Visual categories and concepts in the avian brain.

Birds are excellent model organisms to study perceptual categorization and concept formation. The renewed focus on avian neuroscience has sparked an explosion of new data in the field. At the same time, our understanding of sensory and particularly visual structures in the avian brain has shifted fundamentally. These recent discoveries have revealed how categorization is mediated in the avian brain and has generated a theoretical framework that goes beyond the realm of birds. We review the contribution of avian categorization research-at the methodical, behavioral, and neurobiological levels. To this end, we first introduce avian categorization from a behavioral perspective and the common elements model of categorization. Second, we describe the functional and structural organization of the avian visual system, followed by an overview of recent anatomical discoveries and the new perspective on the avian 'visual cortex'. Third, we focus on the neurocomputational basis of perceptual categorization in the bird's visual system. Fourth, an overview of the avian prefrontal cortex and the prefrontal contribution to perceptual categorization is provided. The fifth section outlines how asymmetries of the visual system contribute to categorization. Finally, we present a mechanistic view of the neural principles of avian visual categorization and its putative extension to concept learning.

The open toolbox for behavioral research.

In this work, we describe a new open-source MATLAB toolbox for the control of behavioral experiments. The toolbox caters to very different types of experiments in different species, and with different underlying hardware. Typical examples are operant chambers in animals, with or without neurophysiology, behavioral experiments in human subjects, and neurophysiological recordings in humans such as EEG and fMRI. In addition, the toolbox supports communication via Ethernet to either control and monitor one or several experimental setups remotely or to implement distributed paradigms across different computers. This flexibility is possible, since the toolbox supports a wide range of hardware, some of which is custom developments. An example is a fast network-based digital-IO device for the communication with experimental hardware such as feeders or triggers in neurophysiological setups. We also included functions for online video analysis allowing paradigms to be contingent on responses to a screen, the head movement of a bird in an operant chamber, or the physical location of an animal in an open arena. While the toolbox is well tested and many components of it have been in use for many years, we do not see it as a finished product but rather a continuing development with a focus on easy extendibility and customization.

RUBubbles as a novel tool to study categorization learning.

Grouping objects into discrete categories affects how we perceive the world and represents a crucial element of cognition. Categorization is a widespread phenomenon that has been thoroughly studied. However, investigating categorization learning poses several requirements on the stimulus set in order to control which stimulus feature is used and to prevent mere stimulus-response associations or rote learning. Previous studies have used a wide variety of both naturalistic and artificial categories, the latter having several advantages such as better control and more direct manipulation of stimulus features. We developed a novel stimulus type to study categorization learning, which allows a high degree of customization at low computational costs and can thus be used to generate large stimulus sets very quickly. 'RUBubbles' are designed as visual artificial category stimuli that consist of an arbitrary number of colored spheres arranged in 3D space. They are generated using custom MATLAB code in which several stimulus parameters can be adjusted and controlled separately, such as number of spheres, position in 3D-space, sphere size, and color. Various algorithms for RUBubble generation can be combined with distinct behavioral training protocols to investigate different characteristics and strategies of categorization learning, such as prototype- vs. exemplar-based learning, different abstraction levels, or the categorization of a sensory continuum and category exceptions. All necessary MATLAB code is freely available as open-source code and can be customized or expanded depending on individual needs. RUBubble stimuli can be controlled purely programmatically or via a graphical user interface without MATLAB license or programming experience.

Cell Encapsulation in Soft, Anisometric Poly(ethylene) Glycol Microgels Using a Novel Radical-Free Microfluidic System.

Complex 3D artificial tissue constructs are extensively investigated for tissue regeneration. Frequently, materials and cells are delivered separately without benefitting from the synergistic effect of combined administration. Cell delivery inside a material construct provides the cells with a supportive environment by presenting biochemical, mechanical, and structural signals to direct cell behavior. Conversely, the cell/material interaction is poorly understood at the micron scale and new systems are required to investigate the effect of micron-scale features on cell functionality. Consequently, cells are encapsulated in microgels to avoid diffusion limitations of nutrients and waste and facilitate analysis techniques of single or collective cells. However, up to now, the production of soft cell-loaded microgels by microfluidics is limited to spherical microgels. Here, a novel method is presented to produce monodisperse, anisometric poly(ethylene) glycol microgels to study cells inside an anisometric architecture. These microgels can potentially direct cell growth and can be injected as rod-shaped mini-tissues that further assemble into organized macroscopic and macroporous structures post-injection. Their aspect ratios are adjusted with flow parameters, while mechanical and biochemical properties are altered by modifying the precursors. Encapsulated primary fibroblasts are viable and spread and migrate across the 3D microgel structure.

Synthetic 3D PEG-Anisogel Tailored with Fibronectin Fragments Induce Aligned Nerve Extension.

An enzymatically cross-linked polyethylene glycol (PEG)-based hydrogel was engineered to promote and align nerve cells in a three-dimensional manner. To render the injectable, otherwise bioinert, PEG-based material supportive for cell growth, its mechanical and biochemical properties were optimized. A recombinant fibronectin fragment (FNIII9*-10/12-14) was coupled to the PEG backbone during gelation to provide cell adhesive and growth factor binding domains in close vicinity. Compared to full-length fibronectin, FNIII9*-10/12-14 supports nerve growth at similar concentrations. In a 3D environment, only the ultrasoft 1 w/v% PEG hydrogels with a storage modulus of ∼10 Pa promoted neuronal growth. This gel was used to establish the first fully synthetic, injectable Anisogel by the addition of magnetically aligned microelements, such as rod-shaped microgels or short fibers. The Anisogel led to linear neurite extension and represents a large step in the direction of clinical translation with the opportunity to treat acute spinal cord injuries.

Nerve Cells Decide to Orient inside an Injectable Hydrogel with Minimal Structural Guidance.

Injectable biomaterials provide the advantage of a minimally invasive application but mostly lack the required structural complexity to regenerate aligned tissues. Here, we report a new class of tissue regenerative materials that can be injected and form an anisotropic matrix with controlled dimensions using rod-shaped, magnetoceptive microgel objects. Microgels are doped with small quantities of superparamagnetic iron oxide nanoparticles (0.0046 vol %), allowing alignment by external magnetic fields in the millitesla order. The microgels are dispersed in a biocompatible gel precursor and after injection and orientation are fixed inside the matrix hydrogel. Regardless of the low volume concentration of the microgels below 3%, at which the geometrical constrain for orientation is still minimum, the generated macroscopic unidirectional orientation is strongly sensed by the cells resulting in parallel nerve extension. This finding opens a new, minimal invasive route for therapy after spinal cord injury.

An Injectable Hybrid Hydrogel with Oriented Short Fibers Induces Unidirectional Growth of Functional Nerve Cells.

To regenerate soft aligned tissues in living organisms, low invasive biomaterials are required to create 3D microenvironments with a structural complexity to mimic the tissue's native architecture. Here, a tunable injectable hydrogel is reported, which allows precise engineering of the construct's anisotropy in situ. This material is defined as an Anisogel, representing a new type of tissue regenerative therapy. The Anisogel comprises a soft hydrogel, surrounding magneto-responsive, cell adhesive, short fibers, which orient in situ in the direction of a low external magnetic field, before complete gelation of the matrix. The magnetic field can be removed after gelation of the biocompatible gel precursor, which fixes the aligned fibers and preserves the anisotropic structure of the Anisogel. Fibroblasts and nerve cells grow and extend unidirectionally within the Anisogels, in comparison to hydrogels without fibers or with randomly oriented fibers. The neurons inside the Anisogel show spontaneous electrical activity with calcium signals propagating along the anisotropy axis of the material. The reported system is simple and elegant and the short magneto-responsive fibers can be produced with an effective high-throughput method, ideal for a minimal invasive route for aligned tissue therapy.

Why birds are smart.

Many cognitive neuroscientists believe that both a large brain and an isocortex are crucial for complex cognition. Yet corvids and parrots possess non-cortical brains of just 1-25 g, and these birds exhibit cognitive abilities comparable with those of great apes such as chimpanzees, which have brains of about 400 g. This opinion explores how this cognitive equivalence is possible. We propose four features that may be required for complex cognition: a large number of associative pallial neurons, a prefrontal cortex (PFC)-like area, a dense dopaminergic innervation of association areas, and dynamic neurophysiological fundaments for working memory. These four neural features have convergently evolved and may therefore represent 'hard to replace' mechanisms enabling complex cognition.

Jackdaws form categorical prototypes based on experience with category exemplars.

Categorization represents one cognitive ability fundamental to animal behavior. Grouping of elements based on perceptual or semantic features helps to reduce processing resources and facilitates appropriate behavior. Corvids master complex categorization, yet the detailed categorization learning strategies are less well understood. We trained two jackdaws on a delayed match to category paradigm using a novel, artificial stimulus type, RUBubbles. Both birds learned to differentiate between two session-unique categories following two distinct learning protocols. Categories were either introduced via central category prototypes (low variability approach) or using a subset of diverse category exemplars from which diagnostic features had to be identified (high variability approach). In both versions, the stimulus similarity relative to a central category prototype explained categorization performance best. Jackdaws consistently used a central prototype to judge category membership, regardless of whether this prototype was used to introduce distinct categories or had to be inferred from multiple exemplars. Reliance on a category prototype occurred already after experiencing only a few trials with different category exemplars. High stimulus set variability prolonged initial learning but showed no consistent beneficial effect on later generalization performance. High numbers of stimuli, their perceptual similarity, and coherent category structure resulted in a prototype-based strategy, reflecting the most adaptive, efficient, and parsimonious way to represent RUBubble categories. Thus, our birds represent a valuable comparative animal model that permits further study of category representations throughout learning in different regions of a brain producing highly cognitive behavior.

Photo-cross-linked and pH-Switchable Soft Polymer Nanocapsules from Polyglycidyl Ethers.

Soft polymer nanocapsules and microgels, which can adapt their shape and, at the same time, sequester and release molecular payloads in response to an external trigger, are a challenging complement to vesicular structures like polymersomes. In this work, we report the synthesis of such capsules by photo-cross-linking of coumarin-substituted polyglycidyl ethers, which we prepared by Williamson etherification of epichlorohydrin (ECH) repeating units with 7-hydroxycoumarin in copolymers with tert-butyl glycidyl ether (tBGE). To control capsule size, we employed the prepolymers in an o/w miniemulsion, where they formed a gel layer at the interface upon irradiation at 365 nm by [2π + 2π] photodimerization of the coumarin groups. Upon irradiation at 254 nm, the reaction could be reversed and the gel wall could be repeatedly disintegrated and rebuilt. We further demonstrated (i) reversible hydrophilization of the gels by hydrolysis of the lactone rings in coumarin dimers as a mechanism to manipulate the permeability of the capsules and (ii) binding functional molecules as amides. Thus, the presented nanogels are remarkably versatile and can be further used as a carrier system.

Avian brain: A scanning beam of attention in the pigeon 'superior colliculus'.

The superior colliculus is important for spatial attention across vertebrates. A new study in pigeons discovered a mechanism of attention: electric fields traveling across the optic tectum, which could be thought of as the avian version of the mammalian superior colliculus.

Transient oscillations as computations for cognition: Analysis, modeling and function.

Our view of neural oscillations is currently changing. The dominant picture of sustained oscillations is now often replaced by transient oscillations occurring in bursts. This phenomenon seems to be quite comprehensive, as it has been reported for different oscillation frequencies, including the theta, beta, and gamma bands, as well as cortical and subcortical regions in a variety of cognitive tasks and species. Here we review recent developments in their analysis, computational modeling, and functional roles. For the analysis of transient oscillations methods using lagged coherence and Hidden Markov Models have been developed and applied in recent studies to ascertain their transient nature and study their contribution to cognitive functions. Furthermore, computational models have been developed that account for their stochastic nature, which poses interesting functional constraints. Finally, as transient oscillations have been observed across many species, they are likely of functional significance and we consider challenges in characterizing their function.

Executive Control of Sequence Behavior in Pigeons Involves Two Distinct Brain Regions.

Executive functions arise from multiple regions of the brain acting in concert. To facilitate such cross-regional computations, the brain is organized into distinct executive networks, like the frontoparietal network. Despite similar cognitive abilities across many domains, little is known about such executive networks in birds. Recent advances in avian fMRI have shown a possible subset of regions, including the nidopallium caudolaterale (NCL) and the lateral part of medial intermediate nidopallium (NIML), that may contribute to complex cognition, forming an action control system of pigeons. We investigated the neuronal activity of NCL and NIML. Single-cell recordings were obtained during the execution of a complex sequential motor task that required executive control to stop executing one behavior and continue with a different one. We compared the neuronal activity of NIML to NCL and found that both regions fully processed the ongoing sequential execution of the task. Differences arose from how behavioral outcome was processed. Our results indicate that NCL takes on a role in evaluating outcome, while NIML is more tightly associated with ongoing sequential steps. Importantly, both regions seem to contribute to overall behavioral output as parts of a possible avian executive network, crucial for behavioral flexibility and decision-making.

Corvids optimize working memory by categorizing continuous stimuli.

Working memory (WM) is a crucial element of the higher cognition of primates and corvid songbirds. Despite its importance, WM has a severely limited capacity and is vulnerable to noise. In primates, attractor dynamics mitigate the effect of noise by discretizing continuous information. Yet, it remains unclear whether similar dynamics are seen in avian brains. Here, we show jackdaws (Corvus monedula) have similar behavioral biases as humans; memories are less precise and more biased as memory demands increase. Model-based analysis reveal discrete attractors are evenly spread across the stimulus space. Altogether, our comparative approach suggests attractor dynamics in primates and corvids mitigate the effect of noise by systematically drifting towards specific attractors. By demonstrating this effect in an evolutionary distant species, our results strengthen attractor dynamics as general, adaptive biological principle to efficiently use WM.

Working memory control dynamics follow principles of spatial computing.

Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts of beta and gamma oscillations. However, it is not clear how oscillations, reflecting coherent activity of millions of neurons, can selectively control individual WM items. Here we propose the novel concept of spatial computing where beta and gamma interactions cause item-specific activity to flow spatially across the network during a task. This way, control-related information such as item order is stored in the spatial activity independent of the detailed recurrent connectivity supporting the item-specific activity itself. The spatial flow is in turn reflected in low-dimensional activity shared by many neurons. We verify these predictions by analyzing local field potentials and neuronal spiking. We hypothesize that spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension.

Working memory performance is tied to stimulus complexity.

Working memory is the cognitive capability to maintain and process information over short periods. Behavioral and computational studies have shown that visual information is associated with working memory performance. However, the underlying neural correlates remain unknown. To identify how visual information affects working memory performance, we conducted behavioral experiments in pigeons (Columba livia) and single unit recordings in the avian prefrontal analog, the nidopallium caudolaterale (NCL). Complex pictures featuring luminance, spatial and color information, were associated with higher working memory performance compared to uniform gray pictures in conjunction with distinct neural coding patterns. For complex pictures, we found a multiplexed neuronal code displaying visual and value-related features that switched to a representation of the upcoming choice during a delay period. When processing gray stimuli, NCL neurons did not multiplex and exclusively represented the choice already during stimulus presentation and throughout the delay period. The prolonged representation possibly resulted in a decay of the memory trace ultimately leading to a decrease in performance. In conclusion, we found that high stimulus complexity is associated with neuronal multiplexing of the working memory representation possibly allowing a facilitated read-out of the neural code resulting in enhancement of working memory performance.

The avian brain.

There is a reason this primer is called 'The avian brain' and not 'The birdbrain' even though the latter term might be more accessible. The term birdbrain was long used as a derogative, yet I hope that this primer will inspire you to see it more as I do - as a compliment. This primer will take you on a short tour. First, I will explore superficial differences between birds and mammals. Then I will briefly mention the behavioral capabilities of birds and explain why the bird brain has the neural makeup to generate these behaviors. This will lead me to briefly describe some key neural circuits and structures and to conclude with the ongoing challenge to identify functional differences in the neural substrates of avian and mammalian cognition. The aim of this short article, therefore, is not to give a full review of the avian brain but rather to highlight important aspects with a focus on the comparison to the mammalian brain and cognition.

Oscillations without cortex: Working memory modulates brainwaves in the endbrain of crows.

Complex cognition requires coordinated neuronal activity at the network level. In mammals, this coordination results in distinct dynamics of local field potentials (LFP) central to many models of higher cognition. These models often implicitly assume a cortical organization. Higher associative regions of the brains of birds do not have cortical layering, yet single-cell correlates of higher cognition are very similar to those found in mammals. We recorded LFP in the avian equivalent of prefrontal cortex while crows performed a highly controlled and cognitively demanding working memory task. We found signatures in local field potentials, modulated by working memory. Frequencies of a narrow gamma and the beta band contained information about the location of target items and were modulated by working memory load. This indicates a critical involvement of these bands in ongoing cognitive processing. We also observed bursts in the beta and gamma frequencies, similar to those that play a vital part in 'activity silent' models of working memory. Thus, despite the lack of a cortical organization the avian associative pallium can create LFP signatures reminiscent of those observed in primates. This points towards a critical cognitive function of oscillatory dynamics evolved through convergence in species capable of complex cognition.

Reduced variability of bursting activity during working memory.

Working memories have long been thought to be maintained by persistent spiking. However, mounting evidence from multiple-electrode recording (and single-trial analyses) shows that the underlying spiking is better characterized by intermittent bursts of activity. A counterargument suggested this intermittent activity is at odds with observations that spike-time variability reduces during task performance. However, this counterargument rests on assumptions, such as randomness in the timing of the bursts, which may not be correct. Thus, we analyzed spiking and LFPs from monkeys' prefrontal cortex (PFC) to determine if task-related reductions in variability can co-exist with intermittent spiking. We found that it does because both spiking and associated gamma bursts were task-modulated, not random. In fact, the task-related reduction in spike variability could largely be explained by a related reduction in gamma burst variability. Our results provide further support for the intermittent activity models of working memory as well as novel mechanistic insights into how spike variability is reduced during cognitive tasks.

Avian navigation: Head direction cells in the quail hippocampus.

Birds are experts in many behaviors akin to those in mammals that are known to involve the hippocampus, yet the avian hippocampus is still poorly understood. A new study finds head-direction cells, but not place cells, in the hippocampal formation of quails.