Regular Cycles of Forward and Backward Signal Propagation in Prefrontal Cortex and in Consciousness

Abstract

This paper addresses two fundamental questions: (1) Is it possible to develop mathematical neural network models which can explain and replicate the way in which higher-order capabilities like intelligence, consciousness, optimization, and prediction emerge from the process of learning (Werbos, 1994, 2016a; National Science Foundation, 2008)? and (2) How can we use and test such models in a practical way, to track, to analyze and to model high-frequency (≥ 500 hz) many-channel data from recording the brain, just as econometrics sometimes uses models grounded in the theory of efficient markets to track real-world time-series data (Werbos, 1990)? This paper first reviews some of the prior work addressing question (1), and then reports new work performed in MATLAB analyzing spike-sorted and burst-sorted data on the prefrontal cortex from the Buzsaki lab (Fujisawa et al., 2008, 2015) which is consistent with a regular clock cycle of about 153.4 ms and with regular alternation between a forward pass of network calculations and a backwards pass, as in the general form of the backpropagation algorithm which one of us first developed in the period 1968–1974 (Werbos, 1994, 2006; Anderson and Rosenfeld, 1998). In business and finance, it is well known that adjustments for cycles of the year are essential to accurate prediction of time-series data (Box and Jenkins, 1970); in a similar way, methods for identifying and using regular clock cycles offer large new opportunities in neural time-series analysis. This paper demonstrates a few initial footprints on the large “continent” of this type of neural time-series analysis, and discusses a few of the many further possibilities opened up by this new approach to “decoding” the neural code (Heller et al., 1995).

Evolutionary Advantages of Stimulus-Driven EEG Phase Transitions in the Upper Cortical Layers

“…The identified cycle length varies depending on the experimental conditions; i.e., it is in the theta/bands in the cinematic theory (Freeman, 2000 ; Kozma and Freeman, 2017 ); while Pereira et al ( 2017 ) estimate a very long cycle of consciousness (2 s). The work by Werbos and Davis ( 2016 ) is unique by identifying a very precise clock cycle of 153 ms, by analyzing Buzsáki lab data (Fujisawa et al, 2015 ).…”

Quantum Measurement, Consciousness, and the Soul: a New, Alternative Position

“…) At this writing, preliminary results have been obtained for one of the three streams of experiment and do appear to violate the Born rule; however, this kind of new direction requires great checking, scrutiny, and replication no matter how the initial results come out. For now, it is enough to say that we know these kinds of experiments are extremely important, not only for quantum optics but for future technologies using related objects like spin gates (Werbos and Dolmatova 2016), regardless of how they come out.…”

Cinematic Operation of the Cerebral Cortex Interpreted via Critical Transitions in Self-Organized Dynamic Systems

“…Mathematical models based on chaos theory have been proved to be useful to describe these bursts patterns (Hansel and Sompolinsky, 1992 ; Tsuda, 2001 ; Kozma, 2003 ). Recent breakthroughs include the comprehensive description of sharp wave ripples representing episodic memory effects (Buzsáki, 2015 ) and systematic analysis of spike bursts (Werbos and Davis, 2016 ). Our work addresses experimental and theoretical findings of transient synchronization in mesoscopic neural populations and their interpretation based on the concept of phase transitions in random graph theory (RGT) and statistical physics.…”