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Neuroprotective and Anticonvulsant Effects of Cannabinoids with Neurotrauma
Lecture
Thursday, December 5, 2024
Hour: 12:30 - 13:30
Location:
Neuroprotective and Anticonvulsant Effects of Cannabinoids with Neurotrauma
Prof.Linda Friedman
<p>Traumatic brain (TBI) injuries result in profound local hypoperfusion, ischemia, chronic inflammation and refractory seizures(post-traumatic epilepsy (PTE)), and restrict drug delivery to the site of impact so that peripheral treatment alone would have limited access to the site of injury during the most critical phases of neurotrauma. Cannabidiol (CBD), the major non-psychotropic cannabinoid, has anti-convulsant, anti-inflammatory, anti-nociceptive, antioxidant, and immuno-suppressive properties not fully understood. In pre-juvenile rats, microinjection of CBD attenuated kainate(KA)-induced seizures to a greater extent than intraperitoneal injection, indicating that local drug administration was more effective. In adult rats after experimental TBI, our modified CBD-infused implant applied extradural with oil injection supplementation restored vestibulomotorand cognitive functions compared to systemic treatment alone. We questioned whether the CBD or the low concentrations of THC in the extract was responsible for behavioral and cellular recovery.We hypothesized that an optimal ratio of cannabidiol (CBD) to tetrahydrocannabinol (THC) is required to protect against neuropathological consequences following TBI greater than either substance alone. Varied CBD:THC extract concentrations were compared with hempCBD lacking THC (CBD0). Neurons, glia, and parvalbumin interneurons (PV-INs) were evaluated. Weight loss was observed following high doses of THC dominant cannabis, THC100:1. Neuroscoresand vestibulomotorperformance were restored more with CBD:THC300:1-10:1. However, THC dominant treatments resulted in early onset to spontaneous seizures post-TBI. In a non-reward T-maze, the CBD10:1group had the highest alternation rates; TBI + vehicle, CBD0, CBD1:1, and THC100:1treatment groups had the lowest. The novel object recognition memory task showed CBD300:1treated animals had the best performance, while TBI or THC100:1treated groups had the worst. The forced swim test (FST) showed immobility time was highest after TBI and lowest after THC100:1treatment. The elevated plus maze (EPM) revealed the CBD0group spent the most time in closed arms. Both tests indicate that reduced anxiety was THC dependent. All combinations resulted in reduced injury but CBD10:1and THC20:1gave the most protection and THC100:1the least. Reduced anxiety level was THC dependent but higher doses were pro-convulsant cautioning THC dosing. Reduced GFAP labeling was highest with CBD dominant cannabis supporting its neuroprotective role against inflammation. Rescue of diminished bilateral PV-INs was observed within the hippocampus and medial prefrontal cortex (mPFC) with CBD dominant treatment (CBD300, CBD0) supporting their anticonvulsant effect. Loss of PV-INs with THC dominant treatment supports their proconvulsant effect. Thus, CBD and THC have different beneficial therapeutic effects indicating an optimal concentration ratio is critical for optimal neuropathological therapeutics.</p><p>Light refreshments before the seminar</p>
The Evolution of 7T (and Beyond) MRI in Basic Research and Clinical Practice
Lecture
Tuesday, December 3, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
The Evolution of 7T (and Beyond) MRI in Basic Research and Clinical Practice
Prof. Noam Harel
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis
The Center for Magnetic Resonance Research (CMRR) has been at the forefront of magnetic resonance imaging (MRI) innovation, pioneering ultra-high field (7 Tesla and above) technologies that are revolutionizing brain research and clinical care. This presentation will explore CMRR's groundbreaking journey, from the first functional MRI study to development of high-resolution fMRI capabilities revealing cortical columns within the human cortex. The presentation will also explore the translation of these technologies into clinical practice, with a focus on the unique visualization capabilities of 7T MRI, particularly for enhancing the precision of Deep Brain Stimulation (DBS) procedures. By exploring the progression from the 7T system to the world’s first 10.5T human MRI, this presentation will illustrate how these transformative technologies have pushed the limits of imaging science, uncovering new insights into brain function and advancing personalized clinical care at the intersection of technology, research, and medicine.
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
Lecture
Monday, October 14, 2024
Hour: 15:00 - 17:00
Location:
Gerhard M.J. Schmidt Lecture Hall
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
Alina Heukamp-Prof. Michal Rivlin Lab
Student Seminar-PhD Thesis Defense
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
The lateral geniculate nucleus (LGN) of the thalamus is a major retinal target, involved in processing and relaying visual information, including direction selectivity (DS) and orientation selectivity (OS). How DS and OS are organized in the LGN is poorly understood, as well as whether this information is directly inherited from the retina or generated de novo within the LGN. Using extracellular recordings from across the mouse LGN, we studied DS and OS responses and their topographic organization. We found that DS responses are absent in the central visual field, and that their preferred directions are topographically aligned to match translational optic flow patterns in the remaining visual field. OS responses were uniformly distributed throughout the visual field. By eliminating retinal DS in transgenic mice, we found that DS- but not OS-responses in the LGN were dependent on retinal DS. Thus, LGN DS is inherited from the retina, but retinogeniculate transfer may be topography-dependent, optimizing representations that support visually-guided behaviors.
Designing Language Models to Think Like Humans
Lecture
Thursday, July 11, 2024
Hour: 11:00 - 12:00
Location:
Gerhard M.J. Schmidt Lecture Hall
Designing Language Models to Think Like Humans
Dr. Chen Shani
Post-doctoral researcher NLP group
Stanford University
While language models (LMs) show impressive text manipulation capabilities, they also lack commonsense and reasoning abilities and are known to be brittle. In this talk, I will suggest a different LMs design paradigm, inspired by how humans understand it. I will present two papers, both shedding light on human-inspired NLP architectures aimed at delving deeper into the meaning beyond words.
The first paper [1] accounts for the lack of commonsense and reasoning abilities by proposing a paradigm shift in language understanding, drawing inspiration from embodied cognitive linguistics (ECL). In this position paper we propose a new architecture that treats language as inherently executable, grounded in embodied interaction, and driven by metaphoric reasoning.
The second paper [2] shows that LMs are brittle and far from human performance in their concept-understanding and abstraction capabilities. We argue this is due to their token-based objectives, and implement a concept-aware post-processing manipulation, showing it matches human intuition better. We then pave the way for more concept-aware training paradigms.
[1] Language (Re)modelling: Towards Embodied Language Understanding
Ronen Tamari, Chen Shani, Tom Hope, Miriam R L Petruck, Omri Abend, and Dafna Shahaf. 2020.
In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), pages 6268–6281, Online. Association for Computational Linguistics.
[2] Towards Concept-Aware Large Language Models
Shani, Chen, Jilles Vreeken, and Dafna Shahaf.
In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 13158-13170. 2023.
Bio: Chen Shani is a post-doctoral researcher at Stanford's NLP group, collaborating with Prof. Dan Jurafsky. Previously, she pursued her Ph.D. at the Hebrew University under the guidance of Prof. Dafna Shahaf and worked at Amazon Research. Her focus lies at the intersection of humans and NLP, where she implements insights from human cognition to improve NLP systems.
This decision, not just the average decision: Factors contributing to one single perceptual judgment
Lecture
Tuesday, July 9, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
This decision, not just the average decision: Factors contributing to one single perceptual judgment
Prof. Mathew E. Diamond
Cognitive Neuroscience, SISSA Trieste, Italy
While cognitive neuroscientists have uncovered principles of perceptual decision-making by analyzing choices and neuronal firing across thousands of trials, we do not yet know the behavioral or neuronal dynamics underlying one SINGLE choice. For instance, why might a subject judge a given stimulus in category A 70% of the time but in category B 30%? Until we can work out precisely what determines single-decisions – this choice, right now – the mechanisms of real-world decision-making will remain unknown. In tactile psychophysical tasks with rats and humans, we are trying to sort out factors that explain the variability in judgments (across trials) to the identical stimulus input. We identify four factors: (i) trial-to-trial fluctuations in sensory coding, (ii) temporal context, namely, the history of preceding stimuli and choices, (iii) attention, and (iv) bias (predictions originating in beliefs about the environment’s probabilistic structure). The strategy is to bring these factors under experimental control, rather than leaving them to vary according to uninterrogated states within the subject. Psychophysics from rats and humans show that large chunks of variability are accounted for by these factors; evidence from cortical neuronal populations in rats provides some mechanistic grounding.
Reading Minds & Machines-AND-The Wisdom of a Crowd of Brains
Lecture
Tuesday, June 25, 2024
Hour: 12:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Reading Minds & Machines-AND-The Wisdom of a Crowd of Brains
Prof. Michal Irani
Dept of Computer Science & Applied Mathematics, WIS
1. Can we reconstruct images that a person saw, directly from his/her fMRI brain recordings?
2. Can we reconstruct the training data that a deep-network trained on, directly from the parameters of the network?
The answer to both of these intriguing questions is “Yes!”
In this talk I will show how these can be done. I will then show how exploring the two domains in tandem can potentially lead to significant breakthroughs in both fields. More specifically:
(i) I will show how combining the power of Brains & Machines can potentially be used to bridge the gap between those two domains.
(ii) Combining the power of Multiple Brains (scanned on different fMRI scanners with NO shared stimuli) can lead to new breakthroughs and discoveries in Brain-Science. We refer to this as “the Wisdom of a Crowd of Brains”. In particular, we show that a Universal Encoder can be trained on multiple brains with no shared data, and that information can be functionally mapped between different brains.
Memory and Obliviscence:From Random to Structured Material
Lecture
Sunday, June 23, 2024
Hour: 14:15 - 15:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Memory and Obliviscence:From Random to Structured Material
Antonis Georgiou-Student Seminar-PhD Thesis Defense
Advisor: Prof. Misha Tsodyks
Dept of Brain Sciences, WIS
The study of human memory is a rich field with a history that spans over a century, traditionally investigated through the prism of psychology. Drawing inspiration from this vast pool of findings, we approached the subject with a more physics-oriented mindset based on first principles. For this reason, we combined mathematical modelling of established ideas from the literature of psychology with large-scale experimentation. In particular, we created a model based on the concept of retroactive interference that states that newly encoded items hinder the retention of older ones in memory. We show that this simple mechanism is sufficient to describe a variety of experimental data of recognition memory with different categories of verbal and pictorial stimuli. The model has a single free parameter and can be solved analytically. We then focus on recall and recognition memory of stories. This transition from discrete random lists to coherent continuous stimuli such as stories introduces a new challenge when it comes to the quantification and the analysis of the results. To address this, we have developed a pipeline that employs large language models and showed that it performs comparably to human evaluators. Using this tool we were able to show that recall scales linearly with recognition and story size for the range we examined. Finally, we discovered that when stories are presented in a scrambled manner, even though recall performance drops, subjects seem to reconstruct the material in their recall in alignment to the unscrambled version.
Elucidating convergence and divergence of neural mechanisms: from genes to behavior
Lecture
Thursday, June 13, 2024
Hour: 14:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Elucidating convergence and divergence of neural mechanisms: from genes to behavior
Asaf Gat-Student Seminar-PhD Thesis Defense
Dr. Meital Oren Lab
The capacity of animals to respond to stimuli in their surroundings is crucial for their survival. In mammals, complex evaluations of the environment require large numbers and different subtypes of neurons. The nematode C. elegans utilize its compact nervous system to process environmental cues and tune behavior. Integration of opposing spatial information and adaptation to distinct types of addictive substances are only a few challenges that require efficient and effective use of the worm’s compact nervous system. We describe how distinct environmental cues can converge onto common neural networks and molecular mechanisms but generate diverse neuronal and behavioral responses. Using a multidisciplinary approach, we completed several parallel aims, including the development of two novel research methods
Memory consolidation and generalization during sleep
Lecture
Wednesday, June 5, 2024
Hour: 10:00 - 11:00
Location:
Nella and Leon Benoziyo Building for Brain Research
Memory consolidation and generalization during sleep
Ella Bar-Student Seminar-PhD Thesis Defense
Prof. Rony Paz Lab &
Prof. Yuval Nir, Tel Aviv University
During sleep, our memories are reactivated and consolidated in an active process that significantly influences our memory and decision-making. In this talk, I will present two studies about sleep-memory consolidation. The first study investigated sleep memory consolidation's local versus global properties within the brain. By exploiting the unique functional neuroanatomy of olfactory system, we were able to manipulate sleep oscillations and enhance memories locally within a single hemisphere during sleep. These findings underscore the local nature of sleep memory consolidation, which can be selectively manipulated within the brain, thereby creating an important link between theories of local sleep and learning. The second research explored the relationship between generalization processes and sleep, acknowledging that overgeneralization of negative stimuli and disruptions in sleep quality contribute to anxiety and PTSD disorders. Specifically, we studied participants' responses to stimuli associated with positive, negative, or neutral outcomes. Our findings revealed significant correlations between brain activity, as detected by fMRI, during the association of a stimulus with an outcome and the perceptual generalization of these stimuli. While activity in limbic brain areas was correlated with immediate negative stimulus generalization, we observed that the activation in these areas predicted recovery and positively related generalization following sleep. Moreover, we identified specific sleep oscillations correlated with this recovery generalization using high-density EEG recordings. These results highlight the crucial role of sleep in both generalization processes and the restoration of balanced responses to stimuli. Understanding these mechanisms can offer valuable insights into developing therapeutic strategies for anxiety and PTSD.
Blood flow perturbations and its impact on brain structure and function: from microstrokes to heartbeats
Lecture
Tuesday, June 4, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Blood flow perturbations and its impact on brain structure and function: from microstrokes to heartbeats
Prof. Pablo Blinder
Dept of Neurobiology, Tel Aviv University
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Neuroprotective and Anticonvulsant Effects of Cannabinoids with Neurotrauma
Lecture
Thursday, December 5, 2024
Hour: 12:30 - 13:30
Location:
Neuroprotective and Anticonvulsant Effects of Cannabinoids with Neurotrauma
Prof.Linda Friedman
<p>Traumatic brain (TBI) injuries result in profound local hypoperfusion, ischemia, chronic inflammation and refractory seizures(post-traumatic epilepsy (PTE)), and restrict drug delivery to the site of impact so that peripheral treatment alone would have limited access to the site of injury during the most critical phases of neurotrauma. Cannabidiol (CBD), the major non-psychotropic cannabinoid, has anti-convulsant, anti-inflammatory, anti-nociceptive, antioxidant, and immuno-suppressive properties not fully understood. In pre-juvenile rats, microinjection of CBD attenuated kainate(KA)-induced seizures to a greater extent than intraperitoneal injection, indicating that local drug administration was more effective. In adult rats after experimental TBI, our modified CBD-infused implant applied extradural with oil injection supplementation restored vestibulomotorand cognitive functions compared to systemic treatment alone. We questioned whether the CBD or the low concentrations of THC in the extract was responsible for behavioral and cellular recovery.We hypothesized that an optimal ratio of cannabidiol (CBD) to tetrahydrocannabinol (THC) is required to protect against neuropathological consequences following TBI greater than either substance alone. Varied CBD:THC extract concentrations were compared with hempCBD lacking THC (CBD0). Neurons, glia, and parvalbumin interneurons (PV-INs) were evaluated. Weight loss was observed following high doses of THC dominant cannabis, THC100:1. Neuroscoresand vestibulomotorperformance were restored more with CBD:THC300:1-10:1. However, THC dominant treatments resulted in early onset to spontaneous seizures post-TBI. In a non-reward T-maze, the CBD10:1group had the highest alternation rates; TBI + vehicle, CBD0, CBD1:1, and THC100:1treatment groups had the lowest. The novel object recognition memory task showed CBD300:1treated animals had the best performance, while TBI or THC100:1treated groups had the worst. The forced swim test (FST) showed immobility time was highest after TBI and lowest after THC100:1treatment. The elevated plus maze (EPM) revealed the CBD0group spent the most time in closed arms. Both tests indicate that reduced anxiety was THC dependent. All combinations resulted in reduced injury but CBD10:1and THC20:1gave the most protection and THC100:1the least. Reduced anxiety level was THC dependent but higher doses were pro-convulsant cautioning THC dosing. Reduced GFAP labeling was highest with CBD dominant cannabis supporting its neuroprotective role against inflammation. Rescue of diminished bilateral PV-INs was observed within the hippocampus and medial prefrontal cortex (mPFC) with CBD dominant treatment (CBD300, CBD0) supporting their anticonvulsant effect. Loss of PV-INs with THC dominant treatment supports their proconvulsant effect. Thus, CBD and THC have different beneficial therapeutic effects indicating an optimal concentration ratio is critical for optimal neuropathological therapeutics.</p><p>Light refreshments before the seminar</p>
The Evolution of 7T (and Beyond) MRI in Basic Research and Clinical Practice
Lecture
Tuesday, December 3, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
The Evolution of 7T (and Beyond) MRI in Basic Research and Clinical Practice
Prof. Noam Harel
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis
The Center for Magnetic Resonance Research (CMRR) has been at the forefront of magnetic resonance imaging (MRI) innovation, pioneering ultra-high field (7 Tesla and above) technologies that are revolutionizing brain research and clinical care. This presentation will explore CMRR's groundbreaking journey, from the first functional MRI study to development of high-resolution fMRI capabilities revealing cortical columns within the human cortex. The presentation will also explore the translation of these technologies into clinical practice, with a focus on the unique visualization capabilities of 7T MRI, particularly for enhancing the precision of Deep Brain Stimulation (DBS) procedures. By exploring the progression from the 7T system to the world’s first 10.5T human MRI, this presentation will illustrate how these transformative technologies have pushed the limits of imaging science, uncovering new insights into brain function and advancing personalized clinical care at the intersection of technology, research, and medicine.
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
Lecture
Monday, October 14, 2024
Hour: 15:00 - 17:00
Location:
Gerhard M.J. Schmidt Lecture Hall
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
Alina Heukamp-Prof. Michal Rivlin Lab
Student Seminar-PhD Thesis Defense
The role of neurons in the direction-selective retinal circuit in visual processing in the retina and in the visual thalamus
The lateral geniculate nucleus (LGN) of the thalamus is a major retinal target, involved in processing and relaying visual information, including direction selectivity (DS) and orientation selectivity (OS). How DS and OS are organized in the LGN is poorly understood, as well as whether this information is directly inherited from the retina or generated de novo within the LGN. Using extracellular recordings from across the mouse LGN, we studied DS and OS responses and their topographic organization. We found that DS responses are absent in the central visual field, and that their preferred directions are topographically aligned to match translational optic flow patterns in the remaining visual field. OS responses were uniformly distributed throughout the visual field. By eliminating retinal DS in transgenic mice, we found that DS- but not OS-responses in the LGN were dependent on retinal DS. Thus, LGN DS is inherited from the retina, but retinogeniculate transfer may be topography-dependent, optimizing representations that support visually-guided behaviors.
Designing Language Models to Think Like Humans
Lecture
Thursday, July 11, 2024
Hour: 11:00 - 12:00
Location:
Gerhard M.J. Schmidt Lecture Hall
Designing Language Models to Think Like Humans
Dr. Chen Shani
Post-doctoral researcher NLP group
Stanford University
While language models (LMs) show impressive text manipulation capabilities, they also lack commonsense and reasoning abilities and are known to be brittle. In this talk, I will suggest a different LMs design paradigm, inspired by how humans understand it. I will present two papers, both shedding light on human-inspired NLP architectures aimed at delving deeper into the meaning beyond words.
The first paper [1] accounts for the lack of commonsense and reasoning abilities by proposing a paradigm shift in language understanding, drawing inspiration from embodied cognitive linguistics (ECL). In this position paper we propose a new architecture that treats language as inherently executable, grounded in embodied interaction, and driven by metaphoric reasoning.
The second paper [2] shows that LMs are brittle and far from human performance in their concept-understanding and abstraction capabilities. We argue this is due to their token-based objectives, and implement a concept-aware post-processing manipulation, showing it matches human intuition better. We then pave the way for more concept-aware training paradigms.
[1] Language (Re)modelling: Towards Embodied Language Understanding
Ronen Tamari, Chen Shani, Tom Hope, Miriam R L Petruck, Omri Abend, and Dafna Shahaf. 2020.
In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), pages 6268–6281, Online. Association for Computational Linguistics.
[2] Towards Concept-Aware Large Language Models
Shani, Chen, Jilles Vreeken, and Dafna Shahaf.
In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 13158-13170. 2023.
Bio: Chen Shani is a post-doctoral researcher at Stanford's NLP group, collaborating with Prof. Dan Jurafsky. Previously, she pursued her Ph.D. at the Hebrew University under the guidance of Prof. Dafna Shahaf and worked at Amazon Research. Her focus lies at the intersection of humans and NLP, where she implements insights from human cognition to improve NLP systems.
This decision, not just the average decision: Factors contributing to one single perceptual judgment
Lecture
Tuesday, July 9, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
This decision, not just the average decision: Factors contributing to one single perceptual judgment
Prof. Mathew E. Diamond
Cognitive Neuroscience, SISSA Trieste, Italy
While cognitive neuroscientists have uncovered principles of perceptual decision-making by analyzing choices and neuronal firing across thousands of trials, we do not yet know the behavioral or neuronal dynamics underlying one SINGLE choice. For instance, why might a subject judge a given stimulus in category A 70% of the time but in category B 30%? Until we can work out precisely what determines single-decisions – this choice, right now – the mechanisms of real-world decision-making will remain unknown. In tactile psychophysical tasks with rats and humans, we are trying to sort out factors that explain the variability in judgments (across trials) to the identical stimulus input. We identify four factors: (i) trial-to-trial fluctuations in sensory coding, (ii) temporal context, namely, the history of preceding stimuli and choices, (iii) attention, and (iv) bias (predictions originating in beliefs about the environment’s probabilistic structure). The strategy is to bring these factors under experimental control, rather than leaving them to vary according to uninterrogated states within the subject. Psychophysics from rats and humans show that large chunks of variability are accounted for by these factors; evidence from cortical neuronal populations in rats provides some mechanistic grounding.
Reading Minds & Machines-AND-The Wisdom of a Crowd of Brains
Lecture
Tuesday, June 25, 2024
Hour: 12:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Reading Minds & Machines-AND-The Wisdom of a Crowd of Brains
Prof. Michal Irani
Dept of Computer Science & Applied Mathematics, WIS
1. Can we reconstruct images that a person saw, directly from his/her fMRI brain recordings?
2. Can we reconstruct the training data that a deep-network trained on, directly from the parameters of the network?
The answer to both of these intriguing questions is “Yes!”
In this talk I will show how these can be done. I will then show how exploring the two domains in tandem can potentially lead to significant breakthroughs in both fields. More specifically:
(i) I will show how combining the power of Brains & Machines can potentially be used to bridge the gap between those two domains.
(ii) Combining the power of Multiple Brains (scanned on different fMRI scanners with NO shared stimuli) can lead to new breakthroughs and discoveries in Brain-Science. We refer to this as “the Wisdom of a Crowd of Brains”. In particular, we show that a Universal Encoder can be trained on multiple brains with no shared data, and that information can be functionally mapped between different brains.
Memory and Obliviscence:From Random to Structured Material
Lecture
Sunday, June 23, 2024
Hour: 14:15 - 15:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Memory and Obliviscence:From Random to Structured Material
Antonis Georgiou-Student Seminar-PhD Thesis Defense
Advisor: Prof. Misha Tsodyks
Dept of Brain Sciences, WIS
The study of human memory is a rich field with a history that spans over a century, traditionally investigated through the prism of psychology. Drawing inspiration from this vast pool of findings, we approached the subject with a more physics-oriented mindset based on first principles. For this reason, we combined mathematical modelling of established ideas from the literature of psychology with large-scale experimentation. In particular, we created a model based on the concept of retroactive interference that states that newly encoded items hinder the retention of older ones in memory. We show that this simple mechanism is sufficient to describe a variety of experimental data of recognition memory with different categories of verbal and pictorial stimuli. The model has a single free parameter and can be solved analytically. We then focus on recall and recognition memory of stories. This transition from discrete random lists to coherent continuous stimuli such as stories introduces a new challenge when it comes to the quantification and the analysis of the results. To address this, we have developed a pipeline that employs large language models and showed that it performs comparably to human evaluators. Using this tool we were able to show that recall scales linearly with recognition and story size for the range we examined. Finally, we discovered that when stories are presented in a scrambled manner, even though recall performance drops, subjects seem to reconstruct the material in their recall in alignment to the unscrambled version.
Elucidating convergence and divergence of neural mechanisms: from genes to behavior
Lecture
Thursday, June 13, 2024
Hour: 14:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Elucidating convergence and divergence of neural mechanisms: from genes to behavior
Asaf Gat-Student Seminar-PhD Thesis Defense
Dr. Meital Oren Lab
The capacity of animals to respond to stimuli in their surroundings is crucial for their survival. In mammals, complex evaluations of the environment require large numbers and different subtypes of neurons. The nematode C. elegans utilize its compact nervous system to process environmental cues and tune behavior. Integration of opposing spatial information and adaptation to distinct types of addictive substances are only a few challenges that require efficient and effective use of the worm’s compact nervous system. We describe how distinct environmental cues can converge onto common neural networks and molecular mechanisms but generate diverse neuronal and behavioral responses. Using a multidisciplinary approach, we completed several parallel aims, including the development of two novel research methods
Memory consolidation and generalization during sleep
Lecture
Wednesday, June 5, 2024
Hour: 10:00 - 11:00
Location:
Nella and Leon Benoziyo Building for Brain Research
Memory consolidation and generalization during sleep
Ella Bar-Student Seminar-PhD Thesis Defense
Prof. Rony Paz Lab &
Prof. Yuval Nir, Tel Aviv University
During sleep, our memories are reactivated and consolidated in an active process that significantly influences our memory and decision-making. In this talk, I will present two studies about sleep-memory consolidation. The first study investigated sleep memory consolidation's local versus global properties within the brain. By exploiting the unique functional neuroanatomy of olfactory system, we were able to manipulate sleep oscillations and enhance memories locally within a single hemisphere during sleep. These findings underscore the local nature of sleep memory consolidation, which can be selectively manipulated within the brain, thereby creating an important link between theories of local sleep and learning. The second research explored the relationship between generalization processes and sleep, acknowledging that overgeneralization of negative stimuli and disruptions in sleep quality contribute to anxiety and PTSD disorders. Specifically, we studied participants' responses to stimuli associated with positive, negative, or neutral outcomes. Our findings revealed significant correlations between brain activity, as detected by fMRI, during the association of a stimulus with an outcome and the perceptual generalization of these stimuli. While activity in limbic brain areas was correlated with immediate negative stimulus generalization, we observed that the activation in these areas predicted recovery and positively related generalization following sleep. Moreover, we identified specific sleep oscillations correlated with this recovery generalization using high-density EEG recordings. These results highlight the crucial role of sleep in both generalization processes and the restoration of balanced responses to stimuli. Understanding these mechanisms can offer valuable insights into developing therapeutic strategies for anxiety and PTSD.
Blood flow perturbations and its impact on brain structure and function: from microstrokes to heartbeats
Lecture
Tuesday, June 4, 2024
Hour: 12:30 - 13:30
Location:
Gerhard M.J. Schmidt Lecture Hall
Blood flow perturbations and its impact on brain structure and function: from microstrokes to heartbeats
Prof. Pablo Blinder
Dept of Neurobiology, Tel Aviv University
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