Biography
Dr. Adhikari joined UCLA’s Psychology Department in 2016, following postdoctoral training at Stanford University with Prof. Karl Deisseroth and Ph.D. studies at Columbia University with Prof. Joshua A. Gordon and Prof. Rene Hen.
Dr. Adhikari’s lab investigates how the brain coordinates the constellation of changes related to emotional behaviors, with a focus on fear and anxiety. These multi-faceted changes involve complex and dynamic adaptations in hormonal, physiological and behavioral realms. Dr. Adhikari dissects how interactions between different brain structures control these processes, seeking insights that shed light on the neural basis of pathological anxiety disorders and adaptive aversion to danger. To do so we use a combination of powerful techniques, including electrophysiology, behavioral assays, optogenetics and calcium imaging to monitor and control neural activity and behavior.
Learn more about our research at our lab website
Publications
A selected list of publications:
Ye Li, Allen William E, Thompson Kimberly R, Tian Qiyuan, Hsueh Brian, Ramakrishnan Charu, Wang Ai-Chi, Jennings Joshua H, Adhikari Avishek, Halpern Casey H, Witten Ilana B, Barth Alison L, Luo Liqun, McNab Jennifer A, Deisseroth Karl Wiring and Molecular Features of Prefrontal Ensembles Representing Distinct Experiences Cell, 2016; 165(7): 1776-88.
Adhikari Avishek, Lerner Talia N, Finkelstein Joel, Pak Sally, Jennings Joshua H, Davidson Thomas J, Ferenczi Emily, Gunaydin Lisa A, Mirzabekov Julie J, Ye Li, Kim Sung-Yon, Lei Anna, Deisseroth Karl Basomedial amygdala mediates top-down control of anxiety and fear Nature, 2015; 527(7577): 179-85.
Adhikari Avishek Distributed circuits underlying anxiety Frontiers in behavioral neuroscience, 2014; 8(7): 112.
Gunaydin Lisa A, Grosenick Logan, Finkelstein Joel C, Kauvar Isaac V, Fenno Lief E, Adhikari Avishek, Lammel Stephan, Mirzabekov Julie J, Airan Raag D, Zalocusky Kelly A, Tye Kay M, Anikeeva Polina, Malenka Robert C, Deisseroth Karl Natural neural projection dynamics underlying social behavior Cell, 2014; 157(7): 1535-51.
Kim Sung-Yon, Adhikari Avishek, Lee Soo Yeun, Marshel James H, Kim Christina K, Mallory Caitlin S, Lo Maisie, Pak Sally, Mattis Joanna, Lim Byung Kook, Malenka Robert C, Warden Melissa R, Neve Rachael, Tye Kay M, Deisseroth Karl Diverging neural pathways assemble a behavioural state from separable features in anxiety Nature, 2013; 496(7444): 219-23.
Tye Kay M, Mirzabekov Julie J, Warden Melissa R, Ferenczi Emily A, Tsai Hsing-Chen, Finkelstein Joel, Kim Sung-Yon, Adhikari Avishek, Thompson Kimberly R, Andalman Aaron S, Gunaydin Lisa A, Witten Ilana B, Deisseroth Karl Dopamine neurons modulate neural encoding and expression of depression-related behaviour Nature, 2013; 493(7433): 537-41.
Warden Melissa R, Selimbeyoglu Aslihan, Mirzabekov Julie J, Lo Maisie, Thompson Kimberly R, Kim Sung-Yon, Adhikari Avishek, Tye Kay M, Frank Loren M, Deisseroth Karl A prefrontal cortex-brainstem neuronal projection that controls response to behavioural challenge Nature, 2012; 492(7429): 428-32.
Adhikari Avishek, Topiwala Mihir A, Gordon Joshua A Single units in the medial prefrontal cortex with anxiety-related firing patterns are preferentially influenced by ventral hippocampal activity Neuron, 2011; 71(5): 898-910.
Nason Malcolm W, Adhikari Avishek, Bozinoski Marjan, Gordon Joshua A, Role Lorna W Disrupted activity in the hippocampal-accumbens circuit of type III neuregulin 1 mutant mice Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2011; 36(2): 488-96.
Adhikari Avishek, Sigurdsson Torfi, Topiwala Mihir A, Gordon Joshua A Cross-correlation of instantaneous amplitudes of field potential oscillations: a straightforward method to estimate the directionality and lag between brain areas Journal of neuroscience methods, 2010; 191(2): 191-200.
Resende Rodrigo R, da Costa José L, Kihara Alexandre H, Adhikari Avishek, Lorençon Eudes Intracellular Ca2+ regulation during neuronal differentiation of murine embryonal carcinoma and mesenchymal stem cells Stem cells and development, 2010; 19(3): 379-94.
Adhikari Avishek, Topiwala Mihir A, Gordon Joshua A Synchronized activity between the ventral hippocampus and the medial prefrontal cortex during anxiety Neuron, 2010; 65(2): 257-69.
Resende Rodrigo R, Adhikari Avishek Cholinergic receptor pathways involved in apoptosis, cell proliferation and neuronal differentiation Cell communication and signaling : CCS, 2009; 7(2): 20.
Resende Rodrigo R, Gomes Katia N, Adhikari Avishek, Britto Luiz R G, Ulrich Henning Mechanism of acetylcholine-induced calcium signaling during neuronal differentiation of P19 embryonal carcinoma cells in vitro Cell calcium, 2008; 43(2): 107-21.
Bechara Etelvino J H, Dutra Fernando, Cardoso Vanessa E S, Sartori Adriano, Olympio Kelly P K, Penatti Carlos A A, Adhikari Avishek, Assunção Nilson A The dual face of endogenous alpha-aminoketones: pro-oxidizing metabolic weapons Comparative biochemistry and physiology. Toxicology & pharmacology : CBP, 2008; 146(1-2): 88-110.
Adhikari Avishek, Penatti Carlos A A, Resende Rodrigo R, Ulrich Henning, Britto Luiz R G, Bechara Etelvino J H 5-Aminolevulinate and 4, 5-dioxovalerate ions decrease GABA(A) receptor density in neuronal cells, synaptosomes and rat brain Brain research, 2006; 1093(1): 95-104.
Publications
A selected list of publications:
Laura A DeNardo, Cindy D Liu, William E Allen, Eliza L Adams, Drew Friedmann, Ehsan Dadgar-Kiani, Lisa Fu, Casey J Guenthner, Jin Hyung Lee, Marc Tessier-Lavigne, Liqun Luo Temporal Evolution of Cortical Ensembles Promoting Remote Memory Retrieval , 2018; .
Berns Dominic S, DeNardo Laura A, Pederick Daniel T, Luo Liqun Teneurin-3 controls topographic circuit assembly in the hippocampus Nature, 2018; 554(7692): 328-333.
Savas Jeffrey N, Wang Yi-Zhi, DeNardo Laura A, Martinez-Bartolome Salvador, McClatchy Daniel B, Hark Timothy J, Shanks Natalie F, Cozzolino Kira A, Lavallée-Adam Mathieu, Smukowski Samuel N, Park Sung Kyu, Kelly Jeffery W, Koo Edward H, Nakagawa Terunaga, Masliah Eliezer, Ghosh Anirvan, Yates John R Amyloid Accumulation Drives Proteome-wide Alterations in Mouse Models of Alzheimer’s Disease-like Pathology Cell reports, 2017; 21(9): 2614-2627.
Allen William E, DeNardo Laura A, Chen Michael Z, Liu Cindy D, Loh Kyle M, Fenno Lief E, Ramakrishnan Charu, Deisseroth Karl, Luo Liqun Thirst-associated preoptic neurons encode an aversive motivational drive Science (New York, N.Y.), 2017; 357(6356): 1149-1155.
DeNardo Laura, Luo Liqun Genetic strategies to access activated neurons Current opinion in neurobiology, 2017; 45(6356): 121-129.
Savas JN, Ribeiro LF, Wierda KD, Wright R, DeNardo-Wilke LA, Chamma I, Wang Yi-Zhi, Zemla R, Lavallee- Adam M, Vennekens KM, O’Sullivan ML, Antonios JK, Hall EA, Thoumine O, Attie AD, Yates JR, Ghosh A, De Wit J The Sorting Receptor SorCS1 Regulates Trafficking of Neurexin and AMPA receptors, Neuron, 2015; 87: 764-80.
DeNardo Laura A, Berns Dominic S, DeLoach Katherine, Luo Liqun Connectivity of mouse somatosensory and prefrontal cortex examined with trans-synaptic tracing Nature neuroscience, 2015; 18(11): 1687-1697.
DeNardo Laura A, de Wit Joris, Otto-Hitt Stefanie, Ghosh Anirvan NGL-2 regulates input-specific synapse development in CA1 pyramidal neurons Neuron, 2012; 76(4): 762-75.
Wilke Scott A, Hall Benjamin J, Antonios Joseph K, Denardo Laura A, Otto Stefanie, Yuan Bo, Chen Fading, Robbins Elissa M, Tiglio Katie, Williams Megan E, Qiu Zilong, Biederer Thomas, Ghosh Anirvan NeuroD2 regulates the development of hippocampal mossy fiber synapses Neural development, 2012; 7(4): 9.
Biography
NEURAL DYNAMICS: THE NEURAL BASIS OF LEARNING AND MEMORY AND TEMPORAL PROCESSING Behavior and cognition are not the product of isolated neurons, but rather emerge from the dynamics of interconnected neurons embedded in complex recurrent networks. Significant progress has been made towards understanding cellular and synaptic properties in isolation, as well as in establishing which areas of the brain are active during specific tasks. However, elucidating how the activity of hundreds of thousands of neurons within local cortical circuits underlie computations remains an elusive and fundamental goal in neuroscience. The primary goal of my laboratory is to understand how functional computations emerge from networks of neurons. One computation we are particularly interested in is how the brain tells time. Temporal processing refers to your ability to distinguish the interval and duration of sensory stimuli, and is a fundamental component of speech and music perception. To answer these questions the main approaches in my laboratory involve: (1) In Vitro Electrophysiology: Using acute and chronic brain slices we study the spatio-temporal dynamics of cortical circuits, as well as the learning rules that allow networks to develop, organize and perform computations ??? that is, to learn. (2) Computer Simulations: Computer models are used to simulate how networks perform computations, as well as test and generate predictions in parallel with our experimental research. (3) Human Psychophysics: We also use human pyschophysical experiments to characterize learning and generalization of temporal tasks, such as interval discrimination.
Publications
A selected list of publications:
Goudar Vishwa, Buonomano Dean V A model of order-selectivity based on dynamic changes in the balance of excitation and inhibition produced by short-term synaptic plasticity Journal of neurophysiology, 2015; 113(2): 509-23.
Goel Anubhuti, Buonomano Dean V Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2014; 369(1637): 20120460.
Laje Rodrigo, Buonomano Dean V Robust timing and motor patterns by taming chaos in recurrent neural networks Nature neuroscience, 2013; 16(7): 925-33.
Lee Tyler P, Buonomano Dean V Unsupervised formation of vocalization-sensitive neurons: a cortical model based on short-term and homeostatic plasticity Neural computation, 2012; 24(10): 2579-603.
Buonomano Dean V, Laje Rodrigo Population clocks: motor timing with neural dynamics Trends in cognitive sciences, 2010; 14(12): 520-7.
Johnson Hope A, Goel Anubhuthi, Buonomano Dean V Neural dynamics of in vitro cortical networks reflects experienced temporal patterns Nature neuroscience, 2010; 13(8): 917-9.
Liu Jian K, Buonomano Dean V Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner The Journal of neuroscience : the official journal of the Society for Neuroscience, 2009; 29(42): 13172-81.
Buonomano Dean V Harnessing chaos in recurrent neural networks Neuron, 2009; 63(4): 423-5.
Buonomano Dean V, Bramen Jennifer, Khodadadifar Mahsa Influence of the interstimulus interval on temporal processing and learning: testing the state-dependent network model Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2009; 364(1525): 1865-73.
Carvalho Tiago P, Buonomano Dean V Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions Neuron, 2009; 61(5): 774-85.
Buonomano Dean V, Maass Wolfgang State-dependent computations: spatiotemporal processing in cortical networks Nature reviews. Neuroscience, 2009; 10(2): 113-25.
Johnson Hope A, Buonomano Dean V A method for chronic stimulation of cortical organotypic cultures using implanted electrodes Journal of neuroscience methods, 2009; 176(2): 136-43.
van Wassenhove V, Buonomano DV, Shimojo S, Shams L. Distortions of subjective time perception within and across senses, PLoS ONE, 2008; 3(1): e1437.
Johnson, Hope A. Buonomano, Dean V. Development and Plasticity of Spontaneous Activity and Up States in Cortical Organotypic Slices J. Neurosci, 2007; 27(22): 5915-5925.
Buonomano, D. V. The biology of time across different scales Nat Chem Biol, 2007; 3(10): 594-7.
Karmarkar, U. R. Buonomano, D. V. Timing in the absence of clocks: encoding time in neural network states Neuron, 2007; 53(3): 427-38.
Karmarkar, U. R. Buonomano, D. V. Different forms of homeostatic plasticity are engaged with distinct temporal profiles, Eur J Neurosci, 2006; 23(6): 1575-84.
Eagleman, D. M. Tse, P. U. Buonomano, D. Janssen, P. Nobre, A. C. Holcombe, A. O. Time and the brain: how subjective time relates to neural time, J Neurosci, 2005; 25(45): 10369-71.
Dong, H. W. Buonomano, D. V. A technique for repeated recordings in cortical organotypic slices, J Neurosci Methods, 2005; 146(1): 69-75.
Buonomano, D. V. A learning rule for the emergence of stable dynamics and timing in recurrent networks, J Neurophysiol, 2005; 94(4): 2275-83.
Marder, C. P. Buonomano, D. V. Timing and balance of inhibition enhance the effect of long-term potentiation on cell firing, J Neurosci, 2004; 24(40): 8873-84.
Mauk, M. D. Buonomano, D. V. The Neural Basis of Temporal Processing, Annual Rev. Neuroscience, 2004; 27: 304-340.
Karmarkar, U. R. Buonomano, D. V. Temporal specificity of perceptual learning in an auditory discrimination task, Learn Mem, 2003; 10(2): 141-7.
Buonomano, D. V. Timing of Neural Responses in Cortical Organotypic Slices, Proc. Natl. Acad. Sci. USA, 2003; 100: 4897-4902.
Marder, C. P. Buonomano, D. V. Differential effects of short- and long-term potentiation on cell firing in the CA1 region of the hippocampus, J Neurosci, 2003; 23(1): 112-21.
Karmarkar, U. R. Buonomano, D. V. A model of spike-timing dependent plasticity: one or two coincidence detectors?, J Neurophysiol, 2002; 88(1): 507-13.
Buonomano, D. V. Karmarkar, U. R. How do we tell time?, Neuroscientist, 2002; 8(1): 42-51.
Karmarkar, U. R. Najarian, M. T. Buonomano, D. V. Mechanisms and significance of spike-timing dependent plasticity, Biol Cybern, 2002; 87(5-6): 373-82.
Buonomano, D. V. Decoding temporal information: a model based on short-term synaptic plasticity, J Neurosci, 2000; 20: 1129-1141.
Buonomano, D. V. Distinct functional types of associative long-term potentiation in neocortical and hippocampal pyramidal neurons, J Neurosci, 1999; 19: 6748-6754.
Buonomano, D. V. Merzenich, M. A neural network model of temporal code generation and position-invariant pattern recognition, Neural Comput, 1999; 11(1): 103-16.
Buonomano, D. V. Merzenich, M. M. Cortical plasticity: from synapses to maps, Annual Rev. Neuroscience, 1998; 21: 149-186.
Buonomano, D. V. Merzenich, M. M. Temporal information transformed into a spatial code by a neural network with realistic properties, Science, 1995; 267: 1028-30.
Buonomano, D. V. Byrne, J. H. Long-term synaptic changes produced by a cellular analog of classical conditioning in Aplysia, Science, 1990; 249(4967): 420-3.