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Bruce R, Weber MA, Bova A, Volkman R, Jacobs C, Sivakumar K, Kim Y, Curtu R, Narayanan N. Complementary cognitive roles for D2-MSNs and D1-MSNs during interval timing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.25.550569. [PMID: 37546735 PMCID: PMC10402049 DOI: 10.1101/2023.07.25.550569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The role of striatal pathways in cognitive processing is unclear. We studied dorsomedial striatal cognitive processing during interval timing, an elementary cognitive task that requires mice to estimate intervals of several seconds and involves working memory for temporal rules as well as attention to the passage of time. We harnessed optogenetic tagging to record from striatal D2-dopamine receptor-expressing medium spiny neurons (D2-MSNs) in the indirect pathway and from D1-dopamine receptor-expressing MSNs (D1-MSNs) in the direct pathway. We found that D2-MSNs and D1-MSNs exhibited distinct dynamics over temporal intervals as quantified by principal component analyses and trial-by-trial generalized linear models. MSN recordings helped construct and constrain a four-parameter drift-diffusion computational model. This model predicted that disrupting either D2-MSNs or D1-MSNs would increase interval timing response times and alter MSN firing. In line with this prediction, we found that optogenetic inhibition or pharmacological disruption of either D2-MSNs or D1-MSNs increased interval timing response times. Pharmacologically disrupting D2-MSNs or D1-MSNs also changed MSN dynamics and degraded trial-by-trial temporal decoding. Together, our findings demonstrate that D2-MSNs and D1-MSNs make complementary contributions to interval timing despite opposing dynamics, implying that striatal direct and indirect pathways work together to shape temporal control of action. These data provide novel insight into basal ganglia cognitive operations beyond movement and have implications for human striatal diseases and therapies targeting striatal pathways.
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Martel AC, Apicella P. Insights into the interaction between time and reward prediction on the activity of striatal tonically active neurons: A pilot study in rhesus monkeys. Physiol Rep 2024; 12:e70037. [PMID: 39245818 PMCID: PMC11381318 DOI: 10.14814/phy2.70037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 08/21/2024] [Accepted: 08/26/2024] [Indexed: 09/10/2024] Open
Abstract
Prior studies have documented the role of the striatum and its dopaminergic input in time processing, but the contribution of local striatal cholinergic innervation has not been specifically investigated. To address this issue, we recorded the activity of tonically active neurons (TANs), thought to be cholinergic interneurons in the striatum, in two male macaques performing self-initiated movements after specified intervals in the seconds range have elapsed. The behavioral data showed that movement timing was adjusted according to the temporal requirements. About one-third of all recorded TANs displayed brief depressions in firing in response to the cue that indicates the interval duration, and the strength of these modulations was, in some instances, related to the timing of movement. The rewarding outcome of actions also impacted TAN activity, as reflected by stronger responses to the cue paralleled by weaker responses to reward when monkeys performed correctly timed movements over consecutive trials. It therefore appears that TAN responses may act as a start signal for keeping track of time and reward prediction could be incorporated in this signaling function. We conclude that the role of the striatal cholinergic TAN system in time processing is embedded in predicting rewarding outcomes during timing behavior.
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Affiliation(s)
- A C Martel
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Université, CNRS, Marseille, France
| | - P Apicella
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Université, CNRS, Marseille, France
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3
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Yang Z, Inagaki M, Gerfen CR, Fontolan L, Inagaki HK. Integrator dynamics in the cortico-basal ganglia loop underlie flexible motor timing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.29.601348. [PMID: 39005437 PMCID: PMC11244898 DOI: 10.1101/2024.06.29.601348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Flexible control of motor timing is crucial for behavior. Before volitional movement begins, the frontal cortex and striatum exhibit ramping spiking activity, with variable ramp slopes anticipating movement onsets. This activity in the cortico-basal ganglia loop may function as an adjustable 'timer,' triggering actions at the desired timing. However, because the frontal cortex and striatum share similar ramping dynamics and are both necessary for timing behaviors, distinguishing their individual roles in this timer function remains challenging. To address this, we conducted perturbation experiments combined with multi-regional electrophysiology in mice performing a flexible lick-timing task. Following transient silencing of the frontal cortex, cortical and striatal activity swiftly returned to pre-silencing levels and resumed ramping, leading to a shift in lick timing close to the silencing duration. Conversely, briefly inhibiting the striatum caused a gradual decrease in ramping activity in both regions, with ramping resuming from post-inhibition levels, shifting lick timing beyond the inhibition duration. Thus, inhibiting the frontal cortex and striatum effectively paused and rewound the timer, respectively. These findings suggest the striatum is a part of the network that temporally integrates input from the frontal cortex and generates ramping activity that regulates motor timing.
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Redinbaugh MJ, Saalmann YB. Contributions of Basal Ganglia Circuits to Perception, Attention, and Consciousness. J Cogn Neurosci 2024; 36:1620-1642. [PMID: 38695762 PMCID: PMC11223727 DOI: 10.1162/jocn_a_02177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
Research into ascending sensory pathways and cortical networks has generated detailed models of perception. These same cortical regions are strongly connected to subcortical structures, such as the basal ganglia (BG), which have been conceptualized as playing key roles in reinforcement learning and action selection. However, because the BG amasses experiential evidence from higher and lower levels of cortical hierarchies, as well as higher-order thalamus, it is well positioned to dynamically influence perception. Here, we review anatomical, functional, and clinical evidence to demonstrate how the BG can influence perceptual processing and conscious states. This depends on the integrative relationship between cortex, BG, and thalamus, which allows contributions to sensory gating, predictive processing, selective attention, and representation of the temporal structure of events.
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Affiliation(s)
| | - Yuri B Saalmann
- University of Wisconsin-Madison
- Wisconsin National Primate Research Center
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Rodriguez AC, Perich MG, Miller L, Humphries MD. Motor cortex latent dynamics encode spatial and temporal arm movement parameters independently. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.26.542452. [PMID: 37292834 PMCID: PMC10246015 DOI: 10.1101/2023.05.26.542452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The fluid movement of an arm requires multiple spatiotemporal parameters to be set independently. Recent studies have argued that arm movements are generated by the collective dynamics of neurons in motor cortex. An untested prediction of this hypothesis is that independent parameters of movement must map to independent components of the neural dynamics. Using a task where monkeys made a sequence of reaching movements to randomly placed targets, we show that the spatial and temporal parameters of arm movements are independently encoded in the low-dimensional trajectories of population activity in motor cortex: Each movement's direction corresponds to a fixed neural trajectory through neural state space and its speed to how quickly that trajectory is traversed. Recurrent neural network models show this coding allows independent control over the spatial and temporal parameters of movement by separate network parameters. Our results support a key prediction of the dynamical systems view of motor cortex, but also argue that not all parameters of movement are defined by different trajectories of population activity.
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Affiliation(s)
| | - Matthew G. Perich
- Département de neurosciences, Faculté de médecine, Université de Montréal, Montréal, Canada
- Québec Artificial Intelligence Institute (Mila), Québec, Canada
| | - Lee Miller
- Northwestern University, Department of Biomedical Engineering, Chicago, USA
| | - Mark D. Humphries
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
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6
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Vignoud G, Venance L, Touboul JD. Anti-Hebbian plasticity drives sequence learning in striatum. Commun Biol 2024; 7:555. [PMID: 38724614 PMCID: PMC11082161 DOI: 10.1038/s42003-024-06203-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 04/17/2024] [Indexed: 05/12/2024] Open
Abstract
Spatio-temporal activity patterns have been observed in a variety of brain areas in spontaneous activity, prior to or during action, or in response to stimuli. Biological mechanisms endowing neurons with the ability to distinguish between different sequences remain largely unknown. Learning sequences of spikes raises multiple challenges, such as maintaining in memory spike history and discriminating partially overlapping sequences. Here, we show that anti-Hebbian spike-timing dependent plasticity (STDP), as observed at cortico-striatal synapses, can naturally lead to learning spike sequences. We design a spiking model of the striatal output neuron receiving spike patterns defined as sequential input from a fixed set of cortical neurons. We use a simple synaptic plasticity rule that combines anti-Hebbian STDP and non-associative potentiation for a subset of the presented patterns called rewarded patterns. We study the ability of striatal output neurons to discriminate rewarded from non-rewarded patterns by firing only after the presentation of a rewarded pattern. In particular, we show that two biological properties of striatal networks, spiking latency and collateral inhibition, contribute to an increase in accuracy, by allowing a better discrimination of partially overlapping sequences. These results suggest that anti-Hebbian STDP may serve as a biological substrate for learning sequences of spikes.
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Affiliation(s)
- Gaëtan Vignoud
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France
| | - Laurent Venance
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France.
| | - Jonathan D Touboul
- Department of Mathematics and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA.
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7
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Reinartz S, Fassihi A, Ravera M, Paz L, Pulecchi F, Gigante M, Diamond ME. Direct contribution of the sensory cortex to the judgment of stimulus duration. Nat Commun 2024; 15:1712. [PMID: 38402290 PMCID: PMC10894222 DOI: 10.1038/s41467-024-45970-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/06/2024] [Indexed: 02/26/2024] Open
Abstract
Decision making frequently depends on monitoring the duration of sensory events. To determine whether, and how, the perception of elapsed time derives from the neuronal representation of the stimulus itself, we recorded and optogenetically modulated vibrissal somatosensory cortical activity as male rats judged vibration duration. Perceived duration was dilated by optogenetic excitation. A second set of rats judged vibration intensity; here, optogenetic excitation amplified the intensity percept, demonstrating sensory cortex to be the common gateway both to time and to stimulus feature processing. A model beginning with the membrane currents evoked by vibrissal and optogenetic drive and culminating in the representation of perceived time successfully replicated rats' choices. Time perception is thus as deeply intermeshed within the sensory processing pathway as is the sense of touch itself, suggesting that the experience of time may be further investigated with the toolbox of sensory coding.
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Affiliation(s)
- Sebastian Reinartz
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
- Brain & Sound Lab, Department of Biomedicine, Basel University, 4056, Basel, Switzerland
| | - Arash Fassihi
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
- Department of Physics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Maria Ravera
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
| | - Luciano Paz
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
| | - Francesca Pulecchi
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
| | - Marco Gigante
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy
| | - Mathew E Diamond
- SENSEx Lab, International School for Advanced Studies (SISSA), 34136, Trieste, Italy.
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Rolando F, Kononowicz TW, Duhamel JR, Doyère V, Wirth S. Distinct neural adaptations to time demand in the striatum and the hippocampus. Curr Biol 2024; 34:156-170.e7. [PMID: 38141617 DOI: 10.1016/j.cub.2023.11.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 10/18/2023] [Accepted: 11/30/2023] [Indexed: 12/25/2023]
Abstract
How do neural codes adjust to track time across a range of resolutions, from milliseconds to multi-seconds, as a function of the temporal frequency at which events occur? To address this question, we studied time-modulated cells in the striatum and the hippocampus, while macaques categorized three nested intervals within the sub-second or the supra-second range (up to 1, 2, 4, or 8 s), thereby modifying the temporal resolution needed to solve the task. Time-modulated cells carried more information for intervals with explicit timing demand, than for any other interval. The striatum, particularly the caudate, supported the most accurate temporal prediction throughout all time ranges. Strikingly, its temporal readout adjusted non-linearly to the time range, suggesting that the striatal resolution shifted from a precise millisecond to a coarse multi-second range as a function of demand. This is in line with monkey's behavioral latencies, which indicated that they tracked time until 2 s but employed a coarse categorization strategy for durations beyond. By contrast, the hippocampus discriminated only the beginning from the end of intervals, regardless of the range. We propose that the hippocampus may provide an overall poor signal marking an event's beginning, whereas the striatum optimizes neural resources to process time throughout an interval adapting to the ongoing timing necessity.
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Affiliation(s)
- Felipe Rolando
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, Université Lyon 1, 67 boulevard Pinel, 69500 Bron, France
| | - Tadeusz W Kononowicz
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, Université Lyon 1, 67 boulevard Pinel, 69500 Bron, France; Université Paris-Saclay, CNRS, Institut des Neurosciences Paris-Saclay (NeuroPSI), 91400 Saclay, France; Institute of Psychology, The Polish Academy of Sciences, ul. Jaracza 1, 00-378 Warsaw, Poland
| | - Jean-René Duhamel
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, Université Lyon 1, 67 boulevard Pinel, 69500 Bron, France
| | - Valérie Doyère
- Université Paris-Saclay, CNRS, Institut des Neurosciences Paris-Saclay (NeuroPSI), 91400 Saclay, France
| | - Sylvia Wirth
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, Université Lyon 1, 67 boulevard Pinel, 69500 Bron, France.
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Oby ER, Degenhart AD, Grigsby EM, Motiwala A, McClain NT, Marino PJ, Yu BM, Batista AP. Dynamical constraints on neural population activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.03.573543. [PMID: 38260549 PMCID: PMC10802336 DOI: 10.1101/2024.01.03.573543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The manner in which neural activity unfolds over time is thought to be central to sensory, motor, and cognitive functions in the brain. Network models have long posited that the brain's computations involve time courses of activity that are shaped by the underlying network. A prediction from this view is that the activity time courses should be difficult to violate. We leveraged a brain-computer interface (BCI) to challenge monkeys to violate the naturally-occurring time courses of neural population activity that we observed in motor cortex. This included challenging animals to traverse the natural time course of neural activity in a time-reversed manner. Animals were unable to violate the natural time courses of neural activity when directly challenged to do so. These results provide empirical support for the view that activity time courses observed in the brain indeed reflect the underlying network-level computational mechanisms that they are believed to implement.
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10
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Merchant H, de Lafuente V. A Second Introduction to the Neurobiology of Interval Timing. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:3-23. [PMID: 38918343 DOI: 10.1007/978-3-031-60183-5_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
Time is a critical variable that organisms must be able to measure in order to survive in a constantly changing environment. Initially, this paper describes the myriad of contexts where time is estimated or predicted and suggests that timing is not a single process and probably depends on a set of different neural mechanisms. Consistent with this hypothesis, the explosion of neurophysiological and imaging studies in the last 10 years suggests that different brain circuits and neural mechanisms are involved in the ability to tell and use time to control behavior across contexts. Then, we develop a conceptual framework that defines time as a family of different phenomena and propose a taxonomy with sensory, perceptual, motor, and sensorimotor timing as the pillars of temporal processing in the range of hundreds of milliseconds.
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Affiliation(s)
- Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico.
| | - Victor de Lafuente
- Institute of Neurobiology National Autonomous University of Mexico, Querétaro, Mexico
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11
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Soldado-Magraner S, Buonomano DV. Neural Sequences and the Encoding of Time. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:81-93. [PMID: 38918347 DOI: 10.1007/978-3-031-60183-5_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.
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Affiliation(s)
| | - Dean V Buonomano
- Department of Neurobiology, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.
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12
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Rueda-Orozco PE, Hidalgo-Balbuena AE, González-Pereyra P, Martinez-Montalvo MG, Báez-Cordero AS. The Interactions of Temporal and Sensory Representations in the Basal Ganglia. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:141-158. [PMID: 38918350 DOI: 10.1007/978-3-031-60183-5_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
In rodents and primates, interval estimation has been associated with a complex network of cortical and subcortical structures where the dorsal striatum plays a paramount role. Diverse evidence ranging from individual neurons to population activity has demonstrated that this area hosts temporal-related neural representations that may be instrumental for the perception and production of time intervals. However, little is known about how temporal representations interact with other well-known striatal representations, such as kinematic parameters of movements or somatosensory representations. An attractive hypothesis suggests that somatosensory representations may serve as the scaffold for complex representations such as elapsed time. Alternatively, these representations may coexist as independent streams of information that could be integrated into downstream nuclei, such as the substantia nigra or the globus pallidus. In this review, we will revise the available information suggesting an instrumental role of sensory representations in the construction of temporal representations at population and single-neuron levels throughout the basal ganglia.
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Affiliation(s)
- Pavel E Rueda-Orozco
- Institute of Neurobiology, National Autonomous University of México, Querétaro, Mexico.
| | | | | | | | - Ana S Báez-Cordero
- Institute of Neurobiology, National Autonomous University of México, Querétaro, Mexico
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13
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Ordás CM, Alonso-Frech F. The neural basis of somatosensory temporal discrimination threshold as a paradigm for time processing in the sub-second range: An updated review. Neurosci Biobehav Rev 2024; 156:105486. [PMID: 38040074 DOI: 10.1016/j.neubiorev.2023.105486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/20/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND AND OBJECTIVE The temporal aspect of somesthesia is a feature of any somatosensory process and a pre-requisite for the elaboration of proper behavior. Time processing in the milliseconds range is crucial for most of behaviors in everyday life. The somatosensory temporal discrimination threshold (STDT) is the ability to perceive two successive stimuli as separate in time, and deals with time processing in this temporal range. Herein, we focus on the physiology of STDT, on a background of the anatomophysiology of somesthesia and the neurobiological substrates of timing. METHODS A review of the literature through PubMed & Cochrane databases until March 2023 was performed with inclusion and exclusion criteria following PRISMA recommendations. RESULTS 1151 abstracts were identified. 4 duplicate records were discarded before screening. 957 abstracts were excluded because of redundancy, less relevant content or not English-written. 4 were added after revision. Eventually, 194 articles were included. CONCLUSIONS STDT encoding relies on intracortical inhibitory S1 function and is modulated by the basal ganglia-thalamic-cortical interplay through circuits involving the nigrostriatal dopaminergic pathway and probably the superior colliculus.
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Affiliation(s)
- Carlos M Ordás
- Universidad Rey Juan Carlos, Móstoles, Madrid, Spain; Department of Neurology, Hospital Rey Juan Carlos, Móstoles, Madrid, Spain.
| | - Fernando Alonso-Frech
- Department of Neurology, Hospital Clínico San Carlos, Universidad Complutense de Madrid, Spain
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14
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Merchant H, Mendoza G, Pérez O, Betancourt A, García-Saldivar P, Prado L. Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:117-140. [PMID: 38918349 DOI: 10.1007/978-3-031-60183-5_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.
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Affiliation(s)
- Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico.
| | - Germán Mendoza
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | - Oswaldo Pérez
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | | | | | - Luis Prado
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
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15
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Lin D, Huang AZ, Richards BA. Temporal encoding in deep reinforcement learning agents. Sci Rep 2023; 13:22335. [PMID: 38102369 PMCID: PMC10724179 DOI: 10.1038/s41598-023-49847-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/12/2023] [Indexed: 12/17/2023] Open
Abstract
Neuroscientists have observed both cells in the brain that fire at specific points in time, known as "time cells", and cells whose activity steadily increases or decreases over time, known as "ramping cells". It is speculated that time and ramping cells support temporal computations in the brain and carry mnemonic information. However, due to the limitations in animal experiments, it is difficult to determine how these cells really contribute to behavior. Here, we show that time cells and ramping cells naturally emerge in the recurrent neural networks of deep reinforcement learning models performing simulated interval timing and working memory tasks, which have learned to estimate expected rewards in the future. We show that these cells do indeed carry information about time and items stored in working memory, but they contribute to behavior in large part by providing a dynamic representation on which policy can be computed. Moreover, the information that they do carry depends on both the task demands and the variables provided to the models. Our results suggest that time cells and ramping cells could contribute to temporal and mnemonic calculations, but the way in which they do so may be complex and unintuitive to human observers.
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Affiliation(s)
- Dongyan Lin
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada.
- Mila, Montreal, QC, H2S 3H1, Canada.
| | - Ann Zixiang Huang
- Mila, Montreal, QC, H2S 3H1, Canada
- School of Computer Science, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Blake Aaron Richards
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Mila, Montreal, QC, H2S 3H1, Canada
- School of Computer Science, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, H3A 0G4, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, ON, M5G 1M1, Canada
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16
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Robbe D. Lost in time: Relocating the perception of duration outside the brain. Neurosci Biobehav Rev 2023; 153:105312. [PMID: 37467906 DOI: 10.1016/j.neubiorev.2023.105312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/08/2023] [Indexed: 07/21/2023]
Abstract
It is well-accepted in neuroscience that animals process time internally to estimate the duration of intervals lasting between one and several seconds. More than 100 years ago, Henri Bergson nevertheless remarked that, because animals have memory, their inner experience of time is ever-changing, making duration impossible to measure internally and time a source of change. Bergson proposed that quantifying the inner experience of time requires its externalization in movements (observed or self-generated), as their unfolding leaves measurable traces in space. Here, studies across species are reviewed and collectively suggest that, in line with Bergson's ideas, animals spontaneously solve time estimation tasks through a movement-based spatialization of time. Moreover, the well-known scalable anticipatory responses of animals to regularly spaced rewards can be explained by the variable pressure of time on reward-oriented actions. Finally, the brain regions linked with time perception overlap with those implicated in motor control, spatial navigation and motivation. Thus, instead of considering time as static information processed by the brain, it might be fruitful to conceptualize it as a kind of force to which animals are more or less sensitive depending on their internal state and environment.
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Affiliation(s)
- David Robbe
- Institut de Neurobiologie de la Méditerranée (INMED), INSERM, Marseille, France; Aix-Marseille Université, Marseille, France.
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17
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Torres NL, Castro SL, Silva S. Beat cues facilitate time estimation at longer intervals. Front Psychol 2023; 14:1130788. [PMID: 37842702 PMCID: PMC10576433 DOI: 10.3389/fpsyg.2023.1130788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 09/18/2023] [Indexed: 10/17/2023] Open
Abstract
Introduction Time perception in humans can be relative (beat-based) or absolute (duration-based). Although the classic view in the field points to different neural substrates underlying beat-based vs. duration-based mechanisms, recent neuroimaging evidence provided support to a unified model wherein these two systems overlap. In line with this, previous research demonstrated that internalized beat cues benefit motor reproduction of longer intervals (> 5.5 s) by reducing underestimation, but little is known about this effect on pure perceptual tasks. The present study was designed to investigate whether and how interval estimation is modulated by available beat cues. Methods To that end, we asked 155 participants to estimate auditory intervals ranging from 500 ms to 10 s, while manipulating the presence of cues before the interval, as well as the reinforcement of these cues by beat-related interference within the interval (vs. beat-unrelated and no interference). Results Beat cues aided time estimation depending on interval duration: for intervals longer than 5 s, estimation was better in the cue than in the no-cue condition. Specifically, the levels of underestimation decreased in the presence of cues, indicating that beat cues had a facilitating effect on time perception very similar to the one observed previously for time production. Discussion Interference had no effects, suggesting that this manipulation was not effective. Our findings are consistent with the idea of cooperation between beat- and duration-based systems and suggest that this cooperation is quite similar across production and perception.
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Affiliation(s)
- Nathércia L. Torres
- Speech Laboratory, Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
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18
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Pourmohammadi A, Sanayei M. Context-specific and context-invariant computations of interval timing. Front Neurosci 2023; 17:1249502. [PMID: 37799342 PMCID: PMC10547875 DOI: 10.3389/fnins.2023.1249502] [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: 06/28/2023] [Accepted: 09/06/2023] [Indexed: 10/07/2023] Open
Abstract
Introduction An accurate sense of time is crucial in flexible sensorimotor control and other cognitive functions. However, it remains unknown how multiple timing computations in different contexts interact to shape our behavior. Methods We asked 41 healthy human subjects to perform timing tasks that differed in the sensorimotor domain (sensory timing vs. motor timing) and effector (hand vs. saccadic eye movement). To understand how these different behavioral contexts contribute to timing behavior, we applied a three-stage Bayesian model to behavioral data. Results Our results demonstrate that the Bayesian model for each effector could not describe bias in the other effector. Similarly, in each task the model-predicted data could not describe bias in the other task. These findings suggest that the measurement stage of interval timing is context-specific in the sensorimotor and effector domains. We also showed that temporal precision is context-invariant in the effector domain, unlike temporal accuracy. Discussion This combination of context-specific and context-invariant computations across sensorimotor and effector domains suggests overlapping and distributed computations as the underlying mechanism of timing in different contexts.
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Affiliation(s)
- Ahmad Pourmohammadi
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mehdi Sanayei
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Center for Translational Neuroscience (CTN), Isfahan University of Medical Sciences, Isfahan, Iran
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19
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Monteiro T, Rodrigues FS, Pexirra M, Cruz BF, Gonçalves AI, Rueda-Orozco PE, Paton JJ. Using temperature to analyze the neural basis of a time-based decision. Nat Neurosci 2023; 26:1407-1416. [PMID: 37443279 DOI: 10.1038/s41593-023-01378-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 06/12/2023] [Indexed: 07/15/2023]
Abstract
The basal ganglia are thought to contribute to decision-making and motor control. These functions are critically dependent on timing information, which can be extracted from the evolving state of neural populations in their main input structure, the striatum. However, it is debated whether striatal activity underlies latent, dynamic decision processes or kinematics of overt movement. Here, we measured the impact of temperature on striatal population activity and the behavior of rats, and compared the observed effects with neural activity and behavior collected in multiple versions of a temporal categorization task. Cooling caused dilation, and warming contraction, of both neural activity and patterns of judgment in time, mimicking endogenous decision-related variability in striatal activity. However, temperature did not similarly affect movement kinematics. These data provide compelling evidence that the timecourse of evolving striatal activity dictates the speed of a latent process that is used to guide choices, but not continuous motor control. More broadly, they establish temporal scaling of population activity as a likely neural basis for variability in timing behavior.
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Affiliation(s)
- Tiago Monteiro
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- Department of Biology, University of Oxford, Oxford, UK
| | | | - Margarida Pexirra
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Bruno F Cruz
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- NeuroGEARS Ltd., London, UK
| | - Ana I Gonçalves
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | | | - Joseph J Paton
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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20
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Levcik D, Sugi AH, Aguilar-Rivera M, Pochapski JA, Baltazar G, Pulido LN, Villas-Boas CA, Fuentes-Flores R, Nicola SM, Da Cunha C. Nucleus Accumbens Shell Neurons Encode the Kinematics of Reward Approach Locomotion. Neuroscience 2023; 524:181-196. [PMID: 37330195 PMCID: PMC10527230 DOI: 10.1016/j.neuroscience.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/30/2023] [Accepted: 06/02/2023] [Indexed: 06/19/2023]
Abstract
The nucleus accumbens (NAc) is considered an interface between motivation and action, with NAc neurons playing an important role in promoting reward approach. However, the encoding by NAc neurons that contributes to this role remains unknown. We recorded 62 NAc neurons in male Wistar rats (n = 5) running towards rewarded locations in an 8-arm radial maze. Variables related to locomotor approach kinematics were the best predictors of the firing rate for most NAc neurons. Nearly 18% of the recorded neurons were inhibited during the entire approach run (locomotion-off cells), suggesting that reduction in firing of these neurons promotes initiation of locomotor approach. 27% of the neurons presented a peak of activity during acceleration followed by a valley during deceleration (acceleration-on cells). Together, these neurons accounted for most of the speed and acceleration encoding identified in our analysis. In contrast, a further 16% of neurons presented a valley during acceleration followed by a peak just prior to or after reaching reward (deceleration-on cells). These findings suggest that these three classes of NAc neurons influence the time course of speed changes during locomotor approach to reward.
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Affiliation(s)
- David Levcik
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 142 20 Prague, Czech Republic
| | - Adam H Sugi
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Department of Pharmacology, Universidade Federal do Paraná, Curitiba, Brazil; Department of Biochemistry, Universidade Federal do Paraná, Curitiba, Brazil
| | - Marcelo Aguilar-Rivera
- Department of Bioengineering, University of California, 9500 Gilman Drive MC 0412, La Jolla, San Diego 92093, USA
| | - José A Pochapski
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Department of Pharmacology, Universidade Federal do Paraná, Curitiba, Brazil
| | - Gabriel Baltazar
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Department of Pharmacology, Universidade Federal do Paraná, Curitiba, Brazil; Department of Biochemistry, Universidade Federal do Paraná, Curitiba, Brazil
| | - Laura N Pulido
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Department of Pharmacology, Universidade Federal do Paraná, Curitiba, Brazil
| | - Cyrus A Villas-Boas
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil
| | - Romulo Fuentes-Flores
- Departamento de Neurociencia, Facultad de Medicina, Universidad de Chile, Av. Independencia 1027, Independencia 8380453, Santiago, Chile
| | - Saleem M Nicola
- Department of Neuroscience, Albert Einstein College of Medicine, 1300 Morris Park Ave, Bronx, NY 10461, USA; Department of Psychiatry, Albert Einstein College of Medicine, New York, USA
| | - Claudio Da Cunha
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil; Department of Pharmacology, Universidade Federal do Paraná, Curitiba, Brazil; Department of Biochemistry, Universidade Federal do Paraná, Curitiba, Brazil.
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21
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Robbe D, Safaie M. Hot times for the dorsal striatum. Nat Neurosci 2023; 26:1320-1321. [PMID: 37443280 DOI: 10.1038/s41593-023-01386-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2023]
Affiliation(s)
- David Robbe
- Institut de Neurobiologie de la Méditerranée (INMED), INSERM, Turing Center for Living System, Aix Marseille Université, Marseille, France.
| | - Mostafa Safaie
- Department of Bioengineering, Imperial College London, London, UK
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22
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Zhou S, Seay M, Taxidis J, Golshani P, Buonomano DV. Multiplexing working memory and time in the trajectories of neural networks. Nat Hum Behav 2023; 7:1170-1184. [PMID: 37081099 PMCID: PMC10913811 DOI: 10.1038/s41562-023-01592-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/22/2023] [Indexed: 04/22/2023]
Abstract
Working memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components. In both cases, the task-irrelevant component influenced performance. We then developed recurrent neural network (RNN) simulations that revealed that cue-specific neural sequences, which multiplexed WM and time, emerged as the dominant regime that captured the behavioural findings. During training, RNN dynamics transitioned from low-dimensional ramps to high-dimensional neural sequences, and depending on task requirements, steady-state or ramping activity was also observed. Analysis of RNN structure revealed that neural sequences relied primarily on inhibitory connections, and could survive the deletion of all excitatory-to-excitatory connections. Our results indicate that in some instances WM is encoded in time-varying neural activity because of the importance of predicting when WM will be used.
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Affiliation(s)
- Shanglin Zhou
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Michael Seay
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Jiannis Taxidis
- Program in Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Peyman Golshani
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Integrative Center for Learning and Memory, Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Semel Institute for Neuroscience and Behavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- West Los Angeles VA Medical Center, Los Angeles, CA, USA
| | - Dean V Buonomano
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, CA, USA.
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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23
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Post S, Mol W, Abu-Wishah O, Ali S, Rahmatullah N, Goel A. Multimodal Temporal Pattern Discrimination Is Encoded in Visual Cortical Dynamics. eNeuro 2023; 10:ENEURO.0047-23.2023. [PMID: 37487713 PMCID: PMC10368206 DOI: 10.1523/eneuro.0047-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/12/2023] [Accepted: 06/29/2023] [Indexed: 07/26/2023] Open
Abstract
Discriminating between temporal features in sensory stimuli is critical to complex behavior and decision-making. However, how sensory cortical circuit mechanisms contribute to discrimination between subsecond temporal components in sensory events is unclear. To elucidate the mechanistic underpinnings of timing in primary visual cortex (V1), we recorded from V1 using two-photon calcium imaging in awake-behaving mice performing a go/no-go discrimination timing task, which was composed of patterns of subsecond audiovisual stimuli. In both conditions, activity during the early stimulus period was temporally coordinated with the preferred stimulus. However, while network activity increased in the preferred condition, network activity was increasingly suppressed in the nonpreferred condition over the stimulus period. Multiple levels of analyses suggest that discrimination between subsecond intervals that are contained in rhythmic patterns can be accomplished by local neural dynamics in V1.
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Affiliation(s)
- Sam Post
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - William Mol
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Omar Abu-Wishah
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Shazia Ali
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Noorhan Rahmatullah
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Anubhuti Goel
- Department of Psychology, University of California, Riverside, Riverside, California 92521
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24
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Xie T, Huang C, Zhang Y, Liu J, Yao H. Influence of Recent Trial History on Interval Timing. Neurosci Bull 2023; 39:559-575. [PMID: 36209314 PMCID: PMC10073370 DOI: 10.1007/s12264-022-00954-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 07/10/2022] [Indexed: 11/30/2022] Open
Abstract
Interval timing is involved in a variety of cognitive behaviors such as associative learning and decision-making. While it has been shown that time estimation is adaptive to the temporal context, it remains unclear how interval timing behavior is influenced by recent trial history. Here we found that, in mice trained to perform a licking-based interval timing task, a decrease of inter-reinforcement interval in the previous trial rapidly shifted the time of anticipatory licking earlier. Optogenetic inactivation of the anterior lateral motor cortex (ALM), but not the medial prefrontal cortex, for a short time before reward delivery caused a decrease in the peak time of anticipatory licking in the next trial. Electrophysiological recordings from the ALM showed that the response profiles preceded by short and long inter-reinforcement intervals exhibited task-engagement-dependent temporal scaling. Thus, interval timing is adaptive to recent experience of the temporal interval, and ALM activity during time estimation reflects recent experience of interval.
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Affiliation(s)
- Taorong Xie
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Can Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yijie Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jing Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Haishan Yao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 201210, China.
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25
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Howard C, Simen P. A Time to Remember: Neural Insights into Rapid Updating of Timed Behaviors. Neurosci Bull 2023; 39:699-702. [PMID: 36525232 PMCID: PMC10073378 DOI: 10.1007/s12264-022-00999-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 11/06/2022] [Indexed: 12/23/2022] Open
Affiliation(s)
| | - Patrick Simen
- Neuroscience Department, Oberlin College, Oberlin, OH, 44074, USA
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26
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Beiran M, Meirhaeghe N, Sohn H, Jazayeri M, Ostojic S. Parametric control of flexible timing through low-dimensional neural manifolds. Neuron 2023; 111:739-753.e8. [PMID: 36640766 PMCID: PMC9992137 DOI: 10.1016/j.neuron.2022.12.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 09/23/2022] [Accepted: 12/08/2022] [Indexed: 01/15/2023]
Abstract
Biological brains possess an unparalleled ability to adapt behavioral responses to changing stimuli and environments. How neural processes enable this capacity is a fundamental open question. Previous works have identified two candidate mechanisms: a low-dimensional organization of neural activity and a modulation by contextual inputs. We hypothesized that combining the two might facilitate generalization and adaptation in complex tasks. We tested this hypothesis in flexible timing tasks where dynamics play a key role. Examining trained recurrent neural networks, we found that confining the dynamics to a low-dimensional subspace allowed tonic inputs to parametrically control the overall input-output transform, enabling generalization to novel inputs and adaptation to changing conditions. Reverse-engineering and theoretical analyses demonstrated that this parametric control relies on a mechanism where tonic inputs modulate the dynamics along non-linear manifolds while preserving their geometry. Comparisons with data from behaving monkeys confirmed the behavioral and neural signatures of this mechanism.
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Affiliation(s)
- Manuel Beiran
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL University, 75005 Paris, France; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Nicolas Meirhaeghe
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS, Aix-Marseille Université, Marseille 13005, France
| | - Hansem Sohn
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mehrdad Jazayeri
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Srdjan Ostojic
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL University, 75005 Paris, France.
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27
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Koh TH, Bishop WE, Kawashima T, Jeon BB, Srinivasan R, Mu Y, Wei Z, Kuhlman SJ, Ahrens MB, Chase SM, Yu BM. Dimensionality reduction of calcium-imaged neuronal population activity. NATURE COMPUTATIONAL SCIENCE 2023; 3:71-85. [PMID: 37476302 PMCID: PMC10358781 DOI: 10.1038/s43588-022-00390-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 12/05/2022] [Indexed: 07/22/2023]
Abstract
Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.
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Affiliation(s)
- Tze Hui Koh
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - William E. Bishop
- Center for the Neural Basis of Cognition, PA
- Department of Machine Learning, Carnegie Mellon University, PA
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Takashi Kawashima
- Janelia Research Campus, Howard Hughes Medical Institute, VA
- Department of Brain Sciences, Weizmann Institute of Science, Israel
| | - Brian B. Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - Ranjani Srinivasan
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Johns Hopkins University, MD
| | - Yu Mu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, China
| | - Ziqiang Wei
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Sandra J. Kuhlman
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Biological Sciences, Carnegie Mellon University, PA
| | - Misha B. Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Steven M. Chase
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
| | - Byron M. Yu
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Carnegie Mellon University, PA
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28
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Alhassen W, Alhassen S, Chen J, Monfared RV, Alachkar A. Cilia in the Striatum Mediate Timing-Dependent Functions. Mol Neurobiol 2023; 60:545-565. [PMID: 36322337 PMCID: PMC9849326 DOI: 10.1007/s12035-022-03095-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/16/2022] [Indexed: 11/07/2022]
Abstract
Almost all brain cells contain cilia, antennae-like microtubule-based organelles. Yet, the significance of cilia, once considered vestigial organelles, in the higher-order brain functions is unknown. Cilia act as a hub that senses and transduces environmental sensory stimuli to generate an appropriate cellular response. Similarly, the striatum, a brain structure enriched in cilia, functions as a hub that receives and integrates various types of environmental information to drive appropriate motor response. To understand cilia's role in the striatum functions, we used loxP/Cre technology to ablate cilia from the dorsal striatum of male mice and monitored the behavioral consequences. Our results revealed an essential role for striatal cilia in the acquisition and brief storage of information, including learning new motor skills, but not in long-term consolidation of information or maintaining habitual/learned motor skills. A fundamental aspect of all disrupted functions was the "time perception/judgment deficit." Furthermore, the observed behavioral deficits form a cluster pertaining to clinical manifestations overlapping across psychiatric disorders that involve the striatum functions and are known to exhibit timing deficits. Thus, striatal cilia may act as a calibrator of the timing functions of the basal ganglia-cortical circuit by maintaining proper timing perception. Our findings suggest that dysfunctional cilia may contribute to the pathophysiology of neuro-psychiatric disorders, as related to deficits in timing perception.
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Affiliation(s)
- Wedad Alhassen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Sammy Alhassen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Jiaqi Chen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Roudabeh Vakil Monfared
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Amal Alachkar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA ,UC Irvine Center for the Neurobiology of Learning and Memory, University of California-Irvine, Irvine, CA 92697 USA ,Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA 92697 USA
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De Corte BJ, Akdoğan B, Balsam PD. Temporal scaling and computing time in neural circuits: Should we stop watching the clock and look for its gears? Front Behav Neurosci 2022; 16:1022713. [PMID: 36570701 PMCID: PMC9773401 DOI: 10.3389/fnbeh.2022.1022713] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 10/31/2022] [Indexed: 12/13/2022] Open
Abstract
Timing underlies a variety of functions, from walking to perceiving causality. Neural timing models typically fall into one of two categories-"ramping" and "population-clock" theories. According to ramping models, individual neurons track time by gradually increasing or decreasing their activity as an event approaches. To time different intervals, ramping neurons adjust their slopes, ramping steeply for short intervals and vice versa. In contrast, according to "population-clock" models, multiple neurons track time as a group, and each neuron can fire nonlinearly. As each neuron changes its rate at each point in time, a distinct pattern of activity emerges across the population. To time different intervals, the brain learns the population patterns that coincide with key events. Both model categories have empirical support. However, they often differ in plausibility when applied to certain behavioral effects. Specifically, behavioral data indicate that the timing system has a rich computational capacity, allowing observers to spontaneously compute novel intervals from previously learned ones. In population-clock theories, population patterns map to time arbitrarily, making it difficult to explain how different patterns can be computationally combined. Ramping models are viewed as more plausible, assuming upstream circuits can set the slope of ramping neurons according to a given computation. Critically, recent studies suggest that neurons with nonlinear firing profiles often scale to time different intervals-compressing for shorter intervals and stretching for longer ones. This "temporal scaling" effect has led to a hybrid-theory where, like a population-clock model, population patterns encode time, yet like a ramping neuron adjusting its slope, the speed of each neuron's firing adapts to different intervals. Here, we argue that these "relative" population-clock models are as computationally plausible as ramping theories, viewing population-speed and ramp-slope adjustments as equivalent. Therefore, we view identifying these "speed-control" circuits as a key direction for evaluating how the timing system performs computations. Furthermore, temporal scaling highlights that a key distinction between different neural models is whether they propose an absolute or relative time-representation. However, we note that several behavioral studies suggest the brain processes both scales, cautioning against a dichotomy.
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Affiliation(s)
- Benjamin J. De Corte
- Department of Psychology, Columbia University, New York, NY, United States
- Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, NY, United States
| | - Başak Akdoğan
- Department of Psychology, Columbia University, New York, NY, United States
- Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, NY, United States
| | - Peter D. Balsam
- Department of Psychology, Columbia University, New York, NY, United States
- Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, NY, United States
- Department of Neuroscience and Behavior, Barnard College, New York, NY, United States
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30
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Polti I, Nau M, Kaplan R, van Wassenhove V, Doeller CF. Rapid encoding of task regularities in the human hippocampus guides sensorimotor timing. eLife 2022; 11:e79027. [PMID: 36317500 PMCID: PMC9625083 DOI: 10.7554/elife.79027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 10/02/2022] [Indexed: 11/17/2022] Open
Abstract
The brain encodes the statistical regularities of the environment in a task-specific yet flexible and generalizable format. Here, we seek to understand this process by bridging two parallel lines of research, one centered on sensorimotor timing, and the other on cognitive mapping in the hippocampal system. By combining functional magnetic resonance imaging (fMRI) with a fast-paced time-to-contact (TTC) estimation task, we found that the hippocampus signaled behavioral feedback received in each trial as well as performance improvements across trials along with reward-processing regions. Critically, it signaled performance improvements independent from the tested intervals, and its activity accounted for the trial-wise regression-to-the-mean biases in TTC estimation. This is in line with the idea that the hippocampus supports the rapid encoding of temporal context even on short time scales in a behavior-dependent manner. Our results emphasize the central role of the hippocampus in statistical learning and position it at the core of a brain-wide network updating sensorimotor representations in real time for flexible behavior.
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Affiliation(s)
- Ignacio Polti
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer’s Disease, Norwegian University of Science and TechnologyTrondheimNorway
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Matthias Nau
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer’s Disease, Norwegian University of Science and TechnologyTrondheimNorway
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Raphael Kaplan
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer’s Disease, Norwegian University of Science and TechnologyTrondheimNorway
- Department of Basic Psychology, Clinical Psychology, and Psychobiology, Universitat Jaume ICastellón de la PlanaSpain
| | - Virginie van Wassenhove
- CEA DRF/Joliot, NeuroSpin; INSERM, Cognitive Neuroimaging Unit; CNRS, Université Paris-SaclayGif-Sur-YvetteFrance
| | - Christian F Doeller
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer’s Disease, Norwegian University of Science and TechnologyTrondheimNorway
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Wilhelm Wundt Institute of Psychology, Leipzig UniversityLeipzigGermany
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31
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Tunes GC, Fermino de Oliveira E, Vieira EUP, Caetano MS, Cravo AM, Bussotti Reyes M. Time encoding migrates from prefrontal cortex to dorsal striatum during learning of a self-timed response duration task. eLife 2022; 11:65495. [PMID: 36169996 PMCID: PMC9519146 DOI: 10.7554/elife.65495] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
Abstract
Although time is a fundamental dimension of life, we do not know how brain areas cooperate to keep track and process time intervals. Notably, analyses of neural activity during learning are rare, mainly because timing tasks usually require training over many days. We investigated how the time encoding evolves when animals learn to time a 1.5 s interval. We designed a novel training protocol where rats go from naive- to proficient-level timing performance within a single session, allowing us to investigate neuronal activity from very early learning stages. We used pharmacological experiments and machine-learning algorithms to evaluate the level of time encoding in the medial prefrontal cortex and the dorsal striatum. Our results show a double dissociation between the medial prefrontal cortex and the dorsal striatum during temporal learning, where the former commits to early learning stages while the latter engages as animals become proficient in the task.
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Affiliation(s)
- Gabriela C Tunes
- Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Sao Bernardo do Campo, Brazil
| | | | - Estevão U P Vieira
- Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Sao Bernardo do Campo, Brazil
| | - Marcelo S Caetano
- Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Sao Bernardo do Campo, Brazil.,Instituto Nacional de Ciência e Tecnologia sobre Comportamento, Cognição e Ensino, Brazil
| | - André M Cravo
- Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Sao Bernardo do Campo, Brazil
| | - Marcelo Bussotti Reyes
- Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Sao Bernardo do Campo, Brazil
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32
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Tsao A, Yousefzadeh SA, Meck WH, Moser MB, Moser EI. The neural bases for timing of durations. Nat Rev Neurosci 2022; 23:646-665. [PMID: 36097049 DOI: 10.1038/s41583-022-00623-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2022] [Indexed: 11/10/2022]
Abstract
Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.
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Affiliation(s)
- Albert Tsao
- Department of Biology, Stanford University, Stanford, CA, USA.
| | | | - Warren H Meck
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - May-Britt Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Edvard I Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway.
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33
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Cruz BF, Guiomar G, Soares S, Motiwala A, Machens CK, Paton JJ. Action suppression reveals opponent parallel control via striatal circuits. Nature 2022; 607:521-526. [PMID: 35794480 DOI: 10.1038/s41586-022-04894-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 05/23/2022] [Indexed: 01/24/2023]
Abstract
The direct and indirect pathways of the basal ganglia are classically thought to promote and suppress action, respectively1. However, the observed co-activation of striatal direct and indirect medium spiny neurons2 (dMSNs and iMSNs, respectively) has challenged this view. Here we study these circuits in mice performing an interval categorization task that requires a series of self-initiated and cued actions and, critically, a sustained period of dynamic action suppression. Although movement produced the co-activation of iMSNs and dMSNs in the sensorimotor, dorsolateral striatum (DLS), fibre photometry and photo-identified electrophysiological recordings revealed signatures of functional opponency between the two pathways during action suppression. Notably, optogenetic inhibition showed that DLS circuits were largely engaged to suppress-and not promote-action. Specifically, iMSNs on a given hemisphere were dynamically engaged to suppress tempting contralateral action. To understand how such regionally specific circuit function arose, we constructed a computational reinforcement learning model that reproduced key features of behaviour, neural activity and optogenetic inhibition. The model predicted that parallel striatal circuits outside the DLS learned the action-promoting functions, generating the temptation to act. Consistent with this, optogenetic inhibition experiments revealed that dMSNs in the associative, dorsomedial striatum, in contrast to those in the DLS, promote contralateral actions. These data highlight how opponent interactions between multiple circuit- and region-specific basal ganglia processes can lead to behavioural control, and establish a critical role for the sensorimotor indirect pathway in the proactive suppression of tempting actions.
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Affiliation(s)
- Bruno F Cruz
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal
| | - Gonçalo Guiomar
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal
| | - Sofia Soares
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal.,Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Asma Motiwala
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal.,Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Christian K Machens
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal
| | - Joseph J Paton
- Champalimaud Neuroscience Programme, Champalimaud Research, Champalimaud Foundation, Lisbon, PT, Portugal.
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34
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Efficient coding of cognitive variables underlies dopamine response and choice behavior. Nat Neurosci 2022; 25:738-748. [PMID: 35668173 DOI: 10.1038/s41593-022-01085-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 04/26/2022] [Indexed: 11/26/2022]
Abstract
Reward expectations based on internal knowledge of the external environment are a core component of adaptive behavior. However, internal knowledge may be inaccurate or incomplete due to errors in sensory measurements. Some features of the environment may also be encoded inaccurately to minimize representational costs associated with their processing. In this study, we investigated how reward expectations are affected by features of internal representations by studying behavior and dopaminergic activity while mice make time-based decisions. We show that several possible representations allow a reinforcement learning agent to model animals' overall performance during the task. However, only a small subset of highly compressed representations simultaneously reproduced the co-variability in animals' choice behavior and dopaminergic activity. Strikingly, these representations predict an unusual distribution of response times that closely match animals' behavior. These results inform how constraints of representational efficiency may be expressed in encoding representations of dynamic cognitive variables used for reward-based computations.
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35
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Lourenco I, Mattila R, Ventura R, Wahlberg B. A Biologically Inspired Computational Model of Time Perception. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2021.3120301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Ines Lourenco
- Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Robert Mattila
- Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Rodrigo Ventura
- Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon, Portugal
| | - Bo Wahlberg
- Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden
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36
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Pimentel-Farfan AK, Báez-Cordero AS, Peña-Rangel TM, Rueda-Orozco PE. Cortico-striatal circuits for bilaterally coordinated movements. SCIENCE ADVANCES 2022; 8:eabk2241. [PMID: 35245127 PMCID: PMC8896801 DOI: 10.1126/sciadv.abk2241] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 01/12/2022] [Indexed: 06/01/2023]
Abstract
Movement initiation and control require the orchestrated activity of sensorimotor cortical and subcortical regions. However, the exact contribution of specific pathways and interactions to the final behavioral outcome are still under debate. Here, by combining structural lesions, pathway-specific optogenetic manipulations and freely moving electrophysiological recordings in rats, we studied cortico-striatal interactions in the context of forelimb bilaterally coordinated movements. We provide evidence indicating that bilateral actions are initiated by motor cortical regions where intratelencephalic bilateral cortico-striatal (bcs-IT) projections recruit the sensorimotor striatum to provide stability and duration to already commanded bilateral movements. Furthermore, striatal spiking activity was correlated with movement duration and kinematic parameters of the execution. bcs-IT stimulation affected only the representation of movement duration but spared that of kinematics. Our findings confirm the modular organization of information processing in the striatum and its involvement in moment-to-moment movement control but not initiation or selection.
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37
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Encoding time in neural dynamic regimes with distinct computational tradeoffs. PLoS Comput Biol 2022; 18:e1009271. [PMID: 35239644 PMCID: PMC8893702 DOI: 10.1371/journal.pcbi.1009271] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 02/08/2022] [Indexed: 11/19/2022] Open
Abstract
Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamic patterns at the level of single intervals, could exhibit fundamentally different properties, including, generalization, the connectivity structure of the trained networks, and the contribution of excitatory and inhibitory neurons. Critically, depending on the task structure RNNs were better suited for generalization or robustness to noise. Further analysis revealed different connection patterns underlying the different regimes. Our results predict that apparently similar neural dynamic patterns at the population level (e.g., neural sequences) can exhibit fundamentally different computational properties in regards to their ability to generalize to novel stimuli and their robustness to noise—and that these differences are associated with differences in network connectivity and distinct contributions of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time. The ability to tell time and anticipate when external events will occur are among the most fundamental computations the brain performs. Converging evidence suggests the brain encodes time through changing patterns of neural activity. Different temporal tasks, however, have distinct computational requirements, such as the need to flexibly scale temporal patterns or generalize to novel inputs. To understand how networks can encode time and satisfy different computational requirements we trained recurrent neural networks (RNNs) on two timing tasks that have previously been used in behavioral studies. Both tasks required producing identically timed output patterns. Using a novel framework to quantify how networks encode different intervals, we found that similar patterns of neural activity—neural sequences—were associated with fundamentally different underlying mechanisms, including the connectivity patterns of the RNNs. Critically, depending on the task the RNNs were trained on, they were better suited for generalization or robustness to noise. Our results predict that similar patterns of neural activity can be produced by distinct RNN configurations, which in turn have fundamentally different computational tradeoffs. Our results also predict that differences in task structure account for some of the experimentally observed variability in how networks encode time.
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38
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Calderon CB, Verguts T, Frank MJ. Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits. PLoS Comput Biol 2022; 18:e1009854. [PMID: 35108283 PMCID: PMC8843237 DOI: 10.1371/journal.pcbi.1009854] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 02/14/2022] [Accepted: 01/21/2022] [Indexed: 11/18/2022] Open
Abstract
Adaptive sequential behavior is a hallmark of human cognition. In particular, humans can learn to produce precise spatiotemporal sequences given a certain context. For instance, musicians can not only reproduce learned action sequences in a context-dependent manner, they can also quickly and flexibly reapply them in any desired tempo or rhythm without overwriting previous learning. Existing neural network models fail to account for these properties. We argue that this limitation emerges from the fact that sequence information (i.e., the position of the action) and timing (i.e., the moment of response execution) are typically stored in the same neural network weights. Here, we augment a biologically plausible recurrent neural network of cortical dynamics to include a basal ganglia-thalamic module which uses reinforcement learning to dynamically modulate action. This “associative cluster-dependent chain” (ACDC) model modularly stores sequence and timing information in distinct loci of the network. This feature increases computational power and allows ACDC to display a wide range of temporal properties (e.g., multiple sequences, temporal shifting, rescaling, and compositionality), while still accounting for several behavioral and neurophysiological empirical observations. Finally, we apply this ACDC network to show how it can learn the famous “Thunderstruck” song intro and then flexibly play it in a “bossa nova” rhythm without further training. How do humans flexibly adapt action sequences? For instance, musicians can learn a song and quickly speed up or slow down the tempo, or even play the song following a completely different rhythm (e.g., a rock song using a bossa nova rhythm). In this work, we build a biologically plausible network of cortico-basal ganglia interactions that explains how this temporal flexibility may emerge in the brain. Crucially, our model factorizes sequence order and action timing, respectively represented in cortical and basal ganglia dynamics. This factorization allows full temporal flexibility, i.e. the timing of a learned action sequence can be recomposed without interfering with the order of the sequence. As such, our model is capable of learning asynchronous action sequences, and flexibly shift, rescale, and recompose them, while accounting for biological data.
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Affiliation(s)
- Cristian Buc Calderon
- Department of Cognitive, Linguistic & Psychological Sciences, Brown University, Providence, Rhode Island, United States of America
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
- * E-mail:
| | - Tom Verguts
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Michael J. Frank
- Department of Cognitive, Linguistic & Psychological Sciences, Brown University, Providence, Rhode Island, United States of America
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
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39
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Auditory time thresholds in the range of milliseconds but not seconds are impaired in ADHD. Sci Rep 2022; 12:1352. [PMID: 35079097 PMCID: PMC8789844 DOI: 10.1038/s41598-022-05425-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 01/11/2022] [Indexed: 11/08/2022] Open
Abstract
The literature on time perception in individuals with ADHD is extensive but inconsistent, probably reflecting the use of different tasks and performances indexes. A sample of 40 children/adolescents (20 with ADHD, 20 neurotypical) was engaged in two identical psychophysical tasks measuring auditory time thresholds in the milliseconds (0.25–1 s) and seconds (0.75–3 s) ranges. Results showed a severe impairment in ADHD for milliseconds thresholds (Log10BF = 1.9). The deficit remained strong even when non-verbal IQ was regressed out and correlation with age suggests a developmental delay. In the seconds range, thresholds were indistinguishable between the two groups (Log10BF = − 0.5) and not correlated with milliseconds thresholds. Our results largely confirm previous evidence suggesting partially separate mechanisms for time perception in the ranges of milliseconds and seconds. Moreover, since the evidence suggests that time perception of milliseconds stimuli might load relatively less on cognitive control and working memory, compared to longer durations, the current results are consistent with a pure timing deficit in individuals with ADHD.
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Popik P, Hogendorf A, Bugno R, Khoo SYS, Zajdel P, Malikowska-Racia N, Nikiforuk A, Golebiowska J. Effects of ketamine optical isomers, psilocybin, psilocin and norpsilocin on time estimation and cognition in rats. Psychopharmacology (Berl) 2022; 239:1689-1703. [PMID: 35234983 PMCID: PMC9166826 DOI: 10.1007/s00213-021-06020-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 11/01/2021] [Indexed: 12/22/2022]
Abstract
RATIONALE Ketamine and psilocybin belong to the rapid-acting antidepressants but they also produce psychotomimetic effects including timing distortion. It is currently debatable whether these are essential for their therapeutic actions. As depressed patients report that the "time is dragging," we hypothesized that ketamine and psilocybin-like compounds may produce an opposite effect, i.e., time underestimation, purportedly contributing to their therapeutic properties. OBJECTIVES Timing was tested following administration of (R)- and (S)-ketamine, and psilocybin, psilocin, and norpsilocin in the discrete-trial temporal discrimination task (TDT) in male rats. Timing related to premature responses, and cognitive and unspecific effects of compounds were tested in the 5-choice serial reaction time task (5-CSRTT) in the standard 1-s, and "easier" 2-s stimulus duration conditions, as well as in the vITI variant promoting impulsive responses. RESULTS (S)-ketamine (15 but not 3.75 or 7.5 mg/kg) shifted psychometric curve to the right in TDT and reduced premature responses in 5-CSRTT, suggesting expected time underestimation, but it also decreased the accuracy of temporal discrimination and increased response and reward latencies, decreased correct responses, and increased incorrect responses. While (R)-ketamine did not affect timing and produced no unspecific actions, it reduced incorrect responses in TDT and increased accuracy in 5-CSRTT, suggesting pro-cognitive effects. Psilocin and psilocybin produced mainly unspecific effects in both tasks, while norpsilocin showed no effects. CONCLUSIONS Time underestimation produced by (S)-ketamine could be associated with its antidepressant effects; however, it was accompanied with severe behavioral disruption. We also hypothesize that behavioral disruption produced by psychedelics objectively reflects their psychotomimetic-like actions.
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Affiliation(s)
- Piotr Popik
- Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343, Kraków, Poland.
| | - Adam Hogendorf
- Medicinal Chemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Ryszard Bugno
- Medicinal Chemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Shaun Yon-Seng Khoo
- Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Montreal, QC Canada
| | - Pawel Zajdel
- Department of Organic Chemistry, Jagiellonian University Medical College, Medyczna 9, 30-383 Kraków, Poland
| | - Natalia Malikowska-Racia
- Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Agnieszka Nikiforuk
- Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
| | - Joanna Golebiowska
- Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland
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41
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Martinez MC, Zold CL, Coletti MA, Murer MG, Belluscio MA. Dorsal striatum coding for the timely execution of action sequences. eLife 2022; 11:74929. [PMID: 36426715 PMCID: PMC9699698 DOI: 10.7554/elife.74929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 10/27/2022] [Indexed: 11/27/2022] Open
Abstract
The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore–exploit balance.
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Affiliation(s)
- Maria Cecilia Martinez
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular “Dr. Héctor Maldonado”Buenos AiresArgentina,Universidad de Buenos Aires - CONICET, Instituto de Fisiología y Biofísica “Dr. Bernardo Houssay” (IFIBIO-Houssay), Grupo de Neurociencia de SistemasBuenos AiresArgentina
| | - Camila Lidia Zold
- Universidad de Buenos Aires - CONICET, Instituto de Fisiología y Biofísica “Dr. Bernardo Houssay” (IFIBIO-Houssay), Grupo de Neurociencia de SistemasBuenos AiresArgentina,Universidad de Buenos Aires, Facultad de Ciencias Médicas, Departamento de FisiologíaBuenos AiresArgentina
| | - Marcos Antonio Coletti
- Universidad de Buenos Aires - CONICET, Instituto de Fisiología y Biofísica “Dr. Bernardo Houssay” (IFIBIO-Houssay), Grupo de Neurociencia de SistemasBuenos AiresArgentina,Universidad de Buenos Aires, Facultad de Ciencias Médicas, Departamento de FisiologíaBuenos AiresArgentina
| | - Mario Gustavo Murer
- Universidad de Buenos Aires - CONICET, Instituto de Fisiología y Biofísica “Dr. Bernardo Houssay” (IFIBIO-Houssay), Grupo de Neurociencia de SistemasBuenos AiresArgentina,Universidad de Buenos Aires, Facultad de Ciencias Médicas, Departamento de FisiologíaBuenos AiresArgentina
| | - Mariano Andrés Belluscio
- Universidad de Buenos Aires - CONICET, Instituto de Fisiología y Biofísica “Dr. Bernardo Houssay” (IFIBIO-Houssay), Grupo de Neurociencia de SistemasBuenos AiresArgentina,Universidad de Buenos Aires, Facultad de Ciencias Médicas, Departamento de FisiologíaBuenos AiresArgentina
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42
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Henke J, Bunk D, von Werder D, Häusler S, Flanagin VL, Thurley K. Distributed coding of duration in rodent prefrontal cortex during time reproduction. eLife 2021; 10:71612. [PMID: 34939922 PMCID: PMC8786316 DOI: 10.7554/elife.71612] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/14/2021] [Indexed: 11/20/2022] Open
Abstract
As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in nonprimate species. Here, we use time interval reproduction to study rodent behavior and its neural correlates in the context of magnitude estimation. We show that gerbils display primate-like magnitude estimation characteristics in time reproduction. Most prominently their behavioral responses show a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results help unveil the organizing neural principles of time reproduction and perhaps magnitude estimation in general.
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Affiliation(s)
- Josephine Henke
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - David Bunk
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Dina von Werder
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Stefan Häusler
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Virginia L Flanagin
- German Center for Vertigo and Balance Disorders,, Ludwig-Maximilians-Universitaet Muenchen, Munich, Germany
| | - Kay Thurley
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
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43
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Time coding in rat dorsolateral striatum. Neuron 2021; 109:3663-3673.e6. [PMID: 34508666 DOI: 10.1016/j.neuron.2021.08.020] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 05/28/2021] [Accepted: 08/16/2021] [Indexed: 12/20/2022]
Abstract
To assess the role of dorsolateral striatum (DLS) in time coding, we recorded neuronal activity in rats tasked with comparing the durations of two sequential vibrations. Bayesian decoding of population activity revealed a representation of the unfolding of the trial across time. However, further analyses demonstrated a distinction between the encoding of trial time and perceived time. First, DLS did not show a privileged representation of the stimulus durations compared with other time spans. Second, higher intensity vibrations were perceived as longer; however, time decoded from DLS was unaffected by vibration intensity. Third, DLS did not encode stimulus duration differently on correct versus incorrect trials. Finally, in rats trained to compare the intensities of two sequential vibrations, stimulus duration was encoded even though it was a perceptually irrelevant feature. These findings lead us to posit that temporal information is inherent to DLS activity irrespective of the rat's ongoing percept.
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44
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Ahissar E. Time in the brain: Encoding does not mean perceiving. Neuron 2021; 109:3542-3544. [PMID: 34793705 DOI: 10.1016/j.neuron.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The neural basis of time perception remains an enigma. In rats performing interval judgment tasks, striatal time coding has drawn attention as one potential substrate. Toso et al. (2021b) find that such time coding does not account for stimulus duration perception.
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Affiliation(s)
- Ehud Ahissar
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
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45
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Vandaele Y, Ottenheimer DJ, Janak PH. Dorsomedial Striatal Activity Tracks Completion of Behavioral Sequences in Rats. eNeuro 2021; 8:ENEURO.0279-21.2021. [PMID: 34725103 PMCID: PMC8607909 DOI: 10.1523/eneuro.0279-21.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 09/24/2021] [Accepted: 10/13/2021] [Indexed: 11/21/2022] Open
Abstract
For proper execution of goal-directed behaviors, individuals require both a general representation of the goal and an ability to monitor their own progress toward that goal. Here, we examine how dorsomedial striatum (DMS), a region pivotal for forming associations among stimuli, actions, and outcomes, encodes the execution of goal-directed action sequences that require self-monitoring of behavior. We trained rats to complete a sequence of at least five consecutive lever presses (without visiting the reward port) to obtain a reward and recorded the activity of individual cells in DMS while rats performed the task. We found that the pattern of DMS activity gradually changed during the execution of the sequence, permitting accurate decoding of sequence progress from neural activity at a population level. Moreover, this sequence-related activity was blunted on trials where rats did not complete a sufficient number of presses. Overall, these data suggest a link between DMS activity and the execution of behavioral sequences that require monitoring of ongoing behavior.
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Affiliation(s)
- Youna Vandaele
- Department of Psychological and Brain Sciences, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218
| | - David J Ottenheimer
- Department of Psychological and Brain Sciences, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD 21205
| | - Patricia H Janak
- Department of Psychological and Brain Sciences, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD 21205
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46
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Harnessing the power of artificial intelligence to transform hearing healthcare and research. NAT MACH INTELL 2021. [DOI: 10.1038/s42256-021-00394-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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47
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Meirhaeghe N, Sohn H, Jazayeri M. A precise and adaptive neural mechanism for predictive temporal processing in the frontal cortex. Neuron 2021; 109:2995-3011.e5. [PMID: 34534456 PMCID: PMC9737059 DOI: 10.1016/j.neuron.2021.08.025] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/02/2021] [Accepted: 08/18/2021] [Indexed: 12/14/2022]
Abstract
The theory of predictive processing posits that the brain computes expectations to process information predictively. Empirical evidence in support of this theory, however, is scarce and largely limited to sensory areas. Here, we report a precise and adaptive mechanism in the frontal cortex of non-human primates consistent with predictive processing of temporal events. We found that the speed of neural dynamics is precisely adjusted according to the average time of an expected stimulus. This speed adjustment, in turn, enables neurons to encode stimuli in terms of deviations from expectation. This lawful relationship was evident across multiple experiments and held true during learning: when temporal statistics underwent covert changes, neural responses underwent predictable changes that reflected the new mean. Together, these results highlight a precise mathematical relationship between temporal statistics in the environment and neural activity in the frontal cortex that may serve as a mechanism for predictive temporal processing.
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Affiliation(s)
- Nicolas Meirhaeghe
- Harvard-MIT Division of Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Hansem Sohn
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Mehrdad Jazayeri
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA,Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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48
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Monteiro T, Hart T, Kacelnik A. Imprinting on time-structured acoustic stimuli in ducklings. Biol Lett 2021; 17:20210381. [PMID: 34582734 PMCID: PMC8478521 DOI: 10.1098/rsbl.2021.0381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 08/27/2021] [Indexed: 01/30/2023] Open
Abstract
Filial imprinting is a dedicated learning process that lacks explicit reinforcement. The phenomenon itself is narrowly heritably canalized, but its content, the representation of the parental object, reflects the circumstances of the newborn. Imprinting has recently been shown to be even more subtle and complex than previously envisaged, since ducklings and chicks are now known to select and represent for later generalization abstract conceptual properties of the objects they perceive as neonates, including movement pattern, heterogeneity and inter-component relationships of same or different. Here, we investigate day-old Mallard (Anas platyrhynchos) ducklings' bias towards imprinting on acoustic stimuli made from mallards' vocalizations as opposed to white noise, whether they imprint on the temporal structure of brief acoustic stimuli of either kind, and whether they generalize timing information across the two sounds. Our data are consistent with a strong innate preference for natural sounds, but do not reliably establish sensitivity to temporal relations. This fits with the view that imprinting includes the establishment of representations of both primary percepts and selective abstract properties of their early perceptual input, meshing together genetically transmitted prior pre-dispositions with active selection and processing of the perceptual input.
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Affiliation(s)
- Tiago Monteiro
- Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
| | - Tom Hart
- Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
| | - Alex Kacelnik
- Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
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49
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Banerjee A, Egger R, Long MA. Using focal cooling to link neural dynamics and behavior. Neuron 2021; 109:2508-2518. [PMID: 34171292 PMCID: PMC8376768 DOI: 10.1016/j.neuron.2021.05.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/23/2021] [Accepted: 05/25/2021] [Indexed: 12/21/2022]
Abstract
Establishing a causal link between neural function and behavioral output has remained a challenging problem. Commonly used perturbation techniques enable unprecedented control over intrinsic activity patterns and can effectively identify crucial circuit elements important for specific behaviors. However, these approaches may severely disrupt activity, precluding an investigation into the behavioral relevance of moment-to-moment neural dynamics within a specified brain region. Here we discuss the application of mild focal cooling to slow down intrinsic neural circuit activity while preserving its overall structure. Using network modeling and examples from multiple species, we highlight the power and versatility of focal cooling for understanding how neural dynamics control behavior and argue for its wider adoption within the systems neuroscience community.
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Affiliation(s)
- Arkarup Banerjee
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA
| | - Robert Egger
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA
| | - Michael A Long
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
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50
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Langdon AJ, Chaudhuri R. An evolving perspective on the dynamic brain: Notes from the Brain Conference on Dynamics of the brain: Temporal aspects of computation. Eur J Neurosci 2021; 53:3511-3524. [PMID: 32896026 PMCID: PMC7946155 DOI: 10.1111/ejn.14963] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 08/15/2020] [Accepted: 08/26/2020] [Indexed: 11/29/2022]
Affiliation(s)
- Angela J. Langdon
- Princeton Neuroscience Institute & Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Rishidev Chaudhuri
- Center for Neuroscience, Department of Mathematics and Department of Neurobiology, Physiology & Behavior, University of California, Davis, Davis CA, USA
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