Tracing Activity Across the Whole Brain Neural Network with Optogenetic Functional Magnetic Resonance Imaging

Despite the overwhelming need, there has been a relatively large gap in our ability to trace network level activity across the brain. The complex dense wiring of the brain makes it extremely challenging to understand cell-type specific activity and their communication beyond a few synapses. Recent development of the optogenetic functional magnetic resonance imaging (ofMRI) provides a new impetus for the study of brain circuits by enabling causal tracing of activities arising from defined cell types and firing patterns across the whole brain. Brain circuit elements can be selectively triggered based on their genetic identity, cell body location, and/or their axonal projection target with temporal precision while the resulting network response is monitored non-invasively with unprecedented spatial and temporal accuracy. With further studies including technological innovations to bring ofMRI to its full potential, ofMRI is expected to play an important role in our system-level understanding of the brain circuit mechanism

Mapping the Connectome: Multi-Level Analysis of Brain Connectivity

Background and scope The brain contains vast numbers of interconnected neurons that constitute anatomical and functional networks. Structural descriptions of neuronal network elements and connections make up the “connectome ” of the brain (Hagmann, 2005; Sporns et al., 2005; Sporns, 2011), and are important for understanding normal brain function and disease-related dysfunction. A long-standing ambition of the neuroscience community has been to achieve complete connectome maps for the human brain as well as the brains of non-human primates, rodents, and other species (Bohland et al., 2009; Hagmann et al., 2010; Van Essen and Ugurbil, 2012). A wide repertoire of experimental tools is currently available to map neural connectivity at multiple levels, from the tracing of mesoscopic axonal connections and the delineation of white matter tracts (Saleem et al., 2002; Van der Linden et al., 2002; Sporns et al., 2005; Schmahmann et al., 2007; Hagmann et al., 2010), the mappin

In vivo identification of brain structures functionally involved in spatial learning and strategy switch

Spatial learning is a complex behavior which includes, among others, encoding of space, sensory and motivational processes, arousal and locomotor performance. Today, our view on spatial navigation is largely hippocampus-centrist. Less is known about the involvement of brain structures up- and downstream, or out of this circuit. Here, I provide the first in vivo assessment of the neural matrix underlying spatial learning, using functional manganese-enhanced MRI (MEMRI) and voxel-wise whole brain analysis. Mice underwent place-learning (PL) vs. response-learning (RL) in the water cross maze (WCM) and its readout was correlated to the Mn2+ contrasts. Thus, I identified structures involved in spatial learning largely overlooked in the past, due to methods focused on region of interest (ROI) analyses. These structures include several sensory-related structures and differ between place-learners and response-learners, with the former (PL) comprising mostly structures involved in different properties of visual processing, such as horizontal gaze (e.g. nucleus prepositus) and saccade (e.g. fastigial nucleus), or provide vision-input and eye movement information from parahippocampal (e.g. presubiculum, perirhinal, postrhinal and ectorhinal areas) and other regions (e.g. orbital area, superior colliculus and vestibular ocular-reflex from the vestibular nucleus) likely to head-direction, grid- and place-cells; and the latter (RL) presenting structures related to more basic rodent sensory computations, like odor (e.g main and accessory olfactory bulb, cortical amygdala, piriform, endopiriform and postpiriform areas) and acoustic stimuli representation (e.g. auditory area, nucleus of the lateral lemniscus and superior olivary complex), or sensory-motor properties, such as body representation (e.g. somatosensory area – upper limbs) and head-direction signal. Add-on experiments pointed to preferential Mn2+ accumulation towards projection terminals, suggesting that our mapping was mostly formed by projection sites of the originally activated structures. This is corroborated by in-depth analysis of MEMRI data after WCM learning showing mostly downstream targets of the hippocampus. These differ between fornical afferences from vCA1 and direct innervation from dCA1/iCA1 (for PL), and structures along the longitudinal association bundle originating in vCA1 (for RL). To elucidate the pattern of Mn2+ accumulation seen on the scans, I performed c-fos expression analyses following learning in the WCM. This helped me identify the structures initially activated during spatial learning and its underlying connectivity to establish the matrix. Finally, to test the causal involvement of selected structures from our previous findings I inhibited them (through DREADDs) while mice performed the WCM task. I also focused on the causal involvement of the vHPC-mPFC circuit on strategy switch during WCM learning. I believe that this study might shed light into new brain structures involved in spatial learning and strategy switch and complement the current knowledge on these circuits’ connectivity. Moreover, I elucidated some functional mechanisms of MEMRI, clarifying the interpretation of data obtained with this method and its possible future applications

In vivo identification of brain structures functionally involved in spatial learning and strategy switch

Spatial learning is a complex behavior which includes, among others, encoding of space, sensory and motivational processes, arousal and locomotor performance. Today, our view on spatial navigation is largely hippocampus-centrist. Less is known about the involvement of brain structures up- and downstream, or out of this circuit. Here, I provide the first in vivo assessment of the neural matrix underlying spatial learning, using functional manganese-enhanced MRI (MEMRI) and voxel-wise whole brain analysis. Mice underwent place-learning (PL) vs. response-learning (RL) in the water cross maze (WCM) and its readout was correlated to the Mn2+ contrasts. Thus, I identified structures involved in spatial learning largely overlooked in the past, due to methods focused on region of interest (ROI) analyses. These structures include several sensory-related structures and differ between place-learners and response-learners, with the former (PL) comprising mostly structures involved in different properties of visual processing, such as horizontal gaze (e.g. nucleus prepositus) and saccade (e.g. fastigial nucleus), or provide vision-input and eye movement information from parahippocampal (e.g. presubiculum, perirhinal, postrhinal and ectorhinal areas) and other regions (e.g. orbital area, superior colliculus and vestibular ocular-reflex from the vestibular nucleus) likely to head-direction, grid- and place-cells; and the latter (RL) presenting structures related to more basic rodent sensory computations, like odor (e.g main and accessory olfactory bulb, cortical amygdala, piriform, endopiriform and postpiriform areas) and acoustic stimuli representation (e.g. auditory area, nucleus of the lateral lemniscus and superior olivary complex), or sensory-motor properties, such as body representation (e.g. somatosensory area ? upper limbs) and head-direction signal. Add-on experiments pointed to preferential Mn2+ accumulation towards projection terminals, suggesting that our mapping was mostly formed by projection sites of the originally activated structures. This is corroborated by in-depth analysis of MEMRI data after WCM learning showing mostly downstream targets of the hippocampus. These differ between fornical afferences from vCA1 and direct innervation from dCA1/iCA1 (for PL), and structures along the longitudinal association bundle originating in vCA1 (for RL). To elucidate the pattern of Mn2+ accumulation seen on the scans, I performed c-fos expression analyses following learning in the WCM. This helped me identify the structures initially activated during spatial learning and its underlying connectivity to establish the matrix. Finally, to test the causal involvement of selected structures from our previous findings I inhibited them (through DREADDs) while mice performed the WCM task. I also focused on the causal involvement of the vHPC-mPFC circuit on strategy switch during WCM learning. I believe that this study might shed light into new brain structures involved in spatial learning and strategy switch and complement the current knowledge on these circuits? connectivity. Moreover, I elucidated some functional mechanisms of MEMRI, clarifying the interpretation of data obtained with this method and its possible future applications

Use of functional neuroimaging and optogenetics to explore deep brain stimulation targets for the treatment of Parkinson's disease and epilepsy

Deep brain stimulation (DBS) is a neurosurgical therapy for Parkinson’s disease and epilepsy. In DBS, an electrode is stereotactically implanted in a specific region of the brain and electrical pulses are delivered using a subcutaneous pacemaker-like stimulator. DBS-therapy has proven to effectively suppress tremor or seizures in pharmaco-resistant Parkinson’s disease and epilepsy patients respectively. It is most commonly applied in the subthalamic nucleus for Parkinson’s disease, or in the anterior thalamic nucleus for epilepsy. Despite the rapidly growing use of DBS at these classic brain structures, there are still non-responders to the treatment. This creates a need to explore other brain structures as potential DBS-targets. However, research in patients is restricted mainly because of ethical reasons. Therefore, in order to search for potential new DBS targets, animal research is indispensable. Previous animal studies of DBS-relevant circuitry largely relied on electrophysiological recordings at predefined brain areas with assumed relevance to DBS therapy. Due to their inherent regional biases, such experimental techniques prevent the identification of less recognized brain structures that might be suitable DBS targets. Therefore, functional neuroimaging techniques, such as functional Magnetic Resonance Imaging and Positron Emission Tomography, were used in this thesis because they allow to visualize and to analyze the whole brain during DBS. Additionally, optogenetics, a new technique that uses light instead of electricity, was employed to manipulate brain cells with unprecedented selectivity

Global and local fMRI signals driven by neurons defined optogenetically by type and wiring

Despite a rapidly-growing scientific and clinical brain imaging literature based on functional magnetic resonance imaging (fMRI) using blood oxygenation level-dependent (BOLD) signals, it remains controversial whether BOLD signals in a particular region can be caused by activation of local excitatory neurons. This difficult question is central to the interpretation and utility of BOLD, with major significance for fMRI studies in basic research and clinical applications. Using a novel integrated technology unifying optogenetic control of inputs with high-field fMRI signal readouts, we show here that specific stimulation of local CaMKIIα-expressing excitatory neurons, either in the neocortex or thalamus, elicits positive BOLD signals at the stimulus location with classical kinetics. We also show that optogenetic fMRI (ofMRI) allows visualization of the causal effects of specific cell types defined not only by genetic identity and cell body location, but also by axonal projection target. Finally, we show that ofMRI within the living and intact mammalian brain reveals BOLD signals in downstream targets distant from the stimulus, indicating that this approach can be used to map the global effects of controlling a local cell population. In this respect, unlike both conventional fMRI studies based on correlations and fMRI with electrical stimulation that will also directly drive afferent and nearby axons, this ofMRI approach provides causal information about the global circuits recruited by defined local neuronal activity patterns. Together these findings provide an empirical foundation for the widely-used fMRI BOLD signal, and the features of ofMRI define a potent tool that may be suitable for functional circuit analysis as well as global phenotyping of dysfunctional circuitry

In vivo Large-Scale Cortical Mapping Using Channelrhodopsin-2 Stimulation in Transgenic Mice Reveals Asymmetric and Reciprocal Relationships between Cortical Areas

We have mapped intracortical activity in vivo independent of sensory input using arbitrary point channelrhodopsin-2 (ChR2) stimulation and regional voltage sensitive dye imaging in B6.Cg-Tg (Thy1-COP4/EYFP)18Gfng/J transgenic mice. Photostimulation of subsets of deep layer pyramidal neurons within forelimb, barrel, or visual primary sensory cortex led to downstream cortical maps that were dependent on synaptic transmission and were similar to peripheral sensory stimulation. ChR2-evoked maps confirmed homotopic connections between hemispheres and intracortical sensory and motor cortex connections. This ability of optogentically activated subpopulations of neurons to drive appropriate downstream maps suggests that mechanisms exist to allow prototypical cortical maps to self-assemble from the stimulation of neuronal subsets. Using this principle of map self-assembly, we employed ChR2 point stimulation to map connections between cortical areas that are not selectively activated by peripheral sensory stimulation or behavior. Representing the functional cortical regions as network nodes, we identified asymmetrical connection weights in individual nodes and identified the parietal association area as a network hub. Furthermore, we found that the strength of reciprocal intracortical connections between primary and secondary sensory areas are unequal, with connections from primary to secondary sensory areas being stronger than the reciprocal

Optogenetic Brain Interfaces

The brain is a large network of interconnected neurons where each cell functions as a nonlinear processing element. Unraveling the mysteries of information processing in the complex networks of the brain requires versatile neurostimulation and imaging techniques. Optogenetics is a new stimulation method which allows the activity of neurons to be modulated by light. For this purpose, the cell-types of interest are genetically targeted to produce light-sensitive proteins. Once these proteins are expressed, neural activity can be controlled by exposing the cells to light of appropriate wavelengths. Optogenetics provides a unique combination of features, including multimodal control over neural function and genetic targeting of specific cell-types. Together, these versatile features combine to a powerful experimental approach, suitable for the study of the circuitry of psychiatric and neurological disorders. The advent of optogenetics was followed by extensive research aimed to produce new lines of light-sensitive proteins and to develop new technologies: for example, to control the distribution of light inside the brain tissue or to combine optogenetics with other modalities including electrophysiology, electrocorticography, nonlinear microscopy, and functional magnetic resonance imaging. In this paper, the authors review some of the recent advances in the field of optogenetics and related technologies and provide their vision for the future of the field.United States. Defense Advanced Research Projects Agency (Space and Naval Warfare Systems Center, Pacific Grant/Contract No. N66001-12-C-4025)University of Wisconsin--Madison (Research growth initiative; grant 101X254)University of Wisconsin--Madison (Research growth initiative; grant 101X172)University of Wisconsin--Madison (Research growth initiative; grant 101X213)National Science Foundation (U.S.) (MRSEC DMR-0819762)National Science Foundation (U.S.) (NSF CAREER CBET-1253890)National Institutes of Health (U.S.) (NIH/NIBIB R00 Award (4R00EB008738)National Institutes of Health (U.S.) (NIH Director’s New Innovator award (1-DP2-OD002989))Okawa Foundation (Research Grant Award)National Institutes of Health (U.S.) (NIH Director’s New Innovator Award (1DP2OD007265))National Science Foundation (U.S.) (NSF CAREER Award (1056008)Alfred P. Sloan Foundation (Fellowship)Human Frontier Science Program (Strasbourg, France) (Grant No. 1351/12)Israeli Centers of Research Excellence (I-CORE grant, program 51/11)MINERVA Foundation (Germany