Since its inception in 2009, the Palestinian Neuroscience Initiative at Al-Quds University aimed to establish infrastructure for neuroscience research in Palestine while training the next generation of scientists and conduct locally relevant and internationally significant research in neuroscience, neuropharmacology, neuropsychiatry, and neurogenetics. Over the past nine years, the Palestinian Neuroscience Initiative has trained more than 150 Palestinian students and researchers at Al-Quds University, sent 40 researchers for advanced research training in Europe and the U.S., helped secure Ph.D. and clinical specialties in the U.S. and Europe for 15 researchers, helped more than 5000 Palestinian patients with psychiatric disorders, secured more than $2 million of funding for research in Palestine, and published 20 research papers in international journals. Currently, there are six different research units under the umbrella of the Palestinian Neuroscience Initiative, including:
(1) the cognitive neuroscience unit,
(2) the behavioral neurogenetics unit,
(3) the developmental neuroscience unit,
(4) the molecular neuroscience unit,
(5) neurophysiology unit, and
(6) the computational neuroscience unit. There are 38 active researchers at the Palestinian Neuroscience Initiative, including, 1 faculty member, 2 post-Ph.D. researchers, 3 Ph.D. researchers, 4 post-M.Sc. researchers, 4 M.Sc. students, 5 post-M.D. researchers, 3 post-B.Sc. researchers, and 16 medical students.
The Palestinian Neuroscience Initiative has ongoing partnerships with scientists at Rutgers, Harvard, NYU, Rockefeller, Northwell Health System and NIH in the U.S., and EPFL, SISSA, NTNU, Oxford, forschungszentrum Jülich, and TU-Berlin in Europe. The main sponsors of the Palestinian Neuroscience Initiative are, in chronological order: Mr. Saad Mouasher, Dr. Samih Darwazah and Hikma Pharmaceuticals LLC., the U.S. National Institutes of Health, and Mr. Fadi Ghandour. The Palestinian Neuroscience Initiative aims to create a powerhouse of neuroscience research in Palestine, train the next generation of Palestinian researchers and healthcare professionals, and create a viable research institution in Palestine to host Palestinian and other neuroscientists to pursue research careers in Palestine.
(Elsevier, 2014-11-01) Herzallah, Mohammad M.; Moustafa, Ahmed A.; Natsheh, Joman Y.; Danoun, Omar A.; Simon, Jessica R.; Tayem, Yasin I.; Sehwail, Mahmud A.; Amleh, Ivona; Bannoura, Issam; Petrides, Georgios; Myers, Catherine E.; Gluck, Mark A.
To better understand how medication status and task demands affect cognition in Major
Depressive Disorder (MDD), we evaluated medication-naïve patients with MDD, medicated
patients with MDD receiving the Selective Serotonin Reuptake Inhibitors (SSRI) paroxetine, and
healthy controls. All three groups were administered a computer-based cognitive task with two
phases, an initial phase in which a sequence is learned through reward-based feedback (which our
prior studies suggest is striatal-dependent), followed by a generalization phase that involves a
change in the context where learned rules are to be applied (which our prior studies suggest is
hippocampal-region dependent). Medication-naïve MDD patients were slow to learn the initial
sequence but were normal on subsequent generalization of that learning. In contrast, medicated
patients learned the initial sequence normally, but were impaired at the generalization phase. We
argue that these data suggest (i) an MDD-related impairment in striatal-dependent sequence
learning which can be remediated by SSRIs and (ii) an SSRI-induced impairment in hippocampaldependent
generalization of past learning to novel contexts, not otherwise seen in the medicationnaïve
MDD group. Thus, SSRIs might have a beneficial effect on striatal function required for
sequence learning, but a detrimental effect on the hippocampus and other medial temporal lobe
structures critical for generalization.
(Karger AG, Basel, 2012-11-01) Moustafa, Ahmed A.; Herzallah, Mohammad M.; Gluck, Mark A.
Background/Aims: Levodopa and dopamine agonists have
different effects on the motor, cognitive, and psychiatric aspects
of Parkinson’s disease (PD). Methods: Using a computational
model of basal ganglia (BG) and prefrontal cortex
(PFC) dopamine, we provide a theoretical synthesis of the
dissociable effects of these dopaminergic medications on
brain and cognition. Our model incorporates the findings
that levodopa is converted by dopamine cells into dopamine,
and thus activates prefrontal and striatal D 1 and D 2 dopamine
receptors, whereas antiparkinsonian dopamine agonists
directly stimulate D 2 receptors in the BG and PFC (although
some have weak affinity to D 1 receptors). Results: In
agreement with prior neuropsychological studies, our model
explains how levodopa enhances, but dopamine agonists
impair or have no effect on, stimulus-response learning and
working memory. Conclusion: Our model explains how levodopa
and dopamine agonists have differential effects on
motor and cognitive processes in PD.
(2013-09-23) Herzallah, Mohammad M.; Moustafa, Ahmed A.; Natsheh, Joman Y.; Abdellatif, Salam M.; Taha, Mohamad B.; Tayem, Yasin I.; Sehwail, Mahmud A.; Amleh, Ivona; Petrides, Georgios; Myers, Catherine E.; Gluck, Mark A.
One barrier to interpreting past studies of cognition and major depressive disorder (MDD) has been the failure in many studies to adequately dissociate the effects of MDD from the potential cognitive side effects of selective serotonin reuptake inhibitors (SSRIs) use. To better understand how remediation of depressive symptoms affects cognitive function in MDD, we evaluated three groups of subjects: medication-naïve patients with MDD, medicated patients with MDD receiving the SSRI paroxetine, and healthy control (HC) subjects. All were administered a category-learning task that allows for dissociation between learning from positive feedback (reward) vs. learning from negative feedback (punishment). Healthy subjects learned significantly better from positive feedback than medication-naïve and medicated MDD groups, whose learning accuracy did not differ significantly. In contrast, medicated patients with MDD learned significantly less from negative feedback than medication-naïve patients with MDD and healthy subjects, whose learning accuracy was comparable. A comparison of subject's relative sensitivity to positive vs. negative feedback showed that both the medicated MDD and HC groups conform to Kahneman and Tversky's (1979) Prospect Theory, which expects losses (negative feedback) to loom psychologically slightly larger than gains (positive feedback). However, medicated MDD and HC profiles are not similar, which indicates that the state of medicated MDD is not "normal" when compared to HC, but rather balanced with less learning from both positive and negative feedback. On the other hand, medication-naïve patients with MDD violate Prospect Theory by having significantly exaggerated learning from negative feedback. This suggests that SSRI antidepressants impair learning from negative feedback, while having negligible effect on learning from positive feedback. Overall, these findings shed light on the importance of dissociating the cognitive consequences of MDD from those of SSRI treatment, and from cognitive evaluation of MDD subjects in a medication-naïve state before the administration of antidepressants. Future research is needed to correlate the mood-elevating effects and the cognitive balance between reward- and punishment-based learning related to SSRIs.
To test a prediction of our previous computational model of cortico-hippocampal interaction (Gluck and Myers [1993, 2001]) for characterizing individual differences in category learning, we studied young healthy subjects using an fMRI-adapted category-learning task that has two phases, an initial phase in which associations are learned through trial-and-error feedback followed by a generalization phase in which previously learned rules can be applied to novel associations (Myers et al. ). As expected by our model, we found a negative correlation between learning-related hippocampal responses and accuracy during transfer, demonstrating that hippocampal adaptation during learning is associated with better behavioral scores during transfer generalization. In addition, we found an inverse relationship between Blood Oxygenation Level Dependent (BOLD) activity in the striatum and that in the hippocampal formation and the orbitofrontal cortex during the initial learning phase. Conversely, activity in the dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobes dominated over that of the hippocampal formation during the generalization phase. These findings provide evidence in support of theories of the neural substrates of category learning which argue that the hippocampal region plays a critical role during learning for appropriately encoding and representing newly learned information so that that this learning can be successfully applied and generalized to subsequent novel task demands.
Building on our previous neurocomputational models of basal ganglia and hippocampal region function
(and their modulation by dopamine and acetylcholine, respectively), we show here how an integration of
these models can inform our understanding of the interaction between the basal ganglia and hippocampal
region in associative learning and transfer generalization across various patient populations. As a
common test bed for exploring interactions between these brain regions and neuromodulators, we focus
on the acquired equivalence task, an associative learning paradigm in which stimuli that have been associated
with the same outcome acquire a functional similarity such that subsequent generalization
between these stimuli increases. This task has been used to test cognitive dysfunction in various patient
populations with damages to the hippocampal region and basal ganglia, including studies of patients
with Parkinson’s disease (PD), schizophrenia, basal forebrain amnesia, and hippocampal atrophy. Simulation
results show that damage to the hippocampal region—as in patients with hippocampal atrophy
(HA), hypoxia, mild Alzheimer’s (AD), or schizophrenia—leads to intact associative learning but impaired
transfer generalization performance. Moreover, the model demonstrates how PD and anterior communicating
artery (ACoA) aneurysm—two very different brain disorders that affect different neural mechanisms—
can have similar effects on acquired equivalence performance. In particular, the model shows
that simulating a loss of dopamine function in the basal ganglia module (as in PD) leads to slow acquisition
learning but intact transfer generalization. Similarly, the model shows that simulating the loss
of acetylcholine in the hippocampal region (as in ACoA aneurysm) also results in slower acquisition learning.
We argue from this that changes in associative learning of stimulus–action pathways (in the basal
ganglia) or changes in the learning of stimulus representations (in the hippocampal region) can have similar