Thalamus Modulates Consciousness via Layer-Specific Control of Cortex

Redinbaugh, Michelle J.; Phillips, Jessica M.; Kambi, Niranjan A.; Mohanta, Sounak; Andryk, Samantha; Dooley, Gaven L.; Afrasiabi, Mohsen; Raz, Aeyal; Saalmann, Yuri B.

doi:10.1016/j.neuron.2020.01.005

Cited by 263 publications

(271 citation statements)

References 73 publications

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“…In subsequent experiments, we used propofol doses between 0.17-0.28 mg/kg/min (M = 0.23, SD = 0.03), and isoflurane doses between 0.8-1.25% (M = 1.04, SD = 0.11) during T stimulation. As previously reported (22), consciousness level changes did not depend on the anesthetic used, nor the dose. For both experimental phases (recordings with or without stimulation), we interleaved resting state epochs and the passive auditory oddball paradigm.…”

Section: Sleepsupporting

confidence: 85%

“…We simultaneously stimulated via 16 electrode contacts, with 400 μs bi-phasic pulses of 200 μA, at 50Hz frequency, for a total of 60 s stimulation duration for each stimulation event (experiments included multiple stimulation events). This stimulation protocol has been shown to reliably increase the consciousness level in (the same) anesthetized monkeys; see (22) for further validation of electrical stimulation methods and behavioral effects. We typically performed three stimulation events within a stimulation block for reproducibility, with a recovery time of at least the stimulation event duration between repetitions, i.e., stimulations from 1-2 minutes, 3-4 minutes, and 5-6 minutes of a seven minute block.…”

Section: Electrical Stimulationsmentioning

confidence: 92%

“…We fitted each craniotomy with a conical plastic guide tube filled with bone wax, through which linear micro-electrode arrays traversed. We prefabricated these guide tubes using a model of the skull based on the T1-weighted structural image (13,22,27). We also inserted two titanium skull screws within the recording chamber, one from which to record the EEG and one to serve as a reference.…”

Section: Surgerymentioning

confidence: 99%

“…We previously reported that 50 Hz thalamic stimulation could increase the consciousness level (measured via 10-point scale; (21)) of monkeys under stable anesthesia relative to control (ineffective) stimulation (22). To assess decodability of stimulation conditions, we calculated LFP power, I, H and F* prior to, during and after effective (consciousness level M = 4.37, SD = 1.52, n = 35) and control (M = 0.66, SD = 0.99, n = 128) stimulations.…”

mentioning

confidence: 99%

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More than just front or back: Parietal-striatal-thalamic circuits predict consciousness level

Afrasiabi

Redinbaugh

Phillips

et al. 2020

Preprint

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Major theories of consciousness disagree on the key neural substrates. In Global Neuronal Workspace Theory and Higher-order Theories, consciousness depends on frontal cortex, whereas Integrated Information Theory and Recurrent Processing Theory highlight posterior contributions. Most theories omit subcortical influences. To test these theories, we performed simultaneous frontal, parietal, striatal and thalamic recordings from awake, sleeping and anesthetized macaques, further manipulating consciousness with deep-brain thalamic stimulation. Information theoretic measures and machine learning approaches suggested parietal cortex, striatum and thalamus contribute more to consciousness level than frontal cortex. While these findings provide greater support for Integrated Information Theory than the others, the theory does not incorporate subcortical structures such as the striatum. We therefore propose that thalamo-striatal circuits have a cause-effect structure to generate integrated information.

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Section: Sleepsupporting

confidence: 85%

Section: Electrical Stimulationsmentioning

confidence: 92%

Section: Surgerymentioning

confidence: 99%

mentioning

confidence: 99%

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More than just front or back: Parietal-striatal-thalamic circuits predict consciousness level

Afrasiabi

Redinbaugh

Phillips

et al. 2020

Preprint

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“…The modulators aj may act via shunting inhibition (103,105), although other mechanisms for multiplying neural signals may be substituted. The modulators may be implemented by V1 parvalbumin-expressing (PV) inhibitory interneurons (180) and/or somatostatin-expressing (SOM) inhibitory neurons (181) and/or loops through higher visual cortical areas (182)(183)(184)(185) and/or thalamocortical loops (186)(187)(188)(189)(190)(191)(192)(193). The modulator neurons are expected to have large RFs and broad orientation-selectivity (reflecting properties of the normalization pool), consistent with the response properties of SOM and PV neurons, respectively.…”

Section: Mechanismsmentioning

confidence: 99%

Dynamic Normalization

Heeger

Zemlianova

2020

Preprint

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Classification. Biological Sciences: Neuroscience; Social Sciences: Psychological and Cognitive Sciences. AbstractThe normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. In spite of the success of the normalization model, there are 3 unresolved issues. 1) Experimental evidence suggests that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normalization arises from a recurrent circuit.3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a new family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1. Significance StatementA family of recurrent circuit models is proposed to explain the dynamics of neural activity in primary visual cortex (V1). Each of the models in this family exhibits steady state output responses that are already known to fit a wide range of experimental data from diverse neural systems. These models can recapitulate the complex dynamics of V1 activity, including oscillations (so-called gamma oscillations, ~30-80 Hz). This theoretical framework also explains key aspects of working memory and motor control. Consequently, the same circuit architecture is applicable to a variety of neural systems, and V1 can be used as a model system for understanding the neural computations in many brain areas.

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State‐specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal

Zhang,

Huang,

Chen

et al. 2024

Advanced Science

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Long‐range thalamocortical communication is central to anesthesia‐induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state‐specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram‐fuctional magnetic resonance imaging (EEG‐fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely‐tuned propofol anesthesia. This approach led to the identification of an intralaminar‐driven network responsible for rapid arousal during slow‐wave oscillations. A network‐based RNA‐sequencing analysis is conducted of region‐, layer‐, and cell‐specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin‐expressing neurons, and oligodendrocytes. Comparison with human RNA‐sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network‐focused transcriptional signatures of arousal.

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Thalamus Modulates Consciousness via Layer-Specific Control of Cortex

Cited by 263 publications

References 73 publications

More than just front or back: Parietal-striatal-thalamic circuits predict consciousness level

More than just front or back: Parietal-striatal-thalamic circuits predict consciousness level

Dynamic Normalization

State‐specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal

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