Biology subjects

Nieder, A.

Publications and source records attributed to Nieder, A..

8 recordsLinked to original sources

bioRxiv2025

High-field fMRI at 7 Tesla reveals topographic responses tuned to number in the developing human brain

In the adult brain, hemodynamic responses to visually presented numerosities reveal receptive field-like tuning curves in topographically organized maps across association cortices. It is currently unknown whether such tuned topographic responses to numerosities can also be detected in the developing brain. Here we conducted a 7 Tesla fMRI experiment in which we presented a large set of visual dot displays to 11-12-year-old children and adults. We found that developing hemodynamic responses indeed revealed logarithmic Gaussian tuning to quantitative information. Tuning models explained comparable amounts of variance in children and adults. In most subjects, six bilateral cortical maps consistently exhibited topographic responses to numerosities. The present study goes beyond previous work by uncovering a population code for quantity detection in individual developing human brains. Our work lays a foundation for a model-based neuroimaging approach to individual cognitive differences in the context of developmental dyscalculia and mathematical giftedness.

neuroscience↗

bioRxiv2024

Exploring Neural Dynamics in the Auditory Telencephalon of Crows using Functional Ultrasound Imaging

Crows, known for advanced cognitive abilities and vocal communication, rely on intricate auditory systems. While the neuroanatomy of corvid auditory pathways is partially explored, the underlying neurophysiological mechanisms are largely unknown. This study used functional ultrasound imaging (fUSi) to investigate sound-induced cerebral blood volume (CBV) changes in the field L complex of the crows auditory telencephalon, a functional analogue to the mammalian auditory cortex. FUSi revealed frequency-specific CBV responses, showing a tonotopic organization within the field L complex, with low frequencies in the posterior-dorsal region and high frequencies in the anterior-ventral region, similar to neuronal patterns reported in other songbirds. The responses were more robust when the crows were awake compared to when they were anesthetized. Machine learning analyses showed fUSi signals could be used to classify sound types accurately. Shorter stimuli reliably triggered transient CBV increases, while longer sounds resulted in variable responses, including negative deflections. This variability in CBV responses suggests a delineation of subregions within the field L complex with the central region (L2) as the primary processing hub and outer regions (L1, L3) integrating auditory information. These findings highlight the potential of fUSi for providing high-resolution insights into functional systems in corvids, enabling future exploration of task-related cognitive dynamics.

neuroscience↗

bioRxiv2024

Parcellation of the primate prefrontal cortex by cognitive control operations

Modular organization, the division of the cerebral cortex into functionally distinct subregions, is well established in the primate sensorimotor cortex, but debated in the cognitive association cortex, including the prefrontal cortex (PFC). Here, we obtained microelectrode recordings with broad spatial coverage from the lateral PFC of two rhesus monkeys performing a working memory task with distractors. We found that neighboring electrodes shared task-related oscillatory neural dynamics that were stable across recording sessions and formed spatially continuous, mesoscale clusters that also segregated by local and long-range frontoparietal connectivity, spiking activity, involvement in working memory processing stages and influence on behavioral accuracy. Remarkably, the degree of parcellation reflected the animals individual mnemonic abilities and strategies. Our findings support functional organization of the PFC by cognitive control operations rather than by the type of processed information, indicating that modularity may be a fundamental architectural principle across the primate cortex.

neuroscience↗

bioRxiv2024

Exploring Anatomical Links Between the Crow's Nidopallium Caudolaterale and its Song System

Crows are corvid songbirds that exhibit remarkable cognitive control over their actions, including their vocalizations. They can learn to vocalize on command and the activity of single neurons from the crows associative telencephalic structure nidopallium caudolaterale (NCL) is correlated with the execution of this vocal and many non-vocal skilled behaviors. However, it remains unknown if specific anatomical adaptations that directly link the crow NCL to any of the nuclei of the crows "song system" exist. To address this issue, we used fluorescent tracers along with histological staining methods (Nissl-, myelin-, and anti tyrosine hydroxylase) to characterize the connectivity of the crows NCL in relation to its song system nuclei. We found that the NCL sends dense projections into the dorsal intermediate arcopallium (AID) directly adjacent to and engulfing the robust nucleus of the arcopallium (RA), which is the telencephalic motor output of the song system. Similarly, we demonstrate dense NCL projections into the striatum surrounding the basal ganglia song nucleus "area X". Both of these descending projections mirror the projections of the nidopallial song nucleus HVC (proper name) into RA and area X, with extremely sparse NCL fibers extending into area X. Furthermore, we characterized the distribution of cells projecting from the lateral part of the magnocellular nucleus of the anterior nidopallium (MAN) to NCL. Notably, a separate medial population of MAN cells projects to HVC. These two sets of connections--MAN to NCL and MAN to HVC--run in parallel but do not overlap. Taken together, our findings support the hypothesis that the NCL is part of a "general motor system" that parallels the song system but exhibits only minimal monosynaptic interconnections with it.

neuroscience↗

bioRxiv2023

The neurocellular implementation of representational geometry in primate prefrontal cortex

Modern neuroscience has seen the rise of a population-doctrine that represents cognitive variables using geometrical structures in activity space. Representational geometry does not, however, account for how individual neurons implement these representations. Here, leveraging the principle of sparse coding, we present a framework to dissect representational geometry into biologically interpretable components that retain links to single neurons. Applied to extracellular recordings from the primate prefrontal cortex in a working memory task with interference, the identified components revealed disentangled and sequential memory representations including the recovery of memory content after distraction, signals hidden to conventional analyses. Each component was contributed by small subpopulations of neurons with distinct electrophysiological properties and response dynamics. Modelling showed that such sparse implementations are supported by recurrently connected circuits as in prefrontal cortex. The perspective of neuronal implementation links representational geometries to their cellular constituents, providing mechanistic insights into how neural systems encode and process information.

neuroscience↗

bioRxiv2022

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) that have been central in many models of higher cognition. Because these models are based on mammalian data, they often implicitly assume a cortical organization. Higher associative regions of the brains of birds do not have cortical layering, yet these regions have neuronal single-cell correlates of higher cognition that are very similar to those found in mammals. Here we recorded LFP in the avian equivalent of prefrontal cortex while crows performed a highly controlled and cognitively demanding working memory task, adapted from monkeys. To further ensure that recordings reflected only cognitive processes detached from motor-related activities we trained and monitored the animals to keep their head still. We found signatures in local field potentials, modulated by working memory. Frequencies of a narrow gamma (30-59 Hz) and the beta band (13-19 Hz) contained information about the location of the target items on the screen 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 observed in monkeys. Such bursts are a vital part of 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. Relevance statementContemporary models of higher cognition, like those of working memory, often include temporal dynamics of neural activity such as gamma oscillations. Birds and mammals convergently evolved these cognitive functions and here we show that, despite the large evolutionary distance and largely different brain organization, crows share many of the oscillatory fingerprints reported in primates. This indicates that neural networks required for such LFP phenomena have evolved in parallel and may be critical to higher cognition.

neuroscience↗

bioRxiv2021

Working memory capacity of crows and monkeys arises from similar neuronal computations

Complex cognition relies on flexible working memory, which is severely limited in its capacity. The neuronal computations underlying these capacity limits have been extensively studied in humans and in monkeys, resulting in competing theoretical models. We probed the working memory capacity of crows (Corvus corone) in a change detection task, developed for monkeys (Macaca mulatta), while we performed extracellular recordings of the prefrontal-like area nidopallium caudolaterale. We found that neuronal encoding and maintenance of information were affected by item load, in a way that is virtually identical to results obtained from monkey prefrontal cortex. Contemporary neurophysiological models of working memory employ divisive normalization as an important mechanism that may result in the capacity limitation. As these models are usually conceptualized and tested in an exclusively mammalian context, it remains unclear if they fully capture a general concept of working memory or if they are restricted to the mammalian neocortex. Here we report that carrion crows and macaque monkeys share divisive normalization as a neuronal computation that is in line with mammalian models. This indicates that computational models of working memory developed in the mammalian cortex can also apply to non-cortical associative brain regions of birds.

neuroscience↗

bioRxiv2017

A random-matrix theory of the number sense

Number sense, a spontaneous ability to process approximate numbers, has been documented in human adults, infants and newborns, and many other animals. Species as distant as monkeys and crows exhibit number-selective neuronal activity. How number sense can emerge in the absence of learning or fine tuning is currently unknown. We introduce a random matrix theory of self-organised neural states where numbers are coded by vectors of activation across multiple units, and where the vector codes for successive integers are obtained through multiplication by a fixed but random matrix. This cortical implementation of the \"von Mises\" algorithm explains many otherwise disconnected observations ranging from neural tuning curves in monkeys to looking times in neonates and cortical numerotopy in adults. The theory clarifies the origin of Weber-Fechners law and yields a novel and empirically validated prediction of multi-peak number neurons. Random matrices constitute a novel mechanism for the emergence of brain states coding for quantity.

neuroscience↗