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Brown LS, Cho JR, Bolkan SS, Nieh EH, Schottdorf M, Tank DW, Brody CD, Witten IB, Goldman MS. Neural circuit models for evidence accumulation through choice-selective sequences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555612. [PMID: 38234715 PMCID: PMC10793437 DOI: 10.1101/2023.09.01.555612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Decision making is traditionally thought to be mediated by populations of neurons whose firing rates persistently accumulate evidence across time. However, recent decision-making experiments in rodents have observed neurons across the brain that fire sequentially as a function of spatial position or time, rather than persistently, with the subset of neurons in the sequence depending on the animal's choice. We develop two new candidate circuit models, in which evidence is encoded either in the relative firing rates of two competing chains of neurons or in the network location of a stereotyped pattern ("bump") of neural activity. Encoded evidence is then faithfully transferred between neuronal populations representing different positions or times. Neural recordings from four different brain regions during a decision-making task showed that, during the evidence accumulation period, different brain regions displayed tuning curves consistent with different candidate models for evidence accumulation. This work provides mechanistic models and potential neural substrates for how graded-value information may be precisely accumulated within and transferred between neural populations, a set of computations fundamental to many cognitive operations.
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Large EW, Roman I, Kim JC, Cannon J, Pazdera JK, Trainor LJ, Rinzel J, Bose A. Dynamic models for musical rhythm perception and coordination. Front Comput Neurosci 2023; 17:1151895. [PMID: 37265781 PMCID: PMC10229831 DOI: 10.3389/fncom.2023.1151895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Rhythmicity permeates large parts of human experience. Humans generate various motor and brain rhythms spanning a range of frequencies. We also experience and synchronize to externally imposed rhythmicity, for example from music and song or from the 24-h light-dark cycles of the sun. In the context of music, humans have the ability to perceive, generate, and anticipate rhythmic structures, for example, "the beat." Experimental and behavioral studies offer clues about the biophysical and neural mechanisms that underlie our rhythmic abilities, and about different brain areas that are involved but many open questions remain. In this paper, we review several theoretical and computational approaches, each centered at different levels of description, that address specific aspects of musical rhythmic generation, perception, attention, perception-action coordination, and learning. We survey methods and results from applications of dynamical systems theory, neuro-mechanistic modeling, and Bayesian inference. Some frameworks rely on synchronization of intrinsic brain rhythms that span the relevant frequency range; some formulations involve real-time adaptation schemes for error-correction to align the phase and frequency of a dedicated circuit; others involve learning and dynamically adjusting expectations to make rhythm tracking predictions. Each of the approaches, while initially designed to answer specific questions, offers the possibility of being integrated into a larger framework that provides insights into our ability to perceive and generate rhythmic patterns.
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Affiliation(s)
- Edward W. Large
- Department of Psychological Sciences, University of Connecticut, Mansfield, CT, United States
- Department of Physics, University of Connecticut, Mansfield, CT, United States
| | - Iran Roman
- Music and Audio Research Laboratory, New York University, New York, NY, United States
| | - Ji Chul Kim
- Department of Psychological Sciences, University of Connecticut, Mansfield, CT, United States
| | - Jonathan Cannon
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Jesse K. Pazdera
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Laurel J. Trainor
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - John Rinzel
- Center for Neural Science, New York University, New York, NY, United States
- Courant Institute of Mathematical Sciences, New York University, New York, NY, United States
| | - Amitabha Bose
- Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, United States
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Momi D, Prete G, Di Crosta A, La Malva P, Palumbo R, Ceccato I, Bartolini E, Palumbo R, Mammarella N, Fasolo M, Di Domenico A. Time reproduction, bisection and doubling: a novel paradigm to investigate the effect of the internal clock on time estimation. PSYCHOLOGICAL RESEARCH 2022; 87:1549-1559. [PMID: 36183026 DOI: 10.1007/s00426-022-01745-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/19/2022] [Indexed: 10/07/2022]
Abstract
Time perception is not always veridical, but it can be modulated by changes in internal and external context. The most-acknowledged theory in this regard hypothesises the existence of an internal clock allowing us to subjectively estimate time intervals. The aim of the present study is to investigate the possible effect of such an internal clock, measured as the ability to reproduce a target duration, in the mental manipulation of time: 63 healthy participants were asked to Bisect and to Double reference time intervals, besides Reproducing them. Moreover, to investigate whether time processing might be predicted by individual differences, handedness, anxiety, and personality traits were also assessed by means of standardized questionnaires. Results show that participants correctly Reproduce time intervals (internal clock), but they overestimate time intervals during Bisection and underestimate them during Doubling. We explain this unexpected pattern of results as a kind of aftereffect, due to the short-term retention (adaptation) to the subjective representation of shorter (Bisection) vs longer (Doubling) intervals, respectively. Moreover, hierarchic regression models reveal that some personality traits can predict Bisection accuracy, but they clearly show that the best predictor for both Bisection and Doubling is the accuracy in Reproducing time intervals, confirming the fundamental role of the internal clock in time estimation. We conclude that time estimation is a unique skill, mostly independent from inter-individual differences, and the new paradigms introduced here (bisection vs doubling) reveal that the correct functioning of the internal clock also explains the ability to mentally manipulate the time.
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Affiliation(s)
- Davide Momi
- Krembil Institute for Neuroinformatics, Toronto, Canada
| | - Giulia Prete
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Adolfo Di Crosta
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Pasquale La Malva
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Rocco Palumbo
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy.
| | - Irene Ceccato
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Emanuela Bartolini
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Riccardo Palumbo
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Nicola Mammarella
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Mirco Fasolo
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
| | - Alberto Di Domenico
- Department of Psychological, Health and Territorial Sciences, Università degli Studi G. d'Annunzio Chieti-Pescara, Chieti, Italy
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