Browsing by Subject "Motor cortex"

Mice produce many ultrasonic vocalizations (USVs) in the 30 - 100 kHz range including pup isolation calls and adult male songs. These USVs are often used as behavioral readouts of internal states, to measure effects of social and pharmacological manipulations, and for behavioral phenotyping of mouse models for neuropsychiatric and neurodegenerative disorders; however, little is known about the biophysical and neurophysiological mechanisms of USV production in rodents. This lack of knowledge restricts the interpretation of data from vocalization-related experiments on mouse models of communication disorders and vocal medical conditions. Meanwhile, there has been increased interest in the social communication aspect of neural disorders such as autism, in addition to the common disorders involving motor control of the larynx: stroke, Parkinson's disease, laryngeal tremor, and spasmodic dysphonia. Therefore, it is timely and critical to begin assessing the neural substrate of vocal production in order to better understand the neuro-laryngeal deficits underlying communication problems.

Additionally, mouse models may generate new insight into the molecular basis of vocal learning. Traditionally, songbirds have been used as a model for speech learning in humans; however, the model is strongly limited by a lack of techniques for manipulating avian genetics. Accordingly, there has long been strong interest in finding a mammalian model for vocal learning studies. The characteristic features of accepted vocal learning species include programming of phonation by forebrain motor areas, a direct cortical projection to brainstem vocal motoneurons, and dependence on auditory feedback to develop and maintain vocalizations. Unfortunately, these features have not been observed in non-human primates or in birds that do not learn songs. Thus, in addition to elucidating vocal brain pathways it is also critical to determine the extent of any vocal learning capabilities present in the mouse USV system.

It is generally assumed that mice lack a forebrain system for vocal modification and that their USVs are innate; however, these basic assumptions have not been experimentally tested. I investigated the mouse song system to determine if male mouse song behavior and the supporting brain circuits resemble those of known vocal learning species. By visualizing activity-dependent immediate early gene expression as a marker of global activity patterns, I discovered that the song system includes motor cortex and striatal regions active during singing. Retrograde and anterograde tracing with pseudorabies virus and biodextran amines, respectively, revealed that the motor cortical region projects directly to the brainstem phonatory motor nucleus ambiguus. Chemical lesions in this region showed that it is not critical for producing innate templates of song syllables, but is required for producing more stereotyped acoustic features of syllables. To test for the basic components of adaptive learning I recorded the songs of mechanically and genetically deaf mice and found that male mice depend on auditory feedback to develop and maintain normal ultrasonic songs. Moreover, male mice that display natural strain specific song features may use auditory experience to copy the pitch of another strain when housed together and stimulated to compete sexually. I conclude that male mice have neuroanatomical and behavioral features thought to be unique to humans and song learning birds, suggesting that mice are capable of adaptive modification of the spectral features of their songs.

Traditionally, brain-machine interfaces (BMI) recorded from neurons in cerebral

cortical regions associated with voluntary motor control including primary motor

(M1), primary somatosensory (S1), and dorsal premotor (PMd) cortices. Wheelchair

BMI where users’ desired velocity commands are decoded from these cortical neu-

rons can be used to restored mobility for the severely paralyzed. In addition,

spatial information in these areas during navigation can potentially can incorpo-

rated to bolster BMI performance. However, the study of spatial representation

and navigation in the brain has traditionally been centered on the hippocampal

structures and the parietal cortex, with the majority of the studies conducted in

rodents. Under this classical model, S1, M1, and PMd would not contain allocen-

tric spatial information. In this dissertation I show that a significant number of

neurons in these brain areras do indeed represent body position and orientation

in space during brain-controlled wheelchair navigation.

First, I describe the design and implementation of the first intracortical BMI

for continuous wheelchair navigation. Two rhesus monkeys were chronically im-

planted with multichannel microelectrode arrays that allowed wireless recordings

from ensembles of premotor and sensorimotor cortical neurons. While monkeys

remained seated in the robotic wheelchair, passive navigation was employed to

train a linear decoder to extract wheelchair velocity from cortical activity. Next,

monkeys employed the wireless BMI to translate their cortical activity into the

ivwheelchair’s translational and rotational velocities. Over time, monkeys improved

their ability to navigate the wheelchair toward the location of a grape reward. The

presence of a cortical representation of the distance to reward location was also

detected during the wheelchair BMI operation. These resutls demonstrate that

intracranial BMIs have the potential to restore whole-body mobility to paralyzed

patients.

Second, building upon the finding of cortical representation of the distance

to reward location, I found that during wheelchair BMI navigation the discharge

rates of M1, S1, and PMd neurons correlated with the two-dimensional (2D) room

position and the direction of the wheelchair and the monkey head. The activities

of these cells were phenomenologically similar to place cells and head direction

(HD) cells found in rat hippocampus and entorhinal cortices. I observed 44.6%

and 33.3% of neurons encoding room position in the two monkeys, respectively,

and the overlapping populations of 41.0% and 16.0% neurons encoding head di-

rection. These observations suggest that primary sensorimotor and premotor cor-

tical areas in primates are likely involved in allocentrically representing body po-

sition in space during whole-body navigation, which is an unexpected finding

given the classical model of spatial processing that attributes the representation of

allocentric space to the hippocampal formations.

Finally, I found that allocentric representation of body position in space was

not clear during passive wheelchair navigation. Two rhesus monkeys were pas-

sively transported in an experimental space with different reward locations while

neuronal ensemble activities from M1 and PMd were recorded wirelessly. The ac-

tivities of the recorded cells did not clearly represent the position and direction

of the wheelchair. These results suggest active navigation might be a prerequisite

for primary sensorimotor and PMd participation in the allocentric representation

of space.

In summary, dorsal premotor and primary sensorimotor cortical correlates of

body position and orientation in space were found in rhesus monkeys during

the operation of an intracortical wheelchair BMI for navigation. These findings

contradict the classical dichotomy of localized spatial processing, support a dis-

tributed model of spatial processing in the primate brain, and suggest both con-

text and species differences are important in neural processing. The incorporation

of the allocentric spatial information present in these cortical areas during brain-

controlled wheelchair navigation can potentially improve future BMI navigation

performance.

Neural activities of the motor cortices have been traditionally known to represent motor information such as velocity of the movement and muscle force. Recent studies show that motor cortices, including primary motor cortex (M1), also represent non-traditional information such as observed movements of others and reward-related signal. However, how the neurons simultaneously multiplex such non-traditional information along with traditional motor parameters and whether the multiplexing leads to significant interactions are not well understood. Furthermore, understanding how the non-traditional information are encoded and they interact with motor information may help the development of more error-resistant, autonomous brain-to-machine interface and the understanding of underlying mechanism behind joint action and motor skill learning. In this dissertation, we investigate in detail how the observed movements and reward are simultaneously multiplexed along with traditional motor information and how each pair of neural representations interact with each other. First, regarding movement observation, we show that significant fraction of M1 neurons simultaneously encode the presence and direction of the movement of others along with those of self-movements. Neurons respond differently to joint action than to self-movements and show an interaction effect from the two representations of observed and executed movements rather than simple averaging of the two. Some neurons that separately encode observed and executed movements turn to suppress the representation of observed movements in joint action. In simultaneous actions, the representation of self-executed movement gets weaker, which suggests an interaction between two information and may possibly lead to behavioral interference. Preferred directions also change to be decoupled for noncongruent joint actions as to allow simultaneous multiplexing of both information with phase difference, while being synced for congruent ones. Conditional probabilities from the distribution of encoding neurons suggest a shared circuitry for movement observation, execution, and simultaneous actions. Shared circuitry with interactions between representations may explain why people can perform movements freely while watching others move; yet if the interaction between the two goes up due to simultaneous occurrence, it may result in interferences in behavior. Second, regarding the multiplexing of reward-related signal with movement signals, we show that both signals are multiplexed in individual and population neurons in M1 and S1. The activity of neural population in M1 and S1 distinguished whether the reward timing before the delivery of the reward. Furthermore, reward per se, reward anticipation, and reward prediction error (RPE) were encoded along with the motor information. The encoding of the reward-related signal interacted with the motor information in that the preferred direction changed when the reward was omitted. Change of spatial tuning of neurons due to reward prediction error signifies that there is interaction between the neural representation of reward and motor information, which may impact and underlie motor skill learning. In conclusion, both observed movements and reward are simultaneously multiplexed with traditional motor information. Co-representation of the two non-traditional information then leads to interaction between them and the motor information. Such interaction suggest that such simultaneous multiplexing may lead to behavioral interferences and motor skill learning.

Auditory sensations can arise from objects in our environment or from our own actions, such as when we speak or make music. We must able to distinguish such sources of sounds, as well as form new associations between our actions and the sounds they produce. The brain is thought to accomplish this by conveying copies of the motor command, termed corollary discharge signals, to auditory processing brain regions, where they can suppress the auditory consequences of our own actions. Despite the importance of such transformations in health and disease, little is known about the mechanisms underlying corollary discharge in the mammalian auditory system. Using a range of techniques to identify, monitor, and manipulate neuronal circuits, I characterized a synaptic and circuit basis for corollary discharge in the mouse auditory cortex. The major contribution of my studies was to identify and characterize a long-range projection from motor cortex that is responsible for suppressing auditory cortical output during movements by activating local inhibitory interneurons. I used similar techniques to understand how this circuit is embedded within a broader neuromodulatory brain network important for learning and plasticity. These findings characterize the synaptic and circuit mechanisms underlying corollary discharge in mammalian auditory cortex, as well as uncover a broad network interaction potentially used to pattern neural associations between our actions and the sounds they produce.