scholarly journals Delta activity encodes taste information in the human brain

2018 ◽  
Author(s):  
Raphael Wallroth ◽  
Kathrin Ohla
Keyword(s):  
Human Brain ◽  
Neuronal Response ◽  
Pattern Discrimination ◽  
Nutrient Sensing ◽  
Response Patterns ◽  
Gustatory System ◽  
Rapid Responses ◽  
Delta Activity ◽  
Taste Discrimination ◽  
Eeg Recordings

The categorization of food via sensing nutrients or toxins is crucial to the survival of any organism. On ingestion, rapid responses within the gustatory system are required to identify the oral stimulus to guide immediate behaviour (swallowing or expulsion). The way in which the human brain accomplishes this task has so far remained unclear. Using multivariate analysis of 64-channel scalp EEG recordings obtained from 16 volunteers during tasting salty, sweet, sour, or bitter solutions, we found that activity in the delta-frequency range (1-4 Hz; delta power and phase) has information about taste identity in the human brain, with discriminable response patterns at the single-trial level within 130 ms of tasting. Importantly, the latencies of these response patterns predicted the point in time at which participants indicated detection of a taste by pressing a button. Furthermore, taste pattern discrimination was independent of motor-related activation and other taste features such as intensity and valence. On comparison with our previous findings from a passive (delayed) taste-discrimination task (Crouzet et al., 2015), taste-specific neural representations emerged earlier during this active (speeded) taste-detection task, suggesting a goal-dependent flexibility in gustatory response coding. Together, these findings provide the first evidence of a role of delta activity in taste-information coding in humans. Crucially, these neuronal response patterns can be linked to the speed of simple gustatory perceptual decisions, a vital performance index of nutrient sensing.

BRAIN-STEM NEURONAL RESPONSE PATTERNS TO MONAURAL AND BINAURAL TONES

1964 ◽  
Vol 27 (6) ◽  
pp. 1174-1191 ◽  
Author(s):  
George Moushegian ◽  
Allen Rupert ◽  
Milton A. Whitcomb
Keyword(s):  
Brain Stem ◽  
Neuronal Response ◽  
Response Patterns

Taste responses of cortical neurons in freely ingesting rats

1989 ◽  
Vol 61 (6) ◽  
pp. 1244-1258 ◽  
Author(s):  
T. Yamamoto ◽  
R. Matsuo ◽  
Y. Kiyomitsu ◽  
R. Kitamura
Keyword(s):  
Cortical Neurons ◽  
Correlation Coefficients ◽  
Entropy Measure ◽  
Response Patterns ◽  
Gustatory System ◽  
Basic Taste ◽  
Quinine Hydrochloride ◽  
Excitatory Responses

1. Activities of 35 taste-responsive neurons in the cortical gustatory area were recorded with chronically implanted fine wires in freely ingesting Wistar rats. Quantitative analyses were performed on responses to distilled water, food solution, and four taste stimuli: sucrose, NaCl, HCl, and quinine hydrochloride. 2. Taste-responsive neurons were classified into type-1 and type-2 groups according to the response patterns to licking of the six taste stimuli. Type-1 neurons (n = 29) responded in excitatory or inhibitory directions to one or more of the taste stimuli. Type-2 neurons (n = 6) showed responses in different directions depending upon palatability of the liquids to rats: neurons showing excitatory (or inhibitory) responses to palatable stimuli exhibited inhibitory (or excitatory) responses to unpalatable stimuli. 3. Correlation coefficients of responses to pairs of stimuli across neurons suggested that palatable stimuli (water, food solution, sucrose, and NaCl) and unpalatable stimuli (HCl and quinine) elicited reciprocal (excitatory vs. inhibitory) responses in type-2 neurons, whereas type-1 neurons showed positively correlated responses to specific combinations of stimuli such as food solution and NaCl, sucrose and HCl, NaCl and quinine, and HCl and quinine. 4. A tendency toward equalization of effectiveness in eliciting responses among the four basic taste stimuli was detected on the cortex. The ratios of mean evoked responses in 29 type-1 neurons in comparison with spontaneous rate (4.4 spikes/s) were 1.7, 1.9, 1.8, and 1.9 for sucrose, NaCl, HCl, and quinine, respectively. 5. The breadth of responsiveness to the four basic taste stimuli was quantified by means of the entropy measure introduced by Smith and Travers (33). The mean entropy value was 0.540 for 29 type-1 neurons, which was similar to 0.588 previously reported for rat chorda tympani fibers, suggesting that breadth of tuning is not more narrowly tuned in a higher level of the gustatory system in the rat. 6. Convergent inputs of other sensory modalities were detected exclusively in type-1 neurons. Thirteen (45%) of 29 type-1 neurons also responded to cold and/or warm water, but none of 6 type-2 neurons responded to thermal stimuli. Two (7%) of 29 type-1 neurons responded to almond and acetic acid odors, but the 6 type-2 neurons did not. Two (13%) of 16 type-1 neurons responded to interperitoneal injection of LiCl, which is known to induce gastrointestinal disorders, with a latency of approximately 5 min, but 4 type-2 neurons tested were not responsive to this stimulation.(ABSTRACT TRUNCATED AT 400 WORDS)

MEG/EEG in the Study of Brain Function

2017 ◽  
pp. 304-310
Author(s):  
Riitta Hari ◽  
Aina Puce
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Social Neuroscience ◽  
Future Research ◽  
Noninvasive Methods ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Combined Use ◽  
Eeg Recordings ◽  
Two Sides

This chapter summarizes some relative advantages and disadvantages of MEG and EEG, most of which have been previously elaborated. MEG and EEG are the two sides of the same coin and provide complementary information about the human brain’s neurodynamics. The combined use of MEG or EEG together and with other noninvasive methods used to study human brain function is advocated to be important for future research in systems and cognitive/social neuroscience. This chapter also examines combined use and interpretation of MEG/EEG with MRI/fMRI, and performing EEG recordings during non-invasive brain stimulation.

Synaptic integration in an excitable dendritic tree

1993 ◽  
Vol 70 (3) ◽  
pp. 1086-1101 ◽  
Author(s):  
B. W. Mel
Keyword(s):  
Pyramidal Cell ◽  
Neuronal Response ◽  
Dendritic Tree ◽  
Pattern Discrimination ◽  
Synaptic Activity ◽  
Visual Neurons ◽  
Voltage Dependent ◽  
Sum Of Products ◽  
Very High ◽  
Synaptic Drive

1. Compartmental modeling experiments were carried out in an anatomically characterized neocortical pyramidal cell to study the integrative behavior of a complex dendritic tree containing active membrane mechanisms. Building on a previously presented hypothesis, this work provides further support for a novel principle of dendritic information processing that could underlie a capacity for nonlinear pattern discrimination and/or sensory processing within the dendritic trees of individual nerve cells. 2. It was previously demonstrated that when excitatory synaptic input to a pyramidal cell is dominated by voltage-dependent N-methyl-D-aspartate (NMDA)-type channels, the cell responds more strongly when synaptic drive is concentrated within several dendritic regions than when it is delivered diffusely across the dendritic arbor. This effect, called dendritic "cluster sensitivity," persisted under wide-ranging parameter variations and directly implicated the spatial ordering of afferent synaptic connections onto the dendritic tree as an important determinant of neuronal response selectivity. 3. In this work, the sensitivity of neocortical dendrites to spatially clustered synaptic drive has been further studied with fast sodium and slow calcium spiking mechanisms present in the dendritic membrane. Several spatial distributions of the dendritic spiking mechanisms were tested with and without NMDA synapses. Results of numerous simulations reveal that dendritic cluster sensitivity is a highly robust phenomenon in dendrites containing a sufficiency of excitatory membrane mechanisms and is only weakly dependent on their detailed spatial distribution, peak conductances, or kinetics. Factors that either work against or make irrelevant the dendritic cluster sensitivity effect include 1) very high-resistance spine necks, 2) very large synaptic conductances, 3) very high baseline levels of synaptic activity, and 4) large fluctuations in level of synaptic activity on short time scales. 4. The functional significance of dendritic cluster sensitivity has been previously discussed in the context of associative learning and memory. Here it is demonstrated that the dendritic tree of a cluster-sensitive neuron implements an approximative spatial correlation, or sum of products operation, such as that which could underlie nonlinear disparity tuning in binocular visual neurons.

Pruning of rat cortical taste neurons by an artificial neural network model

1995 ◽  
Vol 74 (3) ◽  
pp. 1010-1019 ◽  
Author(s):  
T. Nagai ◽  
H. Katayama ◽  
K. Aihara ◽  
T. Yamamoto
Keyword(s):  
Learning Algorithm ◽  
Back Propagation ◽  
Quantitative Measure ◽  
Response Patterns ◽  
Input Unit ◽  
Basic Taste ◽  
Relative Contribution ◽  
Quinine Hydrochloride ◽  
Taste Discrimination ◽  
Hidden Layer

1. Taste qualities are believed to be coded in the activity of ensembles of taste neurons. However, it is not clear whether all neurons are equally responsible for coding. To clarify the point, the relative contribution of each taste neuron to coding needs to be assessed. 2. We constructed simple three-layer neural networks with input units representing cortical taste neurons of the rat. The networks were trained by the back-propagation learning algorithm to classify the neural response patterns to the basic taste stimuli (sucrose, HCl, quinine hydrochloride, and NaCl). The networks had four output units representing the basic taste qualities, the values of which provide a measure for similarity of test stimuli (salts, tartaric acid, and umami substances) to the basic taste stimuli. 3. Trained networks discriminated the response patterns to the test stimuli in a plausible manner in light of previous physiological and psychological experiments. Profiles of output values of the networks paralleled those of across-neuron correlations with respect to the highest or second-highest values in the profiles. 4. We evaluated relative contributions of input units to the taste discrimination of the network by examining their significance Sj, which is defined as the sum of the absolute values of the connection weights from the jth input unit to the hidden layer. When the input units with weaker connection weights (e.g., 15 of 39 input units) were "pruned" from the trained network, the ability of the network to discriminate the basic taste qualities as well as other test stimuli was not greatly affected. On the other hand, the taste discrimination of the network progressively deteriorated much more rapidly with pruning of input units with stronger connection weights. 5. These results suggest that cortical taste neurons differentially contribute to the coding of taste qualities. The pruning technique may enable the evaluation of a given taste neuron in terms of its relative contribution to the coding, with Sj providing a quantitative measure for such evaluation.

scholarly journals Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

2019 ◽  
Author(s):  
Jaclyn L. Farrens ◽  
Aaron M. Simmons ◽  
Steven J. Luck ◽  
Emily S. Kappenman
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
High Temporal Resolution ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Eeg Recordings ◽  
Brain Processing ◽  
Resolution Measure ◽  
Electroencephalogram Eeg

Abstract Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

scholarly journals Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective Human Neuroscience Research

2020 ◽  
Author(s):  
Jaclyn L. Farrens ◽  
Aaron M. Simmons ◽  
Steven J. Luck ◽  
Emily S. Kappenman
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
High Temporal Resolution ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Eeg Recordings ◽  
Brain Processing ◽  
Resolution Measure ◽  
Electroencephalogram Eeg

Abstract Electroencephalography (EEG) is one of the most widely used techniques to measure human brain activity. EEG recordings provide a direct, high temporal resolution measure of cortical activity from noninvasive scalp electrodes. However, the signals are small relative to the noise, and optimizing the quality of the recorded EEG data can significantly improve the ability to identify signatures of brain processing. This protocol provides a step-by-step guide to recording the EEG from human research participants using strategies optimized for producing the best quality EEG.

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