Love at first taste: Activation in reward-related brain regions during single-trial naturalistic appetitive conditioning in humans

Learning which stimuli in our environment co-occur with painful or pleasurable events is critical for survival. Previous research has established the basic neural and behavioural mechanisms of aversive and appetitive conditioning; however, it is unclear what precisely is learned. Here we examined what aspects of the unconditioned stimulus (US), sensory and hedonic, are transferred to the conditioned stimulus (CS). To decode the content of brain activation patterns elicited during appetitive (soft touch) and aversive (painful touch) conditioning of faces, a novel variation of representational similarity analysis (RSA) based on theoretically driven representational patterns of interest (POIs) was applied to fMRI data. Once face associations were learned through conditioning, globally the CS reactivated US representational patterns showing conditioning dependent reactivation. More specifically, in higher order brain regions, the CS only reactivated hedonic but not sensory aspects of the US, suggesting that affective conditioning primarily carries forward the valence of the experience rather than its sensory origins.

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Algebra dissociates from arithmetic in the brain semantic network

10.21203/rs.3.rs-806057/v1 ◽

2021 ◽

Author(s):

Dazhi Cheng ◽

Mengyi Li ◽

Naiyi Wang ◽

Liangyuan Ouyang ◽

Xinlin Zhou

Keyword(s):

Supplementary Motor Area ◽

Semantic Network ◽

Brain Activation ◽

Brain Regions ◽

Motor Area ◽

Angular Gyrus ◽

Precentral Gyrus ◽

Single Trial ◽

Brain Behavior ◽

The Brain

Abstract Background Mathematical expressions mainly include arithmetic (such as 8 − (1 + 3)) and algebraic expressions (such as a − (b + c)). Previous studies shown that both algebraic processing and arithmetic involved the bilateral parietal brain regions. Although behavioral and neuropsychological studies have revealed the dissociation between algebra and arithmetic, how algebraic processing is dissociated from arithmetic in brain networks is still unclear. Methods Using functional magnetic resonance imaging (fMRI), this study scanned 30 undergraduates and directly compared the brain activation during algebra and arithmetic. Brain activations, single-trial (item-wise) interindividual correlation and mean-trial interindividual correlation related to algebra processing were compared with those related to arithmetic. Results Brain activation analyses showed that algebra elicited greater activation in the angular gyrus and arithmetic elicited greater activation in the bilateral supplementary motor area, left insula, and left inferior parietal lobule. Interindividual single-trial brain-behavior correlation revealed significant brain-behavior correlations in the semantic network, including the middle temporal gyri, inferior frontal gyri, dorsomedial prefrontal cortices, and left angular gyrus, for algebra. For arithmetic, the significant brain-behavior correlations were located in the phonological network, including the precentral gyrus and supplementary motor area, and in the visuospatial network, including the bilateral superior parietal lobules. Conclusion These findings suggest that algebra relies on the semantic network and arithmetic relies on the phonological and visuospatial networks.

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Long-term memory is formed immediately without the need for protein synthesis-dependent consolidation in Drosophila

Nature Communications ◽

10.1038/s41467-019-12436-7 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 10

Author(s):

Bohan Zhao ◽

Jiameng Sun ◽

Xuchen Zhang ◽

Han Mo ◽

Yijun Niu ◽

...

Keyword(s):

Protein Synthesis ◽

Mushroom Body ◽

Brain Regions ◽

Long Term Memory ◽

Single Trial ◽

Olfactory Conditioning ◽

Consolidation Process ◽

Independent Manner ◽

Term Memory

Abstract It is believed that long-term memory (LTM) cannot be formed immediately because it must go through a protein synthesis-dependent consolidation process. However, the current study uses Drosophila aversive olfactory conditioning to show that such processes are dispensable for context-dependent LTM (cLTM). Single-trial conditioning yields cLTM that is formed immediately in a protein-synthesis independent manner and is sustained over 14 days without decay. Unlike retrieval of traditional LTM, which requires only the conditioned odour and is mediated by mushroom-body neurons, cLTM recall requires both the conditioned odour and reinstatement of the training-environmental context. It is mediated through lateral-horn neurons that connect to multiple sensory brain regions. The cLTM cannot be retrieved if synaptic transmission from any one of these centres is blocked, with effects similar to those of altered encoding context during retrieval. The present study provides strong evidence that long-term memory can be formed easily without the need for consolidation.

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Attention to Detail: Why Considering Task Demands Is Essential for Single-Trial Analysis of BOLD Correlates of the Visual P1 and N1

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00490 ◽

2014 ◽

Vol 26 (3) ◽

pp. 529-542 ◽

Cited By ~ 9

Author(s):

Tracy Warbrick ◽

Jorge Arrubla ◽

Franks Boers ◽

Irene Neuner ◽

N. Jon Shah

Keyword(s):

Response Selection ◽

Sensory Information ◽

Prediction Method ◽

Brain Regions ◽

Task Demands ◽

Fmri Data ◽

Single Trial ◽

Oddball Task ◽

Sensory Encoding ◽

Visual Oddball

Single-trial fluctuations in the EEG signal have been shown to temporally correlate with the fMRI BOLD response and are valuable for modeling trial-to-trial fluctuations in responses. The P1 and N1 components of the visual ERP are sensitive to different attentional modulations, suggesting that different aspects of stimulus processing can be modeled with these ERP parameters. As such, different patterns of BOLD covariation for P1 and N1 informed regressors would be expected; however, current findings are equivocal. We investigate the effects of variations in attention on P1 and N1 informed BOLD activation in a visual oddball task. Simultaneous EEG-fMRI data were recorded from 13 healthy participants during three conditions of a visual oddball task: Passive, Count, and Respond. We show that the P1 and N1 components of the visual ERP can be used in the integration-by-prediction method of EEG-fMRI data integration to highlight brain regions related to target detection and response production. Our data suggest that the P1 component of the ERP reflects changes in sensory encoding of stimulus features and is more informative for the Passive and Count conditions. The N1, on the other hand, was more informative for the Respond condition, suggesting that it can be used to model the processing of stimulus, meaning specifically discriminating one type of stimulus from another, and processes involved in integrating sensory information with response selection. Our results show that an understanding of the underlying electrophysiology is necessary for a thorough interpretation of EEG-informed fMRI analysis.

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Control of non-homeostatic feeding in sated mice using associative learning of contextual food cues

10.1101/247825 ◽

2018 ◽

Author(s):

Sarah A. Stern ◽

Katherine R. Doerig ◽

Estefania P. Azevedo ◽

Elina Stoffel ◽

Jeffrey M. Friedman

Keyword(s):

Food Consumption ◽

Food Availability ◽

Molecular Mechanisms ◽

Negative Reinforcement ◽

Sensory Information ◽

Insular Cortex ◽

Brain Regions ◽

Appetitive Conditioning ◽

Functional Neuroanatomy ◽

Intensive Training

ABSTRACTFeeding is a complex motivated behavior controlled by a distributed neural network that processes sensory information to generate adaptive behavioral responses. Accordingly, studies using appetitive Pavlovian conditioning confirm that environmental cues that are associated with food availability can induce feeding even in satiated subjects. However, in mice, appetitive conditioning generally requires intensive training and thus can impede molecular studies that often require large numbers of animals. To address this, we developed and validated a simple and rapid context-induced feeding (ctx-IF) task in which cues associated with food availability can later lead to increased food consumption in sated mice. We show that the associated increase in food consumption is driven by both positive and negative reinforcement and that spaced training is more effective than massed training. Ctx-IF can be completed in ∼1 week and provides an opportunity to study the molecular mechanisms and circuitry underlying non-homeostatic eating. We have used this paradigm to map brain regions that are activated during Ctx-IF with cFos immunohistochemistry and found that the insular cortex, and other regions, are activated following exposure to cues denoting the availability of food. Finally, we show that inhibition of the insular cortex using GABA agonists impairs performance of the task. Our findings provide a novel assay in mice for defining the functional neuroanatomy of appetitive conditioning and identify specific brain regions that are activated during the development of learned behaviors that impact food consumption.

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Cerebellar neurodynamics during motor planning predict decision timing and outcome on single-trial level

10.1101/833889 ◽

2019 ◽

Author(s):

Qian Lin ◽

Magdalena Helmreich ◽

Friederike Schlumm ◽

Jennifer M. Li ◽

Drew N. Robson ◽

...

Keyword(s):

Motor Planning ◽

Brain Regions ◽

Decision Time ◽

Single Trial ◽

Movement Initiation ◽

Decision Outcomes ◽

Spatially Distributed ◽

Brain States ◽

The Difference ◽

Subcortical Regions

SUMMARYThe neuronal basis of goal-directed behavior requires interaction of multiple separated brain regions. How subcortical regions and their interactions with brain-wide activity are involved in action selection is less understood. We have investigated this question by developing an assay based on whole-brain volumetric calcium imaging using light-field microscopy combined with an operant-conditioning task in larval zebrafish. We find global and recurring dynamics of brain states to exhibit pre-motor bifurcations towards mutually exclusive decision outcomes which arises from a spatially distributed network. Within this network the cerebellum shows a particularly strong pre-motor activity, predictive of both the timing and outcome of behavior up to ∼10 seconds before movement initiation. Furthermore, on the single-trial level, decision directions can be inferred from the difference neuroactivity between the ipsilateral and contralateral hemispheres, while the decision time can be quantitatively predicted by the rate of bi-hemispheric population ramping activity. Our results point towards a cognitive role of the cerebellum and its importance in motor planning.

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Convolutional Neural Networks with 3D Input for P300 Identification in Auditory Brain-Computer Interfaces

Computational Intelligence and Neuroscience ◽

10.1155/2017/8163949 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Eduardo Carabez ◽

Miho Sugi ◽

Isao Nambu ◽

Yasuhiro Wada

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Spatial Information ◽

Brain Activity ◽

Three Dimensional ◽

Brain Regions ◽

Oddball Paradigm ◽

Brain Computer Interfaces ◽

Single Trial ◽

Computer Interfaces

From allowing basic communication to move through an environment, several attempts are being made in the field of brain-computer interfaces (BCI) to assist people that somehow find it difficult or impossible to perform certain activities. Focusing on these people as potential users of BCI, we obtained electroencephalogram (EEG) readings from nine healthy subjects who were presented with auditory stimuli via earphones from six different virtual directions. We presented the stimuli following the oddball paradigm to elicit P300 waves within the subject’s brain activity for later identification and classification using convolutional neural networks (CNN). The CNN models are given a novel single trial three-dimensional (3D) representation of the EEG data as an input, maintaining temporal and spatial information as close to the experimental setup as possible, a relevant characteristic as eliciting P300 has been shown to cause stronger activity in certain brain regions. Here, we present the results of CNN models using the proposed 3D input for three different stimuli presentation time intervals (500, 400, and 300 ms) and compare them to previous studies and other common classifiers. Our results show >80% accuracy for all the CNN models using the proposed 3D input in single trial P300 classification.

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Analysis of the Complexity Measures in the EEG of Schizophrenia Patients

International Journal of Neural Systems ◽

10.1142/s0129065716500088 ◽

2016 ◽

Vol 26 (02) ◽

pp. 1650008 ◽

Cited By ~ 37

Author(s):

S. Akdemir Akar ◽

S. Kara ◽

F. Latifoğlu ◽

V. Bilgiç

Keyword(s):

Clinical Status ◽

Approximate Entropy ◽

Brain Regions ◽

Brain Dynamics ◽

Single Trial ◽

Complexity Measures ◽

Eyes Closed ◽

Eeg Data ◽

Lower Complexity ◽

The Brain

Complexity measures have been enormously used in schizophrenia patients to estimate brain dynamics. However, the conflicting results in terms of both increased and reduced complexity values have been reported in these studies depending on the patients’ clinical status or symptom severity or medication and age status. The objective of this study is to investigate the nonlinear brain dynamics of chronic and medicated schizophrenia patients using distinct complexity estimators. EEG data were collected from 22 relaxed eyes-closed patients and age-matched healthy controls. A single-trial EEG series of 2[Formula: see text]min was partitioned into identical epochs of 20[Formula: see text]s intervals. The EEG complexity of participants were investigated and compared using approximate entropy (ApEn), Shannon entropy (ShEn), Kolmogorov complexity (KC) and Lempel–Ziv complexity (LZC). Lower complexity values were obtained in schizophrenia patients. The most significant complexity differences between patients and controls were obtained in especially left frontal (F3) and parietal (P3) regions of the brain when all complexity measures were applied individually. Significantly, we found that KC was more sensitive for detecting EEG complexity of patients than other estimators in all investigated brain regions. Moreover, significant inter-hemispheric complexity differences were found in the frontal and parietal areas of schizophrenics’ brain. Our findings demonstrate that the utilizing of sensitive complexity estimators to analyze brain dynamics of patients might be a useful discriminative tool for diagnostic purposes. Therefore, we expect that nonlinear analysis will give us deeper understanding of schizophrenics’ brain.

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Synaptic organization of the gustatory NST

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100168487 ◽

1994 ◽

Vol 52 ◽

pp. 150-151

Author(s):

M. C. Whitehead

Keyword(s):

Central Nervous System ◽

Dendritic Spines ◽

Fundamental Problem ◽

Cell Types ◽

Brain Regions ◽

Excitatory Synapses ◽

Solitary Tract ◽

Synaptic Organization ◽

Synaptic Junctions ◽

Afferent Terminals

A fundamental problem in taste research is to determine how gustatory signals are processed and disseminated in the mammalian central nervous system. An important first step toward understanding information processing is the identification of cell types in the nucleus of the solitary tract (NST) and their synaptic relationships with oral primary afferent terminals. Facial and glossopharyngeal (LIX) terminals in the hamster were labelled with HRP, examined with EM, and characterized as containing moderate concentrations of medium-sized round vesicles, and engaging in asymmetrical synaptic junctions. Ultrastructurally the endings resemble excitatory synapses in other brain regions.Labelled facial afferent endings in the RC subdivision synapse almost exclusively with distal dendrites and dendritic spines of NST cells. Most synaptic relationships between the facial synapses and the dendrites are simple. However, 40% of facial endings engage in complex synaptic relationships within glomeruli containing unlabelled axon endings particularly ones termed "SP" endings. SP endings are densely packed with small, pleomorphic vesicles and synapse with both the facial endings and their postsynaptic dendrites by means of nearly symmetrical junctions.

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Musical Anhedonia

Zeitschrift für Neuropsychologie ◽

10.1024/1016-264x/a000292 ◽

2020 ◽

Vol 31 (2) ◽

pp. 62-68

Author(s):

Sara E. Holm ◽

Alexander Schmidt ◽

Christoph J. Ploner

Keyword(s):

Quality Of Life ◽

Nucleus Accumbens ◽

Brain Damage ◽

Parietal Cortex ◽

Neurological Disorders ◽

Brain Regions ◽

Precise Information ◽

Exact Localization ◽

High Prevalence

Abstract. Some people, although they are perfectly healthy and happy, cannot enjoy music. These individuals have musical anhedonia, a condition which can be congenital or may occur after focal brain damage. To date, only a few cases of acquired musical anhedonia have been reported in the literature with lesions of the temporo-parietal cortex being particularly important. Even less literature exists on congenital musical anhedonia, in which impaired connectivity of temporal brain regions with the Nucleus accumbens is implicated. Nonetheless, there is no precise information on the prevalence, causes or exact localization of both congenital and acquired musical anhedonia. However, the frequent involvement of temporo-parietal brain regions in neurological disorders such as stroke suggest the possibility of a high prevalence of this disorder, which leads to a considerable reduction in the quality of life.

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