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Khilkevich A, Lohse M, Low R, Orsolic I, Bozic T, Windmill P, Mrsic-Flogel TD. Brain-wide dynamics linking sensation to action during decision-making. Nature 2024:10.1038/s41586-024-07908-w. [PMID: 39261727 DOI: 10.1038/s41586-024-07908-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/05/2024] [Indexed: 09/13/2024]
Abstract
Perceptual decisions rely on learned associations between sensory evidence and appropriate actions, involving the filtering and integration of relevant inputs to prepare and execute timely responses1,2. Despite the distributed nature of task-relevant representations3-10, it remains unclear how transformations between sensory input, evidence integration, motor planning and execution are orchestrated across brain areas and dimensions of neural activity. Here we addressed this question by recording brain-wide neural activity in mice learning to report changes in ambiguous visual input. After learning, evidence integration emerged across most brain areas in sparse neural populations that drive movement-preparatory activity. Visual responses evolved from transient activations in sensory areas to sustained representations in frontal-motor cortex, thalamus, basal ganglia, midbrain and cerebellum, enabling parallel evidence accumulation. In areas that accumulate evidence, shared population activity patterns encode visual evidence and movement preparation, distinct from movement-execution dynamics. Activity in movement-preparatory subspace is driven by neurons integrating evidence, which collapses at movement onset, allowing the integration process to reset. Across premotor regions, evidence-integration timescales were independent of intrinsic regional dynamics, and thus depended on task experience. In summary, learning aligns evidence accumulation to action preparation in activity dynamics across dozens of brain regions. This leads to highly distributed and parallelized sensorimotor transformations during decision-making. Our work unifies concepts from decision-making and motor control fields into a brain-wide framework for understanding how sensory evidence controls actions.
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Affiliation(s)
- Andrei Khilkevich
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
| | - Michael Lohse
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
| | - Ryan Low
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Ivana Orsolic
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Tadej Bozic
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Paige Windmill
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Thomas D Mrsic-Flogel
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
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2
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Bennett C, Ouellette B, Ramirez TK, Cahoon A, Cabasco H, Browning Y, Lakunina A, Lynch GF, McBride EG, Belski H, Gillis R, Grasso C, Howard R, Johnson T, Loeffler H, Smith H, Sullivan D, Williford A, Caldejon S, Durand S, Gale S, Guthrie A, Ha V, Han W, Hardcastle B, Mochizuki C, Sridhar A, Suarez L, Swapp J, Wilkes J, Siegle JH, Farrell C, Groblewski PA, Olsen SR. SHIELD: Skull-shaped hemispheric implants enabling large-scale electrophysiology datasets in the mouse brain. Neuron 2024; 112:2869-2885.e8. [PMID: 38996587 DOI: 10.1016/j.neuron.2024.06.015] [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: 02/12/2024] [Revised: 05/02/2024] [Accepted: 06/18/2024] [Indexed: 07/14/2024]
Abstract
To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. Although new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe skull-shaped hemispheric implants enabling large-scale electrophysiology datasets (SHIELD). These 3D-printed skull-replacement implants feature customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedure's high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase SHIELD's scientific utility, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful, large-scale electrophysiological experiments for the study of distributed neural computation.
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Affiliation(s)
- Corbett Bennett
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
| | - Ben Ouellette
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | - Hannah Cabasco
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Yoni Browning
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Anna Lakunina
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Galen F Lynch
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Hannah Belski
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ryan Gillis
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Conor Grasso
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Robert Howard
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Tye Johnson
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Henry Loeffler
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Heston Smith
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | | | - Samuel Gale
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Alan Guthrie
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Vivian Ha
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Warren Han
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ben Hardcastle
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Arjun Sridhar
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Lucas Suarez
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Jackie Swapp
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Joshua Wilkes
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
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3
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Luo TZ, Kim TD, Gupta D, Bondy AG, Kopec CD, Elliot VA, DePasquale B, Brody CD. Transitions in dynamical regime and neural mode underlie perceptual decision-making. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.15.562427. [PMID: 37904994 PMCID: PMC10614809 DOI: 10.1101/2023.10.15.562427] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks 1,2 . However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use an unsupervised, deep learning-based method to discover decision-related dynamics from the simultaneous activity of neurons in frontal cortex and striatum of rats while they accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes, the first dominated by sensory inputs, and the second dominated by the autonomous dynamics, with flow in a direction (i.e., "neural mode") largely orthogonal to that in the first regime. We propose that the second regime corresponds to decision commitment. We developed a simplified model that approximates the coupled transition in dynamics and neural mode and allows precise inference, from each trial's neural activity, of a putative internal decision commitment time in that trial. The simplified model captures diverse and complex single-neuron temporal profiles, such as ramping and stepping 3-5 . It also captures trial-averaged curved trajectories 6-8 , and reveals distinctions between brain regions. The putative neurally-inferred commitment times ("nTc") occurred at times broadly distributed across trials, and not time-locked to stimulus onset, offset, or response onset. Nevertheless, when trials were aligned to nTc, behavioral analysis showed that, as predicted by a decision commitment time, sensory evidence before nTc affected the subjects' decision, but evidence after nTc did not. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process, and suggest the moment of commitment to be a useful entry point for dissecting mechanisms underlying rapid changes in internal state.
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4
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Gavenas J, Rutishauser U, Schurger A, Maoz U. Slow ramping emerges from spontaneous fluctuations in spiking neural networks. Nat Commun 2024; 15:7285. [PMID: 39179554 PMCID: PMC11344096 DOI: 10.1038/s41467-024-51401-x] [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: 10/13/2023] [Accepted: 08/05/2024] [Indexed: 08/26/2024] Open
Abstract
The capacity to initiate actions endogenously is critical for goal-directed behavior. Spontaneous voluntary actions are typically preceded by slow-ramping activity in medial frontal cortex that begins around two seconds before movement, which may reflect spontaneous fluctuations that influence action timing. However, the mechanisms by which these slow ramping signals emerge from single-neuron and network dynamics remain poorly understood. Here, we developed a spiking neural-network model that produces spontaneous slow ramping activity in single neurons and population activity with onsets ~2 s before threshold crossings. A key prediction of our model is that neurons that ramp together have correlated firing patterns before ramping onset. We confirmed this model-derived hypothesis in a dataset of human single neuron recordings from medial frontal cortex. Our results suggest that slow ramping signals reflect bounded spontaneous fluctuations that emerge from quasi-winner-take-all dynamics in clustered networks that are temporally stabilized by slow-acting synapses.
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Affiliation(s)
- Jake Gavenas
- Institute for Interdisciplinary Brain and Behavioral Sciences, Chapman University, Orange, CA, USA.
- Schmid College of Science and Technology, Chapman University, Orange, CA, USA.
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Aaron Schurger
- Institute for Interdisciplinary Brain and Behavioral Sciences, Chapman University, Orange, CA, USA
- Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, USA
- INSERM U992, Cognitive Neuroimaging Unit, NeuroSpin Center, Gif sur Yvette, 91191, France
- Commissariat à l'Energie Atomique, Direction des Sciences du Vivant, I2BM, NeuroSpin Center, Gif sur Yvette, 91191, France
| | - Uri Maoz
- Institute for Interdisciplinary Brain and Behavioral Sciences, Chapman University, Orange, CA, USA.
- Schmid College of Science and Technology, Chapman University, Orange, CA, USA.
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, USA.
- Fowler School of Engineering, Chapman University, Orange, CA, USA.
- Anderson School of Management, University of California, Los Angeles, CA, USA.
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5
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Mountoufaris G, Nair A, Yang B, Kim DW, Vinograd A, Kim S, Linderman SW, Anderson DJ. A line attractor encoding a persistent internal state requires neuropeptide signaling. Cell 2024:S0092-8674(24)00906-1. [PMID: 39191257 DOI: 10.1016/j.cell.2024.08.015] [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: 09/25/2023] [Revised: 06/23/2024] [Accepted: 08/07/2024] [Indexed: 08/29/2024]
Abstract
Internal states drive survival behaviors, but their neural implementation is poorly understood. Recently, we identified a line attractor in the ventromedial hypothalamus (VMH) that represents a state of aggressiveness. Line attractors can be implemented by recurrent connectivity or neuromodulatory signaling, but evidence for the latter is scant. Here, we demonstrate that neuropeptidergic signaling is necessary for line attractor dynamics in this system by using cell-type-specific CRISPR-Cas9-based gene editing combined with single-cell calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1+ neurons that control aggression diminished attack, reduced persistent neural activity, and eliminated line attractor dynamics while only slightly reducing overall neural activity and sex- or behavior-specific tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor in mammals. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.
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Affiliation(s)
- George Mountoufaris
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Program in Computation and Neural Systems, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Bin Yang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Dong-Wook Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Samuel Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA
| | - David J Anderson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA; Howard Hughes Medical Institute, Pasadena, CA 91001, USA.
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6
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Vinograd A, Nair A, Kim JH, Linderman SW, Anderson DJ. Causal evidence of a line attractor encoding an affective state. Nature 2024:10.1038/s41586-024-07915-x. [PMID: 39142337 DOI: 10.1038/s41586-024-07915-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 08/06/2024] [Indexed: 08/16/2024]
Abstract
Continuous attractors are an emergent property of neural population dynamics that have been hypothesized to encode continuous variables such as head direction and eye position1-4. In mammals, direct evidence of neural implementation of a continuous attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles2,3. Dynamical systems modelling has revealed that neurons in the hypothalamus exhibit approximate line-attractor dynamics in male mice during aggressive encounters5. We have previously hypothesized that these dynamics may encode the variable intensity and persistence of an aggressive internal state. Here we report that these neurons also showed line-attractor dynamics in head-fixed mice observing aggression6. This allowed us to identify and manipulate line-attractor-contributing neurons using two-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations yielded integration of optogenetic stimulation pulses and persistent activity that drove the system along the line attractor, while transient off-manifold perturbations were followed by rapid relaxation back into the attractor. Furthermore, single-cell stimulation and imaging revealed selective functional connectivity among attractor-contributing neurons. Notably, individual differences among mice in line-attractor stability were correlated with the degree of functional connectivity among attractor-contributing neurons. Mechanistic recurrent neural network modelling indicated that dense subnetwork connectivity and slow neurotransmission7 best recapitulate our empirical findings. Our work bridges circuit and manifold levels3, providing causal evidence of continuous attractor dynamics encoding an affective internal state in the mammalian hypothalamus.
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Affiliation(s)
- Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Joseph H Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - David J Anderson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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7
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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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8
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Kim JH, Daie K, Li N. A combinatorial neural code for long-term motor memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597627. [PMID: 38895416 PMCID: PMC11185691 DOI: 10.1101/2024.06.05.597627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Motor skill repertoire can be stably retained over long periods, but the neural mechanism underlying stable memory storage remains poorly understood. Moreover, it is unknown how existing motor memories are maintained as new motor skills are continuously acquired. Here we tracked neural representation of learned actions throughout a significant portion of a mouse's lifespan, and we show that learned actions are stably retained in motor memory in combination with context, which protects existing memories from erasure during new motor learning. We used automated home-cage training to establish a continual learning paradigm in which mice learned to perform directional licking in different task contexts. We combined this paradigm with chronic two-photon imaging of motor cortex activity for up to 6 months. Within the same task context, activity driving directional licking was stable over time with little representational drift. When learning new task contexts, new preparatory activity emerged to drive the same licking actions. Learning created parallel new motor memories while retaining the previous memories. Re-learning to make the same actions in the previous task context re-activated the previous preparatory activity, even months later. At the same time, continual learning of new task contexts kept creating new preparatory activity patterns. Context-specific memories, as we observed in the motor system, may provide a solution for stable memory storage throughout continual learning. Learning in new contexts produces parallel new representations instead of modifying existing representations, thus protecting existing motor repertoire from erasure.
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9
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Vinograd A, Nair A, Linderman SW, Anderson DJ. Intrinsic Dynamics and Neural Implementation of a Hypothalamic Line Attractor Encoding an Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.21.595051. [PMID: 38826298 PMCID: PMC11142118 DOI: 10.1101/2024.05.21.595051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Line attractors are emergent population dynamics hypothesized to encode continuous variables such as head direction and internal states. In mammals, direct evidence of neural implementation of a line attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles. Estrogen receptor type 1 (Esr1)-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) show line attractor dynamics in male mice during fighting. We hypothesized that these dynamics may encode continuous variation in the intensity of an internal aggressive state. Here, we report that these neurons also show line attractor dynamics in head-fixed mice observing aggression. We exploit this finding to identify and perturb line attractor-contributing neurons using 2-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations demonstrate that integration and persistent activity are intrinsic properties of these neurons which drive the system along the line attractor, while transient off-manifold perturbations reveal rapid relaxation back into the attractor. Furthermore, stimulation and imaging reveal selective functional connectivity among attractor-contributing neurons. Intriguingly, individual differences among mice in line attractor stability were correlated with the degree of functional connectivity among contributing neurons. Mechanistic modelling indicates that dense subnetwork connectivity and slow neurotransmission are required to explain our empirical findings. Our work bridges circuit and manifold paradigms, shedding light on the intrinsic and operational dynamics of a behaviorally relevant mammalian line attractor.
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Affiliation(s)
- Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Scott W. Linderman
- Department of Statistics, Stanford University, Stanford, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, USA
| | - David J. Anderson
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
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10
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Hasnain MA, Birnbaum JE, Nunez JLU, Hartman EK, Chandrasekaran C, Economo MN. Separating cognitive and motor processes in the behaving mouse. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.23.554474. [PMID: 37662199 PMCID: PMC10473744 DOI: 10.1101/2023.08.23.554474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The cognitive processes supporting complex animal behavior are closely associated with ubiquitous movements responsible for our posture, facial expressions, ability to actively sample our sensory environments, and other critical processes. These movements are strongly related to neural activity across much of the brain and are often highly correlated with ongoing cognitive processes, making it challenging to dissociate the neural dynamics that support cognitive processes from those supporting related movements. In such cases, a critical issue is whether cognitive processes are separable from related movements, or if they are driven by common neural mechanisms. Here, we demonstrate how the separability of cognitive and motor processes can be assessed, and, when separable, how the neural dynamics associated with each component can be isolated. We establish a novel two-context behavioral task in mice that involves multiple cognitive processes and show that commonly observed dynamics taken to support cognitive processes are strongly contaminated by movements. When cognitive and motor components are isolated using a novel approach for subspace decomposition, we find that they exhibit distinct dynamical trajectories. Further, properly accounting for movement revealed that largely separate populations of cells encode cognitive and motor variables, in contrast to the 'mixed selectivity' often reported. Accurately isolating the dynamics associated with particular cognitive and motor processes will be essential for developing conceptual and computational models of neural circuit function and evaluating the function of the cell types of which neural circuits are composed.
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Affiliation(s)
- Munib A. Hasnain
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | - Jaclyn E. Birnbaum
- Graduate Program for Neuroscience, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | | | - Emma K. Hartman
- Department of Biomedical Engineering, Boston University, Boston, MA
| | - Chandramouli Chandrasekaran
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- Department of Neurobiology & Anatomy, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
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11
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Chen S, Liu Y, Wang ZA, Colonell J, Liu LD, Hou H, Tien NW, Wang T, Harris T, Druckmann S, Li N, Svoboda K. Brain-wide neural activity underlying memory-guided movement. Cell 2024; 187:676-691.e16. [PMID: 38306983 DOI: 10.1016/j.cell.2023.12.035] [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: 03/03/2023] [Revised: 09/19/2023] [Accepted: 12/27/2023] [Indexed: 02/04/2024]
Abstract
Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.
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Affiliation(s)
- Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yi Liu
- Stanford University, Palo Alto, CA, USA
| | | | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Liu D Liu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA
| | - Han Hou
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Nai-Wen Tien
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tim Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Timothy Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Johns Hopkins University, Baltimore, MD, USA
| | - Shaul Druckmann
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Stanford University, Palo Alto, CA, USA.
| | - Nuo Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA.
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA.
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12
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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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13
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O'Connor D, Markicevic M, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair MC, Constable RT, Lake EMR, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. Nat Commun 2024; 15:229. [PMID: 38172111 PMCID: PMC10764905 DOI: 10.1038/s41467-023-44363-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.
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Affiliation(s)
- Hadi Vafaii
- Department of Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Marija Markicevic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xinxin Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Section of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Mallar Chakravarty
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA.
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA.
- Maryland Neuroimaging Center, University of Maryland, College Park, MD, 20742, USA.
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14
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Mountoufaris G, Nair A, Yang B, Kim DW, Anderson DJ. Neuropeptide Signaling is Required to Implement a Line Attractor Encoding a Persistent Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.01.565073. [PMID: 37961374 PMCID: PMC10635056 DOI: 10.1101/2023.11.01.565073] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1 + neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.
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15
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Maristany de Las Casas E, Takahashi N. Synaptic crossroads: navigating the circuits of movement. Trends Neurosci 2023; 46:895-897. [PMID: 37690954 PMCID: PMC10591950 DOI: 10.1016/j.tins.2023.08.006] [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: 07/31/2023] [Accepted: 08/17/2023] [Indexed: 09/12/2023]
Abstract
The anterior lateral motor area (ALM) is crucial in preparing and executing voluntary movements through its diverse neuronal subpopulations that target different subcortical areas. A recent study by Xu et al. utilized an elaborate viral tracing strategy in mice to provide comprehensive whole-brain maps of monosynaptic inputs to the major descending pathways of ALM.
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Affiliation(s)
| | - Naoya Takahashi
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, 33000 Bordeaux, France.
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16
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Zhu J, Hasanbegović H, Liu LD, Gao Z, Li N. Activity map of a cortico-cerebellar loop underlying motor planning. Nat Neurosci 2023; 26:1916-1928. [PMID: 37814026 PMCID: PMC10620095 DOI: 10.1038/s41593-023-01453-x] [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: 08/29/2022] [Accepted: 09/06/2023] [Indexed: 10/11/2023]
Abstract
The neocortex and cerebellum interact to mediate cognitive functions. It remains unknown how the two structures organize into functional networks to mediate specific behaviors. Here we delineate activity supporting motor planning in relation to the mesoscale cortico-cerebellar connectome. In mice planning directional licking based on short-term memory, preparatory activity instructing future movement depends on the anterior lateral motor cortex (ALM) and the cerebellum. Transneuronal tracing revealed divergent and largely open-loop connectivity between the ALM and distributed regions of the cerebellum. A cerebellum-wide survey of neuronal activity revealed enriched preparatory activity in hotspot regions with conjunctive input-output connectivity to the ALM. Perturbation experiments show that the conjunction regions were required for maintaining preparatory activity and correct subsequent movement. Other cerebellar regions contributed little to motor planning despite input or output connectivity to the ALM. These results identify a functional cortico-cerebellar loop and suggest the cerebellar cortex selectively establishes reciprocal cortico-cerebellar communications to orchestrate motor planning.
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Affiliation(s)
- Jia Zhu
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | | | - Liu D Liu
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Zhenyu Gao
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands.
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
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17
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Heckman RL, Ludvig D, Perreault EJ. A motor plan is accessible for voluntary initiation and involuntary triggering at similar short latencies. Exp Brain Res 2023; 241:2395-2407. [PMID: 37634132 DOI: 10.1007/s00221-023-06666-x] [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: 12/22/2022] [Accepted: 07/06/2023] [Indexed: 08/29/2023]
Abstract
Movement goals are an essential component of motor planning, altering voluntary and involuntary motor actions. While there have been many studies of motor planning, it is unclear if motor goals influence voluntary and involuntary movements at similar latencies. The objectives of this study were to determine how long it takes to prepare a motor action and to compare this time for voluntary and involuntary movements. We hypothesized a prepared motor action would influence voluntarily and involuntarily initiated movements at the same latency. We trained subjects to reach with a forced reaction time paradigm and used a startling acoustic stimulus (SAS) to trigger involuntary initiation of the same reaches. The time available to prepare was controlled by varying when one of four reach targets was presented. Reach direction was used to evaluate accuracy. We quantified the time between target presentation and the cue or trigger for movement initiation. We found that reaches were accurately initiated when the target was presented 48 ms before the SAS and 162 ms before the cue to voluntarily initiate movement. While the SAS precisely controlled the latency of movement onset, voluntary reach onset was more variable. We, therefore, quantified the time between target presentation and movement onset and found no significant difference in the time required to plan reaches initiated voluntarily or involuntarily (∆ = 8 ms, p = 0.2). These results demonstrate that the time required to plan accurate reaches is similar regardless of if they are initiated voluntarily or triggered involuntarily. This finding may inform the understanding of neural pathways governing storage and access of motor plans.
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Affiliation(s)
- Rosalind L Heckman
- Department of Physical Therapy, Creighton University, Omaha, NE, 68178, USA.
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA.
- Shirley Ryan Ability Lab, Chicago, IL, 60611, USA.
| | - Daniel Ludvig
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Shirley Ryan Ability Lab, Chicago, IL, 60611, USA
| | - Eric J Perreault
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Shirley Ryan Ability Lab, Chicago, IL, 60611, USA
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, 60611, USA
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18
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Jerjian SJ, Harsch DR, Fetsch CR. Self-motion perception and sequential decision-making: where are we heading? Philos Trans R Soc Lond B Biol Sci 2023; 378:20220333. [PMID: 37545301 PMCID: PMC10404932 DOI: 10.1098/rstb.2022.0333] [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: 03/27/2023] [Accepted: 06/18/2023] [Indexed: 08/08/2023] Open
Abstract
To navigate and guide adaptive behaviour in a dynamic environment, animals must accurately estimate their own motion relative to the external world. This is a fundamentally multisensory process involving integration of visual, vestibular and kinesthetic inputs. Ideal observer models, paired with careful neurophysiological investigation, helped to reveal how visual and vestibular signals are combined to support perception of linear self-motion direction, or heading. Recent work has extended these findings by emphasizing the dimension of time, both with regard to stimulus dynamics and the trade-off between speed and accuracy. Both time and certainty-i.e. the degree of confidence in a multisensory decision-are essential to the ecological goals of the system: terminating a decision process is necessary for timely action, and predicting one's accuracy is critical for making multiple decisions in a sequence, as in navigation. Here, we summarize a leading model for multisensory decision-making, then show how the model can be extended to study confidence in heading discrimination. Lastly, we preview ongoing efforts to bridge self-motion perception and navigation per se, including closed-loop virtual reality and active self-motion. The design of unconstrained, ethologically inspired tasks, accompanied by large-scale neural recordings, raise promise for a deeper understanding of spatial perception and decision-making in the behaving animal. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Steven J. Jerjian
- Solomon H. Snyder Department of Neuroscience, Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Devin R. Harsch
- Solomon H. Snyder Department of Neuroscience, Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
- Center for Neuroscience and Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Christopher R. Fetsch
- Solomon H. Snyder Department of Neuroscience, Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
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19
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Pancholi R, Sun-Yan A, Laughton M, Peron S. Sparse and distributed cortical populations mediate sensorimotor integration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558857. [PMID: 37790362 PMCID: PMC10542548 DOI: 10.1101/2023.09.21.558857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Touch information is central to sensorimotor integration, yet little is known about how cortical touch and movement representations interact. Touch- and movement-related activity is present in both somatosensory and motor cortices, making both candidate sites for touch-motor interactions. We studied touch-motor interactions in layer 2/3 of the primary vibrissal somatosensory and motor cortices of behaving mice. Volumetric two-photon calcium imaging revealed robust responses to whisker touch, whisking, and licking in both areas. Touch activity was dominated by a sparse population of broadly tuned neurons responsive to multiple whiskers that exhibited longitudinal stability and disproportionately influenced interareal communication. Movement representations were similarly dominated by sparse, stable, reciprocally projecting populations. In both areas, many broadly tuned touch cells also produced robust licking or whisking responses. These touch-licking and touch-whisking neurons showed distinct dynamics suggestive of specific roles in shaping movement. Cortical touch-motor interactions are thus mediated by specialized populations of highly responsive, broadly tuned neurons.
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Affiliation(s)
- Ravi Pancholi
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Andrew Sun-Yan
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Maya Laughton
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
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20
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Chae S, Sihn D, Kim SP. Bias in Prestimulus Motor Cortical Activity Determines Decision-making Error in Rodents. Exp Neurobiol 2023; 32:271-284. [PMID: 37749928 PMCID: PMC10569143 DOI: 10.5607/en23020] [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: 07/07/2023] [Revised: 08/23/2023] [Accepted: 08/30/2023] [Indexed: 09/27/2023] Open
Abstract
Decision-making is a complex process that involves the integration and interpretation of sensory information to guide actions. The rodent motor cortex, which is generally involved in motor planning and execution, also plays a critical role in decision-making processes. In perceptual delayed-response tasks, the rodent motor cortex can represent sensory cues, as well as the decision of where to move. However, it remains unclear whether erroneous decisions arise from incorrect encoding of sensory information or improper utilization of the collected sensory information in the motor cortex. In this study, we analyzed the rodent anterior lateral motor cortex (ALM) while the mice performed perceptual delayed-response tasks. We divided population activities into sensory and choice signals to separately examine the encoding and utilization of sensory information. We found that the encoding of sensory information in the error trials was similar to that in the hit trials, whereas choice signals evolved differently between the error and hit trials. In error trials, choice signals displayed an offset in the opposite direction of instructed licking even before stimulus presentation, and this tendency gradually increased after stimulus onset, leading to incorrect licking. These findings suggest that decision errors are caused by biases in choice-related activities rather than by incorrect sensory encoding. Our study elaborates on the understanding of decision-making processes by providing neural substrates for erroneous decisions.
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Affiliation(s)
- Soyoung Chae
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
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21
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Majumder S, Hirokawa K, Yang Z, Paletzki R, Gerfen CR, Fontolan L, Romani S, Jain A, Yasuda R, Inagaki HK. Cell-type-specific plasticity shapes neocortical dynamics for motor learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.09.552699. [PMID: 37609277 PMCID: PMC10441538 DOI: 10.1101/2023.08.09.552699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.
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Affiliation(s)
- Shouvik Majumder
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Koichi Hirokawa
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Zidan Yang
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ronald Paletzki
- National Institute of Mental Health, Bethesda, MD 20814, USA
| | | | - Lorenzo Fontolan
- Turing Centre for Living Systems, Aix- Marseille University, INSERM, INMED U1249, Marseille, France
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Sandro Romani
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Anant Jain
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ryohei Yasuda
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
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22
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Deng X, Yang C, Xu J, Liufu M, Li Z, Chen J. Bridging event-related potentials with behavioral studies in motor learning. Front Integr Neurosci 2023; 17:1161918. [PMID: 37168099 PMCID: PMC10164924 DOI: 10.3389/fnint.2023.1161918] [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: 02/08/2023] [Accepted: 03/29/2023] [Indexed: 05/13/2023] Open
Abstract
Behavioral approaches and electrophysiology in understanding human sensorimotor systems have both yielded substantial advancements in past decades. In fact, behavioral neuroscientists have found that motor learning involves the two distinct processes of the implicit and the explicit. Separately, they have also distinguished two kinds of errors that drive motor learning: sensory prediction error and task error. Scientists in electrophysiology, in addition, have discovered two motor-related, event-related potentials (ERPs): error-related negativity (ERN), and feedback-related negativity (FRN). However, there has been a lack of interchange between the two lines of research. This article, therefore, will survey through the literature in both directions, attempting to establish a bridge between these two fruitful lines of research.
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Affiliation(s)
- Xueqian Deng
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Chen Yang
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Jingyue Xu
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States
| | - Mengzhan Liufu
- Institute for Mind and Biology, The University of Chicago, Chicago, IL, United States
| | - Zina Li
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Juan Chen
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
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23
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Nobre AC, van Ede F. Attention in flux. Neuron 2023; 111:971-986. [PMID: 37023719 DOI: 10.1016/j.neuron.2023.02.032] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 04/08/2023]
Abstract
Selective attention comprises essential infrastructural functions supporting cognition-anticipating, prioritizing, selecting, routing, integrating, and preparing signals to guide adaptive behavior. Most studies have examined its consequences, systems, and mechanisms in a static way, but attention is at the confluence of multiple sources of flux. The world advances, we operate within it, our minds change, and all resulting signals progress through multiple pathways within the dynamic networks of our brains. Our aim in this review is to raise awareness of and interest in three important facets of how timing impacts our understanding of attention. These include the challenges posed to attention by the timing of neural processing and psychological functions, the opportunities conferred to attention by various temporal structures in the environment, and how tracking the time courses of neural and behavioral modulations with continuous measures yields surprising insights into the workings and principles of attention.
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Affiliation(s)
- Anna C Nobre
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
| | - Freek van Ede
- Institute for Brain and Behavior Amsterdam, Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam 1081BT, the Netherlands.
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24
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Nietz AK, Streng ML, Popa LS, Carter RE, Flaherty EB, Aronson JD, Ebner TJ. To be and not to be: wide-field Ca2+ imaging reveals neocortical functional segmentation combines stability and flexibility. Cereb Cortex 2023:7024718. [PMID: 36734268 DOI: 10.1093/cercor/bhac523] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/09/2022] [Accepted: 12/10/2022] [Indexed: 02/04/2023] Open
Abstract
The stability and flexibility of the functional parcellation of the cerebral cortex is fundamental to how familiar and novel information is both represented and stored. We leveraged new advances in Ca2+ sensors and microscopy to understand the dynamics of functional segmentation in the dorsal cerebral cortex. We performed wide-field Ca2+ imaging in head-fixed mice and used spatial independent component analysis (ICA) to identify independent spatial sources of Ca2+ fluorescence. The imaging data were evaluated over multiple timescales and discrete behaviors including resting, walking, and grooming. When evaluated over the entire dataset, a set of template independent components (ICs) were identified that were common across behaviors. Template ICs were present across a range of timescales, from days to 30 seconds, although with lower occurrence probability at shorter timescales, highlighting the stability of the functional segmentation. Importantly, unique ICs emerged at the shorter duration timescales that could act to transiently refine the cortical network. When data were evaluated by behavior, both common and behavior-specific ICs emerged. Each behavior is composed of unique combinations of common and behavior-specific ICs. These observations suggest that cerebral cortical functional segmentation exhibits considerable spatial stability over time and behaviors while retaining the flexibility for task-dependent reorganization.
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Affiliation(s)
- Angela K Nietz
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Martha L Streng
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Laurentiu S Popa
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Evelyn B Flaherty
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
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Donegan D, Peleg-Raibstein D, Lambercy O, Burdakov D. Anticipatory countering of motor challenges by premovement activation of orexin neurons. PNAS NEXUS 2022; 1:pgac240. [PMID: 36712356 PMCID: PMC9802298 DOI: 10.1093/pnasnexus/pgac240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022]
Abstract
Countering upcoming challenges with anticipatory movements is a fundamental function of the brain, whose neural implementations remain poorly defined. Recently, premovement neural activation was found outside canonical premotor areas, in the hypothalamic hypocretin/orexin neurons (HONs). The purpose of this hypothalamic activation is unknown. By studying precisely defined mouse-robot interactions, here we show that the premovement HON activity correlates with experience-dependent emergence of anticipatory movements that counter imminent motor challenges. Through targeted, bidirectional optogenetic interference, we demonstrate that the premovement HON activation governs the anticipatory movements. These findings advance our understanding of the behavioral and cognitive impact of temporally defined HON signals and may provide important insights into healthy adaptive movements.
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Affiliation(s)
- Dane Donegan
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology - ETH Zürich, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland
| | - Daria Peleg-Raibstein
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology - ETH Zürich, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland
| | - Olivier Lambercy
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology - ETH Zürich, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland
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