Does experience provide a permissive or instructive influence on the development of direction selectivity in visual cortex?

Functional neuronal circuits emerge in the absence of developmental activity

The complex neuronal circuitry of the brain develops from limited information contained in the genome. After the genetic code instructs the birth of neurons, the emergence of brain regions, and the formation of axon tracts, it is believed that temporally structured spiking activity shapes circuits for behavior. Here, we challenge the learning-dominated assumption that spiking activity is required for circuit formation by quantifying its contribution to the development of visually-guided swimming in the larval zebrafish. We found that visual experience had no effect on the emergence of the optomotor response (OMR) in dark-reared zebrafish. We then raised animals while pharmacologically silencing action potentials with the sodium channel blocker tricaine. After washout of the anesthetic, fish could swim and performed with 75-90% accuracy in the OMR paradigm. Brain-wide imaging confirmed that neuronal circuits came 'online' fully tuned, without requiring activity-dependent plasticity. Thus, complex sensory-guided behaviors can emerge through activity-independent developmental mechanisms.

Anatomical features for an adequate choice of the experimental animal model in biomedicine: III. Ferret, goat, sheep, and horse

The anatomical characteristics of each of the many species today employed in biomedical research are very important when selecting the correct animal model(s), especially for conducting translational research. In previous papers, these features have been considered for fish (D'Angelo et al. Ann. Anat, 2016, 205:75), the most common laboratory rodents, rabbits, and pigs (Lossi et al. 2016). I here follow this line of discussion by dealing with the importance of proper knowledge of ferrets, goats, sheep, and horses' main anatomical features in translational research.

Directional Preference in Avian Midbrain Saliency Computing Nucleus Reflects a Well-Designed Receptive Field Structure

Simple Summary

Directional preference neurons has been found in many vertebrate sensory systems. The isthmi pars magnocellularis (Imc) in avian midbrain, playing a key role in visual selective attention, shows impressive motion directional preference, but little is known about the physiological basis of this phenomenon. Herein, artificial visual stimuli, statistical analyses, and a neural computational model were used to unravel this mystery. This study deepens the understanding of the relationship between the directional preference and special receptive field structure of pigeon’s (Columba livia) Imc neuron.

Abstract

Neurons responding sensitively to motions in several rather than all directions have been identified in many sensory systems. Although this directional preference has been demonstrated by previous studies to exist in the isthmi pars magnocellularis (Imc) of pigeon (Columba livia), which plays a key role in the midbrain saliency computing network, the dynamic response characteristics and the physiological basis underlying this phenomenon are unclear. Herein, dots moving in 16 directions and a biologically plausible computational model were used. We found that pigeon Imc’s significant responses for objects moving in preferred directions benefit the long response duration and high instantaneous firing rate. Furthermore, the receptive field structures predicted by a computational model, which captures the actual directional tuning curves, agree with the real data collected from population Imc units. These results suggested that directional preference in Imc may be internally prebuilt by elongating the vertical axis of the receptive field, making predators attack from the dorsal-ventral direction and conspecifics flying away in the ventral-dorsal direction, more salient for avians, which is of great ecological and physiological significance for survival.

The Role of Inhibitory Interneurons in Circuit Assembly and Refinement Across Sensory Cortices

Sensory information is transduced into electrical signals in the periphery by specialized sensory organs, which relay this information to the thalamus and subsequently to cortical primary sensory areas. In the cortex, microcircuits constituted by interconnected pyramidal cells and inhibitory interneurons, distributed throughout the cortical column, form the basic processing units of sensory information underlying sensation. In the mouse, these circuits mature shortly after birth. In the first postnatal week cortical activity is characterized by highly synchronized spontaneous activity. While by the second postnatal week, spontaneous activity desynchronizes and sensory influx increases drastically upon eye opening, as well as with the onset of hearing and active whisking. This influx of sensory stimuli is fundamental for the maturation of functional properties and connectivity in neurons allocated to sensory cortices. In the subsequent developmental period, spanning the first five postnatal weeks, sensory circuits are malleable in response to sensory stimulation in the so-called critical periods. During these critical periods, which vary in timing and duration across sensory areas, perturbations in sensory experience can alter cortical connectivity, leading to long-lasting modifications in sensory processing. The recent advent of intersectional genetics, in vivo calcium imaging and single cell transcriptomics has aided the identification of circuit components in emergent networks. Multiple studies in recent years have sought a better understanding of how genetically-defined neuronal subtypes regulate circuit plasticity and maturation during development. In this review, we discuss the current literature focused on postnatal development and critical periods in the primary auditory (A1), visual (V1), and somatosensory (S1) cortices. We compare the developmental trajectory among the three sensory areas with a particular emphasis on interneuron function and the role of inhibitory circuits in cortical development and function.

The Ferret as a Model System for Neocortex Development and Evolution

The neocortex is the largest part of the cerebral cortex and a key structure involved in human behavior and cognition. Comparison of neocortex development across mammals reveals that the proliferative capacity of neural stem and progenitor cells and the length of the neurogenic period are essential for regulating neocortex size and complexity, which in turn are thought to be instrumental for the increased cognitive abilities in humans. The domesticated ferret, Mustela putorius furo, is an important animal model in neurodevelopment for its complex postnatal cortical folding, its long period of forebrain development and its accessibility to genetic manipulation in vivo. Here, we discuss the molecular, cellular, and histological features that make this small gyrencephalic carnivore a suitable animal model to study the physiological and pathological mechanisms for the development of an expanded neocortex. We particularly focus on the mechanisms of neural stem cell proliferation, neuronal differentiation, cortical folding, visual system development, and neurodevelopmental pathologies. We further discuss the technological advances that have enabled the genetic manipulation of the ferret in vivo. Finally, we compare the features of neocortex development in the ferret with those of other model organisms.

Postnatal Development of Visual Cortical Function in the Mammalian Brain

This review aims to discuss (1) the refinement of mammalian visual cortical circuits and the maturation of visual functions they subserve in primary visual cortex (V1) and other visual cortical areas, and (2) existing evidence supporting the notion of differential rates of maturation of visual functions in different species. It is well known that different visual functions and their underlying circuitry mature and attain adultlike characteristics at different stages in postnatal development with varying growth rates. The developmental timecourse and duration of refinement varies significantly both in V1 of various species and among different visual cortical areas; while basic visual functions like spatial acuity mature earlier requiring less time, higher form perception such as contour integration is more complex and requires longer postnatal time to refine. This review will highlight the importance of systematic comparative analysis of the differential rates of refinement of visual circuitry and function as that may help reveal underlying key mechanisms necessary for healthy visual development during infancy and adulthood. This type of approach will help future studies to establish direct links between various developmental aspects of different visual cortical areas in both human and animal models; thus enhancing our understanding of vision related neurological disorders and their potential therapeutic remedies.

Discrimination of Motion Direction in a Robot Using a Phenomenological Model of Synaptic Plasticity

Recognizing and tracking the direction of moving stimuli is crucial to the control of much animal behaviour. In this study, we examine whether a bio-inspired model of synaptic plasticity implemented in a robotic agent may allow the discrimination of motion direction of real-world stimuli. Starting with a well-established model of short-term synaptic plasticity (STP), we develop a microcircuit motif of spiking neurons capable of exhibiting preferential and nonpreferential responses to changes in the direction of an orientation stimulus in motion. While the robotic agent processes sensory inputs, the STP mechanism introduces direction-dependent changes in the synaptic connections of the microcircuit, resulting in a population of units that exhibit a typical cortical response property observed in primary visual cortex (V1), namely, direction selectivity. Visually evoked responses from the model are then compared to those observed in multielectrode recordings from V1 in anesthetized macaque monkeys, while sinusoidal gratings are displayed on a screen. Overall, the model highlights the role of STP as a complementary mechanism in explaining the direction selectivity and applies these insights in a physical robot as a method for validating important response characteristics observed in experimental data from V1, namely, direction selectivity.