scholarly journals Sensory feedback can give rise to neural rotations

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Omid G Sani ◽  
Maryam M Shanechi

Investigating how an artificial network of neurons controls a simulated arm suggests that rotational patterns of activity in the motor cortex may rely on sensory feedback from the moving limb.

Neuron ◽  
2018 ◽  
Vol 99 (5) ◽  
pp. 1040-1054.e5 ◽  
Author(s):  
Matthias Heindorf ◽  
Silvia Arber ◽  
Georg B. Keller

Neuron ◽  
2017 ◽  
Vol 93 (4) ◽  
pp. 929-939.e6 ◽  
Author(s):  
Mario Prsa ◽  
Gregorio L. Galiñanes ◽  
Daniel Huber

2017 ◽  
Vol 118 (3) ◽  
pp. 1828-1848 ◽  
Author(s):  
Mohsen Omrani ◽  
Matthew T. Kaufman ◽  
Nicholas G. Hatsopoulos ◽  
Paul D. Cheney

Primary motor cortex has been studied for more than a century, yet a consensus on its functional contribution to movement control is still out of reach. In particular, there remains controversy as to the level of control produced by motor cortex (“low-level” movement dynamics vs. “high-level” movement kinematics) and the role of sensory feedback. In this review, we present different perspectives on the two following questions: What does activity in motor cortex reflect? and How do planned motor commands interact with incoming sensory feedback during movement? The four authors each present their independent views on how they think the primary motor cortex (M1) controls movement. At the end, we present a dialogue in which the authors synthesize their views and suggest possibilities for moving the field forward. While there is not yet a consensus on the role of M1 or sensory feedback in the control of upper limb movements, such dialogues are essential to take us closer to one.


2020 ◽  
Author(s):  
Hari Teja Kalidindi ◽  
Kevin P. Cross ◽  
Timothy P. Lillicrap ◽  
Mohsen Omrani ◽  
Egidio Falotico ◽  
...  

SummaryRecent studies hypothesize that motor cortical (MC) dynamics are generated largely through its recurrent connections based on observations that MC activity exhibits rotational structure. However, behavioural and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback about the limb. Networks were trained to counteract perturbations to the limb and to reach towards spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may reflect dynamics throughout voluntary motor circuits involved in online control of motor actions.HighlightsNeural networks with sensory feedback generate rotational dynamics during simulated posture and reaching tasksRotational dynamics are observed even without recurrent connections in the networkSimilar dynamics are observed not only in motor cortex, but also in somatosensory cortex of non-huma n primates as well as sensory feedback signalsResults highlight rotational dynamics may reflect internal dynamics, external inputs or any combination of the two.


2021 ◽  
Author(s):  
Kevin Patrick Cross ◽  
Douglas J Cook ◽  
Stephen H Scott

An important aspect of motor function is our ability to rapidly generate goal-directed corrections for disturbances to the limb or behavioural goal. Primary motor cortex (M1) is a key region involved in feedback processing, yet we know little about how different sources of feedback are processed by M1. We examined feedback-related activity in M1 to compare how different sources (visual versus proprioceptive) and types of information (limb versus goal) are represented. We found sensory feedback had a broad influence on M1 activity with ~73% of neurons responding to at least one of the feedback sources. Information was also organized such that limb and goal feedback targeted the same neurons and evoked similar responses at the single-neuron and population levels indicating a strong convergence of feedback sources in M1.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Hari Teja Kalidindi ◽  
Kevin P Cross ◽  
Timothy P Lillicrap ◽  
Mohsen Omrani ◽  
Egidio Falotico ◽  
...  

Recent studies have identified rotational dynamics in motor cortex (MC) which many assume arise from intrinsic connections in MC. However, behavioural and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback from the limb. Networks were trained to counteract perturbations to the limb and to reach towards spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may also reflect dynamics throughout the voluntary motor system involved in online control of motor actions.


2019 ◽  
Author(s):  
PD Ganzer ◽  
SC Colachis ◽  
MA Schwemmer ◽  
DA Friedenberg ◽  
CE Swiftney ◽  
...  

AbstractBackgroundThe sense of touch is a key component of motor function. Severe spinal cord injury (SCI) should essentially eliminate sensory information transmission to the brain, that originates from skin innervated from below the lesion. We assessed the hypothesis that, following SCI, residual hand sensory information is transmitted to the brain, can be decoded amongst competing sensorimotor signals, and used to enhance the sense of touch via an intracortically controlled closed-loop brain-computer interface (BCI) system.MethodsExperiments were performed with a participant who has an AIS-A C5 SCI and an intracortical recording array implanted in left primary motor cortex (M1). Sensory stimulation and standard clinical sensorimotor functional assessments were used throughout a series of several mechanistic experiments.FindingsOur results demonstrate that residual afferent hand sensory signals surprisingly reach human primary motor cortex and can be simultaneously demultiplexed from ongoing efferent motor intention, enabling closed-loop sensory feedback during brain-computer interface (BCI) operation. The closed-loop sensory feedback system was able to detect residual sensory signals from up to the C8 spinal level. Using the closed-loop sensory feedback system enabled significantly enhanced object touch detection, sense of agency, movement speed, and other sensorimotor functions.InterpretationTo our knowledge, this is the first demonstration of simultaneously decoding multiplexed afferent and efferent activity from human cortex to control multiple assistive devices, constituting a ‘sensorimotor demultiplexing’ BCI. Overall, our results support the hypothesis that sub-perceptual neural signals can be decoded reliably and transformed to conscious perception, significantly augmenting function.FundingInternal funding was provided for this study from Battelle Memorial Institute and The Ohio State University Center for Neuromodulation.


2021 ◽  
Vol 14 (6) ◽  
pp. 1723
Author(s):  
Angela Radetz ◽  
Umair Hassan ◽  
Rathiga Varatheeswaran ◽  
Stefanie Henauer ◽  
Paul Lang ◽  
...  

2021 ◽  
Author(s):  
Michael Elbaz ◽  
Maxime Demers ◽  
David Kleinfeld ◽  
Christian Ethier ◽  
Martin Deschenes

Whether using our eyes or our hands, we interact with our environment through mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability and prehension would be profoundly impeded. The nervous system may be informed about the position of a sensory organ via two complementary feedback mechanisms: peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training rats to place their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, even in the absence of peripheral reafference. On the other hand, the red nucleus, which receives descending inputs from motor cortex and the cerebellum and projects to facial motoneurons, is critical for the execution of the vibrissa task. All told, our results demonstrate the existence of an open-loop control by an internal model that is sufficient to drive voluntary motion. The internal model is independent of motor cortex and likely contains the cerebellum and associated nuclei.


Neuron ◽  
2019 ◽  
Vol 101 (6) ◽  
pp. 1202 ◽  
Author(s):  
Matthias Heindorf ◽  
Silvia Arber ◽  
Georg B. Keller

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