1
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Dietz AG, Weikop P, Hauglund N, Andersen M, Petersen NC, Rose L, Hirase H, Nedergaard M. Local extracellular K + in cortex regulates norepinephrine levels, network state, and behavioral output. Proc Natl Acad Sci U S A 2023; 120:e2305071120. [PMID: 37774097 PMCID: PMC10556678 DOI: 10.1073/pnas.2305071120] [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: 04/27/2023] [Accepted: 08/08/2023] [Indexed: 10/01/2023] Open
Abstract
Extracellular potassium concentration ([K+]e) is known to increase as a function of arousal. [K+]e is also a potent modulator of transmitter release. Yet, it is not known whether [K+]e is involved in the neuromodulator release associated with behavioral transitions. We here show that manipulating [K+]e controls the local release of monoaminergic neuromodulators, including norepinephrine (NE), serotonin, and dopamine. Imposing a [K+]e increase is adequate to boost local NE levels, and conversely, lowering [K+]e can attenuate local NE. Electroencephalography analysis and behavioral assays revealed that manipulation of cortical [K+]e was sufficient to alter the sleep-wake cycle and behavior of mice. These observations point to the concept that NE levels in the cortex are not solely determined by subcortical release, but that local [K+]e dynamics have a strong impact on cortical NE. Thus, cortical [K+]e is an underappreciated regulator of behavioral transitions.
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Affiliation(s)
- Andrea Grostøl Dietz
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Pia Weikop
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Natalie Hauglund
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Mie Andersen
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Nicolas Caesar Petersen
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Laura Rose
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
| | - Hajime Hirase
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY14642
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of CopenhagenDK-2200, Copenhagen N, Denmark
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY14642
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2
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Wilmes KA, Clopath C. Dendrites help mitigate the plasticity-stability dilemma. Sci Rep 2023; 13:6543. [PMID: 37085642 PMCID: PMC10121616 DOI: 10.1038/s41598-023-32410-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 03/27/2023] [Indexed: 04/23/2023] Open
Abstract
With Hebbian learning 'who fires together wires together', well-known problems arise. Hebbian plasticity can cause unstable network dynamics and overwrite stored memories. Because the known homeostatic plasticity mechanisms tend to be too slow to combat unstable dynamics, it has been proposed that plasticity must be highly gated and synaptic strengths limited. While solving the issue of stability, gating and limiting plasticity does not solve the stability-plasticity dilemma. We propose that dendrites enable both stable network dynamics and considerable synaptic changes, as they allow the gating of plasticity in a compartment-specific manner. We investigate how gating plasticity influences network stability in plastic balanced spiking networks of neurons with dendrites. We compare how different ways to gate plasticity, namely via modulating excitability, learning rate, and inhibition increase stability. We investigate how dendritic versus perisomatic gating allows for different amounts of weight changes in stable networks. We suggest that the compartmentalisation of pyramidal cells enables dendritic synaptic changes while maintaining stability. We show that the coupling between dendrite and soma is critical for the plasticity-stability trade-off. Finally, we show that spatially restricted plasticity additionally improves stability.
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Affiliation(s)
- Katharina A Wilmes
- Imperial College London, London, United Kingdom.
- University of Bern, Bern, Switzerland.
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3
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Boroshok AL, Park AT, Fotiadis P, Velasquez GH, Tooley UA, Simon KR, Forde JCP, Delgado Reyes LM, Tisdall MD, Bassett DS, Cooper EA, Mackey AP. Individual differences in frontoparietal plasticity in humans. NPJ SCIENCE OF LEARNING 2022; 7:14. [PMID: 35739201 PMCID: PMC9226021 DOI: 10.1038/s41539-022-00130-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 05/30/2022] [Indexed: 06/15/2023]
Abstract
Neuroplasticity, defined as the brain's potential to change in response to its environment, has been extensively studied at the cellular and molecular levels. Work in animal models suggests that stimulation to the ventral tegmental area (VTA) enhances plasticity, and that myelination constrains plasticity. Little is known, however, about whether proxy measures of these properties in the human brain are associated with learning. Here, we investigated the plasticity of the frontoparietal system by asking whether VTA resting-state functional connectivity and myelin map values (T1w/T2w ratios) predicted learning after short-term training on the adaptive n-back (n = 46, ages 18-25). We found that stronger baseline connectivity between VTA and lateral prefrontal cortex predicted greater improvements in accuracy. Lower myelin map values predicted improvements in response times, but not accuracy. Our findings suggest that proxy markers of neural plasticity can predict learning in humans.
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Affiliation(s)
- Austin L Boroshok
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Anne T Park
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Panagiotis Fotiadis
- Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Gerardo H Velasquez
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ursula A Tooley
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katrina R Simon
- Teachers College, Columbia University, New York, NY, 10027, USA
| | - Jasmine C P Forde
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lourdes M Delgado Reyes
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Pennsylvania, PA, 19104, USA
- Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Pennsylvania, PA, 19104, USA
- Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Pennsylvania, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
- Santa Fe Institute, Santa Fe, NM, 87501, USA
| | - Emily A Cooper
- Herbert Wertheim School of Optometry & Vision Science, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Allyson P Mackey
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
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4
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Gonzalez KC, Losonczy A, Negrean A. Dendritic Excitability and Synaptic Plasticity In Vitro and In Vivo. Neuroscience 2022; 489:165-175. [PMID: 34998890 PMCID: PMC9392867 DOI: 10.1016/j.neuroscience.2021.12.039] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 12/29/2021] [Accepted: 12/30/2021] [Indexed: 02/06/2023]
Abstract
Much of our understanding of dendritic and synaptic physiology comes from in vitro experimentation, where the afforded mechanical stability and convenience of applying drugs allowed patch-clamping based recording techniques to investigate ion channel distributions, their gating kinetics, and to uncover dendritic integrative and synaptic plasticity rules. However, with current efforts to study these questions in vivo, there is a great need to translate existing knowledge between in vitro and in vivo experimental conditions. In this review, we identify discrepancies between in vitro and in vivo ionic composition of extracellular media and discuss how changes in ionic composition alter dendritic excitability and plasticity induction. Here, we argue that under physiological in vivo ionic conditions, dendrites are expected to be more excitable and the threshold for synaptic plasticity induction to be lowered. Consequently, the plasticity rules described in vitro vary significantly from those implemented in vivo.
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Affiliation(s)
- Kevin C Gonzalez
- Department of Neuroscience, Columbia University, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, New York, NY, USA.
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, New York, NY, USA; Kavli Institute for Brain Science, New York, NY, USA.
| | - Adrian Negrean
- Department of Neuroscience, Columbia University, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, New York, NY, USA.
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5
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The Origin of Abnormal Beta Oscillations in the Parkinsonian Corticobasal Ganglia Circuits. PARKINSON'S DISEASE 2022; 2022:7524066. [PMID: 35251590 PMCID: PMC8896962 DOI: 10.1155/2022/7524066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/12/2022] [Accepted: 02/03/2022] [Indexed: 01/26/2023]
Abstract
Parkinson's disease (PD) is a neurodegenerative brain disorder associated with motor and nonmotor symptoms. Exaggerated beta band (15–30 Hz) neuronal oscillations are widely observed in corticobasal ganglia (BG) circuits during parkinsonism. Abnormal beta oscillations have been linked to motor symptoms of PD, but their exact relationship is poorly understood. Nevertheless, reduction of beta oscillations can induce therapeutic effects in PD patients. While it is widely believed that the external globus pallidus (GPe) and subthalamic nucleus (STN) are jointly responsible for abnormal rhythmogenesis in the parkinsonian BG, the role of other cortico-BG circuits cannot be ignored. To shed light on the origin of abnormal beta oscillations in PD, here we review changes of neuronal activity observed in experimental PD models and discuss how the cortex and different BG nuclei cooperate to generate and stabilize abnormal beta oscillations during parkinsonism. This may provide further insights into the complex relationship between abnormal beta oscillations and motor dysfunction in PD, which is crucial for potential target-specific therapeutic interventions in PD patients.
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6
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Mei J, Muller E, Ramaswamy S. Informing deep neural networks by multiscale principles of neuromodulatory systems. Trends Neurosci 2022; 45:237-250. [DOI: 10.1016/j.tins.2021.12.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 12/04/2021] [Accepted: 12/21/2021] [Indexed: 01/19/2023]
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7
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Yufik Y, Malhotra R. Situational Understanding in the Human and the Machine. Front Syst Neurosci 2021; 15:786252. [PMID: 35002643 PMCID: PMC8733725 DOI: 10.3389/fnsys.2021.786252] [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: 09/30/2021] [Accepted: 11/24/2021] [Indexed: 11/13/2022] Open
Abstract
The Air Force research programs envision developing AI technologies that will ensure battlespace dominance, by radical increases in the speed of battlespace understanding and decision-making. In the last half century, advances in AI have been concentrated in the area of machine learning. Recent experimental findings and insights in systems neuroscience, the biophysics of cognition, and other disciplines provide converging results that set the stage for technologies of machine understanding and machine-augmented Situational Understanding. This paper will review some of the key ideas and results in the literature, and outline new suggestions. We define situational understanding and the distinctions between understanding and awareness, consider examples of how understanding-or lack of it-manifest in performance, and review hypotheses concerning the underlying neuronal mechanisms. Suggestions for further R&D are motivated by these hypotheses and are centered on the notions of Active Inference and Virtual Associative Networks.
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Affiliation(s)
- Yan Yufik
- Virtual Structures Research, Inc., Potomac, MD, United States
| | - Raj Malhotra
- United States Air Force Sensor Directorate, Dayton, OH, United States
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8
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Abstract
In 1959, E. G. Gray described two different types of synapses in the brain for the first time: symmetric and asymmetric. Later on, symmetric synapses were associated with inhibitory terminals, and asymmetric synapses to excitatory signaling. The balance between these two systems is critical to maintain a correct brain function. Likewise, the modulation of both types of synapses is also important to maintain a healthy equilibrium. Cerebral circuitry responds differently depending on the type of damage and the timeline of the injury. For example, promoting symmetric signaling following ischemic damage is beneficial only during the acute phase; afterwards, it further increases the initial damage. Synapses can be also altered by players not directly related to them; the chronic and long-term neurodegeneration mediated by tau proteins primarily targets asymmetric synapses by decreasing neuronal plasticity and functionality. Dopamine represents the main modulating system within the central nervous system. Indeed, the death of midbrain dopaminergic neurons impairs locomotion, underlying the devastating Parkinson’s disease. Herein, we will review studies on symmetric and asymmetric synapses plasticity after three different stressors: symmetric signaling under acute damage—ischemic stroke; asymmetric signaling under chronic and long-term neurodegeneration—Alzheimer’s disease; symmetric and asymmetric synapses without modulation—Parkinson’s disease.
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9
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Aponso M, Patti A, Hearn MTW, Bennett LE. Anxiolytic effects of essential oils may involve anti-oxidant regulation of the pro-oxidant effects of ascorbate in the brain. Neurochem Int 2021; 150:105153. [PMID: 34384852 DOI: 10.1016/j.neuint.2021.105153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/02/2021] [Accepted: 08/05/2021] [Indexed: 01/01/2023]
Abstract
Essential oils (EOs) absorbed via inhalation are consistently reported to produce anxiolytic effects. The underlying neurochemical mechanisms, however, are not well understood. High concentrations of ascorbate in the human brain (~10 mM in neurons) implicates this compound as a key signaling molecule and regulator of oxidative stress. In this study, we demonstrate the significant in vitro capacity of ascorbate to produce H2O2 in the presence of oxygen at physiological pH values, peaking at ~400 μM for ascorbate levels of 1.0 mg/mL (5.6 mM). In comparison, individual EOs and selected neurotransmitters at similar concentrations produced <100 μM H2O2. Systematic studies with binary and ternary mixtures containing ascorbate indicated that EOs and neurotransmitters could variably enhance (pro-oxidant, POX) or suppress (anti-oxidant, AOX) the production of H2O2 versus the ascorbate control, depending on the concentration ratios of the components in the mixture. Moreover, the AOX/POX chemistry observed with binary mixtures did not necessarily predict effects with ternary mixtures, where the POX ascorbate chemistry tended to dominate. A model is proposed to account for the ability of compounds with electron-donating capacity to catalytically regenerate ascorbate from intermediate oxidized forms of ascorbate, thus driving H2O2 production and exerting a net POX effect; whilst compounds that irreversibly reacted with oxidized forms of ascorbate suppressed the production of H2O2 and produced an overall AOX effect. Since the anxiolytic effects of different EOs, including extracts of Lavendula angustifolia (lavender) and Salvia rosmarinus (rosemary), were associated with AOX regulation of H2O2 production by ascorbate, it can be concluded that these anxiolytic effects are potentially related to the AOX properties of EOs. In contrast, EOs driving POX effects (eg, Junipenus communis (Juniper) berry EO) are proposed to be more useful for their potential anti-microbial or cancer cytotoxic applications.
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Affiliation(s)
- Minoli Aponso
- School of Chemistry, Monash University, Clayton, Victoria, 3800, Australia
| | - Antonio Patti
- School of Chemistry, Monash University, Clayton, Victoria, 3800, Australia
| | - Milton T W Hearn
- School of Chemistry, Monash University, Clayton, Victoria, 3800, Australia
| | - Louise E Bennett
- School of Chemistry, Monash University, Clayton, Victoria, 3800, Australia.
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10
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Ang GWY, Tang CS, Hay YA, Zannone S, Paulsen O, Clopath C. The functional role of sequentially neuromodulated synaptic plasticity in behavioural learning. PLoS Comput Biol 2021; 17:e1009017. [PMID: 34111110 PMCID: PMC8192019 DOI: 10.1371/journal.pcbi.1009017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 04/28/2021] [Indexed: 11/28/2022] Open
Abstract
To survive, animals have to quickly modify their behaviour when the reward changes. The internal representations responsible for this are updated through synaptic weight changes, mediated by certain neuromodulators conveying feedback from the environment. In previous experiments, we discovered a form of hippocampal Spike-Timing-Dependent-Plasticity (STDP) that is sequentially modulated by acetylcholine and dopamine. Acetylcholine facilitates synaptic depression, while dopamine retroactively converts the depression into potentiation. When these experimental findings were implemented as a learning rule in a computational model, our simulations showed that cholinergic-facilitated depression is important for reversal learning. In the present study, we tested the model's prediction by optogenetically inactivating cholinergic neurons in mice during a hippocampus-dependent spatial learning task with changing rewards. We found that reversal learning, but not initial place learning, was impaired, verifying our computational prediction that acetylcholine-modulated plasticity promotes the unlearning of old reward locations. Further, differences in neuromodulator concentrations in the model captured mouse-by-mouse performance variability in the optogenetic experiments. Our line of work sheds light on how neuromodulators enable the learning of new contingencies.
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Affiliation(s)
- Grace Wan Yu Ang
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, United Kingdom
| | - Clara S. Tang
- Department of Physiology, Development and Neuroscience, Physiological Laboratory, Cambridge, United Kingdom
| | - Y. Audrey Hay
- Department of Physiology, Development and Neuroscience, Physiological Laboratory, Cambridge, United Kingdom
| | - Sara Zannone
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, United Kingdom
| | - Ole Paulsen
- Department of Physiology, Development and Neuroscience, Physiological Laboratory, Cambridge, United Kingdom
| | - Claudia Clopath
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, United Kingdom
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11
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Daram A, Yanguas-Gil A, Kudithipudi D. Exploring Neuromodulation for Dynamic Learning. Front Neurosci 2020; 14:928. [PMID: 33041754 PMCID: PMC7530271 DOI: 10.3389/fnins.2020.00928] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 08/11/2020] [Indexed: 11/26/2022] Open
Abstract
A continual learning system requires the ability to dynamically adapt and generalize to new tasks with access to only a few samples. In the central nervous system, across species, it is observed that continual and dynamic behavior in learning is an active result of a mechanism known as neuromodulation. Therefore, in this work, neuromodulatory plasticity is embedded with dynamic learning architectures as a first step toward realizing power and area efficient few shot learning systems. An inbuilt modulatory unit regulates learning based on the context and internal state of the system. This renders the system an ability to self modify its weights. In one of the proposed architectures, ModNet, a modulatory layer is introduced in a random projection framework. ModNet's learning capabilities are enhanced by integrating attention along with compartmentalized plasticity mechanisms. Moreover, to explore modulatory mechanisms in conjunction with backpropagation in deeper networks, a modulatory trace learning rule is introduced. The proposed learning rule, uses a time dependent trace to modify the synaptic connections as a function of ongoing states and activations. The trace itself is updated via simple plasticity rules thus reducing the demand on resources. The proposed ModNet and learning rules demonstrate the ability to learn from few samples, train quickly, and perform few-shot image classification in a computationally efficient manner. The simple ModNet and the compartmentalized ModNet architecture learn benchmark image classification tasks in just 2 epochs. The network with modulatory trace achieves an average accuracy of 98.8%±1.16 on the omniglot dataset for five-way one-shot image classification task while requiring 20x fewer trainable parameters in comparison to other state of the art models.
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Affiliation(s)
- Anurag Daram
- Neuromorphic AI Lab, University of Texas, San Antonio, TX, United States
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12
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Pedrosa V, Clopath C. The interplay between somatic and dendritic inhibition promotes the emergence and stabilization of place fields. PLoS Comput Biol 2020; 16:e1007955. [PMID: 32649658 PMCID: PMC7386595 DOI: 10.1371/journal.pcbi.1007955] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/28/2020] [Accepted: 05/15/2020] [Indexed: 01/10/2023] Open
Abstract
During the exploration of novel environments, place fields are rapidly formed in hippocampal CA1 neurons. Place cell firing rate increases in early stages of exploration of novel environments but returns to baseline levels in familiar environments. Although similar in amplitude and width, place fields in familiar environments are more stable than in novel environments. We propose a computational model of the hippocampal CA1 network, which describes the formation, dynamics and stabilization of place fields. We show that although somatic disinhibition is sufficient to form place fields, dendritic inhibition along with synaptic plasticity is necessary for place field stabilization. Our model suggests that place cell stability can be attributed to strong excitatory synaptic weights and strong dendritic inhibition. We show that the interplay between somatic and dendritic inhibition balances the increased excitatory weights, such that place cells return to their baseline firing rate after exploration. Our model suggests that different types of interneurons are essential to unravel the mechanisms underlying place field plasticity. Finally, we predict that artificially induced dendritic events can shift place fields even after place field stabilization.
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Affiliation(s)
- Victor Pedrosa
- Department of Bioengineering, Imperial College London, London, United Kingdom
- CAPES Foundation, Ministry of Education of Brazil, Brasilia - DF, Brazil
| | - Claudia Clopath
- Department of Bioengineering, Imperial College London, London, United Kingdom
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13
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Montangie L, Miehl C, Gjorgjieva J. Autonomous emergence of connectivity assemblies via spike triplet interactions. PLoS Comput Biol 2020; 16:e1007835. [PMID: 32384081 PMCID: PMC7239496 DOI: 10.1371/journal.pcbi.1007835] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 05/20/2020] [Accepted: 03/31/2020] [Indexed: 01/08/2023] Open
Abstract
Non-random connectivity can emerge without structured external input driven by activity-dependent mechanisms of synaptic plasticity based on precise spiking patterns. Here we analyze the emergence of global structures in recurrent networks based on a triplet model of spike timing dependent plasticity (STDP), which depends on the interactions of three precisely-timed spikes, and can describe plasticity experiments with varying spike frequency better than the classical pair-based STDP rule. We derive synaptic changes arising from correlations up to third-order and describe them as the sum of structural motifs, which determine how any spike in the network influences a given synaptic connection through possible connectivity paths. This motif expansion framework reveals novel structural motifs under the triplet STDP rule, which support the formation of bidirectional connections and ultimately the spontaneous emergence of global network structure in the form of self-connected groups of neurons, or assemblies. We propose that under triplet STDP assembly structure can emerge without the need for externally patterned inputs or assuming a symmetric pair-based STDP rule common in previous studies. The emergence of non-random network structure under triplet STDP occurs through internally-generated higher-order correlations, which are ubiquitous in natural stimuli and neuronal spiking activity, and important for coding. We further demonstrate how neuromodulatory mechanisms that modulate the shape of the triplet STDP rule or the synaptic transmission function differentially promote structural motifs underlying the emergence of assemblies, and quantify the differences using graph theoretic measures. Emergent non-random connectivity structures in different brain regions are tightly related to specific patterns of neural activity and support diverse brain functions. For instance, self-connected groups of neurons, known as assemblies, have been proposed to represent functional units in brain circuits and can emerge even without patterned external instruction. Here we investigate the emergence of non-random connectivity in recurrent networks using a particular plasticity rule, triplet STDP, which relies on the interaction of spike triplets and can capture higher-order statistical dependencies in neural activity. We derive the evolution of the synaptic strengths in the network and explore the conditions for the self-organization of connectivity into assemblies. We demonstrate key differences of the triplet STDP rule compared to the classical pair-based rule in terms of how assemblies are formed, including the realistic asymmetric shape and influence of novel connectivity motifs on network plasticity driven by higher-order correlations. Assembly formation depends on the specific shape of the STDP window and synaptic transmission function, pointing towards an important role of neuromodulatory signals on formation of intrinsically generated assemblies.
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Affiliation(s)
- Lisandro Montangie
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Christoph Miehl
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, Freising, Germany
| | - Julijana Gjorgjieva
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, Freising, Germany
- * E-mail:
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14
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Brzosko Z, Mierau SB, Paulsen O. Neuromodulation of Spike-Timing-Dependent Plasticity: Past, Present, and Future. Neuron 2019; 103:563-581. [DOI: 10.1016/j.neuron.2019.05.041] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/20/2019] [Accepted: 05/24/2019] [Indexed: 12/31/2022]
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15
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Madadi Asl M, Vahabie AH, Valizadeh A. Dopaminergic Modulation of Synaptic Plasticity, Its Role in Neuropsychiatric Disorders, and Its Computational Modeling. Basic Clin Neurosci 2019; 10:1-12. [PMID: 31031889 PMCID: PMC6484184 DOI: 10.32598/bcn.9.10.125] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 11/25/2017] [Accepted: 02/05/2018] [Indexed: 01/14/2023] Open
Abstract
Neuromodulators modify intrinsic characteristics of the nervous system in order to reconfigure the functional properties of neural circuits. This reconfiguration is crucial for the flexibility of the nervous system to respond on an input-modulated basis. Such a functional rearrangement is realized by modification of intrinsic properties of the neural circuits including synaptic interactions. Dopamine is an important neuromodulator involved in motivation and stimulus-reward learning process, and adjusts synaptic dynamics in multiple time scales through different pathways. The modification of synaptic plasticity by dopamine underlies the change in synaptic transmission and integration mechanisms, which affects intrinsic properties of the neural system including membrane excitability, probability of neurotransmitters release, receptors’ response to neurotransmitters, protein trafficking, and gene transcription. Dopamine also plays a central role in behavioral control, whereas its malfunction can cause cognitive disorders. Impaired dopamine signaling is implicated in several neuropsychiatric disorders such as Parkinson’s disease, drug addiction, schizophrenia, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder and Tourette’s syndrome. Therefore, dopamine plays a crucial role in the nervous system, where its proper modulation of neural circuits may enhance plasticity-related procedures, but disturbances in dopamine signaling might be involved in numerous neuropsychiatric disorders. In recent years, several computational models are proposed to formulate the involvement of dopamine in synaptic plasticity or neuropsychiatric disorders and address their connection based on the experimental findings.
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Affiliation(s)
- Mojtaba Madadi Asl
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Abdol-Hossein Vahabie
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran.,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
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