Posts classified under: Computational Neuroscience

Avishek Adhikari, Ph.D.

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.
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.

Dean Buonomano, Ph.D.

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:

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.
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.
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.

Steve Cannon, M.D., Ph.D.

Biography

The primary research interests of our laboratory are how ion channels regulate the electrical excitability of cells and how defects in these channels lead to human disease. In the past two decades, mutations of ion channel genes have been found to be the primary cause for over 100 human diseases. Our research program is focused on the mechanistic basis for a group of inherited conditions that alter the electrical excitability of skeletal muscle, including periodic paralysis and myotonia. We have characterized the gating defects of mutant channels, generated computational models of muscle excitability, and produced genetically-engineered mice to gain insights on the pathomechanisms of these disorders and to explore therapeutic interventions.

Melissa Sharpe, Ph.D.

Publications

A selected list of publications:

Maes Etienne J P, Sharpe Melissa J, Usypchuk Alexandra A, Lozzi Megan, Chang Chun Yun, Gardner Matthew P H, Schoenbaum Geoffrey, Iordanova Mihaela D   Causal evidence supporting the proposal that dopamine transients function as temporal difference prediction errors Nature neuroscience, 2020; .
Sharpe Melissa J, Batchelor Hannah M, Mueller Lauren E, Yun Chang Chun, Maes Etienne J P, Niv Yael, Schoenbaum Geoffrey   Dopamine transients do not act as model-free prediction errors during associative learning Nature communications, 2020; 11(1): 106.
Sharpe Melissa J, Stalnaker Thomas, Schuck Nicolas W, Killcross Simon, Schoenbaum Geoffrey, Niv Yael   An Integrated Model of Action Selection: Distinct Modes of Cortical Control of Striatal Decision Making Annual review of psychology, 2019; 70(1): 53-76.
Sharpe Melissa J, Killcross Simon   Modulation of attention and action in the medial prefrontal cortex of rats Psychological review, 2018; 125(5): 822-843.
Sharpe Melissa J   What a relief! A role for dopamine in positive (but not negative) valence Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2018; 43(8): 1-2.
Langdon Angela J, Sharpe Melissa J, Schoenbaum Geoffrey, Niv Yael   Model-based predictions for dopamine Current opinion in neurobiology, 2018; 49(8): 1-7.
Sharpe Melissa J, Schoenbaum Geoffrey   Evaluation of the hypothesis that phasic dopamine constitutes a cached-value signal Neurobiology of learning and memory, 2017; 49(8): 1-7.
Sharpe Melissa J, Batchelor Hannah M, Schoenbaum Geoffrey   Preconditioned cues have no value eLife, 2017; 6(8): 1-7.
Sharpe Melissa J, Marchant Nathan J, Whitaker Leslie R, Richie Christopher T, Zhang Yajun J, Campbell Erin J, Koivula Pyry P, Necarsulmer Julie C, Mejias-Aponte Carlos, Morales Marisela, Pickel James, Smith Jeffrey C, Niv Yael, Shaham Yavin, Harvey Brandon K, Schoenbaum Geoffrey   Lateral Hypothalamic GABAergic Neurons Encode Reward Predictions that Are Relayed to the Ventral Tegmental Area to Regulate Learning Current biology : CB, 2017; 27(14): 2089-2100.e5.
Sharpe Melissa J, Chang Chun Yun, Liu Melissa A, Batchelor Hannah M, Mueller Lauren E, Jones Joshua L, Niv Yael, Schoenbaum Geoffrey   Dopamine transients are sufficient and necessary for acquisition of model-based associations Nature neuroscience, 2017; 20(5): 735-742.
Nasser Helen M, Calu Donna J, Schoenbaum Geoffrey, Sharpe Melissa J   The Dopamine Prediction Error: Contributions to Associative Models of Reward Learning Frontiers in psychology, 2017; 8(5): 244.
Sharpe Melissa J, Schoenbaum Geoffrey   Back to basics: Making predictions in the orbitofrontal-amygdala circuit Neurobiology of learning and memory, 2016; 131(5): 201-6.
Sharpe M J, Clemens K J, Morris M J, Westbrook R F   Daily Exposure to Sucrose Impairs Subsequent Learning About Food Cues: A Role for Alterations in Ghrelin Signaling and Dopamine D2 Receptors Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2016; 41(5): 1357-65.
Sharpe Melissa J, Wikenheiser Andrew M, Niv Yael, Schoenbaum Geoffrey   The State of the Orbitofrontal Cortex Neuron, 2015; 88(6): 1075-1077.
Sharpe Melissa J, Killcross Simon   The prelimbic cortex directs attention toward predictive cues during fear learning Learning & memory (Cold Spring Harbor, N.Y.), 2015; 22(6): 289-93.
Sharpe Melissa, Killcross Simon   The prelimbic cortex uses contextual cues to modulate responding towards predictive stimuli during fear renewal Neurobiology of learning and memory, 2015; 118(6): 20-9.
Sharpe Melissa J, Killcross Simon   The prelimbic cortex contributes to the down-regulation of attention toward redundant cues Cerebral cortex (New York, N.Y. : 1991), 2014; 24(4): 1066-74.
Sharpe Melissa J, Killcross Simon   The prelimbic cortex uses higher-order cues to modulate both the acquisition and expression of conditioned fear Frontiers in systems neuroscience, 2014; 8(6): 235.
Sharpe Melissa J, Fardell Joanna E, Vardy Janette, Johnston Ian N   The chemotherapy agent oxaliplatin impairs the renewal of fear to an extinguished conditioned stimulus in rats Behavioural brain research, 2012; 227(1): 295-9.