@article {67765, title = {Genetically identified amygdala-striatal circuits for valence-specific behaviors.}, journal = {Nature Neuroscience}, volume = {24}, year = {2021}, month = {2021 Oct 18}, pages = {1586-1600}, abstract = {

The basolateral amygdala (BLA) plays essential roles in behaviors motivated by stimuli with either positive or negative valence, but how it processes motivationally opposing information and participates in establishing valence-specific behaviors remains unclear. Here, by targeting Fezf2-expressing neurons in the BLA, we identify and characterize two functionally distinct classes in behaving mice, the negative-valence neurons and positive-valence neurons, which innately represent aversive and rewarding stimuli, respectively, and through learning acquire predictive responses that are essential for punishment avoidance or reward seeking. Notably, these two classes of neurons receive inputs from separate sets of sensory and limbic areas, and convey punishment and reward information through projections to the nucleus accumbens and olfactory tubercle, respectively, to drive negative and positive reinforcement. Thus, valence-specific BLA neurons are wired with distinctive input-output structures, forming a circuit framework that supports the roles of the BLA in encoding, learning and executing valence-specific motivated behaviors.

}, issn = {1546-1726}, doi = {10.1038/s41593-021-00927-0}, author = {Zhang, Xian and Guan, Wuqiang and Yang, Tao and Furlan, Alessandro and Xiao, Xiong and Yu, Kai and An, Xu and Galbavy, William and Ramakrishnan, Charu and Deisseroth, Karl and Ritola, Kimberly and Hantman, Adam and He, Miao and Josh Huang, Z and Li, Bo} } @article {65739, title = {A genetically defined compartmentalized striatal direct pathway for negative reinforcement.}, journal = {Cell}, volume = {181}, year = {2020}, month = {2020 Oct 1}, pages = {211}, abstract = {

The striosome compartment within the dorsal striatum has been implicated in reinforcement learning and regulation of motivation, but how striosomal neurons contribute to these functions remains elusive. Here, we show that a genetically identified striosomal population, which expresses the Teashirt family zinc finger 1 (Tshz1) and belongs to the direct pathway, drives negative reinforcement and is essential for aversive learning in mice. Contrasting a "conventional" striosomal direct pathway, the Tshz1 neurons cause aversion, movement suppression, and negative reinforcement once activated, and they receive a distinct set of synaptic inputs. These neurons are predominantly excited by punishment rather than reward and represent the anticipation of punishment or the motivation for avoidance. Furthermore, inhibiting these neurons impairs punishment-based learning without affecting reward learning or movement. These results establish a major role of striosomal neurons in behaviors reinforced by punishment and moreover uncover functions of the direct pathway unaccounted for in classic models.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2020.08.032}, author = {Xiao, Xiong and Deng, Hanfei and Furlan, Alessandro and Yang, Tao and Zhang, Xian and Hwang, Ga-Ram and Tucciarone, Jason and Wu, Priscilla and He, Miao and Palaniswamy, Ramesh and Ramakrishnan, Charu and Ritola, Kimberly and Hantman, Adam and Deisseroth, Karl and Osten, Pavel and Huang, Z Josh and Li, Bo} } @article {64871, title = {Thirst regulates motivated behavior through modulation of brainwide neural population dynamics.}, journal = {Science}, volume = {364}, year = {2019}, month = {2019 Apr 04}, pages = {253}, abstract = {

Physiological needs produce motivational drives, such as thirst and hunger, that regulate behaviors essential to survival. Hypothalamic neurons sense these needs and must coordinate relevant brainwide neuronal activity to produce the appropriate behavior. We studied dynamics from ~24,000 neurons in 34 brain regions during thirst-motivated choice behavior, as mice consumed water and became sated. Water-predicting sensory cues elicited activity that rapidly spread throughout the brain of thirsty animals. These dynamics were gated by a brainwide mode of population activity that encoded motivational state. Focal optogenetic activation of hypothalamic thirst-sensing neurons, after satiation, returned global activity to the pre-satiation state. Thus, motivational states specify initial conditions determining how a brainwide dynamical system transforms sensory input into behavioral output.

}, issn = {1095-9203}, doi = {10.1126/science.aav3932}, author = {Allen, William E and Chen, Michael Z and Pichamoorthy, Nandini and Tien, Rebecca H and Pachitariu, Marius and Luo, Liqun and Deisseroth, Karl} } @article {48267, title = {A brainstem-spinal cord inhibitory circuit for mechanical pain modulation by GABA and Enkephalins.}, journal = {Neuron}, volume = {93}, year = {2017}, month = {2017 Jan 31}, pages = {822-39}, abstract = {

Pain thresholds are, in part, set as a function of emotional and internal states by descending modulation of nociceptive transmission in the spinal cord. Neurons of the rostral ventromedial medulla (RVM) are thought to critically contribute to this process; however, the neural circuits and synaptic mechanisms by which distinct populations of RVM neurons facilitate or diminish pain remain elusive. Here we used in\ vivo opto/chemogenetic manipulations and trans-synaptic tracing of genetically identified dorsal horn and RVM neurons to uncover an RVM-spinal cord-primary afferent circuit controlling pain thresholds. Unexpectedly, we found that RVM GABAergic neurons facilitate mechanical pain by inhibiting dorsal horn enkephalinergic/GABAergic interneurons. We further demonstrate that these interneurons gate sensory inputs and control pain through temporally coordinated enkephalin- and GABA-mediated presynaptic inhibition of somatosensory neurons. Our results uncover a descending disynaptic inhibitory circuit that facilitates mechanical pain, is engaged during stress, and could be targeted to establish higher pain thresholds.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2017.01.008}, author = {Fran{\c c}ois, Amaury and Low, Sarah A and Sypek, Elizabeth I and Christensen, Amelia J and Sotoudeh, Chaudy and Beier, Kevin T and Ramakrishnan, Charu and Ritola, Kimberly D and Sharif-Naeini, Reza and Deisseroth, Karl and Delp, Scott L and Malenka, Robert C and Luo, Liqun and Hantman, Adam W and Scherrer, Gr{\'e}gory} } @article {6130, title = {Nanotools for neuroscience and brain activity mapping.}, journal = {ACS Nano}, volume = {7}, year = {2013}, month = {2013 Mar 26}, pages = {1850-66}, abstract = {

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.

}, issn = {1936-086X}, doi = {10.1021/nn4012847}, author = {Alivisatos, A Paul and Andrews, Anne M and Boyden, Edward S and Chun, Miyoung and Church, George M and Deisseroth, Karl and Donoghue, John P and Fraser, Scott E and Lippincott-Schwartz, Jennifer and Looger, Loren L and Masmanidis, Sotiris and McEuen, Paul L and Nurmikko, Arto V and Park, Hongkun and Peterka, Darcy S and Reid, Clay and Roukes, Michael L and Scherer, Axel and Schnitzer, Mark and Sejnowski, Terrence J and Shepard, Kenneth L and Tsao, Doris and Turrigiano, Gina and Weiss, Paul S and Xu, Chris and Yuste, Rafael and Zhuang, Xiaowei} } @article {47641, title = {Nanotools for neuroscience and brain activity mapping.}, journal = {ACS nano}, volume = {7}, year = {2013}, month = {2013 Mar 26}, pages = {1850-66}, abstract = {

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.

}, keywords = {Animals, Brain Mapping, Humans, Models, Neurological, Nanomedicine, Nanoparticles, Nanotechnology, Nervous System Physiological Phenomena}, issn = {1936-086X}, doi = {10.1021/nn4012847}, author = {Alivisatos, A Paul and Andrews, Anne M and Boyden, Edward S and Chun, Miyoung and Church, George M and Deisseroth, Karl and Donoghue, John P and Fraser, Scott E and Lippincott-Schwartz, Jennifer and Looger, Loren L and Masmanidis, Sotiris and McEuen, Paul L and Nurmikko, Arto V and Park, Hongkun and Peterka, Darcy S and Reid, Clay and Roukes, Michael L and Scherer, Axel and Schnitzer, Mark and Sejnowski, Terrence J and Shepard, Kenneth L and Tsao, Doris and Turrigiano, Gina and Weiss, Paul S and Xu, Chris and Yuste, Rafael and Zhuang, Xiaowei} } @article {6904, title = {The Open Connectome Project Data Cluster: Scalable analysis and vision for high-throughput neuroscience.}, journal = {Scientific and Statistical Database Management: International Conference, SSDBM ... : Proceedings. International Conference on Scientific and Statistical Database Management}, year = {2013}, month = {2013 Jun 18}, abstract = {

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

}, doi = {10.1145/2484838.2484870}, author = {Burns, Randal and Roncal, William Gray and Kleissas, Dean and Lillaney, Kunal and Manavalan, Priya and Perlman, Eric and Berger, Daniel R. and Bock, Davi D and Chung, Kwanghun and Grosenick, Logan and Kasthuri, Narayanan and Weiler, Nicholas C and Deisseroth, Karl and Kazhdan, Michael and Lichtman, Jeff and Reid, R Clay and Smith, Stephen J and Szalay, Alexander S and Vogelstein, Joshua T and Vogelstein, R Jacob} } @article {1205, title = {Manipulation of an innate escape response in Drosophila: photoexcitation of acj6 neurons induces the escape response.}, journal = {PLoS One}, volume = {4}, year = {2009}, month = {2009 Apr 2}, pages = {e5100}, abstract = {

BACKGROUND: The genetic analysis of behavior in Drosophila melanogaster has linked genes controlling neuronal connectivity and physiology to specific neuronal circuits underlying a variety of innate behaviors. We investigated the circuitry underlying the adult startle response, using photoexcitation of neurons that produce the abnormal chemosensory jump 6 (acj6) transcription factor. This transcription factor has previously been shown to play a role in neuronal pathfinding and neurotransmitter modality, but the role of acj6 neurons in the adult startle response was largely unknown. PRINCIPAL FINDINGS: We show that the activity of these neurons is necessary for a wild-type startle response and that excitation is sufficient to generate a synthetic escape response. Further, we show that this synthetic response is still sensitive to the dose of acj6 suggesting that that acj6 mutation alters neuronal activity as well as connectivity and neurotransmitter production. RESULTS/SIGNIFICANCE: These results extend the understanding of the role of acj6 and of the adult startle response in general. They also demonstrate the usefulness of activity-dependent characterization of neuronal circuits underlying innate behaviors in Drosophila, and the utility of integrating genetic analysis into modern circuit analysis techniques.

}, keywords = {Animal, Animals, Base Sequence, Behavior, DNA Primers, Drosophila melanogaster, Genetically Modified, Neurons, Startle Reaction}, issn = {1932-6203}, doi = {10.1371/journal.pone.0005100}, author = {Zimmermann, Gregor and Wang, Li-Ping and Vaughan, Alexander G and Manoli, Devanand S and Zhang, Feng and Deisseroth, Karl and Baker, Bruce S and Scott, Matthew P} }