Literature DB >> 27790629

Neurocomputational Models of Interval and Pattern Timing.

Nicholas F Hardy1, Dean V Buonomano1.   

Abstract

Most of the computations and tasks performed by the brain require the ability to tell time, and process and generate temporal patterns. Thus, there is a diverse set of neural mechanisms in place to allow the brain to tell time across a wide range of scales: from interaural delays on the order of microseconds to circadian rhythms and beyond. Temporal processing is most sophisticated on the scale of tens of milliseconds to a few seconds, because it is within this range that the brain must recognize and produce complex temporal patterns-such as those that characterize speech and music. Most models of timing, however, have focused primarily on simple intervals and durations, thus it is not clear whether they will generalize to complex pattern-based temporal tasks. Here, we review neurobiologically based models of timing in the subsecond range, focusing on whether they generalize to tasks that require placing consecutive intervals in the context of an overall pattern, that is, pattern timing.

Entities:  

Keywords:  Neural dynamics; State-Dependent network; Synfire Chain; Timing; neural trajectory; population clock

Year:  2016        PMID: 27790629      PMCID: PMC5077164          DOI: 10.1016/j.cobeha.2016.01.012

Source DB:  PubMed          Journal:  Curr Opin Behav Sci        ISSN: 2352-1546


  71 in total

Review 1.  Computer simulation of cerebellar information processing.

Authors:  J F Medina; M D Mauk
Journal:  Nat Neurosci       Date:  2000-11       Impact factor: 24.884

Review 2.  The neural basis of temporal processing.

Authors:  Michael D Mauk; Dean V Buonomano
Journal:  Annu Rev Neurosci       Date:  2004       Impact factor: 12.449

Review 3.  What makes us tick? Functional and neural mechanisms of interval timing.

Authors:  Catalin V Buhusi; Warren H Meck
Journal:  Nat Rev Neurosci       Date:  2005-10       Impact factor: 34.870

4.  Timing in the absence of clocks: encoding time in neural network states.

Authors:  Uma R Karmarkar; Dean V Buonomano
Journal:  Neuron       Date:  2007-02-01       Impact factor: 17.173

5.  Learning reward timing in cortex through reward dependent expression of synaptic plasticity.

Authors:  Jeffrey P Gavornik; Marshall G Hussain Shuler; Yonatan Loewenstein; Mark F Bear; Harel Z Shouval
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-03       Impact factor: 11.205

Review 6.  State-dependent computations: spatiotemporal processing in cortical networks.

Authors:  Dean V Buonomano; Wolfgang Maass
Journal:  Nat Rev Neurosci       Date:  2009-01-15       Impact factor: 34.870

7.  A neurocomputational model for optimal temporal processing.

Authors:  Joachim Hass; Stefan Blaschke; Thomas Rammsayer; J Michael Herrmann
Journal:  J Comput Neurosci       Date:  2008-04-01       Impact factor: 1.621

8.  Speech recognition with primarily temporal cues.

Authors:  R V Shannon; F G Zeng; V Kamath; J Wygonski; M Ekelid
Journal:  Science       Date:  1995-10-13       Impact factor: 47.728

9.  Duration as a cue to the perception of a phrase boundary.

Authors:  D R Scott
Journal:  J Acoust Soc Am       Date:  1982-04       Impact factor: 1.840

Review 10.  Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments.

Authors:  Anubhuti Goel; Dean V Buonomano
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2014-01-20       Impact factor: 6.237

View more
  12 in total

1.  Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

Authors:  N F Hardy; Dean V Buonomano
Journal:  Neural Comput       Date:  2017-11-21       Impact factor: 2.026

2.  The Persistence of Memory: How the Brain Encodes Time in Memory.

Authors:  Sundeep Teki; Bon-Mi Gu; Warren H Meck
Journal:  Curr Opin Behav Sci       Date:  2017-10

3.  Neural population clocks: Encoding time in dynamic patterns of neural activity.

Authors:  Shanglin Zhou; Dean V Buonomano
Journal:  Behav Neurosci       Date:  2022-04-21       Impact factor: 2.154

4.  Short-term depression and transient memory in sensory cortex.

Authors:  Grant Gillary; Rüdiger von der Heydt; Ernst Niebur
Journal:  J Comput Neurosci       Date:  2017-10-13       Impact factor: 1.621

5.  The Time Is Up: Compression of Visual Time Interval Estimations of Bimodal Aperiodic Patterns.

Authors:  Fabiola Duarte; Luis Lemus
Journal:  Front Integr Neurosci       Date:  2017-08-08

6.  Learning and recognition of tactile temporal sequences by mice and humans.

Authors:  Michael R Bale; Malamati Bitzidou; Anna Pitas; Leonie S Brebner; Lina Khazim; Stavros T Anagnou; Caitlin D Stevenson; Miguel Maravall
Journal:  Elife       Date:  2017-08-16       Impact factor: 8.140

7.  Dynamic representation of time in brain states.

Authors:  Fernanda Dantas Bueno; Vanessa C Morita; Raphael Y de Camargo; Marcelo B Reyes; Marcelo S Caetano; André M Cravo
Journal:  Sci Rep       Date:  2017-04-10       Impact factor: 4.379

8.  Temporal-Sequential Learning With a Brain-Inspired Spiking Neural Network and Its Application to Musical Memory.

Authors:  Qian Liang; Yi Zeng; Bo Xu
Journal:  Front Comput Neurosci       Date:  2020-07-02       Impact factor: 2.380

9.  A model of temporal scaling correctly predicts that motor timing improves with speed.

Authors:  Nicholas F Hardy; Vishwa Goudar; Juan L Romero-Sosa; Dean V Buonomano
Journal:  Nat Commun       Date:  2018-11-09       Impact factor: 14.919

10.  A neuromechanistic model for rhythmic beat generation.

Authors:  Amitabha Bose; Áine Byrne; John Rinzel
Journal:  PLoS Comput Biol       Date:  2019-05-09       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.