Category Archives: oscillations

Beta waves

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.

Rhythms - always rhythms

Why do we learn trigonometry in our school days and not get past the triangles and on to the waves? Who knows. But waves, rhythms and sine functions are such a constant part of this world. They are certainly important in biology.

We have seasonal rhythms, some of us have monthly rhythms, and we have circadian daily rhythms. Then we have heart rhythms, breathing rhythms, peristaltic gut waves and we have automatic muscle rhythms for walking and eye movements. We use rhythms in our speech, music, and dancing. Then there are the many brain wave patterns that we are only beginning to understand. The brain seems to function using rhythmic waves, waves of many frequencies, overlapping, synchronized and nested.

I noted a few things lately on this subject.

A paper in Cell, Descending Command Neurons in the Brainstem that Halt Locomotion, by J Bouvier and others (here), looks at the control of the start and stop of walking. The walking rhythm comes from an automatic network in the spinal cord but the commands to start and stop walking come from the brain stem. The question was about this signaling. There might be one signal with walking when it was present and not walking when it was absent. Or there could be two signals and this is what they found, separate on and off signals. The interesting thing from the stand point of rhythms is that a ‘stop’ signal was needed. Stopping a rhythm is not simple. The rhythmic dynamic of walking cannot be stop instantaneously to any point. There is no point that it can be just frozen that would leave a stable position with all feet on the ground and the center of gravity not off center. It takes a special functional network to stop the rhythm without stumbling, tripping or falling. Of course the rhythm could be just slowed until it stopped but most animals want to stop ‘on a dime’ rather than after some time.

In a release from UoW Madison (here) there is an outline of the work of J Samaha. He has found that our sight is controlled by the alpha rhythm in the back of the brain. We do not process the information that arrives from the eyes during the trough in the alpha rhythm but only during the peaks. The faster a persons alpha frequency, the more often they sample the world and the better they can distinguish close flashes of light as separate.

ScienceDaily has an item (here) about a paper by R Cho and others about the strengthening of synapses as we form associations during learning, memory and development.

Over the past 30 years, scientists have found that strong input to a postsynaptic cell causes it to traffic more receptors for neurotransmitters to its surface, amplifying the signal it receives from the presynaptic cell. This phenomenon, known as long-term potentiation (LTP), occurs following persistent, high-frequency stimulation of the synapse. Long-term depression (LTD), a weakening of the postsynaptic response caused by very low-frequency stimulation…Scientists have focused less on the presynaptic neuron’s role in plasticity, in part because it is more difficult to study”

Presynaptic cells occasionally release transmitters into the synapse when there is no activity in the cell as a whole and this was thought of as noise. They are called minis. Cho found that minis were not just random noise but they could also strengthen a synapse if they were delivered with a high frequency. “When we gave a strong activity pulse to these neurons, these mini events, which are normally very low-frequency, suddenly ramped up and they stayed elevated for several minutes before going down.” After a signal was transmitted, activity resembling an action potential continued without an actual signal. High frequency minis causes the synapse to strengthen, but low frequency ones do not.

Hand gestures

About 20 years ago I took an interest in the non-verbal part of speech communication: gesture, facial expression, posture, tone of voice. During this time I watched the hands of speakers carefully and noted how they gestured. I saw four types of movement that seemed distinct:

One.. Word gestures took the place of words, quite literally. They were made at the point were the word would be used and there was a gap in speaking for it to fit into so to speak. Also treated like words were the (sometimes impolite) gestures for which Italians are famous.

Two.. Illustrating gestures do not interrupt speech but are separately ‘saying’ the same as the words, like miming while talking.

Three.. There are emotional gestures that are very ancient and even understood across species. They are often completely unconscious. Palms towards the body communicate submission or at least non-aggression. Palms away from the body communicate rejection or defense.

Four.. The fourth type is also usually unconscious. I called it baton gestures. They set a rhythm to the speech and quite often the listener moved in keeping with the baton. It also seemed to emphasize important phrases. The baton beat seemed to mark out groups of words that should be processed together, a great help to a listener if they used it to wrap up one meaning and start on the analysis of the next words.

It is this last type that has been the subject of a recent paper. Unfortunately I have no access to the paper and must be content with the abstract. (grr) Here are the abstracts of this paper and an earlier one by the same authors.

Abstract of (Biau, Torralba, Fuentemilla, Balaguer, Soto-Faraco; Speaker’s hand gestures modulate speech perception through phase resetting of ongoing neural oscillations; Cortex Dec 2014) “Speakers often accompany speech with spontaneous beat gestures in natural spoken communication. These gestures are usually aligned with lexical stress and can modulate the saliency of their affiliate words. Here we addressed the consequences of beat gestures on the neural correlates of speech perception. Previous studies have highlighted the role of theta oscillations in temporal prediction of speech. We hypothesized that the sight of beat gestures may influence ongoing low-frequency neural oscillations around the onset of the corresponding words. Electroencephalographic (EEG) recordings were acquired while participants watched a continuous, naturally recorded discourse. The phase-locking value (PLV) at word onset was calculated from the EEG from pairs of identical words that had been pronounced with and without a concurrent beat gesture in the discourse. We observed an increase in PLV in the 5-6 Hz theta range as well as a desynchronization in the 8-10 Hz alpha band around the onset of words preceded by a beat gesture. These findings suggest that beats tune low-frequency oscillatory activity at relevant segments during natural speech perception, providing a new insight of how speech and paralinguistic information are integrated.

Abstract of (Biau, Soto-Faraco; Beat gestures modulate auditory integration in speech perception; Brain and Language 124, 2, Feb 1013) “Spontaneous beat gestures are an integral part of the paralinguistic context during face-to-face conversations. Here we investigated the time course of beat-speech integration in speech perception by measuring ERPs evoked by words pronounced with or without an accompanying beat gesture, while participants watched a spoken discourse. Words accompanied by beats elicited a positive shift in ERPs at an early sensory stage (before 100 ms) and at a later time window coinciding with the auditory component P2. The same word tokens produced no ERP differences when participants listened to the discourse without view of the speaker. We conclude that beat gestures are integrated with speech early on in time and modulate sensory/phonological levels of processing. The present results support the possible role of beats as a highlighter, helping the listener to direct the focus of attention to important information and modulate the parsing of the speech stream.

Also from a summary of an oral presentation by the same group: “We observed an increase in phase-locking at the delta–theta frequency range (2–6 Hz) from around 200 ms before word-onset to 200 ms post word-onset, when words were accompanied with a beat gesture compared to audio alone. Furthermore, this increase in phase-locking, most noticeable at fronto-central electrodes, was not accompanied by an increase in power in the same frequency range, confirming the oscillatory-based nature of this effect. These results suggest that beat gestures are used as robust predictive information capable to tune neural oscillations to the optimal phase for auditory integration of relevant parts of the discourse during natural speech processing.

This research points to a synchronization between speaker and listener where a visual clue is used to divide the speech stream into chunks that can be processed (at least to a large degree) in isolation from the words before and after the chunk. The warning at the beginning of a new chunk, given automatically by the speakers hands, is used automatically by the listener to ‘clear the decks’ and begin a new chunk. This takes some of the strain out of listening. Of course, this information probably is also carried by the voice as well. Redundancy in oral language is common. Conversation is a wonderful dance of voice, face, hands and body that transfers an idea from one brain to another. It only seems easy because of how complicated and automatic it is.

 

Astrocyte role in gamma waves

The study of the brain has been very neuron centered. Glial cells outnumber neuron by about 10 to 1 in the cortex and are known to be important to brain function but it is not clear just what they do other than some housekeeping tasks and shepherding neurons to their final locations during development. Astrocyte roles appear to be important but unknown.

Now Lee et al, (see citation below) have published an excellent paper showing one role connected with gamma oscillations. The work was very impressive, but too specialized to describe here - it is summarized in the abstract below. The paper really ‘nailed down’ one role of the astrocytes.

In hippocampus slices they showed that astrocyte intercellular calcium rises before the start of gamma oscillations . This rise does not trigger the gamma but is required for the waves to have duration. They were able to block glutamate release of astrocytes without affecting neuron activity and showed that this glutamate release was the mechanism for maintaining gamma duration. They developed a strain of mouse where astrocyte glutamate release could be switched on and off, and again they showed that neuron behavior was not affected. When the glutamate release from astrocytes was blocked, the gamma power spectrum decreased in the 20 to 40 Hz range. The power spectrum decrease happened only during waking and not in REM or non-REM sleep. The behavior of the mice was examined. There was no difference in maze navigation or in fear conditioning, but novel object recognition was defective when the mice were turned ‘off’ and normal when they were ‘on’. So gamma oscillation in the hippocampus is required for novel object recognition and this ability depends on glutamate release from astrocytes.

They explain in their discussion why there would be a difference in the three behavior tests. “Although both the Y-maze task and the NOR test rely on the rodent’s innate exploratory behavior in the absence of externally applied positive or negative reinforcement, defects were selectively observed in the case of the NOR test. This is particularly relevant because the Y-maze task evaluates a simpler form of memory processing, i.e., short-term spatial working memory, whereas NOR involves a higher memory load engaging long-term storage, retrieval, and restorage of memory processing. During the test phase of the NOR test, a novel object needs to be detected and encoded, whereas the memory trace of a familiar object needs to be updated and reconsolidated after long delays. In contrast, fear conditioning might constitute a strong and highly specific form of learning involving a sympathetic reflex reaction with suppression of voluntary movements (freezing), in which subtle changes in memory content might not be detectable. Moreover, there is strong evidence that suggests fear-conditioned learning encodes a long-term memory process involving the amygdala and the hippocampus, whereas the NOR paradigm engages different structures: the hippocampus and adjacent cortical areas including entorhinal, perirhinal, and parahippocampal cortex.”

Here is the abstract:

Glial cells are an integral part of functional communication in the brain. Here we show that astrocytes contribute to the fast dynamics of neural circuits that underlie normal cognitive behaviors. In particular, we found that the selective expression of tetanus neurotoxin (TeNT) in astrocytes significantly reduced the duration of carbachol-induced gamma oscillations in hippocampal slices. These data prompted us to develop a novel transgenic mouse model, specifically with inducible tetanus toxin expression in astrocytes. In this in vivo model, we found evidence of a marked decrease in electroencephalographic (EEG) power in the gamma frequency range in awake-behaving mice, whereas neuronal synaptic activity remained intact. The reduction in cortical gamma oscillations was accompanied by impaired behavioral performance in the novel object recognition test, whereas other forms of memory, including working memory and fear conditioning, remained unchanged. These results support a key role for gamma oscillations in recognition memory. Both EEG alterations and behavioral deficits in novel object recognition were reversed by suppression of tetanus toxin expression. These data reveal an unexpected role for astrocytes as essential contributors to information processing and cognitive behavior.

Perhaps astrocytes are involved in the production of other brain waves in other locations too.
ResearchBlogging.org

Lee, H., Ghetti, A., Pinto-Duarte, A., Wang, X., Dziewczapolski, G., Galimi, F., Huitron-Resendiz, S., Pina-Crespo, J., Roberts, A., Verma, I., Sejnowski, T., & Heinemann, S. (2014). Astrocytes contribute to gamma oscillations and recognition memory Proceedings of the National Academy of Sciences, 111 (32) DOI: 10.1073/pnas.1410893111