Biology subjects

Grillner, S.

Publications and source records attributed to Grillner, S..

4 recordsLinked to original sources

bioRxiv2024

Motor cortex directly excites the output nucleus of the basal ganglia, the substantia nigra pars reticulata.

Inhibitory neurons of the substantia nigra pars reticulata (SNr) serve as a primary output through which the basal ganglia regulate behaviour. Projections to the SNr from beyond the basal ganglia have also been identified anatomically. Using a virally-targeted optogenetic approach, combined with whole cell patch-clamp recordings of SNr neurons in acute brain slices, we show that projection neurons of the primary and secondary motor cortices (M1 and M2) make functional excitatory synapses with subpopulations of inhibitory SNr neurons. Furthermore, we demonstrate that photostimulation of these cortical axon terminals increases SNr neuron firing rate. To further investigate the spatial organisation of cortical input to SNr, we employed a transsynaptic viral-labelling approach to identify SNr neurons receiving monosynaptic input from M1 and M2. We found a topographical relationship between motor cortex and SNr, and identified downstream targets of cortical-recipient SNr subpopulations. These findings reveal functional pathways by which M1 and M2 can directly modulate basal ganglia output to different downstream targets.

neuroscience↗

bioRxiv2023

A multiscale model of striatum microcircuit dynamics

The striatum is the largest structure in the basal ganglia, and is known for its key role in functions such as learning and motor control. Studying these aspects requires investigating cellular/microcircuits mechanisms, in particular related to learning, and how these small-scale mechanisms affect large-scale behavior, and its interactions with other structures, such as the cerebral cortex. In this paper, we provide a multiscale approach to investigate these aspects. We first investigate striatum dynamics using spiking networks, and derive a mean-field model that captures these dynamics. We start with a brief introduction to the microcircuit of the striatum and we describe, step by step, the construction of a spiking network model, and its mean-field, for this area. The models include explicitly the different cell types and their intrinsic electrophysiological properties, and the synaptic receptors implicated in their recurrent interactions. Then we test the mean-field model by analyzing the response of the striatum network to the main brain rhythms observed experimentally, and compare this response to that predicted by the mean-field. We next study the effects of dopamine, a key neuromodulator in the basal ganglia, on striatal neurons. Integrating dopamine receptors in the spiking network model leads to emerging dynamics, which are also seen in the mean-field model. Finally, we introduce a basic implementation of reinforcement learning (one of the main known functions of the basal-ganglia) using the mean-field model of the striatum microcircuit. In conclusion, we provide a multiscale study of the striatum microcircuits and mean-field, that capture its response to periodic inputs, the effect of dopamine and can be used in reinforcement learning paradigms. Given that several mean-field models have been previously proposed for the cerebral cortex, the mean-field model presented here should be a key tool to investigate large-scale interactions between basal ganglia and cerebral cortex, for example in motor learning paradigms, and to integrate it in large scale and whole-brain simulations.

neuroscience↗

bioRxiv2022

A GPU-based computational framework that bridges Neuron simulation and Artificial Intelligence

Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs at 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience and AI tasks. We investigated how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines; and examined how dendrites protect morphologically detailed neural networks against adversarial attacks in typical image classification tasks.

neuroscience↗

bioRxiv2021

Visuo-vestibular gaze control - conserved subcortical processing

Gaze stabilization compensates for movements of the head or external environment to minimize image blurring, which is critical for visually-guided behaviors. Multisensory information is used to stabilize the visual scene on the retina via the vestibulo-ocular (VOR) and optokinetic (OKR) reflexes. While the organization of neuronal circuits underlying VOR is well described across vertebrates, less is known about the contribution and evolutionary origin of the OKR circuits. Moreover, the integration of these two sensory modalities is still poorly understood. Here, we developed a novel experimental model, the isolated lamprey eye-brain-labyrinth preparation, to analyze the neuronal pathways underlying visuo-vestibular integration which allowed electrophysiological recordings while applying vestibular stimulation using a moving platform, coordinated with visual stimulation via two screens. We show that lampreys exhibit robust visuo-vestibular integration, with optokinetic information processed in the pretectum and integrated with vestibular inputs at several subcortical levels. The enhanced eye movement response to multimodal stimulation favored the vestibular response at increased velocities. The optokinetic signals can be downregulated from tectum. Additionally, saccades are present in the form of nystagmus. The lamprey represents the oldest living group of vertebrates, thus all basic components of the visuo-vestibular control of gaze were present already at the dawn of vertebrate evolution.

neuroscience↗