Deformation of Attractor Landscape via Cholinergic Presynaptic Modulations: A Computational Study Using a Phase Neuron Model
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{"title"=>"Deformation of Attractor Landscape via Cholinergic Presynaptic Modulations: A Computational Study Using a Phase Neuron Model", "type"=>"journal", "authors"=>[{"first_name"=>"Takashi", "last_name"=>"Kanamaru", "scopus_author_id"=>"7006833152"}, {"first_name"=>"Hiroshi", "last_name"=>"Fujii", "scopus_author_id"=>"37063072000"}, {"first_name"=>"Kazuyuki", "last_name"=>"Aihara", "scopus_author_id"=>"7103203284"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"368101471", "doi"=>"10.1371/journal.pone.0053854", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23326520", "issn"=>"19326203", "scopus"=>"2-s2.0-84872226368", "sgr"=>"84872226368"}, "id"=>"1c285439-bc88-3587-b580-2db34603949f", "abstract"=>"Corticopetal acetylcholine (ACh) is released transiently from the nucleus basalis of Meynert (NBM) into the cortical layers and is associated with top-down attention. Recent experimental data suggest that this release of ACh disinhibits layer 2/3 pyramidal neurons (PYRs) via muscarinic presynaptic effects on inhibitory synapses. Together with other possible presynaptic cholinergic effects on excitatory synapses, this may result in dynamic and temporal modifications of synapses associated with top-down attention. However, the system-level consequences and cognitive relevance of such disinhibitions are poorly understood. Herein, we propose a theoretical possibility that such transient modifications of connectivity associated with ACh release, in addition to top-down glutamatergic input, may provide a neural mechanism for the temporal reactivation of attractors as neural correlates of memories. With baseline levels of ACh, the brain returns to quasi-attractor states, exhibiting transitive dynamics between several intrinsic internal states. This suggests that top-down attention may cause the attention-induced deformations between two types of attractor landscapes: the quasi-attractor landscape (Q-landscape, present under low-ACh, non-attentional conditions) and the attractor landscape (A-landscape, present under high-ACh, top-down attentional conditions). We present a conceptual computational model based on experimental knowledge of the structure of PYRs and interneurons (INs) in cortical layers 1 and 2/3 and discuss the possible physiological implications of our results.", "link"=>"http://www.mendeley.com/research/deformation-attractor-landscape-via-cholinergic-presynaptic-modulations-computational-study-using-ph", "reader_count"=>35, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>3, "Researcher"=>5, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>3, "Researcher"=>5, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Unspecified"=>3, "Environmental Science"=>1, "Materials Science"=>1, "Mathematics"=>2, "Medicine and Dentistry"=>3, "Agricultural and Biological Sciences"=>7, "Neuroscience"=>3, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>3, "Psychology"=>3, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Neuroscience"=>{"Neuroscience"=>3}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>7}, "Computer Science"=>{"Computer Science"=>4}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"United States"=>1, "Ireland"=>1, "Japan"=>3, "Chile"=>1, "Switzerland"=>1, "Germany"=>1}, "group_count"=>2}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/509447"], "description"=>"<p>The bottom-up spike signals via layer 4 from the thalamus core circuit and the top-down spike signals onto layer 1 (and layer 6) interact in the perception of external sensory stimuli in the early cortex (V1/V2). Moreover, acetylcholine (ACh) is transiently released from the nucleus basalis of Meynert to all the layers associated with top-down attention. In layers 2/3, pyramidal neurons (PYRs) that project their apical distal dendrites to layer 1, interneurons (INs), and fast spiking neurons exist. Moreover, it is also known that ACh to layer 1 depolarizes calretinin positive () INs in layer 1 through nicotinic receptors. However, we do not consider the latter effect in our model for simplicity.</p>", "links"=>[], "tags"=>["diagram", "cortical", "layers", "cortex"], "article_id"=>179938, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g001", "stats"=>{"downloads"=>9, "page_views"=>373, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_diagram_of_cortical_layers_in_the_early_visual_cortex_V1_V2_/179938", "title"=>"Schematic diagram of cortical layers in the early visual cortex (V1/V2).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:14:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/509826"], "description"=>"<p>The top-down Glu spike volleys are projected only to the 9th and 10th units for . Note that both the 9th and 10th units, indicated by two arrows in each figure, are active only in pattern 2. Moreover, decreases for associated with the release of ACh. (A) In the ongoing state with , after the injection of top-down Glu spike volleys at , the network temporarily retrieves pattern 2. However, the retrieved pattern in the network soon transits to pattern 1 at around because pattern 2 is a quasi-attractor. (B) For , the trajectory also moves to pattern 2 but the staying time increases because of the effect of ACh. (C) In the network with , each quasi-attractor is stabilized to be an attractor. Therefore, once the trajectory transits to pattern 2, it does not move to other patterns.</p>", "links"=>[], "tags"=>["top-down", "glu", "spike", "volleys", "apical", "distal", "dendrites", "ach", "cortical"], "article_id"=>180315, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g006", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effect_of_top_down_Glu_spike_volleys_to_the_apical_distal_dendrites_as_well_as_the_release_of_ACh_in_cortical_layer_1_/180315", "title"=>"The effect of top-down Glu spike volleys to the apical distal dendrites as well as the release of ACh in cortical layer 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:16:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/509666"], "description"=>"<p>(A), (B), and (C) Chaotic synchronization observed in a unit model with PYRs and INs. The values of the parameters are , , , , , , , , , and . (A) Raster plot of spikes of 100 PYRs and 25 INs (randomly chosen). The firing times of neurons have correlations and we call such firing synchronized. (B) Temporal changes in instantaneous firing rates and of the excitatory ensemble and the inhibitory ensemble , respectively, calculated from the firing in Figure A. It is observed that and fluctuate, and it is found that this fluctuation is caused by chaotic dynamics and not by a stochastic one. (C) Trajectory in the (, ) plane obtained from the data in Figure B. It is observed that the trajectory has some complex structure. (D) Asynchronous firing observed in this unit. Raster plot of spikes of 100 PYRs and 25 INs (randomly chosen). The number of firing is very few because the firing rates are low. (E) and (F) Chaotic synchronization in a unit with an infinite number of neurons obtained by analysis with Fokker-Planck equations, which corresponds to the results in Figures B and C obtained in a unit with a finite number of neurons. (E) Temporal changes in the instantaneous firing rates and . The results are similar to those in Figure B. (F) Trajectory in the (, ) plane. A fine structure of a chaotic attractor is visible.</p>", "links"=>[], "tags"=>["simulations"], "article_id"=>180164, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_simulations_in_a_unit_/180164", "title"=>"Results of simulations in a unit.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:15:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/509517"], "description"=>"<p>(A) and (D) Quasi-attractors observed when the concentration of ACh does not exceed its baseline level. In Figure A, the instability of the quasi-attractor is represented by the shallow depth of potential in the landscape, and each quasi-attractor is found to be unstable because there exist repelling orbits from itself. In Figure D, the instability of the quasi-attractor is shown as crossings of trajectories over the boundaries, and each quasi-attractor is unstable because there are many crossing points. The trajectories of the network state successively transit among quasi-attractors as indicated by red arrows. By the top-down Glu spike volleys indicated by green arrows, the network state would jump to another quasi-attractor. However, it would soon transit to other quasi-attractors again. (B) and (E) Quasi-attractors observed when the ACh level is somewhat high. The probability of transitions becomes low, but each quasi-attractor remains unstable. (C) and (F) Stable attractors observed when the concentration of ACh is much higher. Transitive dynamics are not observed because quasi-attractors are stabilized and they become attractors. When top-down Glu spike volleys are injected to cortical layer 1, the trajectories jump to the target pattern (in this example, the attractor of pattern 2) in a short time.</p>", "links"=>[], "tags"=>["diagrams", "deformation", "attractor", "induced", "ach", "cortical", "layers", "shown"], "article_id"=>180007, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_diagrams_of_deformation_of_the_attractor_landscape_induced_by_release_of_ACh_into_cortical_layers_2_3_shown_in_two_ways_/180007", "title"=>"Schematic diagrams of deformation of the attractor landscape induced by release of ACh into cortical layers 2/3, shown in two ways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:15:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/509960"], "description"=>"<p>Quasi-attractors can be stabilized to attractors even when the excitatory synapses are also affected by ACh (). Note that the ongoing state with quasi-attractors is realized when . This result suggests that if at least a balance of the two opposing currents is effectively maintained, the entire scenario in the quasi-attractor hypothesis appears to hold as well.</p>", "links"=>[], "tags"=>["numerically", "quasi-attractors", "attractors", "cholinergic", "modulations"], "article_id"=>180456, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g008", "stats"=>{"downloads"=>0, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_numerically_obtained_boundary_where_quasi_attractors_change_to_attractors_as_a_function_of_cholinergic_modulations_and_/180456", "title"=>"A numerically obtained boundary where quasi-attractors change to attractors as a function of cholinergic modulations and .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:17:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/509896"], "description"=>"<p>In order to simulate more physiologically plausible situations, we evaluated the network dynamics when ACh is decreased according to an exponential function. The top-down Glu spike volleys are injected to the 9th and 10th units for . ACh is also injected at . It is observed that pattern 2 is successfully retrieved while ACh is effective. Therefore, our scenario would hold as well even if the injection of ACh is temporary.</p>", "links"=>[], "tags"=>["ach", "exponential"], "article_id"=>180393, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g007", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_dynamics_when_ACh_is_gradually_decreased_according_to_an_exponential_function_/180393", "title"=>"The dynamics when ACh is gradually decreased according to an exponential function.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:17:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/509741"], "description"=>"<p>(A) An ongoing state of the network of 16 units. The instantaneous firing rates of excitatory ensembles in 16 units are shown. Transitive dynamics among quasi-attractors are observed for , where is the cholinergic reduction of inhibition that reduces the strengths of inhibitory connections as and with . These dynamics correspond to the schematic diagram in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053854#pone-0053854-g002\" target=\"_blank\">Figures 2A and 2D</a>. (B) When , the staying time at each quasi-attractor increases. This corresponds to <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053854#pone-0053854-g002\" target=\"_blank\">Figures 2B and 2E</a>. (C) When , all the quasi-attractors are stabilized. Therefore, transitions between memories do not take place. This corresponds to <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053854#pone-0053854-g002\" target=\"_blank\">Figures 2C and 2F</a>. (D) Dependence of averaged staying time at a quasi-attractor on . The state with is the ongoing state and, for , the strengths of inhibitory connections are decreased by the cholinergic reduction of inhibition. When the quasi-attractors exist, takes finite values. diverges at , and each quasi-attractor is stabilized to become an attractor for .</p>", "links"=>[], "tags"=>["ach"], "article_id"=>180244, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_ACh_in_the_network_/180244", "title"=>"Effect of ACh in the network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:16:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/509595"], "description"=>"<p>(A) As an elemental model of a small network in layers 2/3 in the early visual cortex, we construct a unit model that is composed of PYRs and INs, each of which is modeled as a phase neuron connected to all the other neurons globally. We set and or we take the limit in the analysis of the Fokker-Planck equations (see the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053854#s4\" target=\"_blank\">Methods</a> section). (B) The multiple units in cortical layers 2/3. ACh decreases inhibitions to PYRs through the presynaptic, muscarinic disinhibitions, and it stabilizes the quasi-attractors. The top-downs Glu spike volleys to the apical distal dendrites of PYRs contribute to the selection of attractors. (C) Connections between two units. Only the connections from the left unit to the right one are shown for simplicity.</p>", "links"=>[], "tags"=>["diagram"], "article_id"=>180091, "categories"=>["Physiology", "Mathematics", "Biological Sciences", "Neuroscience", "Cell Biology"], "users"=>["Takashi Kanamaru", "Hiroshi Fujii", "Kazuyuki Aihara"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0053854.g003", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_diagram_of_our_model_/180091", "title"=>"Schematic diagram of our model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 17:15:29"}

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Relative Metric

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