scholarly journals A distributed dopamine-gated circuit underpins reproductive state-dependent behavior in Drosophila females

2021 ◽  
Author(s):  
Ariane C Boehm ◽  
Anja B Friedrich ◽  
Paul Bandow ◽  
K.P. Siju ◽  
Sydney Hunt ◽  
...  
Keyword(s):  
Internal State ◽  
Brain Regions ◽  
Neural Pathways ◽  
Reproductive State ◽  
Behavioral Screening ◽  
Whole Brain ◽  
State Dependent ◽  
Dependent Behavior ◽  
Output Neurons ◽  
And Behavior

Motherhood induces a drastic, sometimes long-lasting, change in internal state and behavior in most female animals. Here, we show that a mating-induced increase in olfactory attraction of female Drosophila flies to nutrients relies on interconnected neural pathways in the two higher olfactory brain regions, the lateral horn (LH) and the mushroom body (MB). Using whole brain calcium imaging, we find that mating does not induce a global change in the activity of the whole brain nor of entire brain regions, suggesting specific neuronal or network changes in the olfactory system. Systematic behavioral screening and electron microscopy (EM) connectomics identify two types of LH output neurons required for the attraction of females to polyamines -one of them previously implicated in the processing of male pheromones. In addition, we characterize multiple MB pathways capable of inducing or suppressing polyamine attraction, with synaptic connections to the identified LH neurons and a prominent role for the β′1 compartment. Moreover, β′1 dopaminergic neurons are modulated by mating and are sufficient to replace mating experience in virgins inducing the lasting behavioral switch in female preference. Taken together, our data in the fly suggests that reproductive state-dependent expression of female choice behavior is regulated by a dopamine-gated distributed learning circuit comprising both higher olfactory brain centers.

scholarly journals Lynn_etal_MathSkills_CPM_Preprint_V1_05July2021

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Math Skills ◽  
Whole Brain ◽  
Building Models ◽  
State Dependent ◽  
Brain Behavior

The human brain comprises multiple canonical networks, several of which are distributed across frontal, parietal, and temporooccipital regions. Studies report both positive and negative correlations between children’s math skills and the strength of functional connectivity among these regions during math-related tasks and at rest. Yet, it is unclear how the relation between children’s math skills and functional connectivity map onto patterns of distributed whole-brain connectivity, canonical network connectivity, and whether these relations are consistent across different task-states. We used connectome-based predictive modeling to test whether functional connectivity during number comparison and at rest predicts children’s math skills (N=31, Mage=9.21years) using distributed whole-brain connections versus connections among canonical networks. We found that weaker connectivity distributed across the whole brain and weaker connectivity between key math-related brain regions in specific canonical networks predicts better math skills in childhood. The specific connections predicting math skills, and whether they were distributed or mapped onto canonical networks, varied between tasks, suggesting that state-dependent rather than trait-level functional network architectures support children’s math skills. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

scholarly journals A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Brad K Hulse ◽  
Hannah Haberkern ◽  
Romain Franconville ◽  
Daniel B Turner-Evans ◽  
Shinya Takemura ◽  
...  
Keyword(s):  
Internal State ◽  
Action Selection ◽  
Brain Regions ◽  
Central Complex ◽  
Network Motifs ◽  
Motor Pathways ◽  
State Dependent ◽  
Attractor Dynamics ◽  
Long Timescales ◽  
Selection Of

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly’s head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

scholarly journals Extracting orthogonal subject- and behavior-specific signatures from fMRI data using whole-brain effective connectivity

2017 ◽  
Author(s):  
Vicente Pallarés ◽  
Andrea Insabato ◽  
Ana Sanjuán ◽  
Simone Kühn ◽  
Dante Mantini ◽  
...  
Keyword(s):  
Effective Connectivity ◽  
Real Life ◽  
Brain Regions ◽  
Fmri Data ◽  
Whole Brain ◽  
Related Information ◽  
Subject Identification ◽  
The Subject ◽  
And Behavior ◽  
Robust Prediction

AbstractThe study of brain communication based on fMRI data is often limited because such measurements are a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications, in particular when only a few recording sessions are available. The present study aims to define a reliable standard for the extraction of multiple signatures from fMRI data, while verifying that they do not mix information about the different modalities. In particular, condition-specific signature should not be contaminated by subject-related information. Practically, signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key for robust prediction is using effective connectivity instead of functional connectivity. Our method demonstrates excellent generalization capabilities for subject identification in two datasets, using only a few sessions per subject as reference. Using another dataset with resting state and movie viewing, we show that the two signatures related to subjects and tasks correspond to distinct subnetworks, which are thus topologically orthogonal. Our results set solid foundations for applications tailored to individual subjects, such as clinical diagnostic.

scholarly journals A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

2020 ◽  
Author(s):  
Brad K. Hulse ◽  
Hannah Haberkern ◽  
Romain Franconville ◽  
Daniel B. Turner-Evans ◽  
Shinya Takemura ◽  
...  
Keyword(s):  
Internal State ◽  
Action Selection ◽  
Brain Regions ◽  
Central Complex ◽  
Network Motifs ◽  
Motor Pathways ◽  
State Dependent ◽  
Attractor Dynamics ◽  
Long Timescales ◽  
Selection Of

ABSTRACTFlexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly’s head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

Conceptual disorganization and redistribution of resting state cortical hubs in untreated first episode psychosis: A 7T MRI study

2020 ◽  
Author(s):  
Avyarthana Dey ◽  
Kara Dempster ◽  
Michael Mackinley ◽  
Peter Jeon ◽  
Tushar Das ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
First Episode Psychosis ◽  
Cortical Reorganization ◽  
First Episode ◽  
Formal Thought Disorder ◽  
Whole Brain ◽  
Episode Psychosis ◽  
Positive And Negative Symptoms

Background:Network level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype which predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs).Methods:We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs and characterized the patterns of network connectivity in the two groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity.Results:Compared to HCs, reduced hubness of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased hubness of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. These two regions were strongly correlated with CD scores but not with other symptom scores.Discussion:Our observations are congruent with previous findings of reduced but not increased hubness. We observed increased hubness of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer.Conclusion:These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. A longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.

Neuromodulatory Feedback to the Inferior Colliculus

2018 ◽  
pp. 576-610 ◽  
Author(s):  
Laura Hurley
Keyword(s):  
Inferior Colliculus ◽  
Auditory System ◽  
Auditory Processing ◽  
Internal State ◽  
Brain Regions ◽  
Auditory Information ◽  
Situational Variables ◽  
Acoustic Stimuli ◽  
Functionally Diverse ◽  
Behavioral Information

The inferior colliculus (IC) receives prominent projections from centralized neuromodulatory systems. These systems include extra-auditory clusters of cholinergic, dopaminergic, noradrenergic, and serotonergic neurons. Although these modulatory sites are not explicitly part of the auditory system, they receive projections from primary auditory regions and are responsive to acoustic stimuli. This bidirectional influence suggests the existence of auditory-modulatory feedback loops. A characteristic of neuromodulatory centers is that they integrate inputs from anatomically widespread and functionally diverse sets of brain regions. This connectivity gives neuromodulatory systems the potential to import information into the auditory system on situational variables that accompany acoustic stimuli, such as context, internal state, or experience. Once released, neuromodulators functionally reconfigure auditory circuitry through a variety of receptors expressed by auditory neurons. In addition to shaping ascending auditory information, neuromodulation within the IC influences behaviors that arise subcortically, such as prepulse inhibition of the startle response. Neuromodulatory systems therefore provide a route for integrative behavioral information to access auditory processing from its earliest levels.

scholarly journals Kiss1 Neurons Drastically Change Their Firing Activity in Accordance With the Reproductive State: Insights From a Seasonal Breeder

Endocrinology ◽  
2014 ◽  
Vol 155 (12) ◽  
pp. 4868-4880 ◽  
Author(s):  
Masaharu Hasebe ◽  
Shinji Kanda ◽  
Hiroyuki Shimada ◽  
Yasuhisa Akazome ◽  
Hideki Abe ◽  
...  
Keyword(s):  
Fluorescent Protein ◽  
Resting Membrane Potential ◽  
Reproductive State ◽  
Firing Patterns ◽  
State Dependent ◽  
Channel Expression ◽  
Physiological Analysis ◽  
Seasonal Breeder ◽  
Green Fluorescent

Kisspeptin (Kiss) neurons show drastic changes in kisspeptin expression in response to the serum sex steroid concentration in various vertebrate species. Thus, according to the reproductive states, kisspeptin neurons are suggested to modulate various neuronal activities, including the regulation of GnRH neurons in mammals. However, despite their reproductive state-dependent regulation, there is no physiological analysis of kisspeptin neurons in seasonal breeders. Here we generated the first kiss1-enhanced green fluorescent protein transgenic line of a seasonal breeder, medaka, for histological and electrophysiological analyses using a whole-brain in vitro preparation in which most synaptic connections are intact. We found histologically that Kiss1 neurons in the nucleus ventralis tuberis (NVT) projected to the preoptic area, hypothalamus, pituitary, and ventral telencephalon. Therefore, NVT Kiss1 neurons may regulate various homeostatic functions and innate behaviors. Electrophysiological analyses revealed that they show various firing patterns, including bursting. Furthermore, we found that their firings are regulated by the resting membrane potential. However, bursting was not induced from the other firing patterns with a current injection, suggesting that it requires some chronic modulations of intrinsic properties such as channel expression. Finally, we found that NVT Kiss1 neurons drastically change their neuronal activities according to the reproductive state and the estradiol levels. Taken together with the previous reports, we here conclude that the breeding condition drastically alters the Kiss1 neuron activities in both gene expression and firing activities, the latter of which is strongly related to Kiss1 release, and the Kiss1 peptides regulate the activities of various neural circuits through their axonal projections.

scholarly journals Cerebrovascular responses of the rat brain to noxious stimuli as examined by functional near-infrared whole brain imaging

2012 ◽  
Vol 107 (10) ◽  
pp. 2853-2865 ◽  
Author(s):  
Ji-Wei He ◽  
Fenghua Tian ◽  
Hanli Liu ◽  
Yuan Bo Peng
Keyword(s):  
Brain Imaging ◽  
Near Infrared ◽  
Small Animal ◽  
Nir Spectroscopy ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Hemodynamic Changes ◽  
Whole Brain ◽  
Brain Hemodynamics

While near-infrared (NIR) spectroscopy has been increasingly used to detect stimulated brain activities with an advantage of dissociating regional oxy- and deoxyhemoglobin concentrations simultaneously, it has not been utilized much in pain research. Here, we investigated and demonstrated the feasibility of using this technique to obtain whole brain hemodynamics in rats and speculated on the functional relevance of the NIR-based hemodynamic signals during pain processing. NIR signals were emitted and collected using a 26-optodes array on rat's dorsal skull surface after the removal of skin. Following the subcutaneous injection of formalin (50 μl, 3%) into a hindpaw, several isolable brain regions showed hemodynamic changes, including the anterior cingulate cortex, primary/secondary somatosensory cortexes, thalamus, and periaqueductal gray ( n = 6). Time courses of hemodynamic changes in respective regions matched with the well-documented biphasic excitatory response. Surprisingly, an atypical pattern (i.e., a decrease in oxyhemoglobin concentration with a concomitant increase in deoxyhemoglobin concentration) was seen in phase II. In a separate group of rats with innocuous brush and noxious pinch of the same area ( n = 11), results confirmed that the atypical pattern occurred more likely in the presence of nociception than nonpainful stimulation, suggesting it as a physiological substrate when the brain processes pain. In conclusion, the NIR whole brain imaging provides a useful alternative to study pain in vivo using small-animal models. Our results support the notion that neurovascular response patterns depend on stimuli, bringing attention to the interpretation of vascular-based neuroimaging data in studies of pain.

scholarly journals Increased sensitivity to strong perturbations in a whole-brain model of LSD

2021 ◽  
Author(s):  
Beatrice M. Jobst ◽  
Selen Atasoy ◽  
Adrián Ponce-Alvarez ◽  
Ana Sanjuán ◽  
Leor Roseman ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
External Perturbation ◽  
Brain Regions ◽  
Lysergic Acid ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Whole Brain ◽  
Response Diversity ◽  
Brain States ◽  
The Brain

AbstractLysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brain’s global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders.HighlightsNovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD)Shift of brain’s global working point to more complex dynamics after LSD intakeConsistently longer recovery time after model perturbation under LSD influenceStrongest effects in resting state networks relevant for psychedelic experienceHigher response diversity across brain regions under LSD influence after an external in silico perturbation

scholarly journals Recovery of neural dynamics criticality in personalized whole brain models of stroke

2020 ◽  
Author(s):  
Rodrigo P. Rocha ◽  
Loren Koçillari ◽  
Samir Suweis ◽  
Michele De Filippo De Grazia ◽  
Michel Thiebaut de Schotten ◽  
...  
Keyword(s):  
Neural Dynamics ◽  
Dynamical Models ◽  
Functional Architecture ◽  
Whole Brain ◽  
Optimal Response ◽  
Single Subjects ◽  
Optimal Function ◽  
Brain Models ◽  
And Behavior ◽  
Over Time

ABSTRACTThe critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single subjects using whole-brain models. Lesions engendered a sub-critical state that recovered over time in parallel with behavior. Notably, this improvement of criticality depended on the re-modeling of specific white matter connections. In summary, personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single subjects.

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