Genetic dissection of circuits underlying the modular structure of the Superior Colliculus

In order to successfully interact with the environment, animals need to produce accurate movements towards specific positions in space. A crucial region of the brain that guides such goal-oriented movements is the superior colliculus (SC), an evolutionary conserved structure of the midbrain. While several lines of research in different model organisms have confirmed that the SC contributes to the initiation of orienting movements, how functionally distinct neuronal groups within the SC are organized to support the production of such motor outputs is poorly understood. One of the reasons why the intrinsic circuit organization of the SC remains elusive is the lack of genetic characterization of the neuronal populations of the motor SC. Here, we performed RNAseq to screen for genetic markers for neuronal subpopulations in the motor SC. We identified a transcription factor, Pitx2, which is exclusively expressed in a subpopulation of glutamatergic neurons in the motor domain of the SC. Strikingly, this population of neurons displays a non-homogenous distribution within the motor layer of the SC, being organised in clusters along the mediolateral and anteroposterior axis. We mapped the pre-synaptic network and the post-synaptic targets of Pitx2ON neurons, unveiling that this modular population receives direct inputs from motor and sensory cortical regions, as well as several midbrain nuclei involved in movement control, and sends projection along the cephalomotor pathway. We then asked whether these modules may act as functional units, each integrating multimodal sensory information and encoding a specific feature of head movement, the main ethologically relevant orienting behaviour in rodents. Optogenetic activation of this modular population in freely moving animals produced a stereotyped, robust head motion characterised by a pronounced quantal nature; furthermore, the amplitude of the elicited head movement varied based on the modular unit activated. Our results suggest that distinct clusters of genetically defined neurons produce head displacement along a characteristic vector. In conclusion, we found that a population of premotor neurons in the SC is organised in a modular conformation and we suggest that such modularity may represent a physical implementation of a discontinuous motor map for orienting movements encoded in the mouse SC. Our work complements previous observations of periodicity in SC circuitry, as well as its afferent and efferent systems. Exploiting the genetic toolkit available in the mouse, our work begins to address the functional relevance of this modularity and paves the way for future experiments to investigate principles of sensorimotor integration in SC circuits.MR

Rhythmic Action Synchronizes Memory Replay During Reinforcement Learning

Our cognitive abilities - learning from the past, sensing the current environment, planning into the future, executing an action, and infusing value into an experience - all rely on precisely timed and widespread electrical communications across neural networks. The brain’s hippocampal formation receives multimodal input, forges episodic associations, and predicts future state. Oscillating electrical bursts originating from the hippocampus, termed ‘sharp-wave ripples’ (SWR), often contain patterns of previously expressed neural spike sequences, and are necessary for certain forms of learning and memory. The discharge of SWR-replay resonates in remote parts of the brain and displays specific characteristics depending on a subject’s state of awareness and sensory context. In the sleep state, when motoric repertoire is limited, waves of breathing synchronize neural activity in several regions of the brain, including SWRs of the hippocampus. During active sensation of the awake state, cyclic licking dynamically entrains taste-reward networks in subcortical and cortical areas throughout learning. However, the neural correlates linking oromotor movements in the active learning state to the memory system of the hippocampal formation have not yet been established. Given the recurrence of SWR-replay during rhythmic ingestion of reinforcement learning and the hierarchical coupling of orofacial behaviors, we hypothesized that repeated licking could provide the oscillatory framework to synchronize memory reactivation during active learning. We approach this question with new technology development to track licking events at a reward port (P-event) during behavior on a spatial alternation task. Additionally, we developed a modular brain implant to simultaneously record from hippocampal area CA1 and medial entorhinal cortex (MEC) - interconnected brain regions that are crucial to episodic memory processing. Along with the co-modulation of individual neurons by licking and SWRs, we provide the first evidence that SWRs detected in dorsal CA1 synchronize with the phase of P-event cycle during learning. Furthermore, we confirmed that SWRs occurring during licking bouts contain neural reactivation of active navigation and trigger enhanced ripple-frequency power in downstream MEC. These results connect movement with memory and may assist in addressing abnormal ingestion behaviors that negatively affect mental or physical healt

Gamma Band Oscillation Response to Somatosensory Feedback Stimulation Schemes Constructed on Basis of Biphasic Neural Touch Representation

abstract: Prosthetic users abandon devices due to difficulties performing tasks without proper graded or interpretable feedback. The inability to adequately detect and correct error of the device leads to failure and frustration. In advanced prostheses, peripheral nerve stimulation can be used to deliver sensations, but standard schemes used in sensorized prosthetic systems induce percepts inconsistent with natural sensations, providing limited benefit. Recent uses of time varying stimulation strategies appear to produce more practical sensations, but without a clear path to pursue improvements. This dissertation examines the use of physiologically based stimulation strategies to elicit sensations that are more readily interpretable. A psychophysical experiment designed to investigate sensitivities to the discrimination of perturbation direction within precision grip suggests that perception is biomechanically referenced: increased sensitivities along the ulnar-radial axis align with potential anisotropic deformation of the finger pad, indicating somatosensation uses internal information rather than environmental. Contact-site and direction dependent deformation of the finger pad activates complimentary fast adapting and slow adapting mechanoreceptors, exhibiting parallel activity of the two associate temporal patterns: static and dynamic. The spectrum of temporal activity seen in somatosensory cortex can be explained by a combined representation of these distinct response dynamics, a phenomenon referred in this dissertation to “biphasic representation.” In a reach-to-precision-grasp task, neurons in somatosensory cortex were found to possess biphasic firing patterns in their responses to texture, orientation, and movement. Sensitivities seem to align with variable deformation and mechanoreceptor activity: movement and smooth texture responses align with potential fast adapting activation, non-movement and coarse texture responses align with potential increased slow adapting activation, and responses to orientation are conceptually consistent with coding of tangential load. Using evidence of biphasic representations’ association with perceptual priorities, gamma band phase locking is used to compare responses to peripheral nerve stimulation patterns and mechanical stimulation. Vibrotactile and punctate mechanical stimuli are used to represent the practical and impractical percepts commonly observed in peripheral nerve stimulation feedback. Standard patterns of constant parameters closely mimic impractical vibrotactile stimulation while biphasic patterns better mimic punctate stimulation and provide a platform to investigate intragrip dynamics representing contextual activation.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201

Exploring the Structural and Functional Organization of the Dorsal Zone of Auditory Cortex in Hearing and Deafness

Recent neuroscientific research has focused on cortical plasticity, which refers to the ability of the cerebral cortex to adapt as a consequence of experience. Over the past decade, an increasing number of studies have convincingly shown that the brain can adapt to the loss or impairment of a sensory system, resulting in the expansion or heightened ability of the remaining senses. A particular region in cat auditory cortex, the dorsal zone (DZ), has been shown to mediate enhanced visual motion detection in deaf animals. The purpose of this thesis is to further our understanding of the structure and function of DZ in both hearing and deaf animals, in order to better understand how the brain compensates following insult or injury to a sensory system, with the ultimate goal of improving the utility of sensory prostheses. First, I demonstrate that the brain connectivity profile of animals with early- and late-onset deafness is similar to that of hearing animals, but the projection strength to visual brain regions involved in motion processing increases as a consequence of deafness. Second, I specifically evaluate the functional impact of the strongest auditory connections to area DZ using reversible deactivation and electrophysiological recordings. I show that projections that ultimately originate in primary auditory cortex (A1) form much of the basis of the response of DZ neurons to auditory stimulation. Third, I show that almost half of the neurons in DZ are influenced by visual or somatosensory information. I further demonstrate that this modulation by other sensory systems can have effects that are opposite in direction during different portions of the auditory response. I also show that techniques that incorporate the responses of multiple neurons, such as multi-unit and local field potential recordings, may vastly overestimate the degree to which multisensory processing occurs in a given brain region. Finally, I confirm that individual neurons in DZ become responsive mainly to visual stimulation following deafness. Together, these results shed light on the function and structural organization of area DZ in both hearing and deaf animals, and will contribute to the development of a comprehensive model of cross-modal plasticity

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction

Experimental and Model-based Approaches to Directional Thalamic Deep Brain Stimulation

University of Minnesota Ph.D. dissertation. September 2016. Major: Biomedical Engineering. Advisor: Matthew Johnson. 1 computer file (PDF); xii, 181 pages.Deep brain stimulation (DBS) is an effective surgical procedure for the treatment of several brain disorders. However, the clinical successes of DBS hinges on several factors. Here, we describe the development of tools and methodologies in the context of thalamic DBS for essential tremor (ET) to address three key challenges: 1) accurate localization of nuclei and fiber pathways for stimulation, 2) model-based programming of high-density DBS electrode arrays (DBSA) and 3) in vivo assessment of computational DBS model predictions. We approached the first challenge through a multimodal imaging approach, utilizing high-field (7T) susceptibility-weighted imaging and diffusion-weighted imaging data. A nonlinear image deformation algorithm was used in conjunction with probabilistic fiber tractography to segment individual thalamic sub-nuclei and reconstruct their afferent fiber pathways. We addressed the second challenge by developing subject-specific computational model-based algorithms built on maximizing population activating function values within a target region using convex optimization principles. The algorithms converged within seconds and only required as many finite-element simulations as the number of electrodes on the DBSA being modeled. For the third challenge, we recorded (in two non-human primates) unit-spike data from neurons in the vicinity of chronically implanted thalamic DBSAs before, during and after high-frequency stimulation. A novel entropy-based method was developed to quantify the degree and significance of stimulation-induced changes in neuronal firing pattern. Results indicated that neurons modulated by thalamic DBS were distributed and not confined to the immediate proximity of the active electrode. For those that were modulated by DBS, their responses increasingly shifted from firing rate modulation to firing pattern modulation with increased stimulation amplitude. Additionally, strong low-pass filtering effect was observed where <4% of DBS pulses produced phase-locked spikes in cells exhibiting significant excitatory firing pattern modulation. Finally, we quantified the spatial distribution of neurons modulated by DBS by developing a novel spherical statistical framework for analysis. Together, these tools and methodologies are poised to improve our understanding of DBS mechanisms and improve the efficacy and efficiency of DBS therapy

Dissection of Affective Catecholamine Circuits Using Traditional and Wireless Optogenetics

Parsing the complexity of the mammalian brain has challenged neuroscientists for thousands of years. In the early 21st century, advances in materials science and neuroscience have enabled unprecedented control of neural circuitry. In particular, cell-type selective manipulations, such as those with optogenetics and chemogenetics, routinely provide answers to previously intractable neurobiological questions in the intact, behaving animal. In this two-part dissertation, I first introduce new minimally invasive, wireless technology to perturb neural activity in the ventral tegmental area dopaminergic system of freely moving animals. I report a series of novel devices for studying and perturbing intact neural systems through optogenetics, microfluidic pharmacology, and electrophysiology. Unlike optogenetic approaches that rely on rigid, glass fiber optics coupled to external light sources, these novel devices utilize flexible substrates to carry microscale, inorganic light emitting diodes (μ-ILEDs), multimodal sensors, and/or microfluidic channels into the brain. Each class of device can be wirelessly controlled, enabling studies in freely behaving mice and achieving previously untenable control of catecholamine neural circuitry. In the second part of this dissertation, I apply existing cell-type selective approaches to dissect the role of the locus coeruleus noradrenergic (LC-NE) system in anxiety-like and aversive behaviors. The LC-NE system is one of the first systems engaged following a stressful event. While LC-NE neurons are known to be activated by many different stressors, the underlying neural circuitry and the role of this activity in generating stress-induced anxiety has not been elucidated until now. I demonstrate that increased tonic activity of LC-NE neurons is both necessary and sufficient for stress-induced anxiety; a behavior which is driven by LC projections to the basolateral amygdala. Furthermore, this activity and behavior is elicited by corticotropin releasing hormone-containing afferent inputs into the LC from the central amygdala. These studies position the LC-NE system as a critical mediator of acute stress-induced anxiety and offer a potential intervention for preventing stress-related affective disorders. Together these two objectives provide a rich technological toolbox for neuroscientists and yield important knowledge of how small catecholamine structures with widespread forebrain innervation can selectively mediate higher order behaviors

The role of medial entorhinal cortex activity in hippocampal CA1 spatiotemporally correlated sequence generation and object selectivity for memory function

The hippocampus is crucial for episodic memory and certain forms of spatial navigation. Firing activity of hippocampal principal neurons contains environmental information, including the presence of specific objects, as well as the animal’s spatial and temporal position relative to environmental and behavioral cues. The organization of these firing correlates may allow the formation of memory traces through the integration of object and event information onto a spatiotemporal framework of cell assemblies. Characterizing how external inputs guide internal dynamics in the hippocampus to enable this process across different experiences is crucial to understanding hippocampal function. A body of literature implicates the medial entorhinal cortex (MEC) in supplying spatial and temporal information to the hippocampus. Here we develop a protocol utilizing bilaterally implanted custom designed triple fiber optic arrays and the red-shifted inhibitory opsin JAWS to transiently inactivate large volumes of MEC in freely behaving rats. This was coupled with extracellular tetrode recording of ensembles in CA1 of the hippocampus during a novel memory task involving temporal, spatial and object related epochs, in order to assess the importance of MEC activity for hippocampal feature selectivity during a rich and familiar experience. We report that inactivation of MEC during a mnemonic temporal delay disrupts the existing temporal firing field sequence in CA1 both during and following the inactivation period. Neurons with firing fields prior to the inactivation on each trial remained relatively stable. The disruption of CA1 temporal firing field sequences was accompanied by a behavioral deficit implicating MEC activity and hippocampal temporal field sequences in effective memory across time. Inactivating MEC during the object or spatial epochs of the task did not significantly alter CA1 object selective or spatial firing fields and behavioral performance remained stable. Our findings suggest that MEC is crucial specifically for temporal field organization and expression during a familiar and rich experience. These results support a role for MEC in guiding hippocampal cell assembly sequences in the absence of salient changing stimuli, which may extend to the navigation of cognitive organization in humans and support memory formation and retrieval

Workshops of the Sixth International Brain–Computer Interface Meeting: brain–computer interfaces past, present, and future

Brain–computer interfaces (BCI) (also referred to as brain–machine interfaces; BMI) are, by definition, an interface between the human brain and a technological application. Brain activity for interpretation by the BCI can be acquired with either invasive or non-invasive methods. The key point is that the signals that are interpreted come directly from the brain, bypassing sensorimotor output channels that may or may not have impaired function. This paper provides a concise glimpse of the breadth of BCI research and development topics covered by the workshops of the 6th International Brain–Computer Interface Meeting