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Falotico, E.

Publications and source records attributed to Falotico, E..

5 recordsLinked to original sources

ctSpyderFields: A Python package for visual field reconstruction in spiders

1The measurement of visual fields in arachnology has a long-standing history. Given the wide variety of eye positions, orientation and structure, the topic is fundamental for studies of taxonomy, evolution, ecology and behavior. The existing methods for measuring visual fields deploy ophthalmoscopic measurements, which require custom microscopes, anatomical structures like the reflective tapetum, which may not always be present, or the capacity to detect photoreceptor autofluorescence. Here we present the ctSpyderFields python package: a tool for geometrically predicting the visual fields of arachnids from digital images of the lens and retina. The tool uses images coming from computed tomography (CT) scans of specimens, but could be applied to other 3D microscopy techniques, to virtually project the boundaries of the retina through the geometrically predicted nodal point of the lens, deriving a rough per-eye visual field both in cartesian and spherical coordinates. The extracted data can then be used to calculate likely visual field overlap between eyes and angular spans, which can be compared within or between species. We also provide a use case, reporting the visual field data extracted from a museum specimen of Philaeus crysops. We propose that the tool will allow a wider comparative analysis of visual fields across spider species, unlocking the potential for a deeper understanding of visual ecology and evolution.

bioinformatics↗

Jumping spiders are not fooled by the peripheral drift illusion

In the peripheral drift illusion, a static circular sawtooth pattern is perceived as if it were rotating. It is believed that this effect is a byproduct of how the neural substrate responsible for motion perception is organized. The structure of the motion perception circuitry is widespread across the animal kingdom, vertebrates and invertebrates alike, which in turn causes the illusion effect to be experienced by virtually all animals. Among invertebrates, jumping spiders possess a unique visual system. For them, the tasks of visual computation are split across 4 pairs of eyes, with motion detection, target recognition, and shape discrimination computed in completely segregated brain areas and visual field sections. In such an organization, it is unlikely that the circuitry for motion perception common to other animals is shared by jumping spiders. Consequently, jumping spiders should be immune to the peripheral drift illusion. To test this hypothesis, we placed jumping spiders on top of an omnidirectional treadmill and presented them with circular visual stimuli in their visual periphery. These were either composed of a sawtooth pattern, and therefore inducing the illusion, or of a sine-wave pattern of equal luminance and spatial frequency but not illusion-inducing. The stimuli could either be static or rotate around their center, either clockwise or counterclockwise. As jumping spiders perform distinctive full-body pivots when detecting a moving object in their visual periphery, we registered the frequency of this behavior to assess the illusory percept. We found that the spiders responded consistently to all moving stimuli, but did not react to the static illusion, therefore it was not perceived as in motion. The absence of the illusory percept in spiders opens many questions about the nature of their motion perception circuitry and casts doubts on how the illusion is widespread in the animal kingdom outside the common model species usually inquired about.

animal behavior and cognition↗

Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and vigor of saccadic eye movements.

Saccadic eye-movements play a crucial role in visuo-motor control by allowing rapid foveation onto new targets. However, the neural processes governing saccades adaptation are not fully understood. Saccades, due to the short-time of execution (20-100 ms) and the absence of sensory information for online feedback control, must be controlled in a ballistic manner. Incomplete measurements of the movement trajectory, such as the visual end-point error, are supposedly used to form internal predictions about the movement kinematics resulting in predictive control. In order to characterize the synaptic and neural circuit mechanisms underlying predictive saccadic control, we have reconstructed the saccadic system in a digital controller embedding a spiking neural network of the cerebellum with spike timing-dependent plasticity (STDP) rules driving parallel fiber - Purkinje cell long-term potentiation and depression (LTP and LTD). This model implements a control policy based on a dual plasticity mechanism, resulting in the identification of the roles of LTP and LTD in optimizing saccade movement control: it turns out that LTD regulates the accuracy and LTP the speed (vigor) of the ballistic eye movement. The control policy also required cerebellar PCs to be divided into two subpopulations, characterized by burst or pause responses. To our knowledge, this is the first model that explains in mechanistic terms the accuracy and vigor regulation of ballistic eye movements in forward mode exploiting spike-timing to regulate firing in different populations of the neuronal network. This elementary model of saccades could be extended and applied to other more complex cases in which single jerks are concatenated to compose articulated and coordinated movements. Author summaryIt has been suggested that the cerebellum plays a crucial role in oculomotor adaptation. Computationally, the cerebellum is described as a supervised learner whose activity can be adjusted by synaptic changes proportional to the amount of mismatch between expected and actual movements outcomes (sensorimotor-errors). However, the spike-timing-dependent-plasticity (STDP) underlying adaptation has been so far modeled in behaviors where the error is continuously available as tracking-error. Such models depend on detailed tracking-errors to improve movement quality. We asked if the cerebellum can maintain good motor control even if the error is not completely available? This is important considering that error-dependent-STDP is only a subset among a family of STDP processes in the cerebellum. Moreover, even the physiological signals that were generally thought to carry sensorimotor-errors (called complex-spikes) are shown to encode multiple types of information regarding the movement. In this context, we characterize the role of cerebellar STDPs in saccade control, where the error information is constrained because of sensory suppression. We show that even in the absence of detailed error, the cerebellum can leverage two of its STDPs to increase movement quality. Hence, we emphasize the need to go beyond error-centric view to understand how the cerebellum improves motor behavior.

neuroscience↗

Rotational dynamics in motor cortex are consistent with a feedback controller

Recent studies hypothesize that motor cortical (MC) dynamics are generated largely through its recurrent connections based on observations that MC activity exhibits rotational structure. However, behavioural and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback about the limb. Networks were trained to counteract perturbations to the limb and to reach towards spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may reflect dynamics throughout voluntary motor circuits involved in online control of motor actions. HighlightsO_LINeural networks with sensory feedback generate rotational dynamics during simulated posture and reaching tasks C_LIO_LIRotational dynamics are observed even without recurrent connections in the network C_LIO_LISimilar dynamics are observed not only in motor cortex, but also in somatosensory cortex of non-huma n primates as well as sensory feedback signals C_LIO_LIResults highlight rotational dynamics may reflect internal dynamics, external inputs or any combination of the two. C_LI

neuroscience↗

Experimental and computational study on motor control and recovery after stroke: towards a constructive loop betweenexperimental and virtual embodiedneuroscience

Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.

neuroscience↗