Cerebellar re-encoding of self-generated head movements

Abstract

Head movements are primarily sensed in a reference frame tied to the head, yet they 2 are used to calculate self-orientation relative to the world. This requires to re-encode head kinematic signals into a reference frame anchored to earth-centered landmarks 4 such as gravity, through computations whose neuronal substrate remains to be determined. Here, we studied the encoding of self-generated head movements in the 6 caudal cerebellar vermis, an area essential for graviceptive functions. We found that, contrarily to peripheral vestibular inputs, most Purkinje cells exhibited a mixed sen-8 sitivity to head rotational and gravitational information and were differentially modulated by active and passive movements. In a subpopulation of cells, this mixed sen-10 sitivity underlay a tuning to rotations about an axis defined relative to gravity. Therefore, we show that the caudal vermis hosts a re-encoded, gravitationally-polarized 12 representation of self-generated head kinematics.

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum during passive whole-body self-motion

“…This finding supports the hypothesis that the SS activity of Purkinje cells carries feedback signals derived from sensory prediction errors, a critical component of a dynamical control framework supporting optimal sensorimotor functions (15-20, 73, 74). The Kalman filter also predicts that feedback signals, and consequently the activity of tilt-and translation-selective cells, should be profoundly attenuated during active tilt and translation, similar to neuronal responses measured in the vestibular nuclei, fastigial nuclei, and cerebellar cortex (42,66,67,(67)(68)(69)(70)(71)75). In agreement with this prediction, one study (75) conducted when rats learn to balance on a swing indicates that Purkinje cells in various lobules (V to X) of the cerebellar vermis encode tilt velocity during external perturbations but not learned active movement.…”

“…The framework of internal models has been the dominant theory of vestibular processing in the past decades (22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) and is closely related to the framework used to model motor control and adaptation (54)(55)(56)(57)(58)(59)(60)(61)(62). Initially supported by behavioral studies using passive motion stimuli (34,(63)(64)(65), the implementation of internal models in central vestibular pathways has been confirmed by neurophysiological experiments of tilt/translation discrimination (35)(36)(37)(38)(39)(40)(41)(42)(43) and active head movements (66)(67)(68)(69)(70)(71)(72).…”

“…1B), thus responding identically to translational acceleration and tilt position (units are m/s 2 , or equivalently, degrees of tilt). Theoretical (22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) and experimental (34)(35)(36)(37)(38)(39)(40)(41)(42)(43) studies have demonstrated that the brain resolves this ambiguity by using head rotation signals, originating from the vestibular semicircular canals, to track head movements relative to vertical, from which the gravitational component (G) can be estimated.…”

Genetically eliminating Purkinje neuron GABAergic neurotransmission increases their response gain to vestibular motion

“…Although mice and macaques experience different head accelerations (22), their vestibular system shows similar properties (12,13,32,33). Previous studies have identified motion responsiveness in lobules IX-X of mice (34)(35)(36)(37), but none have employed controlled testing paradigms required to determine if cells were selectively responding to linear or gravity-reorienting motion. Our recordings have identified Purkinje neurons in mice, which display selective responses to tilt or translation (Fig.…”

Functional Alteration of Cerebello–Cerebral Coupling in an Experimental Mouse Model of Parkinson’s Disease

“…Head movements were recorded using a digital microelectromechanical sensor combining a linear 3D accelerometer and a 3D gyroscope (Ivensense, Mpu-9150). We used a custom printed circuit carrying the surface components (sensor, resistors and capacitors) and the power and data exchange wires (Dugue et al 2017). To communicate with the sensor, we use an I2C interface controlled via the USB port by a program in the LabVIEW software to synchronize the signal from the accelerometer with the electrophysiological system and optogenetic stimulations.…”