Category Archives: thalamus

The indirect route

There has been a bit of mystery around how different areas of the cortex initiate shared synchrony or seem to pass information between them.

A paper from a few years back (Poulet, Fernandez, Crochet, Peterson; Thalamic control of cortical states; Nature 2012) showed that the activity of the whiskers of mice affected the state of activity in the cortex. How did the whiskers affect the whole cortex rather than just the whisker sensory area? It was via the thalamus shown by producing the effect without whisker activity by stimulation of thalamus alone.

We investigated the impact of thalamus on ongoing cortical activity in the awake, behaving mouse. We demonstrate that the desynchronized cortical state during active behavior is driven by a centrally generated increase in thalamic action potential firing, which can also be mimicked by optogenetic stimulation of the thalamus. The thalamus therefore is key in controlling cortical states.”

But that was a very general demonstration of thalamic control of large areas of the cortex. What about more specific action? A more recent paper, which uses a wide array of methods, shows a specific case (Wimmer, Schmitt, Davidson, Nakajima, Desseroth, Halassa; Thalamic control of sensory selection in divided attention; Nature 2016).

From their introduction: “Thirty years ago, Francis Crick proposed that the TRN (thalamic reticular nucleus) functions as a searchlight, directing the internal spotlight of attention to thalamo-cortical circuits that process ongoing behavioral demands. Due to technical limitations, this transformative model has been difficult to test, particularly under conditions where the attentional spotlight shifts. Our study combined novel and established technology to provide mechanistic details for Crick’s ‘searchlight hypothesis’. As such, we have taken important step in understanding the circuit mechanisms of sensory selection.”

The object/s of attention can come from bottom-up or top-down processes. In other words they can be triggered by perception or by cognitive and motor demands; triggered by external events or internal tasks. Top-down demands for attention to specific targets appear to originate in the frontal cortex and travel to specific areas of the sensory cortex making them more active. This paper shows that the information travels from the pre-frontal cortex to the appropriate sensory cortex area by way of the thalamus, via the appropriate part of the thalamic reticular nucleus.

Here is their abstract : “How the brain selects appropriate sensory inputs and suppresses distractors is a central unsolved mystery in neuroscience. Given the well-established role of prefrontal cortex (PFC) in executive function, its interactions with sensory cortical areas during attention have been hypothesized to control sensory selection. To test this idea and more generally dissect the circuits underlying sensory selection, we developed a cross-modal divided attention task in mice enabling genetic access to this cognitive process. By optogenetically perturbing PFC function in a temporally- precise window, the ability of mice to appropriately select between conflicting visual and auditory stimuli was diminished. Surprisingly, equivalent sensory thalamo-cortical manipulations showed that behavior was causally dependent on PFC interactions with sensory thalamus, not cortex. Consistent with this notion, we found neurons of the visual thalamic reticular nucleus (visTRN) to exhibit PFC-dependent changes in firing rate predictive of the modality selected. visTRN activity was causal to performance as confirmed via subnetwork-specific bi-directional optogenetic manipulations. Through a combination of electrophysiology and intracellular chloride photometry, we demonstrated that visTRN dynamically controls visual thalamic gain through feedforward inhibition. Combined, our experiments introduce a new subcortical model of sensory selection, where prefrontal cortex biases thalamic reticular subnetworks to control thalamic sensory gain, selecting appropriate inputs for further processing.

It is worth considering the idea that most of the information flow from one part of the cortex to another, where there is no clear, direct nerve tract, is actually traveling by way of the thalamus.

Where is consciousness?

A particular type of epilepsy has been treated by cutting the corpus callosum, the tracks of nerves connecting the two hemispheres of the cerebrum. The result had very little side effects on the patients. However, with closer experimental studies, the nature of the split brain was examined. Only the left hemisphere spoke and so only stimuli presented to the left visual field resulted in spoken replies and responses of the right hand. The right hemisphere could understand written language presented to the right visual field and made responses with the left hand but never spoke. Based on this and similar evidence, it was assumed that there were two minds (that is two consciousnesses) in a split brain.

A recent paper has upset this hypothesis: Pinto, Neville, Otten, Corballis, Lamme, de Haan, Foschi, & Fabri; Split brain: divided perception but undivided consciousness; Brain Jan 2017. Here is the abstract:

In extensive studies with two split-brain patients we replicate the standard finding that stimuli cannot be compared across visual half-fields, indicating that each hemisphere processes information independently of the other. Yet, crucially, we show that the canonical textbook findings that a split-brain patient can only respond to stimuli in the left visual half-field with the left hand, and to stimuli in the right visual half-field with the right hand and verbally, are not universally true. Across a wide variety of tasks, split-brain patients with a complete and radiologically confirmed transection of the corpus callosum showed full awareness of presence, and well above chance-level recognition of location, orientation and identity of stimuli throughout the entire visual field, irrespective of response type (left hand, right hand, or verbally). Crucially, we used confidence ratings to assess conscious awareness. This revealed that also on high confidence trials, indicative of conscious perception, response type did not affect performance. These findings suggest that severing the cortical connections between hemispheres splits visual perception, but does not create two independent conscious perceivers within one brain.

When they showed an object in both visual fields and if the objects were the same or different, the split brain subject could not answer that question with either hand or by speech. They could not examine the objects together – so it was correct that the perception in the two hemispheres was separate and isolated. But if an object was placed in either or both visual fields, the subjects could say how many objects there were in total and there was no different in the answer coming from the left or right hand, or the voice. So although they could not examine the objects together, their consciousness covered the entire visual field – there was only one consciousness.

What can explain this if the results hold up? Perhaps the two hemispheres have learned unusual ways of communicating outside of the normal connections. Perhaps it is some dualistic magic. Or, to me more likely, consciousness is not a product of the cerebrum. It is created in some other part of the brain that can receive information from both hemispheres and can store its creation in immediate memory where it is available to the hemispheres. There is an obvious candidate, the thalamus. It is not cut in half by the cutting of the corpus callosum. It is connected to almost all areas of the brain and almost all information passes through it at some stage of its processing. It is the one part of the brain that must be functioning for consciousness to occur.

There has been for years an assumption that the cerebrum is the engine of thought and a number of things are puzzles because they cannot be understood looking at the cerebral cortex alone. It is time to thing about the possibility that the thalamus drives the cerebrum: it feeds information to the cortex, it creates the rhythms and synchronization in the cortex, and it controls the communication networks in the cortex. The thalamus may have the cortex as an on-line computer, to use that metaphor. But then the thalamus is in the center of the brain and the cortex is laid out on the surface. It is easier the examine the cortex and so the rest of the brain gets neglected. Like the man looking for his keys under the street lamp because the light is better there even though he lost them elsewhere.


local or not

A recent press release describes a paper ( T. A. Engel, N. A. Steinmetz, M. A. Gieselmann, A. Thiele, T. Moore, K. Boahen. Selective modulation of cortical state during spatial attention. Science, 2016; 354 (6316): 1140 DOI: 10.1126/science.aag1420 ) on the neural activity during awake attention. Here is the abstract:

Neocortical activity is permeated with endogenously generated fluctuations, but how these dynamics affect goal-directed behavior remains a mystery. We found that ensemble neural activity in primate visual cortex spontaneously fluctuated between phases of vigorous (On) and faint (Off) spiking synchronously across cortical layers. These On-Off dynamics, reflecting global changes in cortical state, were also modulated at a local scale during selective attention. Moreover, the momentary phase of local ensemble activity predicted behavioral performance. Our results show that cortical state is controlled locally within a cortical map according to cognitive demands and reveal the impact of these local changes in cortical state on goal-directed behavior.

I find the techniques and the results very interesting. However, I have trouble with the idea that attention has a purely cortical mechanism. Why are the fluctuations in activity said to be endogenously generate? Why is the cortical state controlled locally within a cortical map according to cognitive demands and reveal the impact of these local changes in cortical state on goal-directed behavior? The cortex is not isolated from the rest of the brain. To say some effect is locally generated in the cortex would required showing that the activity level was not affected by the thalamus and associated parts of the brain. The back and forth between cortical columns and the thalamus is the key to cortical function and a requirement for attention, consciousness and wakefulness. This is not a new idea but has been around for a long time. Why does this study not just ignore it, but deny it?

The conclusion to a paper (Sallmann and Kastner, Cognitive and Perceptual Functions of the Visual Thalamus Neuron. 2011 Jul 28; 71(2): 209–223) outlines some signaling between various parts of the thalamus and the cortex.

The overall evidence that has emerged during recent years suggests that the visual thalamus serves a fundamental function in regulating information transmission to the cortex and between cortical areas according to behavioral context. Selective attention and visual awareness have been shown to modulate LGN (thalamus lateral geniculate nucleus) activity, thus indicating that the LGN filters visual information before it reaches the cortex. Behavioral context appears to even more strongly modulate pulvinar activity and, due to its connectivity, the pulvinar (a part of the thalamus) is well-positioned to influence feedforward and feedback information transmission between cortical areas. Because the TRN provides strong inhibitory input to both the LGN and pulvinar, the TRN (thalamic reticular nucleus) may control and coordinate the information transmitted along both retino-cortical and cortico-cortical pathways.

Parasuraman and Davis in Varieties of Attention, page 236, described the networks involved in attention as long ago as 1984.

Three interacting networks mediating different aspects of attention: (1) a posterior attention system comprising parietal cortex, superior colliculus (a midbrain area), and pulvinar(thalamus area) that is concerned was spatial attention; (2) anterior system centered on the anterior cingulate in the medial frontal lobe that mediates target detection and executive control; (3) a vigilance system consisting of the right frontal lobe and brainstem nuclei, principally the noradrenergic locus coerulus (LC).

The brain is a functioning whole not a group of completely independent parts. As the Engel group do not seem to even address the question of involvement of regions of the brain other then the cortex – how can they state that the activity level of a column is locally produced?


Beta waves

Judith Copithorne image

Judith Copithorne image

Brain waves are measured for many reasons and they have been linked to various brain activities. But very little is known about how they arise. Are they the result or the cause of the activities they are associated with? How exactly are they produced at a cellular or network level? We know little about these waves.

One type of wave, beta waves (18-25 Hz) are associated with consciousness and alertness. In the motor cortex they are found when muscle contractions are isotonic (contractions that do not produce movement) but are absent just prior and during movement. They are increased during sensory feedback to static motor control and when movement is resisted or voluntarily suppressed. In the frontal cortex the beta waves are found during attention to cognitive tasks directed to the outside world. They are found in alert attentive states, problem solving, judgment, decision making, and concentration. The more involved the cognitive activity the faster the beta waves.

ScienceDaily reports a press release from Brown University on the work of Stephanie Jones and team, who are attempting to understand how beta waves arise. (here) Three types of study are used: MEG recordings, computer models, and implanted electrodes in animals.

The MEG recordings from the somatosensory cortex (sense of touch) and the inferior frontal cortex (higher cognition) showed a very distinct form for the beta waves, “they lasted at most a mere 150 milliseconds and had a characteristic wave shape, featuring a large, steep valley in the middle of the wave.” This wave form was recreated in a computer model of the layers of the cortex. “They found that they could closely replicate the shape of the beta waves in the model by delivering two kinds of excitatory synaptic stimulation to distinct layers in the cortical columns of cells: one that was weak and broad in duration to the lower layers, contacting spiny dendrites on the pyramidal neurons close to the cell body; and another that was stronger and briefer, lasting 50 milliseconds (i.e., one beta period), to the upper layers, contacting dendrites farther away from the cell body. The strong distal drive created the valley in the waveform that determined the beta frequency. Meanwhile they tried to model other hypotheses about how beta waves emerge, but found those unsuccessful.” The model was tested in mice and rhesus monkeys with implanted electrodes and was supported.

Where do the signals come from that drive the pyramidal neurons? The thalamus is a reasonable guess at the source. Thalamo-cortex-thalamus feedback loop makes those very contacts of the thalamus axons within the cortex layers. The thalamus is known to have signals with 50 millisecond duration. All of the sensory and motor information that enters the cortex (except smell) comes though the thalamus. It regulates consciousness, alertness and sleep. It is involved in processing sensory input and voluntary motor control. It has a hand in language and some types of memory.

The team is continuing their study. “With a new biophysical theory of how the waves emerge, the researchers hope the field can now investigate beta rhythms affect or merely reflect behavior and disease. Jones’s team in collaboration with Professor of neuroscience Christopher Moore at Brown is now testing predictions from the theory that beta may decrease sensory or motor information processing functions in the brain. New hypotheses are that the inputs that create beta may also stimulate inhibitory neurons in the top layers of the cortex, or that they may may saturate the activity of the pyramidal neurons, thereby reducing their ability to process information; or that the thalamic bursts that give rise to beta occupy the thalamus to the point where it doesn’t pass information along to the cortex.

It seems very clear that understanding of overall brain function will depend on understanding the events at a cellular/circuit level; and that those processes in the cortex will not be understood without including other regions like the thalamus in the models.

The brain’s gateway

There have been a few papers lately on the function of the thalamic reticular nucleus (TRN) that characterize it as a filter, a sieve, and a switchboard. The citations and abstracts of 4 of these papers are below. Francis Crick suggested this function for the TRN many years ago but it was not possible until recently to demonstrate it because of the anatomy of the TRN.

The thalamus sits at the center of the brain and is connected to the brain stem and spinal cord below, the cerebral hemispheres above and the basal ganglia to the sides. The thalamus is part of almost all the functional processing loops in the brain. In particular, almost all sensory information enters the cortex from the thalamus, and every corner of the cortex sends signals back to the thalamus. When this traffic, the thalamo-cerebral loops, shut down, so does consciousness.

The TRN is a thin layer of neurons that almost entirely covers the thalamus. Because it is so thin and so deep in the brain, it has been difficult to study. New methods have overcome some of these problems.

In effect all the traffic between the cortex and the thalamus is carried by axons that pass through the TRN and the axons have little branches that make contact with TRN neurons. In other words the TRN gets a smell of all the passing signals – it does not interfere with the axons but just spies on them. The TRN neurons are inhibitory, so when a passing signals activates one of them, it will suppress the neuron in the thalamus that is sending or receiving the signal. This action keeps most activity at a low level. During sleep the thalamo-cerebral loops are effectively turned off and sensory information does not reach the cortex. During attention (and multitasking) the TRN reduces distracting signals but not the attended ones. It also seems to control the type of sleep by controlling types of brain waves in the cortex during sleep. The executive functions of the prefrontal cortex seems to act through the TRN rather than directly on areas of the cortex, to control attention (steer the spotlight of attention).

Here are the abstracts and citations:

Sandra Ahrens, Santiago Jaramillo, Kai Yu, Sanchari Ghosh, Ga-Ram Hwang, Raehum Paik, Cary Lai, Miao He, Z Josh Huang, Bo Li. ErbB4 regulation of a thalamic reticular nucleus circuit for sensory selection. Nature Neuroscience, 2014; DOI: 10.1038/nn.3897

Selective processing of behaviorally relevant sensory inputs against irrelevant ones is a fundamental cognitive function whose impairment has been implicated in major psychiatric disorders. It is known that the thalamic reticular nucleus (TRN) gates sensory information en route to the cortex, but the underlying mechanisms remain unclear. Here we show in mice that deficiency of the Erbb4 gene in somatostatin-expressing TRN neurons markedly alters behaviors that are dependent on sensory selection. Whereas the performance of the Erbb4-deficient mice in identifying targets from distractors was improved, their ability to switch attention between conflicting sensory cues was impaired. These behavioral changes were mediated by an enhanced cortical drive onto the TRN that promotes the TRN-mediated cortical feedback inhibition of thalamic neurons. Our results uncover a previously unknown role of ErbB4 in regulating cortico-TRN-thalamic circuit function. We propose that ErbB4 sets the sensitivity of the TRN to cortical inputs at levels that can support sensory selection while allowing behavioral flexibility.

Ralf D. Wimmer, L. Ian Schmitt, Thomas J. Davidson, Miho Nakajima, Karl Deisseroth, Michael M. Halassa. Thalamic control of sensory selection in divided attention. Nature, 2015; DOI: 10.1038/nature15398

How the brain selects appropriate sensory inputs and suppresses distractors is unknown. Given the well-established role of the prefrontal cortex (PFC) in executive function, its interactions with sensory cortical areas during attention have been hypothesized to control sensory selection. To test this idea and, more generally, dissect the circuits underlying sensory selection, we developed a cross-modal divided-attention task in mice that allowed genetic access to this cognitive process. By optogenetically perturbing PFC function in a temporally precise window, the ability of mice to select appropriately between conflicting visual and auditory stimuli was diminished. Equivalent sensory thalamocortical manipulations showed that behaviour was causally dependent on PFC interactions with the sensory thalamus, not sensory cortex. Consistent with this notion, we found neurons of the visual thalamic reticular nucleus (visTRN) to exhibit PFC-dependent changes in firing rate predictive of the modality selected. visTRN activity was causal to performance as confirmed by bidirectional optogenetic manipulations of this subnetwork. Using a combination of electrophysiology and intracellular chloride photometry, we demonstrated that visTRN dynamically controls visual thalamic gain through feedforward inhibition. Our experiments introduce a new subcortical model of sensory selection, in which the PFC biases thalamic reticular subnetworks to control thalamic sensory gain, selecting appropriate inputs for further processing.

Laura D Lewis, Jakob Voigts, Francisco J Flores, Lukas I Schmitt, Matthew A Wilson, Michael M Halassa, Emery N Brown. Thalamic reticular nucleus induces fast and local modulation of arousal state. eLife, October 2015 DOI: 10.7554/eLife.08760

During low arousal states such as drowsiness and sleep, cortical neurons exhibit rhythmic slow wave activity associated with periods of neuronal silence. Slow waves are locally regulated, and local slow wave dynamics are important for memory, cognition, and behaviour. While several brainstem structures for controlling global sleep states have now been well characterized, a mechanism underlying fast and local modulation of cortical slow waves has not been identified. Here, using optogenetics and whole cortex electrophysiology, we show that local tonic activation of thalamic reticular nucleus (TRN) rapidly induces slow wave activity in a spatially restricted region of cortex. These slow waves resemble those seen in sleep, as cortical units undergo periods of silence phase-locked to the slow wave. Furthermore, animals exhibit behavioural changes consistent with a decrease in arousal state during TRN stimulation. We conclude that TRN can induce rapid modulation of local cortical state.

Michael M. Halassa, Zhe Chen, Ralf D. Wimmer, Philip M. Brunetti, Shengli Zhao, Basilis Zikopoulos, Fan Wang, Emery N. Brown, Matthew A. Wilson. State-Dependent Architecture of Thalamic Reticular Subnetworks. Cell, 2014; 158 (4): 808 DOI: 10.1016/j.cell.2014.06.025

Behavioral state is known to influence interactions between thalamus and cortex, which are important for sensation, action, and cognition. The thalamic reticular nucleus (TRN) is hypothesized to regulate thalamo-cortical interactions, but the underlying functional architecture of this process and its state dependence are unknown. By combining the first TRN ensemble recording with psychophysics and connectivity-based optogenetic tagging, we found reticular circuits to be composed of distinct subnetworks. While activity of limbic-projecting TRN neurons positively correlates with arousal, sensory-projecting neurons participate in spindles and show elevated synchrony by slow waves during sleep. Sensory-projecting neurons are suppressed by attentional states, demonstrating that their gating of thalamo-cortical interactions is matched to behavioral state. Bidirectional manipulation of attentional performance was achieved through subnetwork-specific optogenetic stimulation. Together, our findings provide evidence for differential inhibition of thalamic nuclei across brain states, where the TRN separately controls external sensory and internal limbic processing facilitating normal cognitive function.

The thalamus revisited

For a few decades, I have had the opinion that to understand how the brain works it is important to look at more than the neocortex, but also look to the other areas of the brain that may modify, control or even drive the activity of the cortex. Because of my special interest in consciousness, the thalamus was always interesting in this respect. Metaphorically the cortex seemed to be the big on-line computer run by the thalamus.

A recent paper makes another connection between the cortex and the thalamus, to add to many others – (F. Alcaraz, A. R. Marchand, E. Vidal, A. Guillou, A. Faugere, E. Coutureau, M. Wolff. Flexible Use of Predictive Cues beyond the Orbitofrontal Cortex: Role of the Submedius Thalamic Nucleus. Journal of Neuroscience, 2015; 35 (38): 13183 DOI: 10.1523/JNEUROSCI.1237-15.2015).

The various parts of the thalamus are connected to incoming sensory signals, all parts of the cortex, the hippocampus, the mid-brain areas, the spinal cord and the brain stem. It is one of the ‘hubs’ of the brain and its activity is essential for consciousness. However, the particular bit of the thalamus that is implicated in this particular function (adaptive decision making flexibility) appears to have been mainly studied in relationship to pain and control of pain. There is a lot to learn about the thalamus!

Here is the abstract: “The orbitofrontal cortex (OFC) is known to play a crucial role in learning the consequences of specific events. However, the contribution of OFC thalamic inputs to these processes is largely unknown. Using a tract-tracing approach, we first demonstrated that the submedius nucleus (Sub) shares extensive reciprocal connections with the OFC. We then compared the effects of excitotoxic lesions of the Sub or the OFC on the ability of rats to use outcome identity to direct responding. We found that neither OFC nor Sub lesions interfered with the basic differential outcomes effect. However, more specific tests revealed that OFC rats, but not Sub rats, were disproportionally relying on the outcome, rather than on the discriminative stimulus, to guide behavior, which is consistent with the view that the OFC integrates information about predictive cues. In subsequent experiments using a Pavlovian contingency degradation procedure, we found that both OFC and Sub lesions produced a severe deficit in the ability to update Pavlovian associations. Altogether, the submedius therefore appears as a functionally relevant thalamic component in a circuit dedicated to the integration of predictive cues to guide behavior, previously conceived as essentially dependent on orbitofrontal functions.

SIGNIFICANCE STATEMENT: In the present study, we identify a largely unknown thalamic region, the submedius nucleus, as a new functionally relevant component in a circuit supporting the flexible use of predictive cues. Such abilities were previously conceived as largely dependent on the orbitofrontal cortex. Interestingly, this echoes recent findings in the field showing, in research involving an instrumental setup, an additional involvement of another thalamic nuclei, the parafascicular nucleus, when correct responding requires an element of flexibility (Bradfield et al., 2013a). Therefore, the present contribution supports the emerging view that limbic thalamic nuclei may contribute critically to adaptive responding when an element of flexibility is required after the establishment of initial learning.

The John paper 2


This is the second part of a look at an old paper: E. Roy John; The neurophysics of consciousness; Brain Research Reviews, 39, 2002 pp 1-28. It is about brain waves.

Some background is needed to understand his model. EEG measures the voltage potentials on the scalp and from these are inferred the voltage potentials on/in the the cortex outer layers. From the changes in these potentials it is possible to look at the underlying waves. The trace is mathematically separated into component waves and these are graphed in separate bands of frequency. The amount of energy in each band is calculated. This is the power spectrum. The conventional bands are: gamma (25-50 cycles per second or Hz), beta (12.5-20), alpha (7.5-12.5), theta (3.5-7.5), delta (1.5-3.5). These fluctuations in potential affect the activity of neurons. The potential across the neuron’s membrane has a threshold which allows initiation of an electrical signal to be propagated along the neuron cell and axon. The potentials imposed by the electrical waves bring the neuron membrane closer or further from the threshold and therefore make activity easier or harder. (John does not deal with any contribution glia cells make to this system – perhaps too early a paper for that.) The imposition of a wave will tend to synchronize the activity of neurons because they will tend to reach threshold at nearly the same time and then have similar periods of recovery when they cannot signal. Each cycle of the wave will bring more neurons into the synchrony. The waves arise in pacemaker cells that naturally oscillate at a particular frequency (like heart pace maker cells).

John gives the following picture of the actions of brain waves:

The observed predictability of the EEG power spectrum arises from regulation by anatomically complex homeostatic systems in the brain. Brainstem, limbic, thalamic and cortical processes involving large neuronal populations mediate this regulation, utilizing all the major neurotransmitters. Pacemaker neurons distributed throughout the thalamus normally oscillate synchronously in the alpha (7.5–12.5 Hz) frequency range. Efferent globally distributed thalamo-cortex projections produce the rhythmic electrical activity known as the alpha rhythm, which dominates the EEG of an alert healthy person at rest.”

Note: there are a number of ‘nuclei reticularis’ or ‘reticular nuclei’ in the brain and John does not say which he is referring to. The problem is not serious. There is an extention of the spinal cord that runs through the brain stem, midbrain and ends in the thalamus, called the reticular formation. Somewhere between the brain stem and the thalamus, very probably at the thalamus end is the nucleus he is referring to. The reticular system includes the ascending reticular activating system and it must be active for the brain to function normally.

Nucleus reticularis can hyperpolarize the cell membranes of thalamic neurons by gamma-amino-butyric acid (GABA) release, slowing the dominant alpha rhythm into the lower theta range (3.5–7.5 Hz), and diminishing sensory throughput to the cortex. Theta activity can also be generated in the limbic system, possibly by theta pacemaker cells in the septal nuclei which can be inhibited by entorhinal and hippocampal influences. Slow delta activity (1.5–3.5 Hz) is believed to originate in oscillator neurons in deep cortical layers and in the thalamus, normally inhibited by input from the ascending reticular activating system in the midbrain. Delta activity may reflect hyperpolarization of cortical neurons resulting in dedifferentiation of neural activity. Activity in the beta band (12.5–20 Hz) is believed to reflect cortico-cortical and thalamo-cortical transactions related to specific information processing. Activity in the gamma bands (25– 50 Hz) may reflect cortico-thalamo-cortical reverberatory circuits, as well as back-propagation of axonal discharges to the dendrites of cortical pyramidal cells, which may play an important role in perception as proposed in this paper.”

Note: Although the cortex does affect these rhythms, it is not the source of the original pacemakers.

John works through an example: “…Assume that a subject is asleep, with diminished activity in the ascending reticular activating system, an EEG dominated by slow delta and theta waves reflecting inhibition of the thalamus by nucleus reticularis and consequent diminution of sensory input to the cortex…a sudden increase of stimuli in the environment results in inhibition of nucleus reticularis releasing the thalamic cells from inhibition by n. reticularis. The dominant activity of the EEG power spectrum becomes more rapid, with return of alpha activity. Increased flow of information through the thalamus to the cortex is facilitated, resulting in cortico-cortical interactions reflected by increased beta activity. Coincidence detection by pyramidal cells comparing this exogenous input with readout of endogenous activity activates cortical-thalamic loops generating gamma activity and mediating perception of the sensory information. Collaterals (side branches) go to n. reticularis from corticothalamic axons. The cortex can activate n. reticularis by these axons indirectly en passage or directly by glutamatergic path-ways, to suppress the arrival of information to the cortical level. Indirectly, as an alternative result of cortical influences, dopaminergic striatal projections can inhibit the (reticular formation). Such inhibition enables inhibition of thalamic neurons by n. reticularis, blocking transmission from the thalamus to the cortex. The dominant activity of the power spectrum slows toward or into the theta range. The cortex can thus modulate its own information input. The potential role of this mechanism in awareness and the focusing of attention should be apparent.”

Examination of the momentary voltage fields (LFPs local field potentials) on the scalp reveals a kaleidoscope with positive hills and negative valleys on a landscape, or ‘microstate’, which changes continuously. Computerized classification of microstates observed in EEGs of 400 normal subjects, aged 6–80 years, yielded the same small number of basic topographic patterns in every individual, with approximately equal prevalence. The topographies of these instantaneous brain voltage fields closely resemble the computed modes of factor loadings obtained in SPC (calculated spatial principle component analysis) studies. This correspondence suggests that the SPC loadings are not a computational artifact, but may reflect biologically meaningful processes.

The mean microstate duration slowly decreases during childhood, stabilizing for healthy young adults at ~82+/-4 ms. Although the field strength waxes and wanes, the stable landscapes persist with this duration. … The transition probabilities from microstate to microstate are apparently altered during cognitive tasks. Different microstates seem to correlate with distinctive modes of ideation. The stability of the microstate topographies and their mean duration across much of the human life span again supports the suggestion of genetic regulation.

Note: John does not mention modes such as the default mode but this seems like a description of mode changes – again too early for that.

Perceptual time is regulated, parsed into discontinuous intervals. Although subjective time is experienced as continuous, brain time is discontinuous, parsed by some neuro-physiological process into epochs of ~80 ms which define a ‘traveling moment of perception’. Sequential stimuli that occur within this brief time interval will be perceived as simultaneous, while events separated by a longer time are perceived as sequential. Other evidence has led to similar proposals that consciousness is discontinuous and is parsed into sequential episodes by synchronous thalamo-cortical activity. Multimodal asynchronous sensory information may thereby be integrated into a global instant of conscious experience. The correspondence between the experimentally obtained durations of each subjective episode and the mean duration of microstates suggest that a microstate may correspond to a ‘perceptual frame’. The phenomenon of ‘backward masking’ or metacontrast, consisting of the ability of a later sensory input to block perception of an event earlier in time, suggests that perhaps two separate events within a single frame are required for conscious perception. These two events might represent independent inputs to a comparator. (This seems to mean the a stimulus must be stable over a good part of a frame to be saved.)

The exact time at which conscious perception occurs following sensory input is unclear. Certainly, it is delayed beyond 50–100 ms since stimuli are particularly susceptible to masking by a competing stimulus during this period. Psychophysical evidence shows that the perceptual frame closes at ~80–100 ms after occurrence of a specific event. Although it is clear that time for the brain is discontinuous, the frame duration may differ in the various sensory modalities. A mechanism may be required to synchronize sensory elements sampled at different rates in disparate modalities. Based on train duration studies, Libet has suggested that perception may occur as late as 300–500 ms post stimulus. Extending train duration of repetitive direct cortical stimuli up to but not beyond 300–500 ms lowered perceptual threshold. These train duration effects have been reproduced for stimuli applied to the cerebral cortex via intracerebral electrodes. Similar duration effects have been shown using repetitive transcranial magnetic or direct electrical stimulation of the cortex and sensory deficit or neglect in healthy volunteers.”

In order to achieve the stable persistence of LFP topography revealed by microstate analysis, while displaying such duration effects and susceptibility to disruption by masking stimuli, some reentrant or reverberatory brain process must sustain cortical transactions as a steady state, independent of the activity of individual neurons.”

Note: John seems to be thinking in terms of standing waves here.

Such a process, called the ‘hyperneuron’, has been postulated and described in some detail. This persistent electrical field, produced by reverberating loops, may correspond to a neural correlate of the ‘dynamic core’ postulated by Tononi and Edelman. According to this concept, there must exist a set of spatially distributed and meta-stable thalamo-cortical elements that sustains continuity of awareness in spite of constantly changing composition of the neurons within that set.”

More in a later post.


The John paper 1


I have been looking at a paper that is not very recent but none the less very interesting. It took ages to find a copy of it that I could access and download but now when I go back it is no longer there. The paper is E. Roy John; The neurophysics of consciousness; Brain Research Reviews, 39, 2002 pp 1-28. Those of you who have access to various sources will be able to download the pdf but I can no longer supply a link.

The paper describes a proposed global brain process. There are local processes to establish ‘fragments of sensation’ and these are connected to give ‘fragments of perception’, but a complete ‘frame’ of perception requires non-local processing. Consciousness appears to require a brain-wide process. John sees these processes in terms of EEG patterns. I am going to deal with his theory in several posts rather than try to put everything in one. In this post is John’s diagram of consciousness and descriptions of the numbered phases. I feel there are some ‘almighty leaps’ here but there are also some very convincing processes too.

John model












Perceptual frame opens:

process 1 – stimuli from the environment are captured by the sense organs and directed to the thalamus

process 2 – input in the thalamus is directed to the thalamic regions specific for each modality/sense

process 3 – the thalamic regions send volleys, by fast, direct paths to the cortical primary sensory areas of the cortex, the volleys are parsed into perceptual frames – the information is distributed in the sensory cortex and decomposed into ‘fragments of sensation’

process 4 – activity in the local ensembles becomes non-random, and local negative entropy deepens

process 5 – each perceptual frame lasts ~70–100 ms (1 / alpha frequency) and successive frames are each offset by 20–25 ms (1 / gamma frequency) – “this multiplexed activity will produce a steady state which will persist independent of the discharge of particular neurons” (sample and hold).

Now we have a perceptual frame – a field potential pattern throughout the cortex controlled by volleys of sensory specific thalamo-cortical signals.

Relevant context is represented:

At the same time as the processes above, 1 to 5, other information is entering the frame.

process 6 – activity in the thalamus also activates other (non-cortical) regions such as the brainstem, cerebellum, and limbic system which are primed by inputs in the immediate past

process 7 – this activity adds information from recent working memory, episodic memories, states of autonomic, emotional, motivational and motor systems to the non-sensory thalamic regions where this information forms a value/meaning and is directed to cortical areas by the thalamus – it arrives after the original sensory data because of its longer path and provides context to the ‘sample and hold’.

Sensory fragments are converted to fragments of perception:

process 8 – as frames coalesce, elements with most relevance (strong value signal) deliver stronger signals to the comparator system distributed throughout the cortex

process 9 – those pyamidal cells whose fields produce ‘fragments of sensation’ and who also have value signal input, shift their membrane potential above a critical threshold, giving a higher rate of cortico-thalamic activity. This selects them automatically to convert to ‘fragments of perception’.

Perceptual elements are bound together:

A cooperative process is required for the multidimensional binding which provides the fine texture of consciousness and the global nature of a momentary cognitive instant of experience. No cell nor ensemble can subserve the large scale integration required for cognitive interpretation of the totality of significant departures from randomness which constitutes the GNEGP (global negative potential), the integration of LNEGP (local negative potential) activity synchronized across spatially distributed neuronal masses. The actual binding process has been envisaged as a global resonance state, resulting from the coincidence detection of concurrent specific and nonspecific neuronal processes.”

process 10 – rhythmic oscillatory potentials, synchronous and phase-locked across the cortex, act like a scanning voltage which modulates the membrane potentials of the cortical cells. “Rhythmic fluctuation of cortical membrane potentials intensifies a multi-modal cortico-thalamic volley of the distributed LNEGP fragments of perception that is synchronously projected from many cortical areas upon appropriate thalamic regions. These fragments of percepts converge as a coherent cortico-thalamic volley upon the intralaminar nuclei of the thalamus, where they are ‘bound’ into the multimodal, global negative entropy of perception, GNEG- P1. GNegP is the information content of momentary self-awareness.”

process 11 – At the same time signals cause the nucleus reticularis of the thalamus to inhibit the thalamic regions from sending signals to areas of the cortex that have not been caught up in the concordance that produced the GNEGP. This defines the information content of the moment of awareness.

Consciousness emerges from resonating organized energy:

A reverberatory thalamo-cortico-thalamo interaction arises between the thalamic nodes representing GNEGP and those brain regions wherein LNEGP arose, which endows GNEGP1 with specific sensory and emotional dimensions, the ‘qualia’ of the subjective experience.”

process 12 – At the same time, the global perception is projected from the thalamus to the consciousness system, the set of brain regions which change state reversibly with loss of consciousness, causing the consciousness system to becomes highly coherent.

Process 13 – “coherent activation within this set of structures transposes GNEGP into a concentrated electromagnetic field. Establishment of a sufficiently non-random spatio-temporal charge aggregate within a critical neural mass is postulated to produce consciousness, an emergent property of sufficiently organized energy in matter.” This coherent reverberating activation in the CS acts like an ‘analog’ electrical field in a restricted space. John says that the brain is a hybrid digital-analog system.

The content of consciousness and the self:

process 14 – resonance between the consciousness system and the intralaminar nuclei of the thalamus, the percept is given the qualia of the primary sensory regions of the cortex.

process 15 – subjective awareness emerges as an intrinsic property of the coupling of the analog CS with the digital microstate. “It is postulated that much of the early life of human beings is devoted to learning how to reconcile these two classes of brain activity”

process 16 – “the resonant activity impinging upon the adaptive output systems provides feedback to update the value system. Interactions of the intralaminar nucleus and other thalamic nuclei with CS structures modulate efferent systems to produce adaptive outputs such as speech, movement and emotional expression”


More in future posts.



Remember the thalamus


What are we fairly sure about in regards to consciousness?

  • It only happens when the thalamus and cerebrum are in communication;

  • it seems to be associated with a positive signal 300 ms after an event (the P300);

  • it seems to be connected with working memory and the start of further stages of memory;

  • it seems to be connected to the focus of attention;

  • it is probably discontinuous (like frames of a movie);

  • it seems to be involved in communication of its contents to many parts of the brain;

  • gamma waves (about 40 a second), start in the thalamus and move front to back in the cortex, create synchrony in their path, and are essential for consciousness.

There are theories that put these observations together, such as the global workspace model. I am not convinced that these theories are complete because they appear to by-pass the importance of the thalamus. For years there has been a concentration on the cerebral cortex as if it was the “brain”.

Where is the model that puts the thalamus in the center of the action?

Let us assume for a while that the thalamus is the seat of consciousness. When we wake up a group of neurons in the brain stem “wake up” the thalamus, it “wakes up” the cortex and establishes the thalamo-cortical loops, then we are conscious. When we go to sleep the brain stem puts the thalamus “to sleep” and it puts the cortex “to sleep”. Signals from the thalamus control the activity of most regions of the cortex: the input from outside, activity levels, wave synchrony. Signals from the thalamus coordinate attention and the use of working memory – but, they also are the source of the cycle that produces a “frame” of consciousness and feeds it to the hippocampus to become part of a memory. The gathering of the contents of a frame of consciousness through synchrony or short-term memory in the hippocampus allows a certain type of global access to relevant information across the cortex.

Of course the cortex also affects the activity in the thalamus – this is a two way street. But it does seem to me that the thalamus drives the mechanics of consciousness. Something like attention probably is controlled by the cortical products of cognitive processes, acting through cortical executive processes which feed back to the thalamus to be implemented by its control of cortical activity. There would be all sorts of complex interactions like this where the control was in effect circular. But – the thalamus would be the time keeper and the trigger for each stage of the cycle that produces consciousness.

I cannot see a model of consciousness that ignores the thalamus as any more acceptable than one that ignores the cortex.


The pulvinar and attention

The streetlight effect is a type of observational bias where people only look for whatever they are searching for by looking where it is easiest. The parable is told several ways but includes the following details: A policeman sees a drunk man searching for something under a streetlight and asks what the drunk has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, “this is where the light is.” This is how Wikipedia tells how this old joke gave the streetlight effect its name. The effect seems to me to be common in neuroscience. Many researchers seem to ignore the thalamus and concentrate only on the cortex when trying to understand perception, consciousness, attention, and working memory. Just because it is easier to look only at activity in the cortex does not mean that everything happens there.


Part of the thalamus, the pulvinar, has been shown to be involved in attention, especially visual attention. A recent paper (see citation) examines the pulvinar’s role in maintaining attention. This is another bit of evidence pointing to the importance of thalamus-cortex interaction in the areas of perception, consciousness and attention.


Attention is marked by synchronous firing in a number of cortical areas that represent the visual item being held in attention. “Simultaneous neural recordings from two cortical areas have suggested that this selective routing depends on the degree of synchrony between neuronal groups in each cortical area . However, it is unclear how different cortical areas synchronize their activity. Although direct interaction between two cortical areas may give rise to their synchrony, an alternative possibility is that a third area, connected to both of them, mediates cortical synchronization…We therefore hypothesized that the pulvinar increases synchrony between sequential processing stages across the visual cortex during selective attention. ”


The experimental setup was a screen on which appeared a short cue as to where a trigger was going to appear. The monkey had to hold this cued location in mind during a delay before the trigger appeared. The monkey was to react to the type of trigger and not be distracted by other similar images in other locations. The activity in various brain regions could be examined before, during and after the attention that was forced by the delay between cue and trigger. The activity in three areas was followed: two regions along the ventral visual pathway that are synchronous during visual attention and an area of the pulvinar that was in two-way interaction with both these visual areas. The ventral stream is the ‘what’ visual stream that is involved in object recognition, episodic memory and consciousness (as opposed to the ‘where’ dorsal stream involved in motor control and is largely unconscious). During the attention period these areas had increased activity and were synchronized in the alpha and gamma bands. Further, using conditional Granger causality calculations, it was the pulvinar that was influencing the two visual cortex areas rather than the other way around and rather than the two visual areas influencing each other. This pulvinar driving was only seen during the attention period.


The hypothesis, that the pulvinar nucleus of the thalamus maintains attention by increasing “the synchrony between sequential processing stages across the visual cortex”, has some strong corroborating evidence now. Here is the paper’s abstract:


Selective attention mechanisms route behaviorally relevant information through large-scale cortical networks. Although evidence suggests that populations of cortical neurons synchronize their activity to preferentially transmit information about attentional priorities, it is unclear how cortical synchrony across a network is accomplished. Based on its anatomical connectivity with the cortex, we hypothesized that the pulvinar, a thalamic nucleus, regulates cortical synchrony. We mapped pulvino-cortical networks within the visual system, using diffusion tensor imaging, and simultaneously recorded spikes and field potentials from these interconnected network sites in monkeys performing a visuospatial attention task. The pulvinar synchronized activity between interconnected cortical areas according to attentional allocation, suggesting a critical role for the thalamus not only in attentional selection but more generally in regulating information transmission across the visual cortex.

Saalmann, Y., Pinsk, M., Wang, L., Li, X., & Kastner, S. (2012). The Pulvinar Regulates Information Transmission Between Cortical Areas Based on Attention Demands Science, 337 (6095), 753-756 DOI: 10.1126/science.1223082

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