The Miller Lab

  • Videos: Rhythmic Dynamics and Cognition 6-4-13

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    See lectures from the Cognitive Rhythms Collaborative conference on Rhythmic Dynamics and Cognition, which took place on June 4, 2013 at MIT.

    Talks:
    Elizabeth Buffalo: Neural Signals for Memory and Space in the Primate Medial Temporal Lobe
    Earl K. Miller: Cognition is Rhythmic
    Robert Knight: Oscillations and Human PFC
    Peter Ulhaas: Neural Oscillations in Schizophrenia: Perspectives from MEG
    Charles Schroeder: Neural Substrates of Temporal Prediction in Active Sensing
    Peter Brown: Beta Oscillations in the Human Basal Ganglia
    Christa van Dort: Optogenetic Activation of Cholinergic Neurons in the PPT Induces REM Sleep
    Rosalyn Doran: Dynamic Causal Modeling and Neurophysiology
    Liam Paninski: Statistical Neuroscience
    Astrid Prinz: How do rhythmically active circuits “analyze” their own activity?

  • Entrainment of Prefrontal Beta Oscillations Induces an Endogenous Echo and Impairs Memory Formation

    Miller Lab

    Recent studies have suggested that beta-band oscillatory synchrony plays a role in cognition.  For example, different networks of neurons in the prefrontal cortex dynamically synchronize at beta as animals switch between two different task rules (Buschman et al., 2012) suggesting that beta synchrony is forming the neural ensembles for the rules.  Different items simultaneously held in working memory line-up on different phases of beta/low-gamma oscillations, as if the brain is juggling the two items 30 times a second (Siegel et al., 2009). Hanslmayr et al disrupted these fine temporal relations by stimulating the human with beta-band TMS pulses.   Beta stimulation of the left inferior frontal gyrus impaired memory formation while stimulation at other frequencies did not.  There was a beta “echo” that outlasted the stimulation.  Subjects with better beta entrainment showed more memory impairment.  This lends support for the role of beta rhythms in cognition by showing a causal relationship between beta desynchrony and memory.

    This paper:
    Simon Hanslmayr, Jonas Matuschek, Marie-Christin Fellner, Entrainment of Prefrontal Beta Oscillations Induces an Endogenous Echo and Impairs Memory Formation, Current Biology, Available online 27 March 2014, ISSN 0960-9822

    References
    Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D. and Miller, E.K. (2012) Synchronous oscillatory neural ensembles for rules in the prefrontal cortex. Neuron, 76: 838-846.  View PDF

    Siegel, M., Warden, M.R., and Miller, E.K. (2009) Phase-dependent neuronal coding of objects in short-term memory. Proceedings of the National Academy of Sciences, 106: 21341-21346. View PDF »   Read commentary by Vogel and Fukuda

  • Deep Belief Networks Learn Context Dependent Behavior

    Miller Lab

    Mike Hasselmo and colleagues examined how the brain generalizes and infers new behaviors from previous experience.  They trained different styles of neural network models to learn context-dependent behaviors (i.e., the response to four stimuli, A B C D, mapped onto two different responses X Y differently in different contexts).  There were previously unseen stimuli whose response could be inferred from the other stimuli. They analyzed a Deep Belief Network, a Multi-Layer Perceptron, and the combination of a Deep Belief Network with a Linear Perceptron.  The combination of the Deep Belief Network with Linear Perceptron worked best.

    A Deep Belief Network has multiple layers of hidden units with connections between, but not within, the layers.

  • Attention in the real world: toward understanding its neural basis

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    Peelen and Kastner extend studies of attention in the lab (using simple, neutral displays) to the real world (complex, meaningful scenes).  They discuss interactions between what and where templates shaped by object familiarity, scene context, and memory

  • Neural mechanisms of dual-task interference and cognitive capacity limitation

    Miller Lab

    Think you can multitask well?  Watanabe and Funahasi show that task information signaled by neurons in the prefrontal cortex degrade when animals perform a competing, concurrent task.

  • Functional interactions of prefrontal cortex and the hippocampus in learning and memory

    Miller Lab

    An excellent review by Matt Shapiro and crew on an important topic.  They discuss complementary roles and bidirectional interactions between the prefrontal cortex and hippocampus.

  • Noise in Neural Populations Accounts for Errors in Working Memory

    Miller Lab

    Working memory is limited in capacity.  As you load more “stuff” into working memory, errors increase. Bays shows how this may happen.  Errors with increasing working memory load may be due to decreased signal strength of spiking neurons.  Humans can increase the precision of high priority stimuli in working memory at the expense of low priority stimuli.  The reduction in drive to neurons representing high priority stimuli can explain this tradeoff.

  • A Distinct Contribution of the Frontal Eye Field to the Visual Representation of Saccadic Targets

    Miller Lab

    Noudoost, Clark, and Moore deactivated the frontal eye fields (FEF) and recorded from visual cortical area V4.  This disrupted saccades to targets but *increased* pre-saccade activity in V4.  V4 neurons, however, showed reduced discrimination of the target stimulus.  It seems that the FEF provides details about the saccade target to visual cortex.

  • New book: The Oxford Handbook of Attention

    Miller Lab

    The Oxford Handbook of Attention is a veritable who’s who of attention research.  (Sorry that it costs $149 USD).
    Check out the table of contents:

    Part A: Introduction 
    1. Current landscape and historical context, Michael Posner
    Part B: Theoretical Models of Attention 
    2. Feature integration and guided search, Jeremy Wolfe
    3. Perceptual/Executive load theory, Polly Dalton and Nilli Lavie
    4. A multi-level account of selective attention, Sabine Kastner and John Serences
    5. Large-scale network model of control, Marsel Mesulam and Professor Anna Christina Nobre
    6. Multiple-demand network and adaptive coding, Mark Stokes and John Duncan
    Part C: Spatial Attention 
    7. Spatial covert attention: Perceptual Modulation, Marisa Carrasco
    8. Spatial orienting and attentional capture, Jan Theeuwes
    9. Neural systems of spatial attention (fMRI), Diane Beck and Sabine Kastner
    10. The time course of spatial attention: Insights from event-related brain potentials,Martin Eimer
    11. Neuronal Mechanisms of Spatial Attention in Visual Cerebral Cortex, Marlene Cohen and John Maunsell
    12. Cellular mechanisms of attentional control: Frontal, Jacqueline Gottlieb
    13. Neuronal mechanisms of attentional control: Frontal cortex, Kelsey L. Clark, Behrad Noudoost, and Robert J. Schafer and Professor Tirin Moore
    14. Neural mechanisms of Spatial Attention in the Visual Thalamus, Yuri B. Saalmann and Sabine Kastner
    15. Attentional Functions of the Superior Colliculus, Richard J. Krauzlis
    16. Orienting attention: a crossmodal perspective, Charles Spence
    17. Neuronal Dynamics and the Mechanistic Bases of Selective Attention, Charles E.Schroeder, Jose L. Herrero and Saskia Haegens
    18. The neuropharmacology of attention, Trevor Robbins
    19. Developing attention and self-regulation in childhood, Michael Posner
    Part D: Non-spatial Attention 
    20. Feature- and object-based attentional modulation in the human visual system,Miranda Scolari, Edward F. Ester, and John Serences
    21. Object- and feature-based attention: monkey physiology, Stefan Treue
    22. The Role of Brain Oscillations In The Temporal Limits of Attention, Kimron Shapiro and Simon Hanslmayr
    23. Dynamic Attention, Patrick Cavanagh, Lorella Battelli, and Alex O. Holcombe
    24. Temporal orienting, Anna Christina Nobre
    Part E: Interactions between Attention and Other Psychological Domains 
    25. Attention, Motivation, and Emotion, Luiz Pessoa
    26. Attention and executive functions
    27. Neural mechanisms for the executive control of attention, Earl K. Miller and Timothy J. Buschman
    28. Memory and Attention, Brice A. Kuhl and Marvin M. Chun
    29. Attention and decision-making, Christopher Summerfield and Tobias Egner
    30. Attention and action, Heiner Deubel
    Part F: Attention-related Disorders 
    31. Attention and awareness, Geraint Rees
    32. Attention and Aging, Theodore P. Zanto & Adam Gazzaley
    33. Unilateral Spatial Neglect, Guiseppe Vallar
    34. Neurological disorders of attention, Sanjay Manohar, Valerie Bonnelle and Masud Husain
    35. Balint’s syndrome and the Study of Attention, Lynn C. Robertson
    36. Rehabilitation of Attention Functions, Ian H. Robertson and Redmond G O’Connell
    Part G: Computational Models 
    37. Theory of visual attention, Claus Bundesen and Thomas Habekost
    38. Bottom up and contextual effects, Laurent Itti and Ali Borji
    39. Bayesian models, Angela Yu
    Part H: Conclusions 
    40. Outlook and Future Directions, Anna Christina Nobre and Sabine Kastner

  • Timing of Single-Neuron and Local Field Potential Responses in the Human Medial Temporal Lobe

    Miller Lab

    Rey et al recorded local field potentials and neuron spikes from the human medial temporal lobe during a recognition task.  Single-neuron responses were preceded by a global increase in theta oscillations and a local and stimulus-specific increase in gamma oscillations.  The LFPs responses were correlated with conscious recognition and neuron spiking was time-locked to the LFPs.  They suggest that theta reflects a global recognition signal whereas phase-locked of neurons to gamma reflects activation of local circuits that represent the recognized stimulus.