Awake perception is associated with dedicated neuronal assemblies in cerebral cortex

AbstractNeural activity in sensory cortex combines stimulus responses and ongoing activity, but it remains unclear whether they reflect the same underlying dynamics or separate processes. Here we show that during wakefulness, the neuronal assemblies evoked by sounds in the auditory cortex and thalamus are specific to the stimulus and distinct from the assemblies observed in ongoing activity. In contrast, during anesthesia, evoked assemblies are indistinguishable from ongoing assemblies in cortex, while they remain distinct in the thalamus. A strong remapping of sensory responses accompanies this dynamical state change produced by anesthesia. Together, these results show that the awake cortex engages dedicated neuronal assemblies in response to sensory inputs, which we suggest is a network correlate of sensory perception.One-Sentence SummarySensory responses in the awake cortex engage specific neuronal assemblies that disappear under anesthesia.

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Injecting Information into the Mammalian Cortex: Progress, Challenges, and Promise

The Neuroscientist ◽

10.1177/1073858420936253 ◽

2020 ◽

pp. 107385842093625

Author(s):

Kevin A. Mazurek ◽

Marc H. Schieber

Keyword(s):

Nervous System ◽

Cerebral Cortex ◽

Future Development ◽

Neural Activity ◽

Sensory Inputs ◽

The Subject ◽

Neuroprosthetic Devices ◽

As If

For 150 years artificial stimulation has been used to study the function of the nervous system. Such stimulation—whether electrical or optogenetic—eventually may be used in neuroprosthetic devices to replace lost sensory inputs and to otherwise introduce information into the nervous system. Efforts toward this goal can be classified broadly as either biomimetic or arbitrary. Biomimetic stimulation aims to mimic patterns of natural neural activity, so that the subject immediately experiences the artificial stimulation as if it were natural sensation. Arbitrary stimulation, in contrast, makes no attempt to mimic natural patterns of neural activity. Instead, different stimuli—at different locations and/or in different patterns—are assigned different meanings randomly. The subject’s time and effort then are required to learn to interpret different stimuli, a process that engages the brain’s inherent plasticity. Here we will examine progress in using artificial stimulation to inject information into the cerebral cortex and discuss the challenges for and the promise of future development.

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The future of mapping sensory cortex in primates: three of many remaining issues

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2005.1624 ◽

2005 ◽

Vol 360 (1456) ◽

pp. 653-664 ◽

Cited By ~ 29

Author(s):

Jon H Kaas

Keyword(s):

Cerebral Cortex ◽

Visual Cortex ◽

Auditory Cortex ◽

Primary Auditory Cortex ◽

Sensory Cortex ◽

Cortical Processing ◽

Early Stages ◽

The Future ◽

Somatosensory Areas ◽

Area 3B

After 100 years of progress in understanding the organization of cerebral cortex, three issues have persisted over the last 35 years, which are revisited in this paper. First, is V3 an established or questionable area of visual cortex? Second, does taste cortex include part of area 3b (S1 proper) and other somatosensory areas? Third, is primary auditory cortex, A1, of primates the homologue of A1 in cats? The existence of such questions about even the early stages of cortical processing reflects the difficulties in mapping cerebral cortex, and reminds us that the era of basic discovery is far from over.

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Optical imaging of neural activity of auditory cortex in response to sounds containing a silent period

Neuroscience Research ◽

10.1016/s0168-0102(00)81786-1 ◽

2000 ◽

Vol 38 ◽

pp. S156

Author(s):

J Horikawa

Keyword(s):

Auditory Cortex ◽

Optical Imaging ◽

Neural Activity ◽

Silent Period

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Prior expectations induce prestimulus sensory templates

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1705652114 ◽

2017 ◽

Vol 114 (39) ◽

pp. 10473-10478 ◽

Cited By ~ 96

Author(s):

Peter Kok ◽

Pim Mostert ◽

Floris P. de Lange

Keyword(s):

Sensory Neurons ◽

Temporal Resolution ◽

Representational Content ◽

Sensory Cortex ◽

Top Down ◽

Neural Signals ◽

Neural Signal ◽

Time Resolved ◽

Sensory Inputs ◽

Behavioral Improvement

Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to prestimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn, affect the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from poststimulus processes. Here, we combined human magnetoencephalography (MEG) with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal shortly before they were presented, showing that expectations indeed induce a preactivation of stimulus templates. The strength of these prestimulus expectation templates correlated with participants’ behavioral improvement when the expected feature was task-relevant. These results suggest a mechanism for how predictive perception can be neurally implemented.

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Short-term Effects of Vagus Nerve Stimulation on Learning and Evoked Activity in Auditory Cortex

10.1101/2019.12.19.883165 ◽

2019 ◽

Author(s):

Jesyin Lai ◽

Stephen V. David

Keyword(s):

Auditory Cortex ◽

Vagus Nerve ◽

Nerve Stimulation ◽

Neural Activity ◽

Neural Plasticity ◽

Neural Coding ◽

Vagus Nerve Stimulation ◽

Primary Auditory Cortex ◽

Long Term Effects ◽

Tone Frequency

ABSTRACTChronic vagus nerve stimulation (VNS) can facilitate learning of sensory and motor behaviors. VNS is believed to trigger release of neuromodulators, including norepinephrine and acetylcholine, which can mediate cortical plasticity associated with learning. Most previous work has studied effects of VNS over many days, and less is known about how acute VNS influences neural coding and behavior over the shorter term. To explore this question, we measured effects of VNS on learning of an auditory discrimination over 1-2 days. Ferrets implanted with cuff electrodes on the vagus nerve were trained by classical conditioning on a tone frequency-reward association. One tone was associated with reward while another tone, was not. The frequencies and reward associations of the tones were changed every two days, requiring learning of a new relationship. When the tones (both rewarded and non-rewarded) were paired with VNS, rates of learning increased on the first day following a change in reward association. To examine VNS effects on auditory coding, we recorded single- and multi-unit neural activity in primary auditory cortex (A1) of passively listening animals following brief periods of VNS (20 trials/session) paired with tones. Because afferent VNS induces changes in pupil size associated with fluctuations in neuromodulation, we also measured pupil during recordings. After pairing VNS with a neuron’s best-frequency (BF) tone, responses in a subpopulation of neurons were reduced. Pairing with an off-BF tone or performing VNS during the inter-trial interval had no effect on responses. We separated the change in A1 activity into two components, one that could be predicted by fluctuations in pupil and one that persisted after VNS and was not accounted for by pupil. The BF-specific reduction in neural responses remained, even after regressing out changes that could be explained by pupil. In addition, the size of VNS-mediated changes in pupil predicted the magnitude of persistent changes in the neural response. This interaction suggests that changes in neuromodulation associated with arousal gate the long-term effects of VNS on neural activity. Taken together, these results support a role for VNS in auditory learning and help establish VNS as a tool to facilitate neural plasticity.

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Spatial map of sensory inputs in the human insular cerebral cortex.

The FASEB Journal ◽

10.1096/fasebj.23.1_supplement.835.3 ◽

2009 ◽

Vol 23 (S1) ◽

Author(s):

John Irwin Johnson ◽

John Andrew Morris ◽

Archibald J. Fobbs

Keyword(s):

Cerebral Cortex ◽

Sensory Inputs

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Decoding the sense of smell: understanding the structural organization within the brain

Biotechnology Kiosk ◽

10.37756/bk.20.2.7.1 ◽

2020 ◽

Vol 2 (7) ◽

pp. 4-9

Author(s):

Shripriya Singh

Keyword(s):

Neural Activity ◽

Structural Organization ◽

Piriform Cortex ◽

Molecular Structures ◽

The Other ◽

Multiphoton Imaging ◽

Sensory Inputs ◽

Correlated Patterns ◽

Olfactory Sense ◽

The Brain

The olfactory sense is a potent sensory tool which helps us perceive our environment much better. However, smells despite being similar have different impacts on individuals. What makes one odor categorically different from the other and why do people have a unique and personalized experience with smell is an answer that needs to be addressed. In the present article we have discussed the research in which neuroscientists have decoded and described how the relationships between different odors are encoded in the brain. How the brain transforms information about odor chemistry into the perception of smell is a major highlight of this publication. Carefully selected odors with defined molecular structures were delivered in mice and the neural activity was analyzed. It was observed that neuronal representations of smell in the cortex reflected chemical similarities between odors, thus allowing the brain to categorize scents. The study has employed chemo informatics and multiphoton imaging in the mouse to demonstrate both the piriform cortex and its sensory inputs from the olfactory bulb represent chemical odor relationships through correlated patterns of activity. The research has given us cues in the direction of how the brain translates odor chemistry into neurochemistry and eventually perception of smell.

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Auditory cortex reflects goal-directed movement but is not necessary for behavioral adaptation in sound-cued reward tracking

Journal of Neurophysiology ◽

10.1152/jn.00736.2019 ◽

2020 ◽

Vol 124 (4) ◽

pp. 1056-1071

Author(s):

Vanya V. Stoilova ◽

Beate Knauer ◽

Stephanie Berg ◽

Evelyn Rieber ◽

Frank Jäkel ◽

...

Keyword(s):

Auditory Cortex ◽

Tracking Task ◽

Sensory Cortex ◽

Behavioral Adaptation ◽

Directed Movement ◽

Reward Anticipation

Recent evidence suggests that sensory cortex represents nonsensory variables such as reward expectation, but the relevance of these representations for behavior are not well understood. We show that rat auditory cortex (AC) is modulated during movement and reward anticipation in a sound-cued reward tracking task, whereas AC inactivation only impaired discrimination without affecting reward tracking, consistent with a predominantly sensory role of AC.

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