Monday, 26 August 2013

Just published: From Blickets to Synapses. How brians do causal inference.

From Blickets to Synapses: Inferring Temporal Causal Networks by Observation


  • Causal inference;
  • Rational process model;
  • Neuronal replicator hypothesis;
  • Polychronous groups;
  • Backwards blocking;
  • Screening-off


How do human infants learn the causal dependencies between events? Evidence suggests that this remarkable feat can be achieved by observation of only a handful of examples. Many computational models have been produced to explain how infants perform causal inference without explicit teaching about statistics or the scientific method. Here, we propose a spiking neuronal network implementation that can be entrained to form a dynamical model of the temporal and causal relationships between events that it observes. The network uses spike-time dependent plasticity, long-term depression, and heterosynaptic competition rules to implement Rescorla–Wagner-like learning. Transmission delays between neurons allow the network to learn a forward model of the temporal relationships between events. Within this framework, biologically realistic synaptic plasticity rules account for well-known behavioral data regarding cognitive causal assumptions such as backwards blocking and screening-off. These models can then be run as emulators for state inference. Furthermore, this mechanism is capable of copying synaptic connectivity patterns between neuronal networks by observing the spontaneous spike activity from the neuronal circuit that is to be copied, and it thereby provides a powerful method for transmission of circuit functionality between brain regions.
Read it, or don't. 

Thursday, 22 August 2013

Projects to continue in September

Dear Hackademics, 

The new current list of people is above. We're going to be very much focused on Darwinian neurodynamics and building unconventional robots using 3D printing and soft sensors to test those algorithms. Boris is working on efficient representations of policies. Chris Jack plans to modify our sensorimotor contingencies somehow, but he'll know better after he gets back from Zurich I hope. Mark is making an unconventional worm bot. 

NOTE OF CAUTION: You should begin your projects by September. The week itself is a final get-together to write up papers together in a peaceful and contemplative environment, and demonstrate hardware, along with sci fi poetry writing and sci-fi cooking of-course. 

Travel arrangements will be as follows; We leave from London on 11th in 2-3 large people carriers which we hire. Mark Roper/Chris Jack and I will drive these. We take equipment 3D printer etc… electronics equipment and so forth.. as needed, we get food delivered from Waitrose or take some as well, we arrive in the evening and make dinner. 


Friday, 2 August 2013

Android experiments in child development

Android SDK:

Instructions for Processing in Android:

Aim: Make a set of simple apps that can be used by Frida to test things like causal inference, associative learning, etc... in a flexible manner. Then extend this to Bamara's attempts to make a doll based on firm principles from child development.

Possible Experiments: 

1. Implement a pictorial version of a 3-node temporal causal network. Reward child with a noise if they can predict the next states of the network, given the current states. This is a game in which one must predict the next states of the system.