Natural Intelligence and Anthropic Reasoning

This paper aims to justify the concept of natural intelligence in the biosemiotic context. I will argue that the process of life is (i) a cognitive/semiotic process and (ii) that organisms, from bacteria to animals, are cognitive or semiotic agents. To justify these arguments, the neural-type intelligence represented by the form of reasoning known as anthropic reasoning will be compared and contrasted with types of intelligence explicated by four disciplines of biology – relational biology, evolutionary epistemology, biosemiotics and the systems view of life – not biased towards neural intelligence. The comparison will be achieved by asking questions related to the process of observation and the notion of true observers. To answer the questions I will rely on a range of established concepts including SETI (search for extraterrestrial intelligence), Fermi’s paradox, bacterial cognition, versions of the panspermia theory, as well as some newly introduced concepts including biocivilisations, cognitive/semiotic universes, and the cognitive/semiotic multiverse. The key point emerging from the answers is that the process of cognition/semiosis – the essence of natural intelligence – is a biological universal.Brunel University Londo

Frequency-band coupling in surface EEG reflects spiking activity in monkey V1 during passive fixation

Although EEG is one of the most widely used tools to study brain activity in humans, its neurophysiological constituents are not well understood. We recently showed that during the presentation of movie stimuli, the multi unit activity (MUA) in V1 could be accurately modeled by using the EEG modulations in low frequency (2-4 Hz) phase and high frequency (>30 Hz) power. However, whether this relationship also holds for situations without direct visual stimulation remains unanswered. Therefore, we present data from simultaneous recordings of surface EEG and MUA in area V1 of one behaving monkey during a simple fixation task (trials consisted of a 9 second fixation period). In each trial, we first filtered the data into the delta (2-4Hz) and gamma (>30Hz) band, and found that changes in MUA were positively correlated to gamma power (R=0.12±0.03), and significantly tuned to the phase of the delta oscillation (rayliegh test, p<<0.001). Furthermore, we found that MUA responses were greatest when an increase in gamma power coincided with the negative-going (~ 0.8π) phase of the delta oscillation, suggesting that the strength of MUA in V1 is directly related to the precise interaction of low frequency phase and high frequency power (frequency-band coupling or FBC). These results resemble our earlier findings during the presentation of movie stimuli, and suggest that the relationship between FBC and MUA holds true in both stimulus and stimulus-free conditions

Frequency-band coupling in surface EEG reflects spiking activity in monkey V1 during passive fixation

Although EEG is one of the most widely used tools to study brain activity in humans, its neurophysiological constituents are not well understood. We recently showed that during the presentation of movie stimuli, the multi unit activity (MUA) in V1 could be accurately modeled by using the EEG modulations in low frequency (2 - 4 Hz) phase and high frequency (30 Hz) power. However, whether this relationship also holds for situations without direct visual stimulation remains unanswered. Therefore, we present data from simultaneous recordings of surface EEG and MUA in area V1 of one behaving monkey during a simple fixation task (trials consisted of a 9 second fixation period). In each trial, we first filtered the data into the delta (2 - 4 Hz) and gamma (30 Hz) band, and found that changes in MUA were positively correlated to gamma power (R=0.12±0.03), and significantly tuned to the phase of the delta oscillation (rayliegh test, p0.001). Furthermore, we found that MUA responses were greatest when an increase in gamma power coincided with the negative-going (0.8 ) phase of the delta oscillation, suggesting that the strength of MUA in V1 is directly related to the precise interaction of low frequency phase and high frequency power (frequency-band coupling or FBC). These results resemble our earlier findings during the presentation of movie stimuli, and suggest that the relationship between FBC and MUA holds true in both stimulus and stimulus-free conditions

Predicting surface EEG power through fluctuations in intracortical signals during different behavioral and pharmacological conditions

Although non-invasive EEG is one of the most widely used tools for studying brain activity in humans, we still lack a clear understanding of how EEG signals are related to the spatio temporal organization of the underlying neuronal activity. In particular, it remains unknown how changes in cortical power and synchrony are reflected in the surface EEG signal. Here, we present an approach which incorporates the power and coherence of local field potentials (LFPs) in the striate cortex (V1) to predict fluctuations in the surface EEG signal. We made simultaneous recordings of neural activity with one surface EEG and multiple intracortical electrodes in two awake monkeys during different behavioral conditions as well as under the effect of local Lidocaine injections. Using a General Linear Model (GLM), we found that both LFP power and coherence conveyed individual information which could be used to accurately reconstruct trial-by-trial fluctuations in EEG power. Furthermore, predictive power of the GLM was very robust across different behavioral conditions but highly dependent on frequency. While EEG power could be modeled with high accuracy in the high frequency regime (R^2=0.719±0.042), predictive power vastly reduced for lower frequencies (R^2=0.0795±0.029). During application of Lidocaine, LFP power was reduced, however, inter-electrode coherence strongly increased, resulting in a scenario where the local cortical area was attenuated, though highly synchronized. Interestingly, the EEG showed an overall increase in power under these conditions, being strongest in higher frequencies, which emphasizes its ability to react to changes in synchrony even when the overall power of cortical activity is diminished. The results of our study emphasize two main points: First, our data demonstrates that EEG power indeed depends on changes in both cortical power and coherence and their combination can be used to explain EEG fluctuations across different brain states and stimulus conditions. However, this was mainly true for higher frequencies - perhaps due to larger spatial diversity of high frequency activity across cortical tissue, in which changes in cortical coherence convey more information about fluctuations in EEG power. Second, the local application of Lidocaine did not only reduce LFP power in the affected area but also introduced a strong increase in cortical coherence. Therefore, Lidocaine, which is currently mainly used as a local anesthetic, could be of great value in scientific studies which seek to selectively reduce cortical power while increasing cortical coherence in a localized area

Optogenetically stimulating intact rat corticospinal tract post-stroke restores motor control through regionalized functional circuit formation

Existing methods to improve motor function after stroke include non-specific neuromodulatory approaches. Here the authors use an automated method of analysis of reaching behaviour in rodents to show that optogenetic stimulation of intact corticospinal tract fibres leads to restoration of prior motor functions, rather than compensatory acquisition of new movements

Harnessing behavioral diversity to understand neural computations for cognition

With the increasing acquisition of large-scale neural recordings comes the challenge of inferring the computations they perform and understanding how these give rise to behavior. Here, we review emerging conceptual and technological advances that begin to address this challenge, garnering insights from both biological and artificial neural networks. We argue that neural data should be recorded during rich behavioral tasks, to model cognitive processes and estimate latent behavioral variables. Careful quantification of animal movements can also provide a more complete picture of how movements shape neural dynamics and reflect changes in brain state, such as arousal or stress. Artificial neural networks (ANNs) could serve as artificial model organisms to connect neural dynamics and rich behavioral data. ANNs have already begun to reveal how a wide range of different behaviors can be implemented, generating hypotheses about how observed neural activity might drive behavior and explaining diversity in behavioral strategies

Single-trial neural dynamics are dominated by richly varied movements

When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered 'noise'. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity

Implications of weighting factors on technology preference in net zero energy buildings

With the current movement towards Net Zero Energy Buildings (Net ZEBs) decisions regarding energy carrier weighting factors will have implications on which technologies could be favoured or disfavoured, and therefore adopted or not adopted, in the building sector of the near future. These implications should be taken into consideration by policy makers when developing legislation and regulations addressing the building sector. A parametric analysis was conducted on six buildings in Europe of different typologies and climates in order to assess how different weighting factors would impact the choice of technical systems to be installed. For each combination the amount of PV capacity necessary to achieve a net zero balance has been calculated and used as the main indicator for comparison; where less PV area means more favourable condition. The effect of including a solar thermal system is also discussed. With the current European national weighting factors, biomass boiler is largely the preferred solution, frequently achieving the balance with PV installed on the roof, while gas boiler is the most penalized. The situation changes when strategic weighting factors are applied. Lower weighting factors for electricity and district heating, e.g. reflecting national targets of increased penetration of renewables in such grids, would promote the use of heat pump and district heating, respectively. Asymmetric factors aimed at rewarding electricity export to the grid would facilitate the achievement of the zero balance for all technologies, promoting cogeneration in some cases. On the contrary, low weighting factors for electricity, e.g. reflecting a scenario of high decarbonisation of the power system, prove quite demanding; only few technical solutions would be able to reach the balance within the available roof area for PV, because of the low value credited to exported electricity. In this situation, the preferred solution would be heat pumps combined with solar thermal. In addition, the choice of weighting factors and the resulting favoured technologies will determine the temporal matching of load and generation. While all-electric solutions tend to use the grid as seasonal storage, other solutions will have a yearly net export of electricity to the grid to compensate for the supply of other (thermal) energy carriers. Therefore, it is important to consider the implications for the electricity grid resulting from the choice of weighting factors. (C) 2014 Elsevier B.V. All rights reserved