Good Timing: The Synchronisation of Neural Networks in Computing and Implications for Neurology

A symbiotic relationship now exists between the study of neural networking in computing, and neurology.  Artificial neural networks were originally inspired by neuroscience, although major developments have been guided by insights into the mathematics of efficient optimization, rather than neuroscientific findings.  A H Marblestone 2016.  Now neurology is looking towards the development of neural networks to increase our understanding of how the brain works.  There is the possibility that  the two fields will increasingly merge – with particular recognition of the importance of bio-physics in the study of intelligence.

For a long time, the accepted model of memory formation was linear. Short term memories were thought to directly transform into long term memory in a classical, mechanistic fashion. But this model has been challenged.

The new model emerging is complex and non-linear.  The brain is starting to be seen as ‘more than the sum of its parts’ – analogous to a parallel computer (with many interconnected networks), artificial neural networks/deep learning, or a ‘network of networks (such as the Internet), with all the problems (cascading failures) and solutions (built in redundancy) that are associated with such a model.

Modern neuroscience is going through a renaissance of its own – moving away from mechanistic views of the brain, to focus on connectivity.  It recognises some networks may be particularly important for such connectivity e.g the default mode network – which is effected in various neurological conditions such as Alzheimer’s, as well as altered states of consciousness such as meditation and psychedelic drug use.

A New Model of Memory

Recent neurological research from MIT  has shown that memories (in mice) are formed simultaneously in the hippocampus and prefrontal cortex. Once a long term memory is established it is not necessary to connect to this through the short term memory system.

Researchers labelled memory cells in three parts of the brain: the prefrontal cortex, the hippocampus, and the basolateral amygdala … the amygdala acts as a type of emotional relay station between the hippocampus and prefrontal cortex.

Computing models might provide us with some pointers on how different forms of memory are being associated with each other. For example drawing on models of concurrent and parallel computing, we might choose to explore systems that process multiple tasks simultaneously, or split tasks up into smaller steps, and switch back and forth between them.

In the case of  biological systems, there will also be a need to synchronise information gathered from bio-sensors.  In computing many emerging sensor network applications require that the sensors in the network agree on the time. A global clock in a sensor system will help process and analyze the data correctly and predict future system behavior….Other applications that need global clock synchronization include environment monitoring (for example, temperature), navigation guidance, and any other application that requires the coordination of locally sensed data and mobility.  Q Li 2004.

Such systems require synchronisation, at global or local level.  This type of approach to the brain is already being explored in Multimodal Oscillation-based Connectivity Theory.  The study of collective behaviours  and oscillations in other contexts is also crucial, as it provides various complex models of how individual cells are synchronised. These models tend to emphasis self organisation rather than top-down approaches.

Biological Oscillations and Synchronisation

It is likely that different regions of the brain must be synchronised in order to enable multiple and complex functions to be aligned and delivered simultaneously.  This article considers what mechanisms might provide synchronisation.

In computing, such oscillations are provided by either clocks or pulses.  In biology there are a range of oscillations that might fulfil such a role.

Albert Goldbeter (2007) has set out a range biological oscillations and linked them closely to non-equilibrium processes of ‘self organisation’.

Main Biological Rhythms Period
Neural Rhythms

Cardiac Rhythms

Calcium Oscillations

Biochemical Oscillations

Mitotic Oscillator

Hormonal Rhythms

Circadian Rhythms

Ovarian Cycle

Annual Rhythms

Rhythms in Ecology and Epidemiology

0.001s to 10s

1 s

Sec to min

30 s to 20 mins

10 min to 24 h

10 min to 3-5 h (24h)

24 h

28 days (human)

1 year

years

 

These rhythms can already occur at the cellular level.

Source Goldbeter.

All of these oscillations could have roles to play in the healthy function of the brain, and interact with one another.

The question of how different biological pulses might synchronise has been explored by a number of authors e.g Arthur Winfree, and Kuramoto.

Exploring Neuronal Rhythms Using the Model of Pulse Coupled Neural Networks

In the field of computing, pulse coupled neural networks (PCNN) are derived from research on the cat visual cortex. The network provides a useful biologically inspired tool for image processing. Each neuron represents a pixel on the image and is affected by the initial state of the pixel in the image, and the states of the surrounding neurons. The output of the network generates a series of temporal pulses, which can be used in many different image processing applications such as image segmentation or image fusion. M A Harris 2015

And in recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. W Maass 2001.

The Importance of Neural Oscillations

Our brains operates in a very sporadic, periodic way, with lots of gaps in between the information the brain represents. “The mind is papering over all the gaps and bubbly dynamics and giving us an impression that things are happening in a smooth way, when our brain is actually working in a very periodic fashion, sending packets of information around.”.. These oscillations may help the brain to package information and keep it separate so that different pieces of information don’t interfere with each other. MIT News Office 2016.

Coupled Neural Oscillations in the Brain

Here is it asked whether variations in such oscillations are enabling various cognitive functions including:

  1. The packaging and separating on items in the working memory
  2. Switches in modes of attention,
  3. Fusion of multiple sources of data – including sensory information on the external environment.  This could result in the formation of episodic memory.

There are a range of neural oscillations. It used to be thought that these were merely a form of background noise, but today research is being undertaken into whether they provide way to synchronise different parts of the brain, and enable the smooth working of the memory.

For decades, theta rhythms (5–10 Hz) have been thought to play a critical role in memory processing in the entorhinal– hippocampal network. However, recent evidence suggests that successful memory performance also requires coupling of gamma rhythms to particular phases of the theta cycle.  L L Colgin 2015J Lisman 2013.

Research suggests that the coupling of gamma and theta oscillations influence both the ordering of information in working memory (T K Rajji 2016) and the forming of episodic memory.  B Lega 2016.  Gamma oscillatory responses have also been found to play role in perception, attention and, object recognition, face recognition and emotional paradigms.

It has been proposed that neural ‘bursts’ initially imprint information in the memory, and then reoccur periodically to reinforce this information. The bursts create waves of coordinated activity in the gamma frequency (45 to 100 hertz). The waves occur sporadically, with gaps between them, and each ensemble of neurons, encoding a specific item, produces a different burst of gamma waves. MIT News Office 2016.

Impaired theta-gamma coupling may contribute to working memory dysfunction in schizophrenia. M S Barr 2017.  And in the last decade, there have been studies published on aberrant gamma activity in conditions in which working memory is compromised, including schizophrenia (Y Sun 2011), Alzheimer’s disease (A S Klein 2016) bipolarism (Tai-Ying Liu 2012), autism (D C Rojas 2015) and dyslexia K Lehongre 2013

But the role of these periodic ‘bursts’ may go beyond encoding working memory. Recent research suggests that short high amplitude bursts in the gamma-band, if present in multiple networks, could operate as a transient sync pulse. This pulse would not serve as a clock but may synchronize different gamma activated networks to fire simultaneously. Furthermore, the relative timing of this sync pulse in different networks could also function in the attentional selection of different features of a stimulus. S P Burns 2011 Changes in neural oscillations may trigger different processing modes in the brain, enabling dynamic switching between exploratory and selective modes of attentionD McLelland 2016. 

In addition, because of findings that the coupling of gamma and theta oscillations are found in the forming of episodic memory, there is a possibility that neural ‘pulses’ are also being used to fuse data into complex memory e.g into episodic memory.

Within a parallel or concurrent system, the encoding of working memory, and other tasks could take place during the same time period.

What Causes Gamma Oscillations – The Synchronisation of Data from Multiple Biosensors, and the Creation of Chemical Memory?

If this model is validated, it would raise a further important question. What are causing the gamma oscillations.

Sight

Previous research has found that some forms of gamma oscillations can be strongly associated with tiny eye movement called ‘microsaccades’, and it has been suggested that these could be involved in information flow between brain regions E. Lowet 2015.  Rapid eye movement during sleep could also have a role in sleep consolidation of memory formation.

Microsaccades are thought to contribute to foveal and peripheral vision and to trigger perceptual transitions in a number of bistable illusions, including binocular rivalry.

Bistability may be of particular relevance to biological systems that switch between discrete states, generate oscillatory responses, or production of self-sustaining biochemical “memories”.  D Angeli 2003.  Binocular rivalry has also been found to be influenced by working memory loads, and a number of recent studies have found a link between eye movement and cognition and memory retrieval T Loetscher et al 2010R Johansson 2014,  TM Herrington (2009), Philip Pärnamets et al 2015. Marcos Frank et al 2015, M Cavelli 2015, S Marx et al 2015.

There have been findings that there are differences in eye movements across a range of conditions e.g schzophrenia and biopolarism (D L Levy 2010 and A Y Tien 1996) , Alzheimers (R J Molitor 2015), autism (S V Wass 2015) and dyslexia (S Bellocchi 2013).

Associations between visual awareness, binocular rivalry and the creative trait of ‘openness’ is currently being investigated by some scientists. 

Smell

Nasal respiration rhythms modulate the amplitude of prefrontal gamma rhythms, and contribute to information processing in the prefrontal neuronal network. J Biskamp 2017. C Zelano 2017D H Heck 2017.

Olfactory system beta (15–35 Hz) and gamma (40–110 Hz) oscillations of the local field potential in mammals have both been linked to odor learning and discrimination. Gamma oscillations represent the activity of a local network within the olfactory bulb, and beta oscillations represent engagement of a systemwide network. D E Frederick 2016.  In drosophila and the cockroach, there is a circadian rhythms exhibited in response to specific odorants – driven from a peripheral clock mechanism in the olfactory neurons.

It would seem that neural oscillations and circadian rhythms are being generated in response to external stimulus – and then influencing the encoding of memory.  So there may be a relationship between the generation of the oscillations and rhythms.

Exploring the Possible Role of Biological Clocks – through the Computer Models of Clock Synchronised Systems

The motivation for synchronizing clocks in a computer network is to allow multiple independent agents to coordinate without discussion. Time synchronisation allows for:

  1. Different elements of grid to connect and disconnect.
  2. The imposition of order on streams of data from different sensors.
  3. Multiple updates and reads of data to proceed in parallel with timestamps being used to resolve conflicts.  V Yodaiken 2014.

A well known model of neural networks – Backpropagation – uses adaptation which requires alternating cycles of forward calculation and backward calculation, which in turn requires a kind of master clock…deeper work on systems neuroscience has already revealed flows of information and types of synaptic connection supporting the idea that backward passes (as in the more general family of backpropagation designs) do exist in the brain…  P J Werbos 2016. 

Backpropagation in itself would not be sufficient to explain the workings of the human brain which is a complex self-adaptive system. The brain is able to switch from past – present – future thinking, from fantasy/fiction – to rationalism/fact, from – a focus on detail – to the ‘big picture’ – to mind wandering, from automatic delivery of routine tasks, to high levels of creativeness. Sometimes two very different states can be held simultaneously. Cognitive dissonance is tolerated, as is lying. Goals can be set, and then put aside – with the initiation of new goals or even aimlessness. Options are weighted in different ways depending on the individual. Some data and connections are prioritised for learning – at the cost of losing or holding back other information and connections.

Backpropagation through time” (BPTT) for recurrent networks is widely used in machine learning for training recurrent networks on sequential processing tasks. BPTT “unfolds” a recurrent network across multiple discrete time steps and then runs backpropagation on the unfolded network to assign credit to particular units at particular time steps.

Alternatively models based on versions of Hebbian plasticity may be useful. These can give rise to different forms of correlation and competition between neurons, leading to the self-organized formation of ocular dominance columns, self-organizing maps and orientation columns…To generate complex temporal patterns, the brain may implement other forms of learning that do not require any equivalent of full backpropagation through a multilayer network….(Alternatively), the use of recurrent connections with multiple timescales can remove the need for backpropagation in the direct training of spiking recurrent networks. A H Marblestone 2016.

Researchers have observed that recurrent neural networks, with the kind of reverberations necessary for short-term memory, may play a central role in consciousness, and that a different kind of recurrence and training is required for short term memory than for longer term associative memory of settling down in image processing. (It is not said) that recurrence in the brain is only of the time-delayed kind, but clocks and backwards passes turn out to be necessary for that kind, and for hybrid systems which include that kind of capability P J Werbos 2016. 

We are beginning to understand the connections between the temporal dynamics of biologically realistic networks, and mechanisms of temporal and spatial credit assignment.

Biological Timers and Clocks in the Brain

Timestamps could be used to address conflicts in the parallel processing of data, and researchers have discovered particular neurons that provide ‘time-stamps’ (in the prefrontal cortex and the striatum, and potential elsewhere in the brain.

But in the brain, there is also a need to fuse together experiences of space/time.  Such experiences are often compromised in the early stages of neurological conditions, e.g Alzheimers.

Recently evidence has been discovered of timing signals in hippocampal neurons, including evidence of “time cells”.  Cells that encode for space are also found in the hippocampus. And place cells are not necessarily a distinct sub-network, but seem to be part of a large system that encodes, collectively, more than place information. Place and grid cells do more than simply navigate the environment —rather new research suggests that they may construct a framework of any relevant space, including those defined by sound…Spatial and other types of mapping may turn out to be an integral component of memory.

Characterisation of the space-coding properties of gamma-band oscillations in the avian Optic Tectum lays the foundation for understanding the role of these oscillations in spatial localisation and spatial attention across different classes of vertebrate animals.  Findings in line with recent physiological studies of the neocortex and models of gamma oscillations  indicate that the local field potential oscillations can represent input current with high spatial resolution.  In the optic Tectum this corresponds to a high resolution topological, multimodal map of space.   D Sridharan et al 2011.  Sridharan 2014 

Cells in rats that form the brain’s internal GPS system, known as grid cells, are more malleable than had been anticipated. Typically these cells act like a dead-reckoning system, with certain neurons firing when an animal is in a specific place.  And it has been found that when an animal is kept in place – such as when it runs on a treadmill – the cells keep track of both distance and time B J Kraus 2015. The work suggests that the brain’s sense of space and time are intertwined.

In the natural environment animals must encourage significant events (e.g where to find food, mates and nesting ground, and when to avoid predators, etc) with location and time of day.  This provides them with an experienced based daily and seasonal schedule.  If these stimuli vary predictably, it is advantageous for animals to learn this spatiotemporal day-to-day variability. The ability to encode spatiotemporal reoccurring events, and to exploit this information by efficiently organized daily activities, is believed to constitute a significant fitness advantage which has likely shaped the architecture of cognitive and circadian systems over the course of evolution. The ability to learn spatiotemporal variability has been demonstrated in many species  CK Mulder 2016.

Circadian rhythms might also have a role to play in synchronising information from biological sensors – click here for more information.

Circadian Rhythms and Regulation of Periodicity

Biological clocks (such as circadian rhythms) regulate the proper periodicity of several processes at the cellular and organismal level….. The underlying molecular networks are controlled by delayed negative feedbacks, but the role of positive feedbacks and substrate-depletion has been also proposed to play crucial roles in the regulation of these processes. A Csikász-Nagy 2014

There are a number of biological clocks (generating circadian rhythms) within the body. Circadian rhythms or oscillations are generated by a set of genes forming a feedback loop. In mammals, these include: Clock, Bmal1, Period1, Period 2, Cryptochrome 1, and Cryptochrome 2.

Almost every cell in the body contains a circadian clock, with “elementary clocks” in individual cells, and “ensemble clocks” in cell populations, and intrinsically rhythmic cytosolic signals (cAMP, Ca2+, kinases) support circadian rhythms such as that the cell as a whole has a resonant structure tuned to 24 hour operations.

These cellular clocks form networks that build up the circadian programme in tissues, organs, and the entire organism.

There are circadian rhythms of breathing, eye movement, and many other physiological functions. There are also peripheral clocks including organs, tissues clocks (e.g fibroblasts, liver, kidney, and lungs) throughout the body. The interplay between the central neural and peripheral tissue clocks has been unclear. Timing signals other than light, such as rhythmically timed food intake, can potently reset peripheral clocks directly without affecting clock rhythms in the SCN (J Husse 2015). However increasingly evidence is being found of a coupling between circadian rhythms, redox and the metabolism.

Recently it has been found that perturbation of the transcription–translation feedback loop clockwork or the redox system results in a perturbation of the other, indicating that they have a reciprocal relationship. Lisa Wulund 2015,  A Stangherlin – ‎2013. K Nishio 2015N B Milev 2015.  M Purker 2016.  Most chemical reactions in energy metabolism are redox reactions (of oxidation and reduction), but redox is also known to be involved in signalling to regulate biological and physiological processes , and can also result in oxidative stress

Evidence suggests that circadian clocks control a number of biological processes through an organism in both plants and animals. A N Dodd – ‎2015C. Robertson McClung 2010.  To this day, circadian clocks remain one of the most robust experimental systems wherein perturbations of genetic background or environmental state can be directly linked to changes in physiology and behaviour. Lisa Wulund 2015.

Although circadian rhythms are endogenous (“built-in”, self-sustained), they are adjusted (entrained) to the local environment by external cues called zeitgebers –  which include light, temperature and redox cycles

Clocks normally synchronise to their 24-h world; i.e., they don’t free-run… Successful entrainment equalises internal and external day length, while entrained phase can be variable from individual to individual, and from condition to condition.  Without entrainment, the system loses its main advantage—faithfully predicting the regular changes of its environment. T Roenneberg 2016.

Circadian Rhythms in the Brain and Formation of Memory

It is known that circadian rhythms influence learning, cognitive performance, and memory formation across different species. Studies describe disruption of circadian rhythms altering learning and memory performance, spatial learning, intra and intersession habituation, place learning, long-term potentiation, and trace fear memory (A Jilg 2010 (implicating Per 1), A A Kondratova 2010, E A Van der Zee 2008)… These studies provide much evidence that a functional circadian clock is required for optimal memory formation and persistence. A Malik 2015.   Harini C. Krishnan 2015.  It has also been found that the circadian-controlled mitogen-activated protein kinase (MAPK) and cAMP signal transduction pathway plays critical roles in the consolidation of hippocampus-dependent memory. KL Eckel-Mahan – ‎2012 

There is a biological clock in the suprachiasmatic nucleus (SCN), a structure in the brain made up of 20,000 neurons, all of which can keep daily (circadian) time.

Circadian rhythms of clock genes have been reported in several brain regions, including the prefrontal cortex, olfactory bulb, and hippocampus. The hippocampus exhibits circadian oscillation in the expression of Per2, a hallmark of the TTO. The amplitude and persistence of Long Term Potential (LTP) in the CA1 region varies in a circadian manner. Mutations in Per 2 that impair the circadian clock result in abnormal hippocampal LTP. This supports a necessary role for the circadian clock in permitting and enabling hippocampal plasticity. R Iyer 2014. 

R Iyer 2014 provides an overview of the interactions between circadian rhythms and other forms of biological oscillation in the brain. Circadian rhythms are regulating other forms of oscillations, but as this is a complex adapting system, there may be a feedback system by which the other types of oscillations are influencing circadian rhythms.

Recent findings suggest that circadian rhythms link to other neural oscillations – that the food entrained circadian oscillator involves coordinated activity across a number of brain regions and may underlie a mechanism via which an organism can store and recall salient gustatory events on a circadian timescale. There are circadian-scale periodic bursts in the theta and gamma-band coherence between the hippocampus, cingulate and insular cortices. R G K Munn 2017.

TRPs are becoming seen as a missing bond in the entrainment mechanism of peripheral clocks throughout evolution… Although the data linking thermo-TRP and biological rhythms are still scarce, and most of them were demonstrated in central clocks, valuable information has been provided to trace parallels between the role of thermo-TRP in central and peripheral synchronization. M O Poletini 2015.  Temperature sensitivity or TRPs in the mammalian cortex and hippocampus are not well understood. However there is some evidence that they response to temperature in ways that may influence synaptic plasticity. MG Frank – ‎2016

There is also a strong link between circadian rhythms and sleep, which is still being investigated. This is important because sleep is known to be necessary to memory formation, and potentially influence future behaviour.

The Possible Involvement of Clock Genes

Recent results indicate a key role of cryptochrome proteins in time and place learning (TPL) and confirm the limited role of the SCN in TPLCK Mulder 2016E A Van der Zee 2008 .  It may be the case that different clock genes influence different forms of memory and cognition.

Mice deficient in cryptochrome exhibit impaired recognition memory, increased anxiety, and lack of time-place associations, although no deficits in working or long-term memory formation were reported. In contrast, mice deficient in Bmal1show a diminished learning ability and have previously been reported to display phenotypes associated with accelerated aging. Mice deficient in Per2 showed impaired trace-fear memory, suppressed long-term potentiation (LTP), and diminished CREB phosphorylation. Equivalent effects were observed in mPer1 knockout mice in which spatial memory, CREB activation, and LTP declined, further suggesting that Per genes have additional effects on hippocampal functions, perhaps independent of their role in circadian timingA Malik 2015.

In other species cryptochrome is known to enable to interaction of circadian rhythms and redox. The Cryptochrome protein (CRY) in Arabidopsis, Drosophila, and mouse provide the most direct path by which redox status can interact with the core components of the transcription–translation feedback loop (TTFL). Lisa Wulund 2015.  An altered redox state (due to cryptochrome activation) is thought to influencing clock resetting in Drosophila and zebrafish cells. M L Fanjul-Moles 2015. 

There is a potentially key role for cryptochrome in providing a direct association between a (theorised) navigation system (magnetoreception) and the circadian clock system, which could potentially be key to the maintaining synchronisation across the piece through a combined clock/compass (GPS system) – this is explored in another article – click here to find out more.

Circadian genes and Brain Plasticity

Researchers at Harvard University have also found that circadian genes play a vital role in mammalian brain development and plasticity (that is, the ability of the brain to learn from, and physically change in response to, environmental experiences). Mice deficient for the core circadian gene ‘Clock’ had significantly delayed and prolonged plasticity in the visual system. They found a cell-intrinsic Clock may control the normal trajectory of brain development”. Kobayashi et al., 2015.

Recent studies suggest that cellular circadian clocks may regulate adult neurogenesis and survival of newly formed neurons, although circadian studies of neurogenesis in vitro are lacking. During adult neurogenesis, multipotent neural stem cells self-renew and differentiate to generate neurons.  A Malik 2015. The observed circadian regulation of adult hippocampal neurogenesis (Bouchard-Cannon et al., 2013) could complement circadian regulation of dendritic spine formation and stabilization.  This is not surprising in view the evidence of a wider role circadian rhythms in morphogenesis – click here to find out more.

There is evidence of circadian rhythms in synaptic plasticity, in some cases driven by the central clock and in others by peripheral clocks. Circadian rhythms in brain temperature, hormone/neuromodulator concentrations and GABAergic signalling may adjust the gain of different forms of plasticity as a function of circadian time.  These central influences likely work in concert with peripheral clocks that modulate the response to the central influence and also control cellular processes that impact on plasticity. M G Frank 2016.

In Drosophila, numerous circadian rhythms have also been detected in non-clock neurons, especially in the first optic neuropil (lamina) of the fly’s visual system. Such rhythms have been observed in the number of synapses and in the structure of interneurons, which exhibit changes in size and shape in a circadian manner.. Ewelina Kijak 2017. Circadian rhythms in synaptic morphology are reported in the mammalian cortex and hippocampus.   Also see M Jasinska 2017 on the circadian plasticity of mammalian inhibitory Interneurons.

Clock genes may also have roles outside their classic time keeping functions and orchestrate intercellular events that influence the strength or number of synapses, e.g in the striatum, plasticity can occur in dopaminergic synapses.  Several dopaminergic genes are direct transcriptional targets of the core clock gene clock – resulting in rhythmic expression of dopamine synthesis and metabolism.  M G Frank 2016.

joined up system

Circadian Rhythms as Phase Transitions?

It has been argued that the collective rhythmicity of circadian clocks may be best obtained by studying it at its outset, that is treating it as a kind of phase transition or bifurcation or self-synchronization transition (Y Kuramoto 1984 and Goldbeter 2007). Winfree discovered that such oscillator populations can exhibit a remarkable cooperative phenomenon. Each body clock has been seen to have a distinct role, but harmonizes with the other sections via a precise phase relationship. J. Z. Li 2014.

Evidence of phase transitions is being widely explored in the field of neurobiology e.g  K.-E. Lee 2013R Kozma and W J Freeman 2016F D Ludin 2015.  and Christian Meisel 2015,G Werner 2009, Self Organised Criticality Models may also be useful in considering this approach J D Cowan 2013A de Andrade Costa 2015Plenz and Thiagarajan 2007

Dramatic switching of brain activity to a new state is observed in both healthy and pathological cases, for example during wake–sleep and wake–anaesthesia cycles, and at seizure onset. It has been proposed recently by Jirsa et al. that different bifurcation types may be responsible for these neural state transitions.

The neural criticality hypothesis states that the brain may be poised in a critical state at a boundary between different types of dynamics. Theoretical and experimental studies show that critical systems often exhibit optimal computational properties, suggesting the possibility that criticality has been selected as a useful trait for our nervous systemJanina Hesse 2014.

Circadian Rhythms and Neurological Dysfunction

Circadian and sleep dysfunctions have been linked to various neurological conditions including:

A growing body of research has also identified significant sleep problems and circadian differences in children with specific learning difficulties. This includes:

It has been suggested that dyslexic people can find their visual symptoms mitigated by filtering out certain types of light (including using blue and yellow filters). Dyslexics may be sensitive to blue light because of differences in circadian rhythms.

It has been reported that ‘Many children with visual reading difficulties have disturbed sleep patterns Their parents are often surprised that the blue filters seem to improve their child’s sleeping. Likewise, many such children complain of headaches when they try to read. Migraine headaches are known to be accompanied by disturbed sleep rhythms. Hence, we now have many anecdotal reports that successful treatment of reading difficulties with blue light filters is accompanied by fewer headaches, and we are now following this up more systematically’J Stein 2014.

Specific learning difficulties are also associated with skewing towards particular modes of attention, e.g autism can be result in focus on detail, and dyslexia is associated with poor selective attention.  It could be the case that this skew is due to differences in cross-frequency neural coupling, which may have an influence on switching between selective and exploratory models of attention. D McLelland 2016. 

Beyond sleep disruption, many of the conditions have been linked to increased levels of oxidative stress (e.g in Autism, and Alzheimer’s) and problems with the immune system.  Many of these conditions are also associated with differences in perception in time and problems with navigation and memory.

Connecting Problems with Sleep, Oxidative Stress and the Immune System

The circadian clockwork and sleepwake cycles closely interact with each other, which is most obviously seen by the gating of sleep at distinct phases of the 24hour cycle… several studies indicate an intimate association of circadian dysfunction and sleep disruption with different human diseases including cancers, heart disease, diabetes, metabolic, vascular, and mental conditions.S Ray and A B Reddy 2016.

In mammals global SCN redox state has been found to undergo an autonomous circadian rhythm. Redox state is relatively reduced in daytime, when neuronal activity is high, and oxidized during nighttime, when neurons are relatively inactive. Redox modulates neuronal excitability via tight coupling M U Gillette 2014, and there are links between the redox state and the membrane excitability of SCN neurons, given that oxidizing and reducing agents can produce hyperpolarization and depolarization, respectivelyM L Fanjul-Moles 2016.

It is clear that there is a rhythmic pattern in cell function and cycles of energy utilization in accordance with a daily rhythm, while sleep plays a crucial role in maintaining metabolic homeostasis. However, the mechanism of bidirectional communication between the sleep centers and the circadian pacemaker, and their regulation of diverse metabolic networks is still unclear. S Ray and A B Reddy 2016.

This cycle may also be closely linked with the immune system. In plants it has been found that redox rhythm reinforces the circadian clock to gate immune response. M Zhou 2015.  In humans most immune cells express circadian clock genes and present a wide array of genes expressed with a 24-h rhythm…Consequently, alterations of circadian rhythms (e.g., clock gene mutation in mice or environmental disruption similar to shift work) lead to disturbed immune responsesN Labrecque 2015.  A M Curtis 2014,  C Scheiermann – ‎2013A Nakao – ‎2014.

The Possible Influence of Microbiota

Another area of development is the association being found between microbiota/bacteria and a bidirectional influence on circadian rhythms, which would not be surprising in view of the links between circadian rhythms and immunity and the metabolism.

Microbes have long been implicated in the triggering of a number of neurological conditions, and recently evidence has been found of a number of examples where microbes are influencing the biological clocks of other species. EAC Heath-Heckman (2016)C A Thaiss 2016,   C A Thaiss 2015,  EAC Heath-Heckman – ‎2013.

Circadian Rhythms and Mitohchondrial dysfunction

It has been found that Mitrochondrial dysfunction is common in people with autism (and various other neurological conditions).

Recently findings have shown that more than 68% of ASD cases shared a common histone acetylation pattern at 5,000 gene loci, despite the wide range of genetic and environmental causes of ASD. Histone acetylation and other posttranslational modifications have been linked to clock function.  Rhythms of histone acetylation contribute to the circadian expression pattern of some core circadian genes

Recent work highlights that clock‐driven acetylation modulates a considerable number of mitochondrial proteins involved in multiple metabolic networks . S Ray and A Reddy 2016.

Circadian Rhythms, Language Development and Skills

A number of neurological conditions evidence language dysfunction.

Scientists have identified that dyslexics have problems with the rhythms of speechChildren with dyslexia often find it difficult to count the number of syllables in spoken words or to determine whether words rhyme.  M Huss 2011.

It has been found that generally, there are optimal times in the day for learning other languages (suggesting circadian rhythms influence language learning) Kees De Bot 2015, and may influence language performance. J Rosenberg 2009. 

Hearing may also play a role. During the day a hormone called brain-derived-neurotrophic factor (BDNF) is distributed into the ears. This hormone protects the auditory nerves from damage. It provides a layer of insulation to protect the ears from harmful noises that are more likely during waking or day hours. This mechanism is based on circadian rhythms.

Circadian Rhythms, Social Skills and Different Social Roles

It is interesting to consider whether oscillatory activity could also influence social activities and roles.  Studies of swarms might help develop this understanding.

For example social insects such as honeybees, ants, wasps and termites live in colonies consisting of up to a few million individuals who coordinate almost every aspect of their lives.  The temporal coordination of their activities is thought to be important for efficient colony functioning and therefore colony fitness. The most intuitive aspect of their temporal coordination is synchronising their phase of activity (social entrainment).   Honeybees show a colony level circadian rhythm that is maintained in constant light and can be phase-shifted as the rhythms of individual animals. The synchronization of individuals in insect societies is thought to be functionally significant because it improves colony efficiency. G Bloch 2013, R Menzel 2012.

It should be noted that while both scouts and forager bees look alike, research suggests that they represent stable subpopulations with distinctive patterns of gene expression in their brains, resulting in different behaviours.  We assume that everyone’s neural oscillations should be the same, but it may be the case that genetically driven differences are required to support collective behaviours.

Conclusion

The importance of timing in support the synchronisation of different functions of the brain is just beginning to be explored.  This is likely to reveal a complex, self organising, adapative system.

We need to move away from an approach where we merely focus on assigning individual functions to individual parts of the brain, and argument ‘for and against’ a particular part of the brain having a particular function.

Increasingly we need to focus on how everything fits together and works as a whole.

Within such an approach there are no absolute boundaries, and thus what happens within the brain, might connect to processes taking place elsewhere in the body, and externally.

October 2016 (reworked on 14/04/2017). This article merely joins up other peoples work into an overall system.  These works have been referenced so it is clear that others have provided the individual pieces of evidence that have been used to shape a specific systems approach.    

 

 

 

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