Generation of stable heading representations in diverse visual scenes (Kim et al 2019)

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Accession:261585
"Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by ‘compass’ neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from ‘ring’ neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. ... " See the supplementary information for model details.
Reference:
1 . Kim SS, Hermundstad AM, Romani S, Abbott LF, Jayaraman V (2019) Generation of stable heading representations in diverse visual scenes. Nature 576:126-131 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism: Drosophila;
Cell Type(s): Abstract rate-based neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Spatial Navigation; Synaptic Plasticity; Hebbian plasticity; Attractor Neural Network;
Implementer(s): Kim, Sung Soo [sungsoo at ucsb.edu];
main_config();


%% 
tic_all = tic;


%% Simulation parameter setting

% Model parameters
session.parameters = param_all();

% Simulation conditions (such as ring neuron activity, velocity signal, input polarity etc...)
if ~recycle_sim_conds ...
        || ~exist('session', 'var') || ~isfield(session, 'sim_conds') ...
        || ~strcmp(sim_cond_list{sim_cond_id}, session.sim_conds.description)
    session.sim_conds = sim_cond(session);
end

disp(session.parameters.ring_attractor);
disp(session.parameters.inputs);
disp(session.sim_conds);
disp(session.parameters.plasticity);




%% Simulation

% Randomly initialize the compass neurons (= wedge neurons) activity level
x1 = rand(session.parameters.ring_attractor.n_wedge_neurons,1) * session.parameters.ring_attractor.info.A;

% Initialize the synaptic weight matrix W
if use_prev_sim_W_input && exist('W_last', 'var')
    tmp = W_last;  % uses the W from the last simulation
elseif use_prev_sim_W_input && exist('session', 'var') && isfield(session, 'results') && isfield(session.results, 'W_input')
    tmp = session.results.W_input(:,:,end);  % uses the W from the last simulation
else
    tmp = session.parameters.inputs.W_input; % uses initial value defined by param_all()
end
W_input_dim = size(tmp);
x2 = tmp(:);

sim_x = [x1;x2];
sim_t = session.sim_conds.t;

% Run the model
[t,y] = ode45(@(t, y) RingAttractorODESolver(t, y, session), sim_t, sim_x);
activity = y';

% Collect simulation result
session.results.t = t;
session.results.wedge_neurons = activity(1:numel(x1),:);
session.results.W_input = reshape(activity(numel(x1)+1:end,:),  W_input_dim(1),  W_input_dim(2), numel(t));

W_last = session.results.W_input(:,:,end);



%% check result
result_check(session);


%% display result & save
fn = [session.parameters.plasticity.rule ' - ' session.sim_conds.description ' - ' session.parameters.inputs.initial_weight_description ' - ' datestr(now,'yyyymmdd-HHMMSS')];

if display_and_save_summary_pdf
    result_display(session, [], fn);
end

save(fullfile('simple_result_W', ['W=' fn]), 'W_last');
if save_simulation_result
    save(['sim_result - ' fn], 'session');
end



%%
toc(tic_all)


return;