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Guzulaitis R, Palmer LM. A thalamocortical pathway controlling impulsive behavior. Trends Neurosci 2023; 46:1018-1024. [PMID: 37778915 DOI: 10.1016/j.tins.2023.09.001] [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: 06/08/2023] [Revised: 08/14/2023] [Accepted: 09/08/2023] [Indexed: 10/03/2023]
Abstract
Planning and anticipating motor actions enables movements to be quickly and accurately executed. However, if anticipation is not properly controlled, it can lead to premature impulsive actions. Impulsive behavior is defined as actions that are poorly conceived and are often risky and inappropriate. Historically, impulsive behavior was thought to be primarily controlled by the frontal cortex and basal ganglia. More recently, two additional brain regions, the ventromedial (VM) thalamus and the anterior lateral motor cortex (ALM), have been shown to have an important role in mice. Here, we explore this newly discovered role of the thalamocortical pathway and suggest cellular mechanisms that may be involved in driving the cortical activity that contributes to impulsive behavior.
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Affiliation(s)
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3010, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC 3010, Australia.
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Jiang M, Wang M, Shi Q, Wei L, Lin Y, Wu D, Liu B, Nie X, Qiao H, Xu L, Yang T, Wang Z. Evolution and neural representation of mammalian cooperative behavior. Cell Rep 2021; 37:110029. [PMID: 34788618 DOI: 10.1016/j.celrep.2021.110029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 08/17/2021] [Accepted: 10/29/2021] [Indexed: 11/29/2022] Open
Abstract
Cooperation is common in nature and is pivotal to the development of human society. However, the details of how and why cooperation evolved remain poorly understood. Cross-species investigation of cooperation may help to elucidate the evolution of cooperative strategies. Thus, we design an automated cooperative behavioral paradigm and quantitatively examine the cooperative abilities and strategies of mice, rats, and tree shrews. We find that social communication plays a key role in the establishment of cooperation and that increased cooperative ability and a more efficient cooperative strategy emerge as a function of the evolutionary hierarchy of the tested species. Moreover, we demonstrate that single-unit activities in the orbitofrontal and prelimbic cortex in rats represent neural signals that may be used to distinguish between the cooperative and non-cooperative tasks, and such signals are distinct from the reward signals. Both signals may represent distinct components of the internal drive for cooperation.
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Affiliation(s)
- Mengping Jiang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Miaoyaoxin Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qianqian Shi
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Wei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yongqin Lin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dingcheng Wu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Boyi Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiupeng Nie
- Key Laboratory of Animal Models and Human Disease Mechanisms and Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Hong Qiao
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lin Xu
- Key Laboratory of Animal Models and Human Disease Mechanisms and Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Tianming Yang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Zuoren Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Mapping Large-Scale Networks Associated with Action, Behavioral Inhibition and Impulsivity. eNeuro 2021; 8:ENEURO.0406-20.2021. [PMID: 33509949 PMCID: PMC7920541 DOI: 10.1523/eneuro.0406-20.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 01/06/2021] [Accepted: 01/08/2021] [Indexed: 02/06/2023] Open
Abstract
A key aspect of behavioral inhibition is the ability to wait before acting. Failures in this form of inhibition result in impulsivity and are commonly observed in various neuropsychiatric disorders. Prior evidence has implicated medial frontal cortex, motor cortex, orbitofrontal cortex (OFC), and ventral striatum in various aspects of inhibition. Here, using distributed recordings of brain activity [with local-field potentials (LFPs)] in rodents, we identified oscillatory patterns of activity linked with action and inhibition. Low-frequency (δ) activity within motor and premotor circuits was observed in two distinct networks, the first involved in cued, sensory-based responses and the second more generally in both cued and delayed actions. By contrast, θ activity within prefrontal and premotor regions (medial frontal cortex, OFC, ventral striatum, and premotor cortex) was linked with inhibition. Connectivity at θ frequencies was observed within this network of brain regions. Interestingly, greater connectivity between primary motor cortex (M1) and other motor regions was linked with greater impulsivity, whereas greater connectivity between M1 and inhibitory brain regions (OFC, ventral striatum) was linked with improved inhibition and diminished impulsivity. We observed similar patterns of activity on a parallel task in humans: low-frequency activity in sensorimotor cortex linked with action, θ activity in OFC/ventral prefrontal cortex (PFC) linked with inhibition. Thus, we show that δ and θ oscillations form distinct large-scale networks associated with action and inhibition, respectively.
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Miyazaki K, Miyazaki KW, Sivori G, Yamanaka A, Tanaka KF, Doya K. Serotonergic projections to the orbitofrontal and medial prefrontal cortices differentially modulate waiting for future rewards. SCIENCE ADVANCES 2020; 6:6/48/eabc7246. [PMID: 33246957 PMCID: PMC7695476 DOI: 10.1126/sciadv.abc7246] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 10/14/2020] [Indexed: 06/12/2023]
Abstract
Optogenetic activation of serotonergic neurons in the dorsal raphe nucleus (DRN) enhances patience when waiting for future rewards, and this effect is maximized by both high probability and high timing uncertainty of reward. Here, we explored which serotonin projection areas contribute to these effects using optogenetic axon terminal stimulation. We found that serotonin stimulation in the orbitofrontal cortex (OFC) is nearly as effective as that in the DRN for promoting waiting, while in the nucleus accumbens, it does not promote waiting. We also found that serotonin stimulation in the medial prefrontal cortex (mPFC) promotes waiting only when the timing of future rewards is uncertain. Our Bayesian decision model of waiting assumed that the OFC and mPFC calculate the posterior probability of reward delivery separately. These results suggest that serotonin in the mPFC affects evaluation of time committed, while serotonin in the OFC is responsible for overall valuation of delayed rewards.
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Affiliation(s)
- Katsuhiko Miyazaki
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan.
| | - Kayoko W Miyazaki
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan
| | - Gaston Sivori
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan
| | - Akihiro Yamanaka
- Department of Neuroscience II, Research Institute of Environmental Medicine, Nagoya University, Nagoya 464-8601, Japan
| | - Kenji F Tanaka
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo 160-8582, Japan
| | - Kenji Doya
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan
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Increase in Mutual Information During Interaction with the Environment Contributes to Perception. ENTROPY 2019; 21:e21040365. [PMID: 33267079 PMCID: PMC7514849 DOI: 10.3390/e21040365] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/22/2019] [Accepted: 04/02/2019] [Indexed: 02/04/2023]
Abstract
Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with the physical environment are partly accounted for by a reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level, but belonging to different networks. The increase in mutual information is partly accounted for by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta (Front. Neurosci. 2018). We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs' and neural circuits' connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. The increase in mutual information, given the knowledge about environmental sensory stimuli and the type of motor response produced, is responsible for the coupling between action and perception. In addition, the processing of sensory inputs within neural circuits, with no prior knowledge of the occurrence of a sensory stimulus, increases Shannon information. Consequently, the increase in surprise serves to increase the evidence of the sensory model of physical surroundings.
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Lamanna J, Sulpizio S, Ferro M, Martoni R, Abutalebi J, Malgaroli A. Behavioral assessment of activity-based-anorexia: how cognition can become the drive wheel. Physiol Behav 2019; 202:1-7. [DOI: 10.1016/j.physbeh.2019.01.016] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 01/17/2019] [Accepted: 01/19/2019] [Indexed: 12/19/2022]
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Persistent Neuronal Activity in Anterior Cingulate Cortex Correlates with Sustained Attention in Rats Regardless of Sensory Modality. Sci Rep 2017; 7:43101. [PMID: 28230158 PMCID: PMC5322335 DOI: 10.1038/srep43101] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Accepted: 01/19/2017] [Indexed: 12/02/2022] Open
Abstract
The anterior cingulate cortex (ACC) has long been thought to regulate conflict between an object of attention and distractors during goal-directed sustained attention. However, it is unclear whether ACC serves to sustained attention itself. Here, we developed a task in which the time course of sustained attention could be controlled in rats. Then, using pharmacological lesion experiments, we employed it to assess function of ACC in sustained attention. We then recorded neuronal activity in ACC using multichannel extracellular recording techniques and identified specific ACC neurons persistently activated during the period of attention. Further experiments showed that target modality had minimal influence on the neuronal activity, and distracting external sensory input during the attention period did not perturb persistent neuronal activity. Additionally, minimal trial-to-trial variability in neuronal activity observed during sustained attention supports a role for ACC neurons in that behavior. Therefore, we conclude that the ACC neuronal activity correlates with sustained attention.
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