Cell-type specific pallial circuits shape categorical tuning responses in the crow telencephalon

Functional role of cell classes in monkey prefrontal cortex after learning a working memory task

The prefrontal cortex (PFC) is important for learning and performing working memory tasks. However, its precise role for spatial and non-spatial working memory, and the role of different cell types in the circuits that maintain working memory remain poorly understood. To investigate this issue, we analyzed single-unit recordings from the PFC of monkeys during the passive viewing phase before they learned the task rules and after learning, during the execution of active working memory tasks (spatial and feature). Through cluster analysis of extracellular spike waveform features, we identified two classes of narrow-spiking neurons (putative inhibitory cells) and two classes of broad-spiking neurons (putative pyramidal cells). These putative cell classes exhibited distinct physiological characteristics, including baseline firing rates, baseline neural firing variability, and visual stimulus-evoked responses. Neuronal response modulation varied heterogeneously across these cell classes after training and performing active tasks. Training and execution of spatial working memory resulted in higher activity in all class types, highlighting the involvement of diverse prefrontal circuits in spatial information processing. In contrast, feature working memory training and execution affected activity of broad-spiking cell classes alone, suggesting less involvement of a prefrontal circuit in the representation of feature information. We also revealed hitherto unknown, differential effects of training and task execution on different broad-spiking cell types. One broad-spiking neuron subtype exhibited significant response modulation, with increased baseline firing rate, stimulus-evoked responses, and working memory-related firing rates. Another broad-spiking subtype showed decreased baseline firing rate and variability, which may optimize neural coding efficiency. This study advances our understanding of the functional heterogeneity within the PFC and the specialized contributions of different neuronal subtypes to cognitive processes.

NSF Workshop Report: Exploring Measurements and Interpretations of Intelligent Behaviors Across Animal Model Systems

Defining intelligence is a challenging and fraught task, but one that neuroscientists are repeatedly confronted with. A central goal of neuroscience is to understand how phenomena like intelligent behaviors emerge from nervous systems. This requires some determination of what defines intelligence and how to measure it. The challenge is multifaceted. For instance, as we begin to describe and understand the brain in increasingly specific physical terms (e.g., anatomy, cell types, activity patterns), we amplify an ever-growing divide in how we connect measurable properties of the brain to less tangible concepts like intelligence. As our appreciation for evolutionary diversity in neuroscience grows, we are further confronted with whether there can be a unifying theory of intelligence. The National Science Foundation (NSF) NeuroNex consortium recently gathered experts from multiple animal model systems to discuss intelligence across species. We summarize here the different perspectives offered by the consortium, with the goal of promoting thought and debate of this ancient question from a modern perspective, and asking whether defining intelligence is a useful exercise in neuroscience or an ill-posed and distracting question. We present data from the vantage points of humans, macaques, ferrets, crows, octopuses, bees, and flies, highlighting some of the noteworthy capabilities of each species within the context of each species' ecological niche and how these may be challenged by climate change. We also include a remarkable example of convergent evolution between primates and crows in the circuit and molecular basis for working memory in these highly divergent animal species.

Neuronal mechanisms enhancing selectivity of the innate number sense via learning

In their feature article, Lorenzi et al. (2025) compiled extensive biological evidence on the ontogenetic origins of the number sense. Drawing on both behavioral and neurobiological data, they convincingly argue that the "number sense" is fundamentally innate and present from birth in numerically competent animals, including humans. At the same time, the authors acknowledge the role of learning and experience in shaping numerical cognition. This commentary builds on the idea of learning-induced changes to the number sense, extending the concept of an innate number sense to one that is modifiable through learning and experience. It summarizes evidence from single-neuron recordings and proposes neurophysiological mechanisms underlying these learning-induced changes in numerical cognition.

The calculating brain

The human brain possesses neural networks and mechanisms enabling the representation of numbers, basic arithmetic operations, and mathematical reasoning. Without the ability to represent numerical quantity and perform calculations, our scientifically and technically advanced culture would not exist. However, the origins of numerical abilities are grounded in an intuitive understanding of quantity deeply rooted in biology. Nevertheless, more advanced symbolic arithmetic skills require a cultural background with formal mathematical education. In the past two decades, cognitive neuroscience has seen significant progress in understanding the workings of the calculating brain through various methods and model systems. This review begins by exploring the mental and neuronal representations of nonsymbolic numerical quantity and then progresses to symbolic representations acquired in childhood. During arithmetic operations (addition, subtraction, multiplication, and division), these representations are processed and transformed according to arithmetic rules and principles, leveraging different mental strategies and types of arithmetic knowledge that can be dissociated in the brain. Although it was once believed that number processing and calculation originated from the language faculty, it is now evident that mathematical and linguistic abilities are primarily processed independently in the brain. Understanding how the healthy brain processes numerical information is crucial for gaining insights into debilitating numerical disorders, including acquired conditions like acalculia and learning-related calculation disorders such as developmental dyscalculia.

Convergent Circuit Computation for Categorization in the Brains of Primates and Songbirds

Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.

Distinct neuronal representation of small and large numbers in the human medial temporal lobe

Whether small numerical quantities are represented by a special subitizing system that is distinct from a large-number estimation system has been debated for over a century. Here we show that two separate neural mechanisms underlie the representation of small and large numbers. We performed single neuron recordings in the medial temporal lobe of neurosurgical patients judging numbers. We found a boundary in neuronal coding around number 4 that correlates with the behavioural transition from subitizing to estimation. In the subitizing range, neurons showed superior tuning selectivity accompanied by suppression effects suggestive of surround inhibition as a selectivity-increasing mechanism. In contrast, tuning selectivity decreased with increasing numbers beyond 4, characterizing a ratio-dependent number estimation system. The two systems with the coding boundary separating them were also indicated using decoding and clustering analyses. The identified small-number subitizing system could be linked to attention and working memory that show comparable capacity limitations.

Neural coding of numerousness

Perception of numerousness, i.e. number of items in a set, is an important cognitive ability, which is present in several animal taxa. In spite of obvious differences in neuroanatomy, insects, fishes, reptiles, birds, and mammals all possess a "number sense". Furthermore, information regarding numbers can belong to different sensory modalities: animals can estimate a number of visual items, a number of tones, or a number of their own movements. Given both the heterogeneity of stimuli and of the brains processing these stimuli, it is hard to imagine that number cognition can be traced back to the same evolutionary conserved neural pathway. However, neurons that selectively respond to the number of stimuli have been described in higher-order integration brain centres both in primates and in birds, two evolutionary distant groups. Although most probably not of the same evolutionary origin, these number neurons share remarkable similarities in their response properties. Instead of homology, this similarity might result from computational advantages of the underlying coding mechanism. This means that one might expect numerousness information to undergo similar steps of neural processing even in evolutionary distant neural pathways. Following this logic, in this review we summarize our current knowledge of how numerousness is processed in the brain from sensory input to coding of abstract information in the higher-order integration centres. We also propose a list of key open questions that might promote future research on number cognition.

Categorising: Inside the crow's brain

Crows can learn to categorise line lengths into experimenter-defined categories. The crow's brain codes and recodes line lengths in individual neurons in the nidopallium caudolaterale, part of the telencephalon.

Categorical representation of abstract spatial magnitudes in the executive telencephalon of crows

The ability to group abstract continuous magnitudes into meaningful categories is cognitively demanding but key to intelligent behavior. To explore its neuronal mechanisms, we trained carrion crows to categorize lines of variable lengths into arbitrary "short" and "long" categories. Single-neuron activity in the nidopallium caudolaterale (NCL) of behaving crows reflected the learned length categories of visual stimuli. The length categories could be reliably decoded from neuronal population activity to predict the crows' conceptual decisions. NCL activity changed with learning when a crow was retrained with the same stimuli assigned to more categories with new boundaries ("short", "medium," and "long"). Categorical neuronal representations emerged dynamically so that sensory length information at the beginning of the trial was transformed into behaviorally relevant categorical representations shortly before the crows' decision making. Our data show malleable categorization capabilities for abstract spatial magnitudes mediated by the flexible networks of the crow NCL.

Neural correlates of cognitively controlled vocalizations in a corvid songbird

The neuronal basis of the songbird's song system is well understood. However, little is known about the neuronal correlates of the executive control of songbird vocalizations. Here, we record single-unit activity from the pallial endbrain region "nidopallium caudolaterale" (NCL) of crows that vocalize to the presentation of a visual go-cue but refrain from vocalizing during trials without a go-cue. We find that the preparatory activity of single vocalization-correlated neurons, but also of the entire population of NCL neurons, before vocal onset predicts whether or not the crows will produce an instructed vocalization. Fluctuations in baseline neuronal activity prior to the go-cue influence the premotor activity of such vocalization-correlated neurons and seemingly bias the crows' decision to vocalize. Neuronal response modulation significantly differs between volitional and task-unrelated vocalizations. This suggests that the NCL can take control over the vocal motor network during the production of volitional vocalizations in a corvid songbird.

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.

Glutamatergic pathways in the brains of turtles: A comparative perspective among reptiles, birds, and mammals

Glutamate acts as the main excitatory neurotransmitter in the brain and plays a vital role in physiological and pathological neuronal functions. In mammals, glutamate can cause detrimental excitotoxic effects under anoxic conditions. In contrast, Trachemys scripta, a freshwater turtle, is one of the most anoxia-tolerant animals, being able to survive up to months without oxygen. Therefore, turtles have been investigated to assess the molecular mechanisms of neuroprotective strategies used by them in anoxic conditions, such as maintaining low levels of glutamate, increasing adenosine and GABA, upregulating heat shock proteins, and downregulating KATP channels. These mechanisms of anoxia tolerance of the turtle brain may be applied to finding therapeutics for human glutamatergic neurological disorders such as brain injury or cerebral stroke due to ischemia. Despite the importance of glutamate as a neurotransmitter and of the turtle as an ideal research model, the glutamatergic circuits in the turtle brain remain less described whereas they have been well studied in mammalian and avian brains. In reptiles, particularly in the turtle brain, glutamatergic neurons have been identified by examining the expression of vesicular glutamate transporters (VGLUTs). In certain areas of the brain, some ionotropic glutamate receptors (GluRs) have been immunohistochemically studied, implying that there are glutamatergic target areas. Based on the expression patterns of these glutamate-related molecules and fiber connection data of the turtle brain that is available in the literature, many candidate glutamatergic circuits could be clarified, such as the olfactory circuit, hippocampal–septal pathway, corticostriatal pathway, visual pathway, auditory pathway, and granule cell–Purkinje cell pathway. This review summarizes the probable glutamatergic pathways and the distribution of glutamatergic neurons in the pallium of the turtle brain and compares them with those of avian and mammalian brains. The integrated knowledge of glutamatergic pathways serves as the fundamental basis for further functional studies in the turtle brain, which would provide insights on physiological and pathological mechanisms of glutamate regulation as well as neural circuits in different species.

A brain atlas of the carrion crow (Corvus corone)

Corvidae, passerine songbirds such as jays, crows, and ravens known as corvids, have become model systems for the study of avian cognition. The superior cognitive capabilities of corvids mainly emerge from a disproportionally large telencephalon found in these species. However, a systematic mapping of the neuroanatomy of the corvid brain, and the telencephalon in particular, is lacking so far. Here, we present a brain atlas of the carrion crow, Corvus corone, with special emphasis on the telencephalic pallium. We applied four staining techniques to brain slices (Nissl, myelin, combination of Nissl and myelin, and tyrosine hydroxylase targeting catecholaminergic neurons). This allowed us to identify brain nuclei throughout the brain and delineate the known pallial subdivisions termed hyperpallium, entopallium, mesopallium, nidopallium, arcopallium, and hippocampal complex. The extent of these subdivisions and brain nuclei are described according to stereotaxic coordinates. In addition, 3D depictions of pallial regions were reconstructed from these slices. While the overall organization of the carrion crow's brain matches other songbird brains, the relative proportions and expansions of associative pallial areas differ considerably in agreement with enhanced cognitive skills found in corvids. The presented global organization of the crow brain in stereotaxic coordinates will help to guide future neurobiological studies in corvids.