A linear theory for global electrocortical activity and its control by the lateral hypothalamus

The mesoanatomy of the cortex, minimization of free energy, and generative cognition

Capacity for generativity and unlimited association is the defining characteristic of sentience, and this capacity somehow arises from neuronal self-organization in the cortex. We have previously argued that, consistent with the free energy principle, cortical development is driven by synaptic and cellular selection maximizing synchrony, with effects manifesting in a wide range of features of mesoscopic cortical anatomy. Here, we further argue that in the postnatal stage, as more structured inputs reach the cortex, the same principles of self-organization continue to operate at multitudes of local cortical sites. The unitary ultra-small world structures that emerged antenatally can represent sequences of spatiotemporal images. Local shifts of presynapses from excitatory to inhibitory cells result in the local coupling of spatial eigenmodes and the development of Markov blankets, minimizing prediction errors in each unit's interactions with surrounding neurons. In response to the superposition of inputs exchanged between cortical areas, more complicated, potentially cognitive structures are competitively selected by the merging of units and the elimination of redundant connections that result from the minimization of variational free energy and the elimination of redundant degrees of freedom. The trajectory along which free energy is minimized is shaped by interaction with sensorimotor, limbic, and brainstem mechanisms, providing a basis for creative and unlimited associative learning.

A new method of presentation of the average spectral properties of the EEG time series

In framework of the AR model the transfer function and the impulse response function of the EEG time series were found. The parameters of the impulse response function were interpreted in terms of: frequencies, damping factors and amplitudes of the hypothetical brain rhythm generators. The method of the rhythm diagrams was proposed to describe the spectral properties of the EEG time series. It makes possible the accurate estimation of the EEG rhythm's frequencies and their intensities, especially weak components hardly visible in the conventional spectral analysis are well distinguished. Rhythm diagrams can be a useful tool in the clinical applications and offer new possibilities in the direct comparison of the results of modeling with the experimental data.

Gross electrocortical activity as a linear wave phenomenon with variable temporal damping, regulated by ascending catecholamine neurones

We report critical tests for a theory of electrocortical wave processes, in which telencephalic dendritic potentials reflect the mass action of coupled oscillatory circuits exhibiting complicated and unspecified non-linearities, the whole system being driven by active cell firing. Specific assumptions were: stochastic independence for instantaneous coupling parameters in the system, an individual central tendency to the cycle time for each circuit, and the maintenance of steady state conditions. Application of the central limit theorem to the state transition matrix shows that the gross electrocortical waves should be linear waves, exhibiting a multitude of invariant resonant modes, with the natural frequencies of all the modes being clustered about a smaller number of center values. Ascending brain-stem neurones of at least the dopaminergic and noradrenergic classes should regulate both the power of noise-like signals driving the telencephalic resonant patterns, and the temporal damping of each resonance. We devised tests which involved between hemisphere comparisons of electrocortical spectra, before and after unilateral lesion of transhypothalamic ascending fibres, thus obtaining ratio power changes attributable to post lesion asymmetry of damping and driving, in modes of equivalent left-right center-frequencies. These ratio spectra were curve-fitted to an approximate theoretical expression, and the parameters obtained enabled tests of several specific predictions. Estimates of the center values for resonant mode frequencies, comparison of the relative changes in left/right phase with that expected from the ratio changes in power, and estimates of the surface-to-signal transformation of left and right signals made by a back-calculation, all conform to expectation from the theory, and are consistent across lesion of different types of ascending neurone.

Schizophrenia as a disorder of cerebral state transition

This paper offers a speculative consideration of the schizophrenic process in the light of recent findings concerning the wave nature of electrocortical activity. These findings indicate that changes of brain state can be described in the terminology of finite-state machines, and both the instantaneous states and the state transitions can be specified. It is suggested that the mental phenomena of schizophrenia may be reducible to events (some specific type of instability) which could be observed by appropriate analytic techniques applied to EEG. Present empirical EEG findings in schizophrenics are reviewed in this light, and the role of dopamine blockade in treatment is also considered.

Mental phenomena as changes of state in a finite-state machine

This paper examines the classical functions of the psyche--cognition, affection and conation--from a phenomenological viewpoint and finds them to be defined each in terms of the other. It is held that this circularity of definition reflects the fundamental unity of conscious experience and, as a consequence, that the search for the biological substrate underlying individual functions too readily degenerates into a morphological and biochemical phrenology. An alternative approach, based on considerations from the field of artificial intelligence, is discussed. This approach provides a description of mental phenomena as changes of state in a finite-state machine, the next state being determined by both previous states and current inputs. This concept is shown to be compatible with the descriptions of conscious experience outlined in the phenomenology of Karl Jaspers. It is suggested that neurobiological investigations should be directed towards defining the processes by which state changes occur and further seeking to define mental pathology as aberrations of these dynamic processes.

Event related aspects of somatosensory and auditory evoked potentials: noise or signals?

The so-called Vertex Potential (VP) of human scalp-conducted and event related brain potential (ERBP), which occur as a slow and often large, biphasic sinusoid within the 100-400 msec time segment after transient stimulation in the three main sensory modalities, are the longest researched of all human evoked potential (EP) phenomena. Its variable amplitude has been directly correlated, in experiments expressly tailored for the purpose, with input/output variables such as the rate of acceleration of given stimulus parameters from a state of relative rest (RM function), interstimulus interval (ISI), stimulus intensity, skin potential and resistance changes (SPR and SRR), the peripheral electroneurogram (ENG), and experimentally isolated C-fiber afference; and with neuropsychological variables such as attention or vigilance, visual acuity, response time, subjective stimulus probability or expectancy, acute pain of both fast and slow kinds, intelligence quotient (IQ), and psychometric personality scores (e.g., extraversion versus introversion and neuroticism versus normality). Unfortunately, the cerebral, neural origins of the VP, if any, are unknown; it is reported as usually absent from cortex-surface EP in those primates and mammals hitherto studied, and also from human extracranial event related magnetic fields of the brain (ERMFb) insofar as these reveal only superficial tangential sources; but a possible analog has been recorded from deep subcortical electrodes during human neurosurgery. In view of the increasing published range and quantity of direct correlates of VP amplitude, and of the scarcity of data about its neuroanatomy and neurophysiology, it seemed a good idea to do some rudimentary signal analysis. Preliminary results from five subjects confirm earlier data: The VP of somatosensory (SEP) and auditory (AEP) evoked potentials, as obtained by scalp-conductance and either averaged or single-epoch, can be resolved into inconsistently stimulus synchronized frequency components which are also present as relatively unsynchronized waves in the theta and alpha bands (approx. 2-13 Hz) of the unstimulated or near-threshold-stimulated electroencephalogram (EEG). In averages of numerous single trials (20 less than N less than 102), initiated at interstimulus intervals longer than 2.5 sec and deliberately sequenced so that the initiator could learn to estimate the timing of stimulus onsets, the phase coherence of the power-dominant alpha and theta waves within the 100-400 msec time segment of ERBP is obvious when the stimulus is an intense transient and psychologically not "habituated".(ABSTRACT TRUNCATED AT 400 WORDS)

Amplitude and phase relations of electrocortical waves regulated by transhypothalamic dopaminergic neurones: a test for a linear theory

We have previously proposed that electrocortical activity (EEG) arises as a manifestation of linear waves generated by resonance among telencephalic neurones, and that this activity is controlled in part by ascending neurones from the brain-stem, which regulate the damping of each resonance. The present experiments focus on a specific class of ascending neurones, the mesotelencephalic dopaminergic cells, because these cells are thought to mediate important psychological effects, and are conveniently subject to selective lesion. A critical test of the theory is undertaken, by performing selective unilateral lesion, assessing the changes in the power spectrum of the EEG attributable to lesion, and determining whether the changes in phase of the EEG correspond to that predicted from the changes in power. Results support the theory, although the model order applicable in these experiments in inadequate. The consequences of these findings for automata theory, linear network theory and their application to mammalian brains are briefly discussed.

A test for constant natural frequencies in electrocortical activity under lateral hypothalamic control

An initial test for a theory of lateral hypothalamic regulation of electrocortical activity is undertaken. The theory supposes lateral hypothalamic input directly or indirectly damps telencephalic resonances involving linear wave phenomena, enabling this pathway to act as parametric control of information processing in cortical neural networks. Relative changes in left and right electrocortical power spectra are used to test for the presence of resonant modes with constant natural frequencies in conditions of asymmetrical damping, following unilateral lesion of the lateral hypothalamus. Natural frequency values for the modes clustered about center frequencies in the EEG band are obtained. This method has the advantage of minimising the effects of time-variation and the recorded signal's distortion from the electrocortical local spatial average, but limits consideration to five dominant modes of resonance. The uncertainty of true model order, and errors in curve-fitting impose limitations on the test.

Inference of a stable dispersion relation for electrocortical activity controlled by the lateral hypothalamus

A second test is undertaken for a theory of linear wave motion in electrocortical waves, under lateral hypothalamic control via regulation of damping. This test invokes a general property of linear systems, namely that wave motion with characteristic natural frequencies implies fixed phase velocities associated with each wavelength, independent of the changes in hypothalamic input. A means of testing the invariance of this dispersion relation at the point of recording is derived from a simplified biophysical model for waves in a dipole layer. The method avoids some problems implicit in direct spatio-temporal wave analysis. Results confirm that the model under test is internally consistent, and is also consistent with other findings concerning the origin and spatial nature of the EEG.