Monthly Archives: October 2015

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.

Attention on attention

A recent paper does a magnificent job of marshaling many sources of information on attention and developing a theory to fit those pieces of research. (Timothy J. Buschman, Sabine Kastner. From Behavior to Neural Dynamics: An Integrated Theory of Attention. Neuron, 2015; 88 (1): 127 DOI: 10.1016/j.neuron.2015.09.017). “The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘‘attention.’’ Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits, and neurons. We then integrate these disparate results into a unified theory of attention.

They concentrate on visual attention because there has been most research in that area. Recent work has pointed to the visual cortex creating a ‘dictionary’ of objects and object features through learning. The learning process captures the regularities of the world and visual representations are coded in this ‘dictionary’. “Importantly, embedding object-based representations will ensure that the system is tolerant to noise as any input will be transformed by the learned object dictionary: signals that match an expected pattern will be boosted, while signals that are orthogonal to representations in the dictionary will be ignored. As the dictionary has been trained to optimally represent the world, this means the system will, in effect, perform pattern completion, settling on nearby ‘‘known’’ representations, even when provided with a noisy input.” These representations are what top-down and bottom-up attention controls act on.

Their theory proposes a cascade and its regular reset.

(1) Attention can either be (a) automatically grabbed by salient stimuli or (b) guided by task representations in frontal and parietal regions to specific spatial locations or features.

(2) The pattern-completion nature of sensory cortex sharpens the broad top-down attentional bias, restricting it to perceptually relevant representations. Interactions with bottom-up sensory drive will emphasize specific objects.

(3) Interneuron-mediated lateral inhibition normalizes activity and, thus, suppresses competing stimuli. This results in increased sensitivity and decreased noise correlations.

(4) Lateral inhibition also leads to the generation of high-frequency synchronous oscillations within a cortical region. Inter-areal synchronization follows as these local oscillations synchronize along with the propagation of a bottom-up sensory drive. Both forms of synchrony act to further boost selected representations.

(5) Further buildup of inhibition acts to ‘‘reset’’ the network, thereby restarting the process. This reset allows the network to avoid being captured by a single stimulus and allows a positive-only selection mechanism to move over time.

Two things on language

There are a couple of interesting reports about language.

First, it has been shown that repeating something aloud helps us remember it. But a recent study goes further – we remember even better if we repeat it aloud to someone. The act of communication helps the memory. The paper is: Alexis Lafleur, Victor J. Boucher. The ecology of self-monitoring effects on memory of verbal productions: Does speaking to someone make a difference? Consciousness and Cognition, 2015; 36: 139 DOI:10.1016/j.concog.2015.06.015.

From ScienceDaily (here) Previous studies conducted at Professor Boucher’s Phonetic Sciences Laboratory have shown that when we articulate a sound, we create a sensory and motor reference in our brain, by moving our mouth and feeling our vocal chords vibrate. “The production of one or more sensory aspects allows for more efficient recall of the verbal element. But the added effect of talking to someone shows that in addition to the sensorimotor aspects related to verbal expression, the brain refers to the multisensory information associated with the communication episode,” Boucher explained. “The result is that the information is better retained in memory.

No one can tell me that language is not about and for communication.

The second item is reported in ScienceDaily (here) Infants cannot perceive the difference between certain sounds when their tongue is restricted with a teether. They have to be able to mimic the sounds in order to distinguish them. The paper is: Alison G. Bruderer, D. Kyle Danielson, Padmapriya Kandhadai, and Janet F. Werker. Sensorimotor influences on speech perception in infancy. PNAS, October 12, 2021 DOI: 10.1073/pnas.1508631112.

From ScienceDaily: …teething toys were placed in the mouths of six-month-old English-learning babies while they listened to speech sounds-two different Hindi “d” sounds that infants at this age can readily distinguish. When the teethers restricted movements of the tip of the tongue, the infants were unable to distinguish between the two “d” sounds. But when their tongues were free to move, the babies were able to make the distinction. Lead author Alison Bruderer, a postdoctoral fellow in the School of Audiology and Speech Sciences at UBC, said the findings call into question previous assumptions about speech and language development. “Until now, research in speech perception development and language acquisition has primarily used the auditory experience as the driving factor,” she said. “Researchers should actually be looking at babies’ oral-motor movements as well.”

hey say that parents do not need to worry about using teething toys but a child should also have time to freely use their tongue for good development.


Memory switch

A new tool has been used for the first time to look at brain activity - ribosomal profiling. The method identifies the proteins that are being made at any time. Ribosomes make proteins using messenger RNA that was copied from the DNA of genes. The method is to destroy all the messenger RNA that is not actually within a ribosome, or in other words, being actively used to make protein. The protected RNA can be used to identify the genes that were being translated into proteins at the moment that the cell was broken and the free RNA destroyed.

ScienceDaily reports on a press release from the Institute for Basic Science describing the use of this technique to study memory formation. (here) The research was done in the IBS Center for RNA Research and Department of Biological Sciences at Seoul National University. There is a on-off switch for formation of memories that is based on changes in protein production.

When an animal experiences no stimulus in an environment the hippocampus undergoes gene repression which prevents the formation of new memories. Upon the introduction of a stimulus, the hippocampus’ repressive gene regulation is turned off allowing for new memory creation, and as Jun Cho puts it, “Our study illustrates the potential importance of negative gene regulation in learning and memory”.

I assume this research will appear in a journal paper and that the technique will be used in other studies of the brain. It is always good to hear of new methods being available.

Islands and ocean of memory

Episodic memories are tagged with information about time and place. If we remember an event then it is almost certain we will remember where it happened and where it lies in the temporal sequence of events. Research has shown that an activity pattern in a part of the brain involved in memory, the entorhinal cortex, feeds where and when information to the hippocampus which forms the new memory.

The research is reported in a recent paper: Takashi Kitamura, Chen Sun, Jared Martin, Lacey J. Kitch, Mark J. Schnitzer, Susumu Tonegawa. Entorhinal Cortical Ocean Cells Encode Specific Contexts and Drive Context-Specific Fear Memory. Neuron, 2015; DOI: 10.1016/j.neuron.2015.08.036.

The entorhinal area involved has been likened to an ocean of context specific ‘where’ cells with islands of ‘when’ cells. The ocean cells signal the CA3 cells of the hippocampus and the island cells signal the CA1 cells. If ocean cells are blocked, animals cannot learn to connect fear with a particular environment. Island cells seem to react to the speed an animal is moving at and manipulating their signals changed the gap between events being linked in an animals memory. This is probably one of many ingredients in the processing of time-and-space.

Absract: “Forming distinct representations and memories of multiple contexts and episodes is thought to be a crucial function of the hippocampal-entorhinal cortical network. The hippocampal dentate gyrus (DG) and CA3 are known to contribute to these functions, but the role of the entorhinal cortex (EC) is poorly understood. Here, we show that Ocean cells, excitatory stellate neurons in the medial EC layer II projecting into DG and CA3, rapidly form a distinct representation of a novel context and drive context-specific activation of downstream CA3 cells as well as context-specific fear memory. In contrast, Island cells, excitatory pyramidal neurons in the medial EC layer II projecting into CA1, are indifferent to context-specific encoding or memory. On the other hand, Ocean cells are dispensable for temporal association learning, for which Island cells are crucial. Together, the two excitatory medial EC layer II inputs to the hippocampus have complementary roles in episodic memory.