Cocaine Sensitization and Addiction: Different Across Sexes?

 In Dr. Steidl’s 2022 paper titled “Glutamate inputs from the laterodorsal tegmental nucleus to the ventral tegmental area are essential for the induction of cocaine sensitization in male mice,” the researchers aimed to determine how cocaine sensitization is affected by glutamatergic projections from the laterodorsal tegmental nucleus (LDTg) to the ventral tegmental area (VTA). They used locomotor assessments to deduce whether cocaine sensitization occured after optogenetic manipulation where LDTg glutamatergic cells and their VTA projections were inhibited after blue light was inputted to the brains of halorhodopsin infected mice. The study found that mice in the halorhodopsin experimental group exposed to cocaine had no change in  locomotor activity, indicating no increase in cocaine sensitization, as opposed to the control group which did show increases and thus sensitization. This led the researchers to deduce that glutamatergic inputs are crucial for developing cocaine sensitization.

A neuroscience research group at Florida Atlantic University, led by Amanda Catalfio, explored how cocaine-induced sensitization and glutamate plasticity in the nucleus accumbens (NAc) core are affected by biological sex. Similar to Dr. Steidl’s study, who studied the role of upstream glutamate inputs in sensitization, Catalfio’s group aimed to recognize if repeated cocaine exposure leads to neuroplasticity in glutamatergic signaling in the nucleus accumbens core, and if these changes may be different between sexes. In their experiment, rats of both sexes were exposed to repeated cocaine injections, and measures of locomotor sensitization (similar to the test in Dr. Steidl’s study) and spontaneous excitatory postsynaptic currents (sEPSCs) in the nucleus accumbens core were collected to assess behavioral and neural adaptations.

The study found that both male and female rats exhibited psychomotor sensitization — which is increased locomotor activity over repeated cocaine exposure. However, only males showed enhanced sEPSC frequency in the nucleus accumbens core, suggesting a sex-specific strengthening of glutamatergic inputs higher in males. Females, despite showing behavioral sensitization, did not display the same glutamatergic plasticity shown by changing postsynaptic currents. These results indicate that while behavioral sensitization after sustained cocaine  exposure occurs in both sexes, the underlying synaptic mechanisms, particularly glutamate signaling in the nucleus accumbens, may differ between males and females.

Based off of Dr. Steidl’s study finding that glutamate signaling into the VTA is necessary for initiating sensitization (as the group with inhibited glutamate inputs to VTA did not show sensitization), and Dr. Catalfio’s study findings that glutamate plasticity within the nucleus accumbens is sex-dependent following cocaine sensitization, perhaps cocaine addiction involves a multi-level glutamatergic cascade: glutamate first acts upstream to drive VTA dopamine neuron changes, and later induces circuit-specific plasticity in the basal ganglia- specifically the nucleus accumbens- that may be influenced differently across biological sexes. However, the discovery that females experienced behavioral sensitization without major neural circuitry changes in nucleus accumbens glutamate activity suggests that females may rely on different or additional neural mechanisms that lead to the behavioral changes exhibited. Further research could explore how upstream VTA inputs and downstream nucleus accumbens adaptations interact differently between sexes, which could have important implications for developing sex-specific addiction treatments. Either way, these studies together highlight the critical and complex role of glutamate pathways in drug-induced plasticity and addiction. 

Works Cited

Catalfio AM, Fetterly TL, Nieto AM, Robinson TE, Ferrario CR. Cocaine-induced sensitization and glutamate plasticity in the nucleus accumbens core: effects of sex. Biol Sex Differ. 2023 Jun 24;14(1):41. doi: 10.1186/s13293-023-00525-8. PMID: 37355656; PMCID: PMC10290362.

Puranik A, Buie N, Arizanovska D, Vezina P, Steidl S. Glutamate inputs from the laterodorsal tegmental nucleus to the ventral tegmental area are essential for the induction of cocaine sensitization in male mice. Psychopharmacology (Berl). 2022 Oct;239(10):3263-3276. doi: 10.1007/s00213-022-06209-2. Epub 2022 Aug 25. PMID: 36006414.

Sunk Costs on Decision-Making Across Species

Decision-making is a fundamental psychological process, where the course of action can shape human behavior as well as perceptions of the world. An important concept in determination is the sunk cost fallacy; a classification of cognitive bias that leads to continued investments in nonbeneficial courses of action simply because of prior investment of significant resources such as time or money, which cannot be recovered.     

Dr. Brian Sweis et al. (2018) explore psychological decision-making in animal models, such as mice and rats, to understand if the subjects exhibit sunk cost sensitivity. The aim of his research is to gain insight into managerial behaviors in non-human models; and whether or not animal models participate in cognitive biases, and the neural mechanisms behind them. Through considerable research, Dr. Sweis and his team discovered that across species, sensitivity to sunk costs is conserved, challenging the notion that sunk cost cognition is uniquely human. Interestingly, sunk cost sensitivities only occurred after the initial decision was made; if the subject decided to wait, then the longer they waited, the less likely they were to quit. This means that subjects made rational and logical choices before they committed to waiting but once invested, they became more prone to bias, making ongoing decisions distorted. 

In Harm to Others Reduces the Sunk-Cost Effects, Dr. Hamzagic et al. (2021) investigates how morals and ethics influence irrational behaviors tied to sunk costs. This study is revolutionary due to ethics and decision-making being studied alongside one another rather that separately. Dr. Hamzagic’s studies were divided into 3 experiments. Experiment one, subjects were given vignettes with conditions of varying sunk costs (high and low) as well as varying levels of potential harm. They found that the sunk cost-effect was significantly smaller in simulations where harm would occur to others, in essence subjects were less trapped by sunk costs when ethical concerns were on the line. In experiment 2, what was being tested was the role perspective plays in decision-making. The conditions being modulated were who the decision was for (subject or someone else) as well as high and low sunk costs. Surprisingly, researchers found that perspective does not have any significant effects on decision making, sunk cost effects were still present regardless of who the decision was for. This means subjects stick to irrational decisions even when deciding for others. Finally in experiment 3, they retested experiment 1 to confirm or deny key findings. The same conditions were present but with the addition of Bayesian analysis where they found the results were statistically strong and replicative. 

A multitude of research is being conducted on the biases of decision-making with sunk costs being an area of interest. Through sustained research, models can then predict decision making based on what the given circumstances are. 

REFERENCES

Brian M. Sweis et al. ,Sensitivity to “sunk costs” in mice, rats, and  humans.Science361,178-181(2018).DOI:10.1126/science.aar8644

Hamzagic, Z.I., Derksen, D.G., Matsuba, M.K. et al. Harm to others reduces the sunk-cost effect. Mem Cogn 49, 544–556 (2021). https://doi.org/10.3758/s13421-020-01112-7

The Cellular Mechanisms of Fear and Post-Traumatic Stress Disorder.

 Post-traumatic stress disorder is a form of mental illness that occurs when one suffers or witnesses a traumatic experience causing them to have nightmares, flashbacks, and can also lead to anxiety or depression. PTSD is common among veterans who have served in active duty, a study conducted in 2017 found 12.9% of veterans were diagnosed with PTSD almost doubling the 6.8% of the United States population diagnosed with the disorder¹. PTSD symptoms vary from person to person creating difficulties for individuals to understand what they are going through. An interview between Dr. Call and the wife of a veteran (Shelly), whose husband suffers from PTSD shows the common struggles of receiving treatment and the disorders complexities².  Shelly expresses her husband’s frustration in seeking out treatment and guidance from a military mental health clinic but was denied any form of care. This occurred even during an instance where he experienced a panic attack and was told to return home and rest. After numerous visits to the clinic, he was diagnosed with PTSD and was able to receive treatment to improve his symptoms. This veterans experience is not unique, many others are denied any form of help due to the differences in the expression of PTSD. It is important for us as a society to further understand this disorder and its severity.

A study which expresses the neuronal mechanisms of emotion and stress was conducted by Stephanie Grella during her time at Boston University, “Artificially enhancing and suppressing hippocampus-mediated memories”³. Grella and her team’s research manipulate the ventral and dorsal hippocampus with optogenetics and chemogenetics to drive context-specific behaviors. The two regions of the hippocampus have different ways of driving emotion and cognition, the dorsal region processing spatial, temporal and other framework details while the ventral region is directly linked to emotion and stress. The initial procedure includes injecting a mix virus of AAV9-c-Fos-tTA and AAV9-TRE-eYFP into the dentate gyrus of adult mice to express the c-Fos gene to enhance response to stimuli. The mice were fear conditioned in a chamber where they would receive foot shocks and then returned into the same environment the following day without the fear stimulus. Changes were found within the dentate gyrus where dorsal and ventral regions were activated with the presence of the fear stimulus, but only the ventral region was activated when the mice was returned to the fear environment. 

The following procedure includes the use of optogenetic stimulation of tagged cells along the longitudinal axis of the hippocampus to drive fear or appetitive behaviors. The mice were placed into a neutral, fear, or female exposure stimulus to compare. The manipulation of these memories within the fear stimulus have expressed fear related behaviors within the mice exhibiting location avoidances and preferences. Next, the mice were split into two fear stimulus groups receiving 1 foot-shock and stimulation of the ventral DG or 4 foot-shocks and stimulation to the dorsal DG. Mice receiving 4 shocks produced suppression in freezing while those receiving 1 shock produced and increase in freezing. Finally, the chemogenetic inhibition of the basolateral amygdala within both groups receiving stimulation to the ventral or dorsal DG. When BLA cells were inhibited, there was a disruption of stimulation-induced enhancement when the ventral DG received persistent stimulus. Only within the ventral DG group there was an overlap between BLA cells active during recall of the fear memory and during the encoding of the memory. 

The ability to manipulate and observe how fear memories are encoded and recalled can provide the foundation of a greater understanding for stress-related psychological disorders such as PTSD. These findings provide the specific locations where fear memories are generated and how location can trigger these memories to resurface. This can allow the formulation of more effective medications and new organizations of psychotherapy mechanisms.

References

1.     PTSD and Veterans. Hill & Ponton, P.A. April 16, 2025. Accessed April 28, 2025. https://www.hillandponton.com/resources/veterans-statistics-ptsd/#:~:text=In%20a%202017%20study%20involving,any%20point%20in%20their%20lives.

2.     Call J. PTSD in the military: An interview with a military wife. Psychology Today. January 2009. Accessed April 28, 2025. https://www.psychologytoday.com/us/blog/crisis-center/200901/ptsd-in-the-military-interview-military-wife. 

3.     Chen BK, Murawski NJ, Cincotta C, et al. Artificially enhancing and suppressing hippocampus-mediated memories. Current Biology. 2019;29(11). doi:10.1016/j.cub.2019.04.065 

Sunk Costs: From the Lab to Wall Street

Sunk Costs: From the Lab to Wall Street

By: Cordelia de la Fuente 

Understanding human behaviour is the essence of cognitive neuroscience. From psychological decision making to neuronal mechanisms, being able to predict and foresee how the brain will react to its given environment is the foundation of this field of study. In the research study “Sensitivity to ‘sunk costs’ in mice, rats and humans,” published by Dr. Brain Sweiss on the concept of ‘sunk costs,’ he and his team analyzed how organisms deal with decisions that cannot be revoked in present time. Sweis was able to break down the idea that organisms have the capacity to envision and construct different futuristic outcomes given the decisions they make in the present moment. 

The main results from this study concluded that the sensitivity that organisms have to temporal sunk costs, lies in a conceptual vulnerability to distinguish between deliberation and differentiation processes. Decision making based on deliberation means that the brain will actively compare and weigh the available options, whereas differentiation implies that the organism uses previous bias to conduct their next decision move, and will justify it afterwards. 

 Sweis' study arrived at the conclusion that rather than making new evaluations at each decision point, organisms will often lean into their prior investments to serve as a bias for their behavior moving forward, even when it is not rational to do so.

Despite the findings and focus point of the research being purely biological,  the science behind sunk costs is at the center of psychological applications of decision making. In another article published in the Wall Street Journal, “The Psychologist that Turned the Investing World on its Head,” featured how the work of Daniel Kahneman, who was awarded the Nobel prize for economics,  linked the neuroscience of decision making into the world of economics through sunk costs. The article goes into depth on how sunk costs in neuroscience is what originally led Kahneman to publish his theories on behavioral economics. This difference in application showcases how the sensitivity that humans have to sunk costs, is present in the way that we work and function in modern society. 

The article explains how Kahneman dedicated his career to the development of behavioral economics, conducting studies that prove how there is a sunk cost misconception that spreads throughout financial markets. Kahneman takes the objective understanding of Swies work and applies it to how investors consistently hold onto declining assets simply because of prior investments. He concludes that the emotional weight of sunk costs often overrides rational decision-making, constantly leading to millions of dollars in losses for finance professionals.

By understanding how brain decision making on the neural level works, scientists can take the biological findings and apply them in fields of human behaviour. In the Wall Street Journal example, there is a clear tie in how sunk costs contribute to the fluctuation of economic markets. Being able to apply and see the broader application of this neuroscience, shows there is a powerful truth that is being underscored: the sensitivity to sunk costs is critical not only for advancing neuroscience but for addressing real-world behaviors. As the scientific community continues to understand the neurological mechanisms that coordinate the way humans think and make decisions, the potential to apply this knowledge in tangible and transformative ways increases across society. 

Work Cited

Zweig, Jason. “The Psychologist Who Turned the Investing World on Its Head.” WSJ, 29 March 2024, https://www.wsj.com/finance/investing/daniel-kahneman-behavioral-economics-270c9797. Accessed 27 April 2025.

Sweis, Brian M., et al. “Sensitivity to ‘Sunk Costs’ in Mice, Rats, and Humans.” Science, vol. 361, no. 6398, 2018, pp. 178–181, https://doi.org/10.1126/science.aar8644.

 

Novel Breakthroughs in Early Detection of Autism Spectrum Disorder

        Approximately one in 36 children is diagnosed with autism spectrum disorder (ASD); however, most kids are diagnosed with ASD after the age of four, even though children can be diagnosed before the age of two (Loftus, 2024). Early intervention is crucial for better outcomes and for equipping families with the necessary tools and support. Only up until recently has the significance of early detection in research gained momentum, since previous decades of research have neglected this overlooked gap in pediatric care. 

A major barrier to early diagnosis for ASD is our current reliance on behavioral observation, since it may not capture early-emerging differences in infants (Guy, 2017). In their research, Maggie Guy focused on identifying neural correlates that may signal ASD risk earlier in development. Guy et al. investigated neural responses to social stimuli, specifically faces, in infants who are at an elevated risk for ASD (Guy, 2017). By measuring event-related potential (ERP) components, such as the N290, which reflects automatic recognition of faces, and Nc, which reflects attention allocation and stimulus salience, they provided insight into early perceptual and attentional mechanisms. The team looked at infants with fragile X-syndrome (FXS) and infant siblings of children with ASD (ASIB) since these groups have a high susceptibility to developing ASD (Guy, 2017). Their findings highlight that both groups have different neural processing of social stimuli, even though they are both at an elevated risk for developing ASD. This means that they must have different, unique developmental trajectories from what was previously thought. 

Other areas of research aiming to diagnose ASD earlier include the investigation of abnormal biological processes that are associated with ASD. Biomarkers are a great way to improve the diagnosis and treatment of ASD (Frye et al., 2019). In a systematic literature review conducted by Richard Frye et al., they pinpointed several distinct categories of biomarkers that are associated with the history of ASD. Examples of such biomarkers include, but are not limited to, behavioral, genetic, immune, metabolic, neuroimaging, and nutritional biomarkers (Frye et al., 2019). 

In a study conducted by Anna Esparham et al., their team dove into specific nutritional and metabolic biomarkers in ASD. For example, such metabolic biomarkers associated with ASD included an elevated copper to zinc ratio due to lower levels of zinc, and low levels of vitamin D (Esparham et al., 2015). Although copper is an important trace mineral for angiogenesis and neurotransmission, increased levels of it may be toxic to the nervous system and the liver. Regarding children with ASD, elevated levels of copper are found to induce oxidative damage to their phospholipid membranes. As for vitamin D, regular levels of this vitamin regulate tryptophan metabolism and control serotonin production. Children with ASD have altered levels of these due to having lower levels of vitamin D (Esparham et al., 2015). 

Further investigation of the biomarkers and neural correlates associated with ASD remains a pivotal area of research for enabling earlier detection of ASD. Although many questions still arise on ASD, these novel breakthroughs provide the primary steps towards getting there, which is promising and significant for future research. 

References

Data and Statistics on Autism Spectrum Disorder. (2025). 

Centers for Disease Control and Prevention. https://www.cdc.gov/autism/data-research/index. 

html.

Esparham, A. E., Smith, T., Belmont, J. M., Haden, M., Wagner, L. E., Evans, R. G., & Drisko, J. A. 

(2015). Nutritional and Metabolic Biomarkers in Autism Spectrum Disorders: An Exploratory 

Study. Integrative medicine (Encinitas, Calif.), 14(2), 40–53.

Frye, R. E., Vassall, S., Kaur, G., Lewis, C., Karim, M., & Rossignol, D. (2019). Emerging biomarkers in 

autism spectrum disorder: a systematic review. Annals of translational medicine, 7(23), 792. 

https://doi.org/10.21037/atm.2019.11.53

Guy, M. W., Richards, J. E., Tonnsen, B. L., & Roberts, J. E. (2018). Neural correlates of face processing 

in etiologically-distinct 12-month-old infants at high-risk of autism spectrum disorder. 

Developmental cognitive neuroscience, 29, 61–71. https://doi.org/10.1016/j.dcn.2017.03.002.

Integrating Structural Plasticity and Systems-Level Adaptation: Insights into Cortico-Basal Ganglia and Cerebellar Contributions to Motor Learning

 The article The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach (Baladron et al., 2023) presents a systems-level computational model that elucidates the complementary roles of the basal ganglia and cerebellum in motor learning. The authors propose that the cortico-basal ganglia loop facilitates the selection of motor actions based on a novelty-driven motor prediction error, while the cerebellum minimizes the remaining aiming error through fine-grained corrective adjustments. Using a robotic arm simulation, the model demonstrates successful learning of reaching movements and motor adaptation, emphasizing that different brain regions employ distinct learning algorithms—reinforcement learning in the basal ganglia and perturbation-based supervised learning in the cerebellum. This work supports integrative frameworks of motor learning, suggesting that the synergy between cortical, basal ganglia, and cerebellar systems enables both action selection and continuous performance refinement.

The computational framework proposed by Baladron et al. (2023) expands on several principles discussed in Cortico-basal ganglia plasticity in motor learning (Roth & Ding, 2024). Both articles highlight the fundamental role of the cortico-basal ganglia circuits in the acquisition and execution of motor skills. However, while Roth and Ding focus primarily on experimental evidence for synaptic and circuit-level plasticity within motor cortical and striatal pathways, Baladron et al. provide a functional computational perspective by incorporating cerebellar contributions to action refinement. Notably, Roth and Ding (2024) discuss plastic changes such as dendritic spine remodeling and the formation of stable spatiotemporal activity patterns in the motor cortex and striatum, but they do not model the interactive dynamics between these brain regions and the cerebellum during motor learning. The addition of cerebellar mechanisms in Baladron et al. (2023) provides critical insights into how online error correction complements the structural plasticity described by Roth and Ding.

In Cortico-basal ganglia plasticity in motor learning, Roth and Ding (2024) review advances in understanding how motor learning is supported by both functional and structural plasticity within the cortico-basal ganglia circuits. They emphasize that skilled motor behaviors are associated with the reorganization of activity patterns in cortical and striatal neurons, long-term synaptic potentiation, and dynamic changes in inhibitory interneuron activity. The review particularly underscores the importance of early plastic changes in superficial cortical layers (L2/3) and the gradual decorrelation of cortical activity patterns after extensive training, highlighting the evolving division of labor between cortical and subcortical systems over time. These findings establish a detailed biological basis for how motor memories are encoded and maintained.

Taken together, the two articles converge on the central role of the cortico-basal ganglia system in motor learning but differ in their emphasis. Roth and Ding (2024) provide rich experimental detail on the biological substrates of motor learning, focusing on the mechanisms of synaptic and circuit plasticity. In contrast, Baladron et al. (2023) present a computational model that extends this understanding by demonstrating how different learning signals—novelty-driven reinforcement for the basal ganglia and error-driven adjustment for the cerebellum—cooperate to optimize motor behavior. Together, these studies offer complementary perspectives, linking cellular and circuit-level adaptations with systems-level dynamics necessary for robust motor learning and adaptation.

 

Citations:

Baladron, J., Vitay, J., Fietzek, T., & Hamker, F. H. (2023). The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach. PLOS Computational Biology, 19(4), e1011024. https://doi.org/10.1371/journal.pcbi.1011024

Roth, R. H., & Ding, J. B. (2024). Cortico-basal ganglia plasticity in motor learning. Neuron, 112(15), 2486–2493. https://doi.org/10.1016/j.neuron.2024.06.014

Bridging Research and Policy: Insights from ERP Studies and the Autism CARES Act

         In the United States, autism spectrum disorder (ASD) affects one in 36 children, with a 175 percent increase in diagnoses between 2011 and 2022 alone (Feldman Law Group, 2025). Given this growing prevalence, ongoing research and services are critical to support individuals with ASD. Early intervention remains a key focus for understanding, diagnosing, and improving outcomes for those on the spectrum. A major source of funding for autism research comes from the Autism Collaboration, Accountability, Research, Education and Support Act (Autism CARES Act), which allocates billions of dollars in federal funding to support research, education, and training programs, with a significant emphasis on early detection and intervention strategies (Feldman Law Group, 2025). This past fall, lawmakers reauthorized the Act, and it was signed into law in early 2025, just before expiration. The updated legislation dedicates nearly $2 billion over five years to advancing research, education, and programs aimed at improving quality of life for individuals with autism (Feldman Law Group, 2025). The Autism CARES Act is essential for the autistic community, underscoring a national commitment to early intervention and investment in research. 

         One area of research that directly aligns with the goals of the Autism CARES Act is the work conducted by Dr. Maggie Guy from Loyola University Chicago, titled "Neural correlates of face processing among preschoolers with fragile X syndrome, autism spectrum disorder, autism siblings, and typical development." In collaboration with other researchers, Dr. Guy investigated patterns of face processing in children across a continuum of ASD symptom severity. The study utilized event related potentials (ERPs) to explore early biomarkers that could help distinguish between environmental and genetic factors influencing social communication impairments (Richards, Guy, Hogan, & Roberts, 2024). Since core features of ASD include deficits in social communication and interaction, as well as restricted and repetitive behaviors, the researchers focused on neural responses related to these areas. By identifying early differences in face processing, the study provides valuable insights into the origins of cognitive and social communication challenges (Richards, Guy, Hogan, & Roberts, 2024). Such research is crucial for informing earlier diagnoses and developing targeted early intervention programs.

         Dr. Maggie Guy’s research illustrates the practical applications of the Autism CARES Act’s funding priorities. Her use of event related potentials associated with face processing highlights the sustained and unique developmental pathways in individuals with autism, contributing to a better understanding of early brain functioning and improved methods for early testing in children. These findings help inform the development of early diagnostic tools and personalized interventions, directly aligning with the goals of the recently reauthorized Autism CARES Act.

References

Richards, J. E., Guy, M. W., Hogan, A. L., & Roberts, J. E. (2024). Neural correlates of face processing among preschoolers with fragile X syndrome, autism spectrum disorder, autism siblings, and typical development. Autism research: official journal of the International Society for Autism Research, 17(1), 89-108. https://doi.org/10/1002/aur.3045 

 

Feldman Law Group. For people with autism, New Law Signals Renewed Support. FeldmanLawGroup. March 18, 2025. Accessed April 25, 2025. https://www.feldmanlawgroup.com/blog/2025/april/for-people-with-autism-new-law-signals-renewed-s/

 

 

AI in Disease Detection

                    AI is Revolutionizing Disease Detection

Within the last couple of years, “Artificial Intelligence” has become a household name. It has evolved from a taboo concept to a central entity in modern medicine. The best kind of medicine is disease prevention, but humans are not equipped to predict the unreliability of the human anatomy and the disease/immune system. Therefore, lately, various intelligence models have been programmed and trained to identify complex medical patterns in imaging and test results that even the best physicians may miss. As demand for healthcare is through the roof and physicians are spread too thin, AI is becoming a critical partner in clinical decision-making. 

As a result, an auspicious development in the AI realm is the use of artificial neural networks (ANNs). ANNs are an adaptive type of intelligence modeled after the human brain. They are fascinating because they can process vast volumes of imaging data in minutes. Not only are they incredibly accurate in identifying early signs of cancer or respiratory abnormalities, but ANNs also offer speed and scalability.  However, when a new system gains popularity, physicians and patients become skeptical about how it can achieve its claimed accuracy and whether that accuracy is absolute. Is it true that the ANNs are “seeing” the imaging in the same way a radiologist would? 

A 2023 study by Alsharif et al., published in Bioengineering, addresses this question. The author and his partners review how ANNs played a role in diagnosing COVID-19 while noting an advancement called ConXNet. This particular program was designed to detect COVID-19 by simply processing chest X-rays. When tested, it was found that ConXNEt achieved 97.8% accuracy in its diagnosis. The author continued to explain what makes ConXNet stand out from its competitors. It was determined that its advantages lie in its thoughtful training process. The ConXNet program utilizes dropout layers, batch normalization, and convolutional blocks, which help reduce overfitting and improve generalization. Furthermore, another essential ConXNEt trait is its high success rate when tested with extensive image pools and more diverse scans. This means that ConXNEt applies to real-world situations.

Additionally, the pinnacle of this program's innovative genius lies in its ability to accurately interpret the visuals given to it. When a physician deciphers an image, they have to be able to locate even the most minor differences in texture, shape, or color- because this can mean the difference between health and life-threatening disease. However, how does this neural network see these slight differences and distinguish between healthy and diseased? This is where research in The Journal of Vision offers a valuable perspective. Researchers from Loyola University found that ANNs have difficulty visualizing images from unusual angles, relying instead on relations and 3D visual cues. This means that while ConXNet is incredibly impressive, it still can improve how it interprets depth, spatial orientation, and shape changes. 

As ConXNEt continues to break barriers and set the foundation for ANNs in medical imaging, it can still be improved. Recognizing diseases isn't just about detecting differences in color and texture but understanding what differences in shape could mean. AI needs to be able to see images the same way a physician would; one day, it may even surpass them in every way. 

References 

Azeem, M.; Javaid, S.; Khalil, R.A.; Fahim, H.; Althobaiti, T.; Alsharif, N.; Saeed, N. Neural Networks for the Detection of COVID-19 and Other Diseases: Prospects and Challenges. Bioengineering 2023, 10, 850. https://doi.org/10.3390/ bioengineering10070850

Cutler, M; Baumel, L; Tocco, J; Friebel, W; Thiruvathukal, G; Baker, N. Beyond the Contour: How 3D Cues Enhance Object Recogntion in Humans and Neural Networks: Journal of Vision (20??),?,1-?.file:///Users/yoliestarck/Downloads/Cutler%20&%20Baumel%202025%20(Pre-Publication)%20(3).pdf (not yet published). 

Is It Possible to Map Regret? The New Reality Connecting Functional Neuroscience with Structural Breakthroughs

 Is It Possible to Map Regret? The New Reality Connecting Functional Neuroscience with Structural Breakthroughs 

Back in 2022, Durand-de Cuttoli et al. released a research paper focused on the topic of regret specifically the stress altering decision-making in mice. The experiment was possible bypassing something positive or remaining in something adverse. However, that same new brain map of 2024 does give to us a high-def wiring diagram of precisely how brain regions like the mPFC are in its build. Put together, they are related to GPS in addition to Google Street View for the brain. We know the location of where behavior happens, and now we can zoom in on just how it is built. That’s the future for neuroscience, pairing behavior with structure for decoding of the mind. 

In the 2022 study by Durand-de Cuttoli et al., researchers explored into how different forms of regret in mice, either it be rejecting high-value offers or accepting low-value ones, are regulated with stress susceptibility and brain region–specific CREB function. Their work, published inside Science Advances, stressed such functional dimensions of such brain activity via the linking of behavioral patterns under certain stress alongside molecular and regional brain mechanisms, particularly within some medial prefrontal cortex (mPFC) and nucleus accumbens.

In the 2022 study by Durand-de Cuttoli et al., researchers explored whether stress susceptibility and brain region–specific CREB function are regulating different forms of regret in mice, such as rejecting high-value offers or even accepting low-value ones. They extensively published their thorough work in Science Advances. The work stressed functional dimensions of brain activity as it linked behavioral patterns under stress to molecular and regional brain mechanisms, mainly in the medial prefrontal cortex (mPFC) as well as nucleus accumbens.

The synergy of these two studies is quite powerful. Durand-de Cuttoli et al. teach to us the specific places and also just how behavioral regret emerges within decision-making circuits during stress. The Nature connectome study, conversely, reveals to us the precise anatomical layout of similar circuits, what connects to what, as well as how synaptic architecture supports or constrains function. They do represent a turning point together in neuroscience, and it is one where structure and function converge for decoding mental processes with precision. From a class standpoint, this intersection highlights how important it is to be a consumer of neuroscience, and not just in academic literature; it also indicates how emerging data shapes a real comprehension of behavior in the world. For instance, if CREB activity alters regret behaviors via the mPFC, the structural map could guide subsequent hypotheses about which pathways mediate those effects, or how stress might reorganize distinct inhibitory and excitatory networks.

As we move forward, the challenge is to connect these structural discoveries with behavioral meaning. If we had a full wiring diagram of the decision-making regions studied in the regret paper, what else might we decode? What could we learn? Could these understandings help us build new treatments for mood disorders where decision-making often goes away? These are mostly the types of integrative questions that may define for sure the next generation of neuroscience.

Work Cited

Devlin, Hannah. “US Scientists Create Most Comprehensive Circuit Diagram of Mammalian Brain.” The Guardian, Guardian News and Media, 9 Apr. 2025, https://www.theguardian.com/science/2025/apr/09/us-scientists-create-most-comprehensive-circuit-diagram-of-mammalian-brain

Durand-de Cuttoli, Romain, et al. “Distinct forms of regret linked to resilience versus susceptibility to stress are regulated by region-specific CREB function in mice.” Science Advances, vol. 8, no. 42, 21 Oct. 2022, https://doi.org/10.1126/sciadv.add5579.

Predicting Depression Relapse

Depression doesn’t always leave for good with mental health treatment. Unfortunately, for many adults, it quietly creeps back, even after sustained remission. Late-life Depression (LLD) is a relatively common illness for individuals 60 years of age and older, and is characterized by a plethora of symptoms with the capacity to affect nearly every facet of life. In addition to having a higher mortality rate, those with LLD are more susceptible to disability, medical illness comorbidity, suicidal ideation, impaired cognitive functioning, and dementia. These consequences can significantly reduce an individual's quality of life, impacting their relationship dynamics, ability to be independent, and physical health. Given the serious toll that LLD relapse can take on an individual’s well-being, it is incredibly important to study the factors that predict relapse so that more effective, preventative strategies can be implemented in clinical care settings. When clinicians can accurately identify early warning signs of relapse, they can quickly adjust treatment strategies before a full depressive episode sets in, whether that be by increasing the dosage of psychotropic medication, increasing the frequency of cognitive behavioral therapy sessions, or strengthening the patients’ social support circles. This way, mental health practitioners will be more apt to not just treat depression, but also predict and prevent its relapse. Recent research in this domain has offered valuable insight into both the internal risk factors and environmental stress factors that predict LLD relapse. 

One study looks predominantly at social, medical, and cognitive factors and their implications for depressive episode relapse in patients with LLD. Olusola Ajilore and colleagues recruited 135 participants with LLD and 69 control group comparison participants with no known mental health disorders. All participants were evaluated according to a variety of standardized tests to assess their psychiatric, social, neurological, and medical history. Participants were then longitudinally assessed for indicators of a depressive episode relapse recurrently over two years. Results showed that 44% of participants in the LLD group experienced a relapse while 56% showed sustained remission. For the individuals in the LLD relapse subgroup, their neuropsychological and behavioral test markers indicated that the main predictors of depressive relapse are higher and more severe levels of rumination, greater medical illness comorbidity, lower executive function performance, lower education level, poorer social support networks, and greater perceived life stress. Furthermore, this subgroup was differentiated from the sustained remission subgroup for their higher levels of self-reported apathy, lower levels of extraversion and conscientiousness, and more severe anxiety symptoms. It should be noted that the two strongest predictor factors of a future relapse were high levels of rumination and medical illness comorbidity. This makes sense given that the severity of self-reflective ruminative thought patterns is likely compounded by additional medical burdens that are unrelated to depression, but still affect any number of other neuropsychological processes and social dynamics. Understanding these predictive factors is critical in the development of personalized and targeted mental health interventions that address not just the depressive symptoms themselves, but also the underlying vulnerabilities that make some individuals more susceptible to relapse than others (Taylor et al., 2024).

A second study supports these findings while providing additional information specifically in regards to the relationship between an individual’s personality traits and their risk of depression relapse. Nada Altaweel and colleagues ran a systematic literature review to investigate which personality traits are associated with major depressive disorder (MDD) episode relapse. They included studies that both assessed MDD relapse using a clinical interview and included a standardized personality test, such as the Big 5 personality test. The personality traits evaluated in this model are extraversion,   openness, conscientiousness, agreeableness, and neuroticism. The results indicated that neuroticism, characterized by a tendency to experience negative emotions, such as anxiety, worry, and irritability, was most consistently associated with an increased risk of depression relapse. Furthermore, this study found that the presence of various other mental health disorders also significantly amplified the risk of future relapse after remission. These include borderline personality disorder (BPD) and obsessive-compulsive personality disorder (OCPD). This is because these personality disorders are often characterized by persistent emotional, interpersonal, and cognitive dysregulation that can cause difficulties in daily functioning and ultimately destabilize depression recovery. Lastly, this study found that those with high levels of self-criticism, dependency, impulsivity, and emotional dysregulation, as well as low levels of self-esteem and self-efficacy, were at a heightened risk of MDD relapse as well. Overall, this study investigated the internal personality-based characteristics that make someone more vulnerable to a depressive relapse, often through a heightened tendency to engage in maladaptive thought patterns and behaviors (Altaweel et al., 2023). In summary, both studies identify emotional dysregulation, rumination, and self-criticism, and the presence of comorbid disorders as central contributors to depression relapse. Patients who are in remission from either MDD or LLD and who show these risk factors should be more closely monitored by their mental health professionals so that a relapse can be prevented before it even occurs.

Works Cited: 

Altaweel, N., et al. (2023). Personality traits as risk factors for relapse or recurrence in major depression: A systematic review. Frontiers in Psychiatry, 14, Article 1176355. https://doi.org/10.3389/fpsyt.2023.1176355

Taylor W.D., et al (2024). Reconsidering remission in recurrent late-life depression: clinical presentation and phenotypic predictors of relapse following successful antidepressant treatment. Psychological Medicine 54, 4896–4907. https://doi.org/10.1017/S0033291724003246