Publications related to Sensory nervous system

Task-driven hierarchical deep neural network models of the proprioceptive pathway

Pranav Mamidanna, Mackenzie Mathis, Alexander Mathis, Kai Jappe Sandbrink

Biological motor control is versatile and efficient. Muscles are flexible and undergo continuous changes requiring distributed adaptive control mechanisms. How proprioception solves this problem in the brain is unknown. Here we pursue a task-driven modeling approach that has provided important insights into other sensory systems. However, unlike for vision and audition where large annotated datasets of raw images or sound are readily available, data of relevant proprioceptive stimuli are not. We generated a large-scale dataset of human arm trajectories as the hand is tracing the alphabet in 3D space, then using a musculoskeletal model derived the spindle firing rates during these movements. We propose an action recognition task that allows training of hierarchical models to classify the character identity from the spindle firing patterns. Artificial neural networks could robustly solve this task, and the networks’ units show directional movement tuning akin to neurons in the primate somatosensory cortex. The same architectures with random weights also show similar kinematic feature tuning but do not reproduce the diversity of preferred directional tuning nor do they have invariant tuning across 3D space. Taken together our model is the first to link tuning properties in the proprioceptive system to the behavioral level.

Neuroscience2020

Selective electrical and optical neuromodulation of the central nervous system with conformable microfabricated implants

Amélie Anne Guex

Neuroprosthetic systems are designed to interface with the nervous system, for the replacement or restoration of damaged functions in the motor and/or sensory systems. In order to have an efficient communication with the nervous tissue leading to optimized clinical outcomes, achieving neural stimulation with high selectivity is essential. This thesis aims at finding technological routes to enable spatial, structural and cell-type selective surface neuromodulation using electrical and optogenetic stimulation and to validate them in in vivo models. Thin and conformable electrode arrays enable close contact with the target tissue, thereby leading to minimal distances with the target neurons and maximal spatial selectivity. Flexible polymer technologies based on polyimide (PI) are used to design thin (< 10 ÎŒm thick) electrode arrays with small feature size (< 100 ÎŒm), resulting in miniaturized conformable arrays for surface stimulation. PEDOT conducting polymer coatings are used on the miniaturized electrical stimulation sites (100 ÎŒm diameter) to improve their charge injection properties. This implant is used for auditory brainstem stimulation in a rat model, and is shown to generate robust activation of the auditory system. Analysis of the multiunit recordings obtained from the inferior colliculus (IC), an auditory structure of the midbrain, led to the identification of different phases in the responses, with various frequency tuning properties. The stimulation configuration is shown to influence the tonotopic organisation of the frequency-tuned responses. Bipolar stimulation with small interelectrode distances (400 ÎŒm) is shown to generate responses that are more frequency-selective than with larger interelectrode distances (800 ÎŒm). The orientation of the electrode pair and the waveformof stimulation current are also shown to influence the response properties. An updated design of the clinical auditory brainstem implant(ABI) is then proposed, integrating higher electrode density and guidelines for a more tissue-conformal format. The main steps in the road towards improvement of ABI outcomes are then discussed, with proposed changes in the stimulation protocol and electrode array in parallel. Another approach to cell-specific neuromodulation is the implementation of optogenetics. This requires not only genetic engineering of the neurons but also the manufacturing of implantable light-emitting devices. Here, we introduce a fabrication process for the integration of thin (50 ÎŒm) LEDs into a polyimide-based device. A proof-of-concept in vivo study shows that stimulation of the spinal cord of a mouse model generates robust EMG responses in both legs over the course of several weeks. The walking integrity is confirmed, showing the absence of functional damages to the spinal cord. These results show that the presented LED array can provide a way of stimulating key elements of the locomotor neural circuitry, potentially leading to a greater understanding of the role of each neuronal subtypes in the spinal cord. Through the applications of ABI and spinal cord stimulation, this thesis thus highlights the importance and potential use of specifically tailored technologies enabling selective surface stimulation of the nervous system.

EPFL2017

A Whisker Stimulator For Sensory System Research

Reymond Clavel, Raphael Holzer, Madeleine Kägi

L'outil, le "whisker stimulator" doit permettre de simuler les mouvements naturels des moustaches tout en mesurant simultanément l'activité cérébrale de la souris. Le cahier de charges demande un stimulateur pouvant faire une impulsion de 100um de déplacement à 1kHz. Dans le cadre de ce travail, différentes solutions sont recherchées. Le choix de l'actionneur est un piézotube à quatre segments.

2005

Motor state transitions and Breathing in Brain Machine Interfaces

Bastien Orset

Brain-Machine interfaces aim to create a direct neural link between user's brain and machines. This goal has pushed scientists to investigate a large spectrum of applications in the realm of assistive and rehabilitation technologies. However, despite great progress, the possibility of being in full control of a device with our brain is still far to be reached. One of the primary limitations of BMIs is the notion of self-paced control, which states that a user should be able to activate or deactivate such interface by mere modulation of brain activity. Many studies have investigated this question, focusing notably on the use of endogenous signals (such as Event-Related Desynchronization/Synchronization, ERD/S) to control the activation of these interfaces in natural interaction scenarios. This question is, however, largely ignored when looking at their interruption. Hence, in this first part of the thesis, my work was devoted to investigate how a BMI user would be able to control the interruption of non-invasive BMIs based on Motor Imagery (MI), a paradigm promoting natural and endogenous signals that can be used for BMI control. I investigated the decoding of motor termination as well as its correlates characterized by the post-movement ERS phenomenon. Specifically, this part of the thesis aimed to study (i) the feasibility to decode motor termination from a specific neural correlate as well as the adaptation from the user in closed-loop scenarios, (ii) the benefits of using motor termination correlates to detect the stopping process, and (iii) the effect of BMI effectors such as an exoskeleton on the detection of motor termination correlates. The obtained results provide new insights into closed-loop decoding of motor termination. In particular, I show that BMI users exhibit an adaptation of their EEG correlates enabling them to have a reliable control when switching off a BMI in closed-loop scenarios. Second, I show that the decoding of motor termination is a particular process different from a resting state and, hence, should be decoded independently so as to achieve a faster and more robust detection. Finally, I investigate the use of BMI effectors with respect to the decoding of motor termination showing an effect of the effectors on the correlates of motor termination. However, due to the nature of these correlates, motor termination can still be reliably decoded with a similar latency. In the second part of my thesis, I also investigate how the interoceptive system affects BMI and particularly how breathing signals affect BMI based on MI. Breathing has been shown to have a key effect on numerous human functions, including, perceptual, cognitive and motor functions. However, currently not much is known about the role of respiratory signals in BMI and such signals have rather been considered as physiological noise. In my thesis, I evaluated how the breathing process affects the correlates of MI (ERD in mu and beta bands) as well as actual BMI performance. The results provide an extensive analysis regarding the effect of the breathing cycle specifically on mu-ERDs, showing stronger ERD during the late expiration phase. Moreover, I identified a link between breathing and BMI performance and propose that breathing signals are a valuable predictor for BMI performance highlighting the importance of monitoring such signals and, more generally, present the interoceptive system as a key component of motor preparation and motor imagery

EPFL2021

Uncovering the neural encoding of behavior in the adult Drosophila motor system

Chin-Lin Chen

One of the most important goals in neuroscience research has always been to understand how animals control their behavior. However, the long focus on the role of brain neurons in behavioral control might be missing the full story. In fact, brain-wide fluctuations in neural activity are highly correlated to the behavioral state, suggesting a closed-loop system where the behavioral command and the body state interact to interpret sensory inputs and dynamically guide action selection. However, to date, little is known about how and where information about the behavioral state is generated. In principle, information about the behavioral state is a relatively high-level encoding of the body state derived from the integration of signals from primary sensors and the local network. Local motor circuits residing in the spinal cord of mammals or the ventral nerve cord (VNC) of insects may give rise to the behavioral state and pass to the brain via brain-projecting interneurons---termed ascending neurons (ANs). However, what information ANs carry and where this information originates is still a mystery due to the technical challenges in measuring these signals in behaving animals. Therefore, it is critical to develop tools to track neuron identity and record neuronal activity during behavior to crack the functional network. In this work, a method is introduced for imaging the motor circuit in the VNC of Drosophila melanogaster. This preparation demonstrates how to retain fly limb function after dissection and allows simultaneous recording of a tethered fly's behavior and its neural activity in the VNC. Incorporating this methodology with other approaches can verify the conclusions from the experiments such as those manipulating neuronal excitability, and motivate further investigation into neuronal function in specific types of behavior. Since it has long been theorized that ANs are the cellular basis of the behavioral state information sent in the brain, the technique introduced in this work was designed to resolve questions relating to what type of information ANs convey. Here, a large-scale functional screen was performed to relate neural activity, behavior, and neuronal morphology for 247 genetically identified ANs in the adult fly. This is the first large-scale screen of neural activity in a behaving animal, and this work uncovered three fundamental features of AN populations. First, rather than low-level limb movements, ANs encode high-level behaviors like walking, grooming, and resting. Second, ANs project nearly exclusively to an integrative sensory center (AVLP) and an action selection hub (GNG). Remarkably, the encodings projected to these distinct areas reflect their potential roles in contextualizing sensory cues (AVLP) and guiding future actions (GNG). Third, the behavioral encodings of ANs are closely linked to their motor system patterning. In conclusion, this work provides an indispensable tool to study the motor system beyond the brain network by overcoming a major technical barrier in in-vivo recording of the VNC of a behaving fly. This tool was used to help resolve what is encoded by ANs as a higher-level behavioral state, suggesting that the primary cellular origin of the behavioral information that is used to modulate brain function comes from the VNC. Overall, the technique and the findings on AN encoding should inspire follow-up studies to uncover additional neural mechanisms used in adaptive behavior generation.

EPFL2022

In the mouse whisker system, sensory information is relayed to the whisker somatosensory cortex by two major thalamic nuclei, the ventral posterior medial nucleus (VPM) and the posterior medial nucleus (POM). While the cortical axonal innervation pattern of these two nuclei has been studied anatomically in some detail, their synaptic input to distinct cell-types across different layers in barrel cortex is incompletely understood. I used the specificity of optogenetics to selectively stimulate axons from VPM or POM, and I measured the evoked excitatory postsynaptic potentials in vitro with whole-cell patch-clamp recordings in primary whisker somatosensory cortex (wS1). VPM or POM was infected in vivo with an adenoassociated virus (AAV) encoding the light-gated cation channel channelrhodopsin (ChR2). Synaptic input onto individual neurons of the barrel cortex was recorded in brain slices in vitro by activating the ChR2-expressing thalamic axons with blue light. I measured thalamic inputs onto excitatory and three distinct classes of GABAergic neurons, expressing Parvalbumin (PV), somatostatin (SST) or vasoactive intestinal peptide (VIP) neurons across all layers of the barrel cortex. In excitatory and PV neurons, I found that the biggest inputs appeared to largely colocalize with the anatomical innervation pattern Anatomically, VPM preferentially innervates layer4 (L4), deep L3 and the L5B/6A border, and, functionally, we found that the biggest input was observed in L4, followed by L3. Anatomically, POM innervates L5A and L1, and, functionally, I found the biggest input in L5A. SST neurons received very weak input from both thalamic nuclei. VIP neurons on the other hand received larger inputs than SST neurons, however, they were weaker than excitatory and PV neurons. POM is considered to have both first-order and higher-order properties and I, therefore, began to investigate connectivity within sub-parts of POM. Taking advantage of a recently developed anterograde transsynaptic AAV injected into somatosensory brainstem nuclei, I defined first-order and higher-order sub-nuclei of POM and investigated their functional connectivity with somatosensory cortex. Anatomically, the first-order POM preferentially innervates L4 of the secondary somatosensory cortex (wS2) and functionally, I found that neurons across many layers in wS2 received direct synaptic input from first-order POM. Higher-order POM innervates both wS2 and wS1, and I found that neurons in wS2 also receive direct synaptic input. The data suggest that first-order POM relays sensory information to wS2, apparently in a parallel signaling pathway to the classical VPM to wS1 sensory pathway. In contrast, higher order POM does not appear to receive direct sensory input from the brainstem Our results begin to provide a more complete understanding of the distribution of thalamic input to specific cell-types across the layers of the mouse somatosensory cortex

EPFL2018

Membrane potential correlates of sensory perception in mouse barrel cortex

Yves Kremer, Alexandros Kyriakatos, Carl Petersen, Shankar Sachidhanandam, Varun Sreenivasan

Neocortical activity can evoke sensory percepts, but the cellular mechanisms remain poorly understood. We trained mice to detect single brief whisker stimuli and report perceived stimuli by licking to obtain a reward. Pharmacological inactivation and optogenetic stimulation demonstrated a causal role for the primary somatosensory barrel cortex. Whole-cell recordings from barrel cortex neurons revealed membrane potential correlates of sensory perception. Sensory responses depended strongly on prestimulus cortical state, but both slow-wave and desynchronized cortical states were compatible with task performance. Whisker deflection evoked an early (

Nature Publishing Group2013

Motor control by sensory cortex

Rachel Aronoff, Fred Marbach, Céline Matéo, Ferenc Mátyás, Carl Petersen, Varun Sreenivasan, Catherine Wacongne

Classical studies of mammalian movement control define a prominent role for the primary motor cortex. Investigating the mouse whisker system, we found an additional and equally direct pathway for cortical motor control driven by the primary somatosensory cortex. Whereas activity in primary motor cortex directly evokes exploratory whisker protraction, primary somatosensory cortex directly drives whisker retraction, providing a rapid negative feedback signal for sensorimotor integration. Motor control by sensory cortex suggests the need to reevaluate the functional organization of cortical maps.

2010

The olfactory system, like other sensory systems, can detect specific stimuli of interest amidst complex, varying backgrounds. To gain insight into the neural mechanisms underlying this ability, we imaged responses of mouse olfactory bulb glomeruli to mixtures. We used this data to build a model of mixture responses that incorporated nonlinear interactions and trial-to-trial variability and explored potential decoding mechanisms that can mimic mouse performance when given glomerular responses as input. We find that a linear decoder with sparse weights could match mouse performance using just a small subset of the glomeruli (∼15). However, when such a decoder is trained only with single odors, it generalizes poorly to mixture stimuli due to nonlinear mixture responses. We show that mice similarly fail to generalize, suggesting that they learn this segregation task discriminatively by adjusting task-specific decision boundaries without taking advantage of a demixed representation of odors.

2016

Neuroprosthetics to support impaired hand functions: A multidisciplinary approach combining brain-machine interfaces and wearable exoskeletons

Luca Randazzo

Neuroprosthetics, the discipline that aims at interfacing neural systems to artificially engineered devices, has witnessed in recent years important advancements towards the ultimate goal of augmenting and restoring human functions through technology and artificial systems. Research in this field covers a wide range of efforts, from advancing our basic understanding of the neural processes involved into human sensory, motor and cognitive functions, to developing artificial intelligence algorithms for their decoding, to the physical interfacing between artificial devices and the human nervous system and biomechanics. Ultimately, this discipline aims at fusing these systems in order to restore, replace and rehabilitate lost and impaired functions due to motor disabling conditions or traumatic accidents. In this thesis, I present a multidisciplinary approach that aimed at developing a neuroprosthesis for the assistance and restoration of hand functions impaired by neurological disorders or traumatic accidents, such as cerebrovascular accidents and spinal cord injuries. These efforts encompassed the conceptualization and development of a robotic hand exoskeleton and brain-machine interface (BMI) algorithms for its control. Specifically, this thesis focused on the design, development and testing of (i) a novel mechatronic hand exoskeleton to assist hand motions within domestic and clinical settings, (ii) non-invasive BMI approaches based on electroencephalography (EEG) to decode neural correlates of intended hand movements, and on (iii) the closed-loop integration of the proposed exoskeleton and BMI for the sake of providing continuous feedback about ongoing neural modulations through hand motions and to trigger sensorimotor rehabilitation within clinical scenarios. Results showed that the proposed mechatronic system can successfully control hand opening and closing within a fully wearable, portable and lightweight package. The system was tested with users who suffered from motor disabling impairments, showing that it could help them in performing several activities of daily living for the first time since their accidents. From a brain-machine interfacing perspective, this work shows how imagined hand movements can be decoded, through EEG, in parallel with exoskeleton-induced motions, with important implications for the development of more embodied human-machine interaction protocols. Finally, this work shows how the closed-loop control of exoskeleton motions by means of the decoded ongoing neural activity enhances the discriminability of sensorimotor neural patterns and improves the performance of the brain-machine control channel. Overall, the results presented here represent important advancements within the field of neuroprosthetics, with interesting implications for the development of assistive exoskeletal technologies and non-invasive brain-machine interfaces aimed at controlling such systems in clinical or domestic settings, for both assistive and neurorehabilitative purposes.

EPFL2018