Project acronym CoSI
Project Functional connectomics of the amygdala in social interactions of different valence
Researcher (PI) Ewelina KNAPSKA
Host Institution (HI) INSTYTUT BIOLOGII DOSWIADCZALNEJ IM. M. NENCKIEGO POLSKIEJ AKADEMII NAUK
Call Details Starting Grant (StG), LS5, ERC-2016-STG
Summary Understanding how brain controls social interactions is one of the central goals of neuroscience. Whereas social interactions and their effects on the emotional state of an individual are relatively well described at the behavioral level, much less is known about neural mechanisms involved in these very complex phenomena, especially in the amygdala, a key structure processing emotions in the brain.
Recent investigations, mainly on fear learning and extinction, have shown that there are highly specialized neuronal circuits within the amygdala that control specific behaviors. However, a high density of interconnections, both among amygdalar nuclei and between amygdalar nuclei and other brain regions, and the lack of a predictable distribution of functional cell types make defining behavioral functions of the amygdalar neuronal circuits challenging. Therefore, to understand how different neuronal circuits in the amygdala produce different behaviors tracing anatomical connections between activated neurons, i.e., the functional anatomy is needed.
Published data and our preliminary results suggest that within the amygdala there exist different neuronal circuits mediating social interactions of different valence (positive or negative affective significance) and that circuits controlling social and non-social emotions differ. Combining our recently developed behavioral models of adult, non-aggressive, same-sex social interactions with the methods of tracing anatomical connections between activated neurons, we plan to identify neural circuitry underlying social interactions of different emotional valence. This goal will be achieved by: (1) Characterizing functional anatomy of neuronal circuits in the amygdala underlying socially transferred emotions; (2) Examining role of the identified neuronal subpopulations in control of social behaviors; (3) Verifying role of matrix metalloproteinase-9-dependent neuronal subpopulations within the amygdala in social motivation.
Summary
Understanding how brain controls social interactions is one of the central goals of neuroscience. Whereas social interactions and their effects on the emotional state of an individual are relatively well described at the behavioral level, much less is known about neural mechanisms involved in these very complex phenomena, especially in the amygdala, a key structure processing emotions in the brain.
Recent investigations, mainly on fear learning and extinction, have shown that there are highly specialized neuronal circuits within the amygdala that control specific behaviors. However, a high density of interconnections, both among amygdalar nuclei and between amygdalar nuclei and other brain regions, and the lack of a predictable distribution of functional cell types make defining behavioral functions of the amygdalar neuronal circuits challenging. Therefore, to understand how different neuronal circuits in the amygdala produce different behaviors tracing anatomical connections between activated neurons, i.e., the functional anatomy is needed.
Published data and our preliminary results suggest that within the amygdala there exist different neuronal circuits mediating social interactions of different valence (positive or negative affective significance) and that circuits controlling social and non-social emotions differ. Combining our recently developed behavioral models of adult, non-aggressive, same-sex social interactions with the methods of tracing anatomical connections between activated neurons, we plan to identify neural circuitry underlying social interactions of different emotional valence. This goal will be achieved by: (1) Characterizing functional anatomy of neuronal circuits in the amygdala underlying socially transferred emotions; (2) Examining role of the identified neuronal subpopulations in control of social behaviors; (3) Verifying role of matrix metalloproteinase-9-dependent neuronal subpopulations within the amygdala in social motivation.
Max ERC Funding
1 312 500 €
Duration
Start date: 2016-12-01, End date: 2021-11-30
Project acronym Human Decisions
Project The Neural Determinants of Perceptual Decision Making in the Human Brain
Researcher (PI) Redmond O'connell
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Starting Grant (StG), LS5, ERC-2014-STG
Summary How do we make reliable decisions given sensory information that is often weak or ambiguous? Current theories center on a brain mechanism whereby sensory evidence is integrated over time into a “decision variable” which triggers the appropriate action upon reaching a criterion. Neural signals fitting this role have been identified in monkey electrophysiology but efforts to study the neural dynamics underpinning human decision making have been hampered by technical challenges associated with non-invasive recording. This proposal builds on a recent paradigm breakthrough made by the applicant that enables parallel tracking of discrete neural signals that can be unambiguously linked to the three key information processing stages necessary for simple perceptual decisions: sensory encoding, decision formation and motor preparation. Chief among these is a freely-evolving decision variable signal which builds at an evidence-dependent rate up to an action-triggering threshold and precisely determines the timing and accuracy of perceptual reports at the single-trial level. This provides an unprecedented neurophysiological window onto the distinct parameters of the human decision process such that the underlying mechanisms of several major behavioral phenomena can finally be investigated. This proposal seeks to develop a systems-level understanding of perceptual decision making in the human brain by tackling three core questions: 1) what are the neural adaptations that allow us to deal with speed pressure and variations in the reliability of the physically presented evidence? 2) What neural mechanism determines our subjective confidence in a decision? and 3) How does aging impact on the distinct neural components underpinning perceptual decision making? Each of the experiments described in this proposal will definitively test key predictions from prominent theoretical models using a combination of temporally precise neurophysiological measurement and psychophysical modelling.
Summary
How do we make reliable decisions given sensory information that is often weak or ambiguous? Current theories center on a brain mechanism whereby sensory evidence is integrated over time into a “decision variable” which triggers the appropriate action upon reaching a criterion. Neural signals fitting this role have been identified in monkey electrophysiology but efforts to study the neural dynamics underpinning human decision making have been hampered by technical challenges associated with non-invasive recording. This proposal builds on a recent paradigm breakthrough made by the applicant that enables parallel tracking of discrete neural signals that can be unambiguously linked to the three key information processing stages necessary for simple perceptual decisions: sensory encoding, decision formation and motor preparation. Chief among these is a freely-evolving decision variable signal which builds at an evidence-dependent rate up to an action-triggering threshold and precisely determines the timing and accuracy of perceptual reports at the single-trial level. This provides an unprecedented neurophysiological window onto the distinct parameters of the human decision process such that the underlying mechanisms of several major behavioral phenomena can finally be investigated. This proposal seeks to develop a systems-level understanding of perceptual decision making in the human brain by tackling three core questions: 1) what are the neural adaptations that allow us to deal with speed pressure and variations in the reliability of the physically presented evidence? 2) What neural mechanism determines our subjective confidence in a decision? and 3) How does aging impact on the distinct neural components underpinning perceptual decision making? Each of the experiments described in this proposal will definitively test key predictions from prominent theoretical models using a combination of temporally precise neurophysiological measurement and psychophysical modelling.
Max ERC Funding
1 382 643 €
Duration
Start date: 2015-05-01, End date: 2020-04-30
Project acronym MEME
Project Memory Engram Maintenance and Expression
Researcher (PI) Tomas RYAN
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Starting Grant (StG), LS5, ERC-2016-STG
Summary The goal of this project is to understand how specific memory engrams are physically stored in the brain. Connectionist theories of memory storage have guided research into the neuroscience of memory for over a half century, but have received little direct proof due to experimental limitations. The major confound that has limited direct testing of such theories has been an inability to identify the cells and circuits that store specific memories. Memory engram technology, which allows the tagging and in vivo manipulation of specific engram cells, has recently allowed us to overcome this empirical limitation and has revolutionised the way memory can be studied in rodent models. Based on our research it is now known that sparse populations of hippocampal neurons that were active during a defined learning experience are both sufficient and necessary for retrieval of specific contextual memories. More recently we have established that hippocampal engram cells preferentially synapse directly onto postsynaptic engram cells. This “engram cell connectivity” could provide the neurobiological substrate for the storage of multimodal memories through a distributed engram circuit. However it is currently unknown whether engram cell connectivity itself is important for memory function. The proposed integrative neuroscience project will employ inter-disciplinary methods to directly probe the importance of engram cell connectivity for memory retrieval, storage, and encoding. The outcomes will directly inform a novel and comprehensive neurobiological model of memory engram storage.
Summary
The goal of this project is to understand how specific memory engrams are physically stored in the brain. Connectionist theories of memory storage have guided research into the neuroscience of memory for over a half century, but have received little direct proof due to experimental limitations. The major confound that has limited direct testing of such theories has been an inability to identify the cells and circuits that store specific memories. Memory engram technology, which allows the tagging and in vivo manipulation of specific engram cells, has recently allowed us to overcome this empirical limitation and has revolutionised the way memory can be studied in rodent models. Based on our research it is now known that sparse populations of hippocampal neurons that were active during a defined learning experience are both sufficient and necessary for retrieval of specific contextual memories. More recently we have established that hippocampal engram cells preferentially synapse directly onto postsynaptic engram cells. This “engram cell connectivity” could provide the neurobiological substrate for the storage of multimodal memories through a distributed engram circuit. However it is currently unknown whether engram cell connectivity itself is important for memory function. The proposed integrative neuroscience project will employ inter-disciplinary methods to directly probe the importance of engram cell connectivity for memory retrieval, storage, and encoding. The outcomes will directly inform a novel and comprehensive neurobiological model of memory engram storage.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-02-01, End date: 2022-01-31
Project acronym RLPHARMFMRI
Project Beyond dopamine: Characterizing the computational functions of midbrain modulatory neurotransmitter systems in human reinforcement learning using model-based pharmacological fMRI
Researcher (PI) John O'doherty
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Starting Grant (StG), LS5, ERC-2009-StG
Summary Understanding how humans and other animals are able to learn from experience and use this information to select future behavioural strategies to obtain the reinforcers necessary for survival, is a fundamental research question in biology. Considerable progress has been made in recent years on the neural computational underpinnings of this process following the observation that the phasic activity of dopamine neurons in the midbrain resembles a prediction error from a formal computational theory known as reinforcement learning (RL). While much is known about the functions of dopamine in RL, much less is known about the computational functions of other modulatory neurotransmitter systems in the midbrain such as the cholinergic, norcpinephrine, and serotonergic systems. The goal of this research proposal to the ERC, is to begin a systematic study of the computational functions of these other neurotransmitter systems (beyond dopamine) in RL. To do this we will combine functional magnetic resonance imaging in human subjects while they perform simple decision making tasks and undergo pharmacological manipulations to modulate systemic levels of these different neurotransmitter systems. We will combine computational model-based analyses with fMRI and behavioural data in order to explore the effects that these pharmacological modulations exert on different parameters and modules within RL. Specifically, we will test the contributions that the cholinergic system makes in setting the learning rate during RL and in mediating computations of expected uncertainty in the distribution of rewards available, we will test for the role of norepinephrine in balancing the rate of exploration and exploitation during decision making, as well as in encoding the level of unexpected uncertainty, and we will explore the possible role of serotonin in setting the rate of temporal discounting for reward, or in encoding prediction errors during aversive as opposed to reward-learning.
Summary
Understanding how humans and other animals are able to learn from experience and use this information to select future behavioural strategies to obtain the reinforcers necessary for survival, is a fundamental research question in biology. Considerable progress has been made in recent years on the neural computational underpinnings of this process following the observation that the phasic activity of dopamine neurons in the midbrain resembles a prediction error from a formal computational theory known as reinforcement learning (RL). While much is known about the functions of dopamine in RL, much less is known about the computational functions of other modulatory neurotransmitter systems in the midbrain such as the cholinergic, norcpinephrine, and serotonergic systems. The goal of this research proposal to the ERC, is to begin a systematic study of the computational functions of these other neurotransmitter systems (beyond dopamine) in RL. To do this we will combine functional magnetic resonance imaging in human subjects while they perform simple decision making tasks and undergo pharmacological manipulations to modulate systemic levels of these different neurotransmitter systems. We will combine computational model-based analyses with fMRI and behavioural data in order to explore the effects that these pharmacological modulations exert on different parameters and modules within RL. Specifically, we will test the contributions that the cholinergic system makes in setting the learning rate during RL and in mediating computations of expected uncertainty in the distribution of rewards available, we will test for the role of norepinephrine in balancing the rate of exploration and exploitation during decision making, as well as in encoding the level of unexpected uncertainty, and we will explore the possible role of serotonin in setting the rate of temporal discounting for reward, or in encoding prediction errors during aversive as opposed to reward-learning.
Max ERC Funding
1 841 404 €
Duration
Start date: 2010-01-01, End date: 2010-09-30
