Biology subjects

Everling, S.

Publications and source records attributed to Everling, S..

4 recordsLinked to original sources

bioRxiv2018

Macaque anterior cingulate cortex deactivation impairs performance and alters lateral prefrontal oscillatory activities in a rule-switching task

In primates, both the dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (dlPFC) are key regions of the frontoparietal cognitive control network. To study the role of the dACC and its communication with the dlPFC in cognitive control, we recorded the local field potentials from the dlPFC before and during the reversible deactivation of the dACC, in macaque monkeys engaging in uncued switches between two stimulus-response rules. Cryogenic dACC deactivation impaired response accuracy during rule-maintenance, but not rule-switching, which coincided with a reduction in the correct-error difference in dlPFC beta activities specifically during maintenance of the more challenging rule. During both rule switching and maintenance, dACC deactivation prolonged the animals reaction time and reduced task-related theta/alpha activities in the dlPFC; it also weakened dlPFC theta-gamma phase-amplitude modulation. Thus, the dACC and its interaction with the dlPFC plays a critical role in the maintenance of a new, challenging rule.

neuroscience↗

bioRxiv2018

Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex

Reconstructing the anatomical pathways of the brain to study the human connectome has become an important endeavour for understanding brain function and dynamics. Reconstruction of the cortico-cortical connectivity matrix in vivo often relies on noninvasive diffusion-weighted imaging (DWI) techniques but the extent to which they can accurately represent the topological characteristics of structural connectomes remains unknown. We explored this question by constructing connectomes using DWI data collected from macaque monkeys in vivo and with data from published invasive tracer studies. We found the strength of fiber tracts was well estimated from DWI and topological properties like degree and modularity were captured by tractography-based connectomes. Rich-club/core-periphery type architecture could also be detected but the classification of hubs using betweenness centrality, participation coefficient and core-periphery identification techniques was inaccurate. Our findings indicate that certain aspects of cortical topology can be faithfully represented in noninvasively-obtained connectomes while other network analytic measures warrant cautionary interpretations.

neuroscience↗

bioRxiv2017

Methods for chair restraint and training of the common marmoset on oculomotor tasks

The oculomotor system is the most thoroughly understood sensorimotor system in the brain, due in large part to electrophysiological studies carried out in macaque monkeys trained to perform ocuolomotor tasks. A disadvantage of the macaque model is that many cortical oculomotor areas of interest lie within sulci, making high-density array and laminar recordings impractical. Further, many techniques of molecular biology developed in rodents, such as transgenic animals and optogenetic manipulation of neuronal subtypes, are limited in this species. The common marmoset (Callithrix jacchus) may potentially bridge the gap between systems neuroscience in macaques and molecular techniques, and additionally possesses a smooth cortex allowing easy access to frontoparietal oculomotor areas. To date, techniques for restraint and training of these animals to perform oculomotor tasks remain in an early stage of development. Here we provide details of a custom-designed chair for restraint of marmosets, a combination head restraint/recording chamber providing stability suitable for eye movement and neural recordings, and a training protocol for oculomotor tasks. As proof-of-principle, we report the results of a psychophysical study in marmosets trained to perform a saccade task using these methods, showing that, as in rhesus and humans, marmosets exhibit a \"gap effect\" - a decrease in reaction time when the fixation stimulus is removed prior to the onset of a visual saccade target. These results provide evidence that the common marmoset is a suitable model for neurophysiogical investigations of oculomotor control.\n\nNEW AND NOTEWORTHYThe ability to carry out neuronal recordings in behaving primates has provided a wealth of information regarding the neural circuits underlying the control of eye movements. Such studies require restraint of the animal within a primate chair, head fixation, methods of acclimating the animals to this restraint, and the use of operant conditioning methods for training on oculomotor tasks. In contrast to the macaque model, relatively few studies have reported in detail methods for use in the common marmoset. Here we detail custom-designed equipment and methods by which we have used to successfully train head-restrained marmosets to perform basic oculomotor tasks.

neuroscience↗

bioRxiv2017

An open resource for nonhuman primate imaging

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience.\n\nUnfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

neuroscience↗