion perception models. Additionally, we showcase the application of the proposed model in motion segmentation tasks and compare its performance with state-of-the-art motion-based segmentation models using challenging video segmentation benchmarks. The results indicate competitive performance. The motion maps generated by the proposed model can be utilized for action recognition in input videos.

Two mechanisms for direction selectivity in a model of the primate starburst amacrine cell.

In a recent study, visual signals were recorded for the first time in starburst amacrine cells of the macaque retina, and, as for mouse and rabbit, a directional bias observed in calcium signals was recorded from near the dendritic tips. Stimulus motion from the soma toward the tip generated a larger calcium signal than motion from the tip toward the soma. Two mechanisms affecting the spatiotemporal summation of excitatory postsynaptic currents have been proposed to contribute to directional signaling at the dendritic tips of starbursts: (1) a "morphological" mechanism in which electrotonic propagation of excitatory synaptic currents along a dendrite sums bipolar cell inputs at the dendritic tip preferentially for stimulus motion in the centrifugal direction; (2) a "space-time" mechanism that relies on differences in the time-courses of proximal and distal bipolar cell inputs to favor centrifugal stimulus motion. To explore the contributions of these two mechanisms in the primate, we developed a realistic computational model based on connectomic reconstruction of a macaque starburst cell and the distribution of its synaptic inputs from sustained and transient bipolar cell types. Our model suggests that both mechanisms can initiate direction selectivity in starburst dendrites, but their contributions differ depending on the spatiotemporal properties of the stimulus. Specifically, the morphological mechanism dominates when small visual objects are moving at high velocities, and the space-time mechanism contributes most for large visual objects moving at low velocities.

A Novel Artificial Visual System for Motion Direction Detection in Grayscale Images

How specific features of the environment are represented in the mammalian brain is an important unexplained mystery in neuroscience. Visual information is considered to be captured most preferentially by the brain. As one of the visual information elements, motion direction in the receptive field is thought to be collected already at the retinal direction-selective ganglion cell (DSGC) layer. However, knowledge of direction-selective (DS) mechanisms in the retina has remained only at a cellular level, and there is a lack of complete direction-sensitivity understanding in the visual system. Previous studies of DS models have been limited to the stage of one-dimensional black-and-white (binary) images or still lack biological rationality. In this paper, we innovatively propose a two-dimensional, eight-directional motion direction detection mechanism for grayscale images called the artificial visual system (AVS). The structure and neuronal functions of this mechanism are highly faithful to neuroscientific perceptions of the mammalian retinal DS pathway, and thus highly biologically reasonable. In particular, by introducing the horizontal contact pathway provided by horizontal cells (HCs) in the retinal inner nuclear layer and forming a functional collaboration with bipolar cells (BCs), the limitation that previous DS models can only recognize object motion directions in binary images is overcome; the proposed model can solve the recognizing problem of object motion directions in grayscale images. Through computer simulation experiments, we verified that AVS is effective and has high detection accuracy, and it is not affected by the shape, size, and location of objects in the receptive field. Its excellent noise immunity was also verified by adding multiple types of noise to the experimental data set. Compared to a classical convolutional neural network (CNN), it was verified that AVS is completely significantly better in terms of effectiveness and noise immunity, and has various advantages such as high interpretability, no need for learning, and easy hardware implementation. In addition, activation characteristics of neurons in AVS are highly consistent with those real in the retinal DS pathway, with strong neurofunctional similarity and brain-like superiority. Moreover, AVS will also provide a novel perspective and approach to understanding and analyzing mechanisms as well as principles of mammalian retinal direction-sensitivity in face of a cognitive bottleneck on the DS pathway that has persisted for nearly 60 years.

A Computational Model of Direction Selectivity in Macaque V1 Cortex Based on Dynamic Differences between On and Off Pathways.

This paper is about neural mechanisms of direction selectivity (DS) in macaque primary visual cortex, V1. We present data (on male macaque) showing strong DS in a majority of simple cells in V1 layer 4Cα, the cortical layer that receives direct afferent input from the magnocellular division of the lateral geniculate nucleus (LGN). Magnocellular LGN cells are not direction-selective. To understand the mechanisms of DS, we built a large-scale, recurrent model of spiking neurons called DSV1. Like its predecessors, DSV1 reproduces many visual response properties of V1 cells including orientation selectivity. Two important new features of DSV1 are (1) DS is initiated by small, consistent dynamic differences in the visual responses of OFF and ON Magnocellular LGN cells, and (2) DS in the responses of most model simple cells is increased over those of their feedforward inputs; this increase is achieved through dynamic interaction of feedforward and intracortical synaptic currents without the use of intracortical direction-specific connections. The DSV1 model emulates experimental data in the following ways: (1) most 4Cα Simple cells were highly direction-selective but 4Cα Complex cells were not; (2) the preferred directions of the model's direction-selective Simple cells were invariant with spatial and temporal frequency (TF); (3) the distribution of the preferred/opposite ratio across the model's population of cells was very close to that found in experiments. The strong quantitative agreement between DS in data and in model simulations suggests that the neural mechanisms of DS in DSV1 may be similar to those in the real visual cortex.SIGNIFICANCE STATEMENT Motion perception is a vital part of our visual experience of the world. In monkeys, whose vision resembles that of humans, the neural computation of the direction of a moving target starts in the primary visual cortex, V1, in layer 4Cα that receives input from the eye through the lateral geniculate nucleus (LGN). How direction selectivity (DS) is generated in layer 4Cα is an outstanding unsolved problem in theoretical neuroscience. In this paper, we offer a solution based on plausible biological mechanisms. We present a new large-scale circuit model in which DS originates from slightly different LGN ON/OFF response time-courses and is enhanced in cortex without the need for direction-specific intracortical connections. The model's DS is in quantitative agreement with experiments.

Antagonistic Center-Surround Mechanisms for Direction Selectivity in the Retina

SummaryAn antagonistic center-surround receptive field is a key feature in sensory processing, but how it contributes to specific computations such as direction selectivity is often unknown. Retinal On-starburst amacrine cells (SACs), which mediate direction selectivity in direction-selective ganglion cells (DSGCs), exhibit antagonistic receptive field organization: depolarizing to light increments and decrements in their center and surround, respectively. We find that a repetitive stimulation exhausts SAC center and enhances its surround and use it to study how center-surround responses contribute to direction selectivity. Center, but not surround, activation induces direction-selective responses in SACs. Nevertheless, both SAC center and surround elicited direction-selective responses in DSGCs, but to opposite directions. Physiological and modeling data suggest that the opposing direction selectivity can result from inverted temporal balance between excitation and inhibition in DSGCs, implying that SAC’s response timing dictates direction selectivity. Our findings reveal antagonistic center-surround mechanisms for direction selectivity and demonstrate how context-dependent receptive field reorganization enables flexible computations.

Dual and Direction-Selective Mechanisms of Phosphate Transport by the Vesicular Glutamate Transporter

Vesicular glutamate transporters (VGLUTs) fill synaptic vesicles with glutamate and are thus essential for glutamatergic neurotransmission. However, VGLUTs were originally discovered as members of a transporter subfamily specific for inorganic phosphate (Pi). It is still unclear how VGLUTs accommodate glutamate transport coupled to an electrochemical proton gradient ΔμH+ with inversely directed Pi transport coupled to the Na+ gradient and the membrane potential. Using both functional reconstitution and heterologous expression, we show that VGLUT transports glutamate and Pi using a single substrate binding site but different coupling to cation gradients. When facing the cytoplasm, both ions are transported into synaptic vesicles in a ΔμH+-dependent fashion, with glutamate preferred over Pi. When facing the extracellular space, Pi is transported in a Na+-coupled manner, with glutamate competing forbinding but at lower affinity. We conclude that VGLUTs have dual functions in both vesicle transmitter loading and Pi homeostasis within glutamatergic neurons.

Neural mechanisms of direction selectivity in the retina

Neural mechanisms of direction selectivity in the retina

Pharmacological study of direction selectivity in the archer fish retina.

Direction selective cells have been found in the retina, the first level of the visual system, in mammals and recently also in the archer fish. These cells are involved in a variety of fast neural computation processes, from the control of eye movements to the detection of prey by the archer fish. The standard model for this mechanism in mammalian retina is well understood and is based on the asymmetry of inhibitory and excitatory inputs to the retinal ganglion cells. However, it remains unclear whether the mechanism that underlies direction selectivity is similar across animal classes. This study reports a pharmacological investigation designed to elucidate the mechanism that underlies motion detection in the archer fish retina. Direction selectivity in the retina was characterized under the influence of specific channel blockers that are known to be present in the different types of neurons of the retina. The results show that the direction-selective mechanism in the archer fish retina is modified only when the inhibitory channels of GABA and Glycine are manipulated. This suggests that the mechanism of direction selectivity in the archer fish retina is fundamentally different from the mechanism of direction selectivity in the mammalian retina.

Balance or imbalance: inhibitory circuits for direction selectivity in the auditory system.

The auditory system detects and processes dynamic sound information transmitted in the environment. Other than the basic acoustic parameters, such as frequency, amplitude and phase, the time-varying changes of these parameters must also be encoded in our brain. Frequency-modulated (FM) sound is socially and environmentally significant, and the direction of FM sweeps is essential for animal communication and human speech. Many auditory neurons selectively respond to the directional change of such FM signals. In the past half century, our knowledge of auditory representation and processing has been updated frequently, due to technological advancement. Recently, in vivo whole-cell voltage clamp recordings have been applied to different brain regions in sensory systems. These recordings illustrate the synaptic mechanisms underlying basic sensory information processing and provide profound insights toward our understanding of neural circuits for complex signal analysis. In this review, we summarize the major findings of direction selectivity at several key auditory regions and emphasize on the recent discoveries on the synaptic mechanisms for direction selectivity in the auditory system. We conclude this review by describing promising technical developments in dissecting neural circuits and future directions in the study of complex sound analysis.

Aftereffect of motion-in-depth based on binocular cues: Effects of adaptation duration, interocular correlation, and temporal correlation.

There are at least two possible binocular cues to motion-in-depth, namely disparity change over time and interocular velocity differences. There has been significant controversy about their relative contributions to the perception of motion-in-depth. In the present study, we used the technique of selective adaptation to address this question. In Experiment 1, we found that adaptation to motion-in-depth depicted by temporally correlated random-dot stereograms, which contained coherent interocular velocity difference, produced motion aftereffect in the depth direction irrespective of the adaptors' interocular correlation for any adaptation duration tested. This suggests that coherent changing disparity does not contribute to motion-in-depth adaptation. Because the aftereffect duration did not saturate in the tested range of adaptation duration, it is unlikely that the lack of the effect of changing disparity was due to a ceiling effect. In Experiment 2, we used a novel adaptor that contained a unidirectional coherent interocular velocity difference signal and a bidirectional changing disparity signal that should not induce a motion aftereffect in depth. Following the adaptation, motion aftereffect in depth occurred in the opposite direction to the adaptor's motion-in-depth based on interocular velocity difference. Experiment 3 demonstrated that these results generalized in 12 untrained subjects. These experiments suggest that the contribution of interocular velocity difference to the perception of motion-in-depth is substantial, while that of changing disparity is very limited (if any), at least at the stages of direction-selective mechanisms subject to an aftereffect phenomenon.

WM: an integrated framework for modeling the visual system

WM: an integrated framework for modeling the visual system

Inter-Neuronal Correlation Distinguishes Mechanisms of Direction Selectivity in Cortical Circuit Models

Direction selectivity is a fundamental physiological property that arises from primary visual cortex (V1) circuitry, yet basic questions of how direction-selective (DS) receptive fields are constructed remain unanswered. We built a set of simple, plausible neuronal circuits that produce DS cells via different mechanisms and tested these circuits to determine how they can be distinguished experimentally. Our models consisted of populations of spiking units representing physiological cell classes ranging from LGN cells to V1 complex DS cells. They differed in network architecture and DS mechanism, including linear summation of non-DS simple-cell inputs or nonlinear pairwise combinations of non-DS inputs. The circuits also varied in the location of the DS time delay and whether the DS interaction was facilitatory or suppressive. We tested the models with visual stimuli often used experimentally, including sinusoidal gratings and flashed bars, and computed shuffle-corrected cross-correlograms (CCGs) of spike trains from pairs of units that would be accessible to extracellular recording. We found that CCGs revealed fundamental features of the DS models, including the location of signal delays in the DS circuit and the sign (facilitatory or suppressive) of DS interactions. We also found that correlation was strongly stimulus-dependent, changing with direction and temporal frequency in a manner that generalized across model architectures. Our models make specific predictions for designing, optimizing, and interpreting electrophysiology experiments aimed at resolving DS circuitry and provide new insights into mechanisms that could underlie stimulus-dependent correlation. The models are available and easy to explore at www.imodel.org.

Dynamics of Macaque MT Cell Responses to Grating Triplets

Neurons in area MT are sensitive to the direction of motion of gratings and of plaids made by summing 2 gratings moving in different directions. MT component direction-selective (CDS) neurons respond to the individual gratings of a plaid. Pattern direction-selective (PDS) neurons on the other hand, combine component information and respond selectively to the resulting pattern motion. Adding a third grating creates a "triplaid," which contains 3 grating and 3 plaid motions and is perceptually multistable. To examine how direction-selective mechanisms parse the motion signals in triplaids, we recorded MT responses of anesthetized and awake macaques to stimuli in which 3 identical moving gratings whose directions were separated by 120° were introduced in 3 successive epochs, going from grating to plaid to triplaid. CDS and PDS neurons-selected based on their responses to gratings and plaids-had strikingly different tuning properties in the triplaid epoch. CDS neurons were strongly tuned for the direction of motion of individual gratings, but PDS neurons nearly lost their selectivity for either the gratings or the plaids in the stimulus. We explain this reduced motion selectivity with a model that relates pattern selectivity of PDS neurons to a broad pooling of V1 afferents with a near-cosine weighting profile. Because PDS neurons signal both component and pattern motion in gratings and plaids, their reduced selectivity for motion in triplaids may be what makes these stimuli perceptually multistable.

Direction-selective patterns of activity in human visual cortex suggest common neural substrates for different types of motion

A sense of motion can be elicited by the movement of both luminance- and texture-defined patterns, what is commonly referred to as first- and second-order, respectively. Although there are differences in the perception of these two classes of motion stimuli, including differences in temporal and spatial sensitivity, it is debated whether common or separate direction-selective mechanisms are responsible for processing these two types of motion. Here, we measured direction-selective responses to luminance- and texture-defined motion in the human visual cortex by using functional MRI (fMRI) in conjunction with multivariate pattern analysis (MVPA). We found evidence of direction selectivity for both types of motion in all early visual areas (V1, V2, V3, V3A, V4, and MT+), implying that none of these early visual areas is specialized for processing a specific type of motion. More importantly, linear classifiers trained with cortical activity patterns to one type of motion (e.g., first-order motion) could reliably classify the direction of motion defined by the other type (e.g., second-order motion). Our results suggest that the direction-selective mechanisms that respond to these two types of motion share similar spatial distributions in the early visual cortex, consistent with the possibility that common mechanisms are responsible for processing both types of motion.

Mechanisms of direction selectivity in cat primary visual cortex as revealed by visual adaptation.

In contrast to neurons of the lateral geniculate nucleus (LGN), neurons in the primary visual cortex (V1) are selective for the direction of visual motion. Cortical direction selectivity could emerge from the spatiotemporal configuration of inputs from thalamic cells, from intracortical inhibitory interactions, or from a combination of thalamic and intracortical interactions. To distinguish between these possibilities, we studied the effect of adaptation (prolonged visual stimulation) on the direction selectivity of intracellularly recorded cortical neurons. It is known that adaptation selectively reduces the responses of cortical neurons, while largely sparing the afferent LGN input. Adaptation can therefore be used as a tool to dissect the relative contribution of afferent and intracortical interactions to the generation of direction selectivity. In both simple and complex cells, adaptation caused a hyperpolarization of the resting membrane potential (-2.5 mV, simple cells, -0.95 mV complex cells). In simple cells, adaptation in either direction only slightly reduced the visually evoked depolarization; this reduction was similar for preferred and null directions. In complex cells, adaptation strongly reduced visual responses in a direction-dependent manner: the reduction was largest when the stimulus direction matched that of the adapting motion. As a result, adaptation caused changes in the direction selectivity of complex cells: direction selectivity was reduced after preferred direction adaptation and increased after null direction adaptation. Because adaptation in the null direction enhanced direction selectivity rather than reduced it, it seems unlikely that inhibition from the null direction is the primary mechanism for creating direction selectivity.

Neuroimaging of direction-selective mechanisms for first-order and second-order motion stimuli

Psychophysical findings have indicated functional segregation of processing pathways for first-order motion (movement of luminance modulation, LM) and second-order motion (e.g., movement of contrast modulation, CM). However, neural correlates of those pathways are still controversial. To investigate whether there is corresponding anatomical segregation, we conducted a novel fMRI study with deliberate control of attention, to localize direction-selective cortical mechanisms for first- and second-order motion stimuli by measuring direction-contingent response changes induced by motion adaptation. We used Siemens 3T scanner along with a flattened occipital format. The stimulus was a rotating windmill defined by a 10% LM superimposed on a static random-dot noise, or by a 100% CM of a static noise. Every 32s, the rotating stimulus (LM or CM) gradually disappeared and reappeared with or without direction reversal between the 32-s periods (a reversal occurred every 64s). We asked subjects to maintain fixation at a central spot and to detect speed changes of the stimulus rotation, which occurred at unpredictable timings (independent of the direction reversals) and were as tiny as the detection threshold, in order to keep the subject's attention to the motion stimulus. We obtained time courses of MR signals from V1, V2, V3, VP, V3A, V4v and MT+, defined by other retinotopic stimuli. We compared cortical activations between the first 32s period (after direction reversal) and the second period (without reversal) to isolate the effects of direction-selective adaptation from those of motion onset. The results obtained so far suggest that the CM stimulus generated direction-selective adaptation in V3A and MT+, but not in V1 and V2. However, the LM stimuli produced clear direction-selective adaptation in V3A, MT+, and (if the LM depth was increased) also in V1 and V2. Therefore, the functional difference between the first- and second-order motions may originate in V1 and V2.

Direction-selective mechanism mediates identification of spatial patterns moving behind narrow slits

Direction-selective mechanism mediates identification of spatial patterns moving behind narrow slits

Synaptic Mechanisms of Direction Selectivity in Primary Auditory Cortex

Frequency modulation (FM) is a prominent feature in animal vocalization and human speech. Although many neurons in the auditory cortex are known to be selective for FM direction, the synaptic mechanisms underlying this selectivity are not well understood. Previous studies of both visual and auditory neurons have suggested two general mechanisms for direction selectivity: (1) differential delays of excitatory inputs across the spatial/spectral receptive field and (2) spatial/spectral offset between excitatory and inhibitory inputs. In this study, we have examined the contributions of both mechanisms to FM direction selectivity in rat primary auditory cortex. The excitatory and inhibitory synaptic inputs to each cortical neuron were measured by in vivo whole-cell recording. The spectrotemporal receptive field of each type of inputs was mapped with random tone pips and compared with direction selectivity of the neuron measured with FM stimuli. We found that both the differential delay of the excitatory input and the spectral offset between excitation and inhibition are positively correlated with direction selectivity of the neuron. Thus, both synaptic mechanisms are likely to contribute to FM direction selectivity in the auditory cortex. Finally, direction selectivity measured from the spiking output is significantly stronger than that based on the subthreshold membrane potentials, indicating that the selectivity is further sharpened by the spike generation mechanism.

Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity.

Event Abstract Back to Event Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity. Pamela M. Baker1* and Wyeth Bair1 1 University of Oxford, Department of Physiology, Anatomy and Genetics, United Kingdom Cross-correlation of spike trains from pairs of neurons has proved valuable for investigating functional connectivity in the visual system. It has revealed the specific functional connections between the lateral geniculate nucleus (LGN) and simple cells in primary visual cortex (V1) [1], and exposed properties of simple cells that drive complex cells [2]. Direction selectivity is a fundamental physiological property that arises from V1 circuitry yet basic questions of how direction selective (DS) receptive fields are constructed remain unanswered. To guide experiments for uncovering cortical mechanisms of direction selectivity, we implemented a set of plausible network models of DS neurons. We demonstrate how cross-correlation analysis can reveal the circuitry and mechanisms generating DS cells, including the nature of the DS nonlinearity and the stage in the visual pathway where the time delay, inherent to motion detection, originates. Our models consisted of LGN cells, V1 simple and complex DS cells that were spiking, conductance-based integrate and fire units with physiologically-realistic intrinsic currents connected by AMPA and GABA-A synapses. We tested model architectures where DS neurons are built directly from LGN inputs or indirectly via orientation-tuned simple cells. In some models, the time delay was implemented via temporal diversity in LGN inputs, in others it was ascribed to dendritic mechanisms in the DS neuron. Both have received recent attention experimentally [3,4]. We also varied whether the DS interaction was facilitatory or suppressive. We computed shuffle-corrected cross-correlograms (CCGs) of spike trains from pairs of units that are accessible to extracellular recording in vivo. We tested the models with visual stimuli employed experimentally, including sinusoidal gratings and flashed dots. We found that cross-correlation is well-suited to determine where the DS time delay arises. In models where temporally-offset inputs synapse onto the DS unit, the peak in the CCG between any non-DS input and the DS cell occurred at the time lag typical of monosynaptically connected cells. In models where the delay was generated in dendritic subunits within the DS cell, the CCG peak shifted systematically to reflect the postsynaptic delays. Cross-correlation revealed the nature of the DS nonlinearity, with facilitatory and suppressive DS mechanisms generating distinct shapes in CCGs. We also identified key factors that determine whether connections between non-DS and DS cells are revealed in CCGs. For example, suppressive mechanisms may only become apparent in CCGs if stimuli that drive the cell in the anti-preferred direction are used. This stimulus dependence reflects the selectivity of the DS mechanism, not the input cells themselves, and is thus independent of network architecture. We explored how the magnitude of peaks and dips in the CCG change as strength and number of inputs to the DS cell vary. We address how these factors create challenges for employing this analysis in electrophysiological recording. Overall, our results suggest that CCGs from simultaneously recorded pre- and post-synaptic non-DS and DS cells, respectively, are necessary and likely sufficient for solving long-standing problems of circuitry and mechanisms underlying cortical direction selectivity. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session II Citation: Baker PM and Bair W (2010). Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity.. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00332 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 08 Mar 2010; Published Online: 08 Mar 2010. * Correspondence: Pamela M Baker, University of Oxford, Department of Physiology, Anatomy and Genetics, Oxford, United Kingdom, pb2001@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. 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Mechanisms of after‐hyperpolarization following activation of fly visual motion‐sensitive neurons

In many neurons, strong excitatory stimulation causes an after-hyperpolarization (AHP) at stimulus offset, which might give rise to activity-dependent adaptation. Graded-potential visual motion-sensitive neurons of the fly Calliphora vicina respond with depolarization and hyperpolarization during motion in their preferred direction and their anti-preferred direction, respectively. A prominent after-response, opposite in sign to the response during motion, is selectively expressed after stimulation with preferred-direction motion. Previous findings suggested that this AHP is generated in the motion-sensitive neurons themselves rather than in presynaptic processing layers. However, it remained unknown whether the AHP is caused by membrane depolarization itself or by another process, e.g. a signaling cascade triggered by activity of excitatory input channels. Here we showed by current injections and voltage clamp that the AHP and a corresponding current are generated directly by depolarization. To test whether the generation of an AHP is linked to depolarization via a Ca(2+)-dependent mechanism, we used photoactivation of a high-affinity Ca(2+) buffer. In accordance with previous findings the AHP was insensitive to manipulation of cytosolic Ca(2+). We propose that membrane depolarization presents a more direction-selective mechanism for the control of AHP than other potential control parameters.