Walter Heiligenberg: the jamming avoidance response and beyond.

Walter Heiligenberg (1938-1994) was an exceptionally gifted behavioral physiologist who made enormous contributions to the analysis of behavior and to our understanding of how the brain initiates and controls species-typical behavioral patterns. He was distinguished by his rigorous analytical approach used in both behavioral studies and neuroethological investigations. Among his most significant contributions to neuroethology are a detailed analysis of the computational rules governing the jamming avoidance response in weakly electric fish and the elucidation of the principal neural pathway involved in neural control of this behavior. Based on his work, the jamming avoidance response is perhaps the best-understood vertebrate behavior pattern in terms of the underlying neural substrate. In addition to this pioneering work, Heiligenberg stimulated research in a significant number of other areas of ethology and neuroethology, including: the quantitative assessment of aggressivity in cichlid fish; the ethological analysis of the stimulus-response relationship in the chirping behavior of crickets; the exploration of the neural and endocrine basis of communicatory behavior in weakly electric fish; the study of cellular mechanisms of neuronal plasticity in the adult fish brain; and the phylogenetic analysis of electric fishes using a combination of morphology, electrophysiology, and mitochondrial sequence data.

Are the electroencephalograms mainly rhythmic? Assessment of periodicity in wide-band time series.

To test the hypotheses that (i). electroencephalograms (EEGs) are largely made up of oscillations at many frequencies and (ii). that the peaks in the power spectra represent oscillations, we applied a new method, called the period specific average (PSA) to a wide sample of EEGs. Both hypotheses can be rejected. Although the principal peaks in the two spectra agree most of the time, quite often a peak in the power spectrum accompanies no periodicity peak and some periodicity peaks have no power spectral peak. The Fourier spectrum is not a reliable indication of rhythms. EEG samples from patients during waking, sleeping and seizure states, and volunteer healthy subjects doing cognitive tasks quite often show no significant rhythms, on an arbitrary, common sense definition. When clear rhythms are seen, they involve one or two, rarely up to four or five simultaneous non-harmonically related frequencies. Rhythms are special cases; most of the power spectrum most of the time is nonrhythmic. "Good" rhythms usually have quite narrow peaks, with frequency modulation of <5%, strengths of >2.5 up to >10 times the expectation from chance, and they often show fine structure by being quite local and brief. Most rhythms are quasisinusoidal but others are sharp-cornered recurrent events with <50% duty cycle. In the face of wide variability, we do not report any systematic differences in periodicity among EEGs from different parts of the brain or different brain states or species; it will take many more exemplars of each state, species or brain part to establish characteristic features. The PSA method may be the best so far proposed to demonstrate and quantify periodicity in wide-band time series with noise, but it has serious limitations. Discussion leads to the conclusion that it is time for a new paradigm or metaphor for brain waves.

Event-related potentials in an invertebrate: crayfish emit 'omitted stimulus potentials'.

Electrical signs of neural activity correlated with stimuli or states include a subclass called event-related potentials. These overlap with, but can often be distinguished from, simple stimulus-bound evoked potentials by their greater dependence on endogenous (internal state) factors. Studied mainly in humans, where they are commonly associated with cognition, they are considered to represent objective signs of moderately high-level brain processing. We tested the hypothesis that invertebrates lack such signs by looking in the crayfish Procambarus clarkii for a class of OFF-effects shown in humans to index expectancy. Disproving the hypothesis, we find, using chronic, implanted preparations, that a good omitted stimulus potential is reliably present. The system learns in a few cycles of a regularly repeated light flash to expect one on schedule. Omitted stimulus potentials are found in the protocerebrum, the circumesophageal connective and in the optic tract - perhaps arising in the retina, as in vertebrates. These potentials can be very local and can include loci with and without direct visual evoked potentials in response to each flash. In some loci, the omitted stimulus potential has a slow wave component, in others only a spike burst. Omitted stimulus potentials are more endogenous than visual evoked potentials, with little dependence on flash or ambient light intensity or on train duration. They vary little in size at different times of the day, but abruptly fail to appear if the ambient light is cut off. They can occur during walking, eating or the maintained defense posture but are diminished by 'distraction' and are often absent from an inert crayfish until it is aroused. We consider this form of apparent expectation of a learned rhythm (a property that makes it 'cognitive' in current usage), to be one of low level, even though some properties suggest endogenous factors. The flashes in a train have an inhibitory effect on a circuit that quickly 'learns' the stimulus interval so that the omitted stimulus potential, ready to happen after the learned interval, is prevented by each flash, until released by a missing stimulus.

Revisiting the concept of identifiable neurons.

Although eutely in nematodes was known, giant neurons in several taxa and unique motor neurons to leg muscles in decapod crustaceans, the idea that many animals have many identifiable neurons with relatively consistent dynamical properties and connections was only slowly established in the late 1960s and early 1970s. This has to be one of the important quiet revolutions in neurobiology. It stimulated a vast acquisition of specific information and led to some euphoria in the degree and pace of understanding activity of nervous systems and consequent behavior in terms of neuronal connections and properties. Some implications, problems and opportunities for new discovery are developed. The distribution of identifiable neurons among taxa and parts of the nervous system is not yet satisfactorily known. Their evolution may have been a case of several independent inventions. The degree of consistency has been quantified only in a few examples and the plasticity is little known. Identified neurons imply identifiable circuits but whether this extends to discrete systems, functionally definable, seems likely to have several answers in different animals or sites. Very limited attempts have been made to extend the concept to cases of two or ten or a hundred fully equivalent neurons, on all kinds of criteria. These attempts suggest a much smaller redundancy and vaster number of types of neurons than hitherto believed. Theory as well as empirical information has not yet interpreted the range of systems from those with small sets of relatively reliable neurons to those with large numbers of parallel, partially redundant units. The now classical notion of local circuits has to be extended to take account of and find roles for the plethora of integrative variables, of evidence for neural processing independent of spikes and classical synapses, of spatial configurations of terminal arbors and dendritic geometry, of modulators and transmitters, degrees of rhythmicity (regularity varying several orders of magnitude), and of synchrony. Adequate language and models need to go beyond 'circuits' in any engineering sense. Identifiable neurons can contribute to a broad spectrum of issues in neurobiology.

Odor input generates approximately 1.5 Hz and approximately 3 Hz spectral peaks in the helix pedal ganglion.

In 1999 we reported that odorants evoke in the Helix pedal ganglion (PG) activity patterns which are largely odorant-specific and related to the nature of odor and its behavioral output. Notably, some activities (for example, approximately 1.5 and approximately 3 Hz), nonspecific to odorants, were consistently evoked in PG. The present contribution goes farther in a deeper survey of the intrinsic and odorant-evoked activities of PG with special weight on the nonspecific fluctuations. We address the following questions. (i) What are the features of the activities? (ii) Are they comparable to the activities found in the motor systems of the other invertebrates? (iii) To what functions can they be related? Three main frequency components represented by power peaks at <1 Hz, 1-2 Hz and 2-8 Hz seem to feature the response activities of PG. (a) The aversive odorants induce odorant-specific patterns represented by peak power frequencies at <1 Hz. (b) The oscillation at approximately 1 Hz, which exists intrinsically in the Helix PG, can be specifically enhanced by appetitive odors. Activities induced in the procerebrum (PC), the visceral ganglion (VG) and PG by appetitive odorants, such as ethanol and apple, peak at 1.3-2 Hz, whereas those induced by aversive ones, such as formic acid and onion at <1 Hz. (c) The 2-8 Hz components always accompany the odorant-evoked activities of the PG either as the second or third strongest component, or in the form of conspicuous, long-lasting approximately 3 Hz oscillations. (d) The nonspecific odor-evoked 1-2 Hz and approximately 3 Hz activities, and the intrinsic approximately 1 Hz activity of the PG seem to be interrelated by a degree of mutual exclusion. We may therefore consider these activities as elementary, slow components that are involved in the processing of signals in this ganglion. It can be inferred from the findings in other invertebrates that the 1-3 Hz spontaneous discharge is strongly connected with motor activity that involves the feedback mechanism of the procerebro-cerebro-buccal or -procerebro-cerebro-pedal circuit. Our approach differs from most others reported so far in the following aspects: (i) use of gross steel electrodes for recording population activities; (ii) lengthy stimulation (10 min); (iii) long observation during and after stimulation; (iv) power spectral presentation of temporal evolution of activity patterns; (v) estimation of peak power frequency by Frequency-Amplitude Plot (FAP) (obtained from signals averaged in the frequency domain; a method based on systems theory).

Precision of the pacemaker nucleus in a weakly electric fish: network versus cellular influences.

We investigated the relative influence of cellular and network properties on the extreme spike timing precision observed in the medullary pacemaker nucleus (Pn) of the weakly electric fish Apteronotus leptorhynchus. Of all known biological rhythms, the electric organ discharge of this and related species is the most temporally precise, with a coefficient of variation (CV = standard deviation/mean period) of 2 x 10(-4) and standard deviation (SD) of 0.12-1.0 micros. The timing of the electric organ discharge is commanded by neurons of the Pn, individual cells of which we show in an in vitro preparation to have only a slightly lesser degree of precision. Among the 100-150 Pn neurons, dye injection into a pacemaker cell resulted in dye coupling in one to five other pacemaker cells and one to three relay cells, consistent with previous results. Relay cell fills, however, showed profuse dendrites and contacts never seen before: relay cell dendrites dye-coupled to one to seven pacemaker and one to seven relay cells. Moderate (0.1-10 nA) intracellular current injection had no effect on a neuron's spiking period, and only slightly modulated its spike amplitude, but could reset the spike phase. In contrast, massive hyperpolarizing current injections (15-25 nA) could force the cell to skip spikes. The relative timing of subthreshold and full spikes suggested that at least some pacemaker cells are likely to be intrinsic oscillators. The relative amplitudes of the subthreshold and full spikes gave a lower bound to the gap junctional coupling coefficient of 0.01-0.08. Three drugs, called gap junction blockers for their mode of action in other preparations, caused immediate and substantial reduction in frequency, altered the phase lag between pairs of neurons, and later caused the spike amplitude to drop, without altering the spike timing precision. Thus we conclude that the high precision of the normal Pn rhythm does not require maximal gap junction conductances between neurons that have ordinary cellular precision. Rather, the spiking precision can be explained as an intrinsic cellular property while the gap junctions act to frequency- and phase-lock the network oscillations.

Gap junction effects on precision and frequency of a model pacemaker network.

We investigated the precision of spike timing in a model of gap junction-coupled oscillatory neurons. The model incorporated the known physiology, morphology, and connectivity of the weakly electric fish's high-frequency and extremely precise pacemaker nucleus (Pn). Two neuron classes, pacemaker and relay cells, were each modeled with two compartments containing Hodgkin-Huxley sodium and potassium currents. Isolated pacemaker cells fired periodically, due to a constant current injection; relay cells were silent but slightly depolarized at rest. When coupled by gap junctions to other neurons, a model neuron, like its biological correlate, spiked at frequencies and amplitudes that were largely independent of current injections. The phase distribution in the network was labile to intracellular current injections and to gap junction conductance changes. The model predicts a biologically plausible gap junction conductance of 4-5 nS (200-250 MOmega). This results in a coupling coefficient of approximately 0.02, as observed in vitro. Network parameters were varied to test which could improve the temporal precision of oscillations. Increased gap junction conductances and larger numbers of cells (holding total junctional conductance per cell constant) both substantially reduced the coefficient of variation (CV = standard deviation/mean) of relay cell spike times by 74-85% and more, and did so with lower gap junction conductance when cells were contacted axonically compared with somatically. Pacemaker cell CV was only reduced when the probability of contact was increased, and then only moderately: a fivefold increase in the probability of contact reduced CV by 35%. We conclude that gap junctions facilitate synchronization, can reduce CV, are most effective between axons, and that pacemaker cells must have low intrinsic CV to account for the low CV of cells in the biological network.

Direct evidence for local oscillatory current sources and intracortical phase gradients in turtle visual cortex.

Visual stimuli induce oscillations in the membrane potential of neurons in cortices of several species. In turtle, these oscillations take the form of linear and circular traveling waves. Such waves may be a consequence of a pacemaker that emits periodic pulses of excitation that propagate across a network of excitable neuronal tissue or may result from continuous and possibly reconfigurable phase shifts along a network with multiple weakly coupled neuronal oscillators. As a means to resolve the origin of wave propagation in turtle visual cortex, we performed simultaneous measurements of the local field potential at a series of depths throughout this cortex. Measurements along a single radial penetration revealed the presence of broadband current sources, with a center frequency near 20 Hz (gamma band), that were activated by visual stimulation. The spectral coherence between sources at two well-separated loci along a rostral-caudal axis revealed the presence of systematic timing differences between localized cortical oscillators. These multiple oscillating current sources and their timing differences in a tangential plane are interpreted as the neuronal activity that underlies the wave motion revealed in previous imaging studies. The present data provide direct evidence for the inference from imaging of bidirectional wave motion that the stimulus-induced electrical waves in turtle visual cortex correspond to phase shifts in a network of coupled neuronal oscillators.

Human auditory fast and slow omitted stimulus potentials and steady-state responses.

Two kinds of omitted stimulus potentials (OSP) are called "fast" and 'slow." Fast OSPs, recently found with visual stimuli, are here extended to auditory; they occur after omissions or after the end of trains of 1 to > 20 Hz clicks. Slow OSPs, long known, follow trains of 0.3 to 4 Hz. Each has its constant peak latency after the due-time of the first missing stimulus, as though the system is expecting something quite accurately on schedule. They differ in dynamics and slow OSPs require the subject to attend; fast OSPs do not. Steady-state responses (SSR) at a critical click rate of 6-7 Hz sometimes appear to alternate between two forms and OSPs may depend on which they follow. Fast OSPs can occur to the first, second and even the third omissions after the end of a train. Short conditioning periods suffice. Irregular interstimulus intervals do not reduce fast OSPs but attenuate slow OSPs.

Neuroethology has pregnant agendas.

Two of the many agendas of neuroethology are illustrated with examples. The first issue is what cells or assemblies of cells and what patterns of activity are sufficient to accomplish recognition of ethologically important stimulus configurations and initiation of behavioral action. The theme is the opportunities available in relatively neglected approaches to these objectives. As an example, the approach is developed of gentle microstimulation of loci in the brain where cells have been found to be responsive to complex, natural stimuli, under conditions conducive to the performance of tell-tale behavior. Other approaches include: (a) microinjection of modulatory substances into regions with such complex recognition cells, and (b) recording in efficient and informative ways, by using multiple electrode arrays, registering wideband activity, in behaving animals. The second issue is what brain and behavior differences has evolution produced between major taxa at distinct grades of complexity. Emphasized are our relative ignorance of basic aspects of connectivity, physiology and cognitive capacities in the major grades and the probability of surprises from new studies that employ comparison.

Sensory processing in the pallium of a mormyrid fish.

To investigate the functional organization of higher brain levels in fish we test the hypothesis that the dorsal gray mantle of the telencephalon of a mormyrid fish has discrete receptive areas for several sensory modalities. Multiunit and compound field potentials evoked by auditory, visual, electrosensory, and water displacement stimuli in this weakly electric fish are recorded with multiple semimicroelectrodes placed in many tracks and depths in or near telencephalic area dorsalis pars medialis (Dm). Most responsive loci are unimodal; some respond to two or more modalities. Each modality dominates a circumscribed area, chiefly separate. Auditory and electrical responses cluster in the dorsal 500 micrometer of rostral and caudolateral Dm, respectively. Two auditory subdivisions underline specialization of this sense. Mechanoreception occupies a caudal area overlapping electroreception but centered 500 micrometer deeper. Visual responses scatter widely through ventral areas. Auditory, electrosensory, and mechanosensory responses are dominated by a negative wave within the first 50 msec, followed by 15-55 Hz oscillations and a slow positive wave with multiunit spikes lasting from 200 to 500 msec. Stimuli can induce shifts in coherence of certain frequency bands between neighboring loci. Every electric organ discharge command is followed within 3 msec by a large, mainly negative but generally biphasic, widespread corollary discharge. At certain loci large, slow ("deltaF") waves usually precede transient shifts in electric organ discharge rate. Sensory-evoked potentials in this fish pallium may be more segregated than in elasmobranchs and anurans and have some surprising similarities to those in mammals.

Submicrosecond pacemaker precision is behaviorally modulated: the gymnotiform electromotor pathway.

What are the limits and modulators of neural precision? We address this question in the most regular biological oscillator known, the electric organ command nucleus in the brainstem of wave-type gymnotiform fish. These fish produce an oscillating electric field, the electric organ discharge (EOD), used in electrolocation and communication. We show here that the EOD precision, measured by the coefficient of variation (CV = SD/mean period) is as low as 2 x 10(-4) in five species representing three families that range widely in species and individual mean EOD frequencies (70-1,250 Hz). Intracellular recording in the pacemaker nucleus (Pn), which commands the EOD cycle by cycle, revealed that individual Pn neurons of the same species also display an extremely low CV (CV = 6 x 10(-4), 0.8 micro sec SD). Although the EOD CV can remain at its minimum for hours, it varies with novel environmental conditions, during communication, and spontaneously. Spontaneous changes occur as abrupt steps (250 ms), oscillations (3-5 Hz), or slow ramps (10-30 s). Several findings suggest that these changes are under active control and depend on behavioral state: mean EOD frequency and CV can change independently; CV often decreases in response to behavioral stimuli; and lesions of one of the two inputs to the Pn had more influence on CV than lesions of the other input.

Signals and signs in the nervous system: the dynamic anatomy of electrical activity is probably information-rich.

The dichotomy between two groups of workers on neuroelectrical activity is retarding progress. To study the interrelations between neuronal unit spike activity and compound field potentials of cell populations is both unfashionable and technically challenging. Neither of the mutual disparagements is justified: that spikes are to higher functions as the alphabet is to Shakespeare and that slow field potentials are irrelevant epiphenomena. Spikes are not the basis of the neural code but of multiple codes that coexist with nonspike codes. Field potentials are mainly information-rich signs of underlying processes, but sometimes they are also signals for neighboring cells, that is, they exert influence. This paper concerns opportunities for new research with many channels of wide-band (spike and slow wave) recording. A wealth of structure in time and three-dimensional space is different at each scale-micro-, meso-, and macroactivity. The depth of our ignorance is emphasized to underline the opportunities for uncovering new principles. We cannot currently estimate the relative importance of spikes and synaptic communication vs. extrasynaptic graded signals. In spite of a preponderance of literature on the former, we must consider the latter as probably important. We are in a primitive stage of looking at the time series of wide-band voltages in the compound, local field, potentials and of choosing descriptors that discriminate appropriately among brain loci, states (functions), stages (ontogeny, senescence), and taxa (evolution). This is not surprising, since the brains in higher species are surely the most complex systems known. They must be the greatest reservoir of new discoveries in nature. The complexity should not deter us, but a dose of humility can stimulate the flow of imaginative juices.

Comparative physiology of acoustic and allied central analyzers.

To exploit comparisons among classes of vertebrates and invertebrates, and between higher and lower levels of the brain, and between modalities, some important needs and opportunities for new research into the way central processing of acoustic input takes place are pointed out. Most of these are suggested by unfamiliar results on fish and reptiles that call for new controls in mammalian experiments as well as more systematic study of nonmammalian taxa. Three frameworks or basic agendas are outlined; i) systematic comparison of dynamical properties to acoustic variables including especially repetition at different rates and the related states of expectation; ii) comparison of response measures, including especially sequences such as oscillations and measures of assembly cooperativity such as synchrony, coherence and bicoherence; and iii) comparison of auditory subsystems, including especially modal categories such as complex feature selective regions and small sets. Some recent and some new results are summarized on human acoustic and non-mammalian event related potentials (ERPs) in response to expectations. When a regular and frequent standard stimulus is omitted, the omitted stimulus potential (OSP) after conditioning with low repetition rates (long ISIs--1-3 s) is a slow, broad positivity P600-900), previously known. With high rates (ISI < 1 s), a new form of response appears, with fast components (P22), different dynamics and less dependence on attention. Slow and fast OSPs each show a constant peak latency after the due-time of the missing stimulus, as though a temporal expectation has been learned. Unlike the visual OSP we have reported earlier, both fast and slow can occur together in the 1-2 Hz range. Very few conditioning stimuli suffice to create the "expectation" that causes an OSP--only two for the slow type. These and more familiar ERPs, considered in human subjects to index cognitive events, need to be compared in other classes of vertebrates and invertebrates.

Bicoherence of intracranial EEG in sleep, wakefulness and seizures.

The hypothesis that the intracranial EEG has local structure and short-term non-stationarity is tested with a little-studied measure of non-linear phase coupling, the bicoherence in human subdural and deep temporal lobe probe data from 11 subjects during sleeping, waking and seizure states. This measure of cooperativity estimates the proportion of energy in every possible pair of frequency components, F1, F2 (from 1 to 50 Hz in this study), that satisfies the definition of quadratic phase coupling (phase of component at F3, which is F1 + F2, equals phase of F1 + phase of F2). Derived from the bispectrum, which segregates the non-Gaussian energy, auto-bicoherence uses the frequency components in one channel; cross-bicoherence uses one channel for F1 and F2 and another for F3. These higher order spectra are used in physical systems for detection of episodes of non-linearity and transients, for pattern recognition and robust classification, relatively immune to Gaussian components and low signal to noise ratios. Bicoherence is found not to be a fixed character of the EEG but quite local and unstable, in agreement with the hypothesis. Bicoherence can be quite different in adjacent segments as brief as 1.6 s as well as adjacent intracranial electrodes as close as 6.5 mm, even when the EEG looks similar. It can rise or fall steeply within millimeters. It is virtually absent in many analysis epochs of 17s duration. Other epochs show significant bicoherence with diverse form and distribution over the bifrequency plane. Isolated peaks, periodic peaks or rounded mountain ranges are either widely scattered or confined to one or a few parts of the plane. Bicoherence is generally an invisible feature: one cannot usually recognize the responsible form of non-linearity or any obvious correlate in the raw EEG. During stage II/III sleep overall mean bicoherence is generally higher than in the waking state. During seizures the diverse EEG patterns average a significant elevation in bicoherence but have a wide variance. Maximum bispectrum, maximum power spectrum, maximum and mean bicoherence, skewness and asymmetry all vary independently of each other. Cross-bicoherence is often intermediate between the two auto-bicoherence spectra but commonly resembles one of the two. Of the known factors that contribute to bicoherence, transient as distinct from ongoing wave forms can be more important in our data sets. This measure of non-linear higher moments is very sensitive to weak quadratic phase coupling; this can come from several kinds of waveforms. New methods are needed to evaluate their respective contributions. Utility of this descriptor cannot be claimed before more carefully defined and repeatable brain states are studied.

Temporal fluctuations in coherence of brain waves.

As a measure of dynamical structure, short-term fluctuations of coherence between 0.3 and 100 Hz in the electroencephalogram (EEG) of humans were studied from recordings made by chronic subdural macroelectrodes 5-10 mm apart, on temporal, frontal, and parietal lobes, and from intracranial probes deep in the temporal lobe, including the hippocampus, during sleep, alert, and seizure states. The time series of coherence between adjacent sites calculated every second or less often varies widely in stability over time; sometimes it is stable for half a minute or more. Within 2-min samples, coherence commonly fluctuates by a factor up to 2-3, in all bands, within the time scale of seconds to tens of seconds. The power spectrum of the time series of these fluctuations is broad, extending to 0.02 Hz or slower, and is weighted toward the slower frequencies; little power is faster than 0.5 Hz. Some records show conspicuous swings with a preferred duration of 5-15s, either irregularly or quasirhythmically with a broad peak around 0.1 Hz. Periodicity is not statistically significant in most records. In our sampling, we have not found a consistent difference between lobes of the brain, subdural and depth electrodes, or sleeping and waking states. Seizures generally raise the mean coherence in all frequencies and may reduce the fluctuations by a ceiling effect. The coherence time series of different bands is positively correlated (0.45 overall); significant nonindependence extends for at least two octaves. Coherence fluctuations are quite local; the time series of adjacent electrodes is correlated with that of the nearest neighbor pairs (10 mm) to a coefficient averaging approximately 0.4, falling to approximately 0.2 for neighbors-but-one (20 mm) and to < 0.1 for neighbors-but-two (30 mm). The evidence indicates fine structure in time and space, a dynamic and local determination of this measure of cooperativity. Widely separated frequencies tending to fluctuate together exclude independent oscillators as the general or usual basis of the EEG, although a few rhythms are well known under special conditions. Broad-band events may be the more usual generators. Loci only a few millimeters apart can fluctuate widely in seconds, either in parallel or independently. Scalp EEG coherence cannot be predicted from subdural or deep recordings, or vice versa, and intracortical microelectrodes show still greater coherence fluctuation in space and time. Widely used computations of chaos and dimensionality made upon data from scalp or even subdural or depth electrodes, even when reproducible in successive samples, cannot be considered representative of the brain or the given structure or brain state but only of the scale or view (receptive field) of the electrodes used. Relevant to the evolution of more complex brains, which is an outstanding fact of animal evolution, we believe that measures of cooperativity are likely to be among the dynamic features by which major evolutionary grades of brains differ.