Today’s post tries to fit the theoretical concept of Predictive Coding with the unusual structure and connectivity of Pyramidal cells in the Neocortex. Pyramidal neurons Pyramidal neurons are interesting because they are one of the most common neuron types in the computational layers of the neocortex. This almost certainly means… Read More »Pyramidal Neurons and Predictive Coding
Figure 1: The Region-Layer component. The upper surface in the figure is the Region-Layer, which consists of Cells (small rectangles) grouped into Columns. Within each Column, only a few cells are active at any time. The output of the Region-Layer is the activity of the Cells. Columns in the Region-Layer… Read More »The Region-Layer: A building block for AGI
This month’s reading list continues with a subtheme on recurrent neural networks, and in particular Long Short Term Memory (LSTM). First here’s an interesting report on a panel discussion about the future of Deep Learning at the International Conference on Machine Learning (ICML), 2015: http://deeplearning.net/2015/07/13/a-brief-summary-of-the-panel-discussion-at-dl-workshop-icml-2015/ Participants included Yoshua Bengio (University… Read More »Reading list – July 2015
By Gideon Kowadlo, David Rawlinson and Alan Zhang Can you hear silence or see pitch black? Should we classify no input as a valid state or ignore it? To my knowledge, the machine learning and statistics literature mainly regards an absence of input as missing data. There are several ways… Read More »When is missing data a valid state?
Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
This post is about a fantastic new paper by Michael R. Ferrier, titled: Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function The paper was posted to the NUPIC mailing list and can be found via: http://numenta.org/community-content.html The paper itself… Read More »Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
This is a quick post to link a poster paper by Ryan McCall, who has experimented with a Predictive-Coding / Cortical Learning Algorithm (PC-CLA) hybrid approach. We found the paper via Ryan writing to the NUPIC theory mailing list. What’s great about the paper is it links to some of… Read More »Cortical Learning Algorithms with Predictive Coding for a Systems-Level Cognitive Architecture
Introduction Predictive Coding (PC) is a popular theory of cortical function within the neuroscience community. There is considerable biological evidence to support the essential concepts (see e.g. “Canonical microcircuits for predictive coding” by Bastos et al). PC describes a method of encoding messages passed between processing units. Specifically, PC states that… Read More »On Predictive Coding and Temporal Pooling