The transplanted cells formed circuits, reached the spinal cord and responded to injury.
Neuroscientists have long believed that language processing was only found in regions of the brain’s left hemisphere, including the well-known Broca’s area. However, new evidence suggests the brain’s language network is far more widespread than previously thought.
Researchers at the Massachusetts Institute of Technology (MIT) analyzed functional magnetic resonance imaging (fMRI) scans from 772 participants and identified 17 additional brain regions involved in language comprehension. These newly discovered areas are distributed across the brain, including the cerebellum, hippocampus, amygdala, and several regions of the cerebral cortex. In total, this accounts for five percent of the adult brain volume (roughly the size of a large strawberry).
“Even though there are all these distant components, it’s pretty restricted in terms of volume. You don’t need that much of the brain to do language,” says senior author Evelina Fedorenko, an MIT associate professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research, in a statement.
To find these hidden language-related regions in the brain, the researchers revisited years of brain imaging data collected since 2013. Additionally, participants completed a standard “language localizer” task, during which they read or listened to meaningful sentences and sequences of meaningless nonwords. By comparing brain activity between these two conditions, the research team identified regions that responded more strongly to language.
“When we initially started looking at language, in the first couple of papers, I tried to be comprehensive and include anything that seemed consistent across participants, and there was a huge amount of resistance,” said Fedorenko. “People would say things like, ‘Well, we know those are not language areas, so please focus on the language areas.’”
The team decided to adopt a more flexible statistical approach to detect weaker signals and identify previously overlooked language-sensitive regions beyond the classical language areas. They then compared these regions’ responses during a spatial working memory task to distinguish language-specific areas from those involved in what would be considered general cognitive functions.
Interestingly, five of the newly identified language regions are located in the cerebellum, a structure traditionally associated with movement and coordination. Some of these cerebellar regions were also active during non-language tasks, suggesting they may help integrate information across different brain systems rather than process language alone.
“It’s a very simple paradigm that lets you identify this core language system in individual brains,” says MIT postdoc Agata Wolna, the lead author of the paper.
Additional language-sensitive regions were identified in the hippocampus and amygdala, areas better known for their roles in memory and emotion. Their involvement suggests that understanding language may rely more on integrating memory, emotional context, and higher-order cognitive functions than previously understood in science.
“We always see this frontal temporal network, but there’s quite a lot of evidence that there are other regions that are also critical for language processing,” said Wolna. “By using a laxer threshold and zooming in on areas with weak MRI signal, we tried to maximize the chances of finding small and weakly responsive regions outside of this left frontal temporal system.”
The findings challenge long-held assumptions about the brain’s organization and can open new avenues for research into how language processing is understood in neuroscience.
The recent study was published in the Journal of Neuroscience.
Chrissy Newton is a PR professional and the founder of VOCAB Communications. She currently appears on The Discovery Channel and Max and hosts the Rebelliously Curious podcast, which can be found on YouTube and on all audio podcast streaming platforms. Follow her on X: @ChrissyNewton, Instagram: @BeingChrissyNewton, and chrissynewton.com. To contact Chrissy with a story, please email chrissy @ thedebrief.org.
While a patient is fully anesthetized and unresponsive, neurons in the hippocampus continue to process language, distinguish different types of words, and generate neural activity consistent with predicting upcoming words.
Researchers at Baylor College of Medicine directly recorded this neural activity, offering new insight into how unconsciousness works at the cellular level. Their findings, published in Nature, show that hippocampal neurons continue to process aspects of language even when the brain is unconscious.
“Our findings show that the brain is far more active and capable during unconsciousness than previously thought,” said Dr. Sameer Sheth, professor and Cullen Foundation Endowed Chair of neurosurgery and a McNair Scholar at Baylor. “Even when patients are fully anesthetized, their brains continue to analyze the world around them.”
Sheth’s team recorded from hundreds of individual neurons in the hippocampus, a region of the brain essential for memory formation. Researchers collected data during epilepsy surgeries, specifically anterior temporal lobectomies, when patients were under general anesthesia and the hippocampus was temporarily accessible. This rare opportunity allowed researchers to directly record hippocampal activity, something scalp EEG cannot.
The researchers used Neuropixels probes, high-density recording devices that can monitor hundreds of neurons simultaneously. This study represents the first use of this technology in the human hippocampus during anesthesia. Seven patients participated, all under propofol anesthesia with consistent sedation levels maintained throughout the recordings.
In the initial test, researchers played patients a repeating tone with occasional unexpected pitches. Hippocampal neurons consistently detected these outlier tones, and their sensitivity increased over approximately ten minutes. Researchers usually observe this kind of adaptive neural response during wakefulness.
To dig deeper, the researchers built a computer model of a recurrent neural network, trained to perform the same tone discrimination task. The model showed the same pattern as the human brain recordings, suggesting that this increased sensitivity to outlier tones can arise from local brain circuits alone, without the need for higher-level conscious processing.
The researchers also played short stories to anesthetized patients while recording from the same neurons. Hippocampal activity tracked language in real time, distinguishing between nouns, verbs, and adjectives. Neural activity reflected both the current word and prediction of the upcoming word in the sequence. “The brain appears to anticipate what comes next in a story, even without conscious awareness,” Sheth said.
“This kind of predictive coding is something we associate with being awake and attentive, yet it’s happening here in an unconscious state,” added Baylor neurosurgery professor Benjamin Hayden.
The results show that the hippocampus can support neural computations associated with complex cognition even during unconsciousness. This suggests that at least some components of language processing and prediction may not require conscious awareness. Sheth’s team proposes that consciousness does not arise from a single brain region but rather emerges from interactions among multiple brain regions. The hippocampus may process information that later becomes part of awareness.
The researchers noted a parallel with artificial intelligence. Large language models generate text by predicting the next word in a sequence; the anesthetized hippocampus showed a similar pattern of prediction. This similarity may provide neuroscientists and AI researchers with a shared framework for studying language prediction based on biological circuitry.
“Can we use these signals to deploy and run a speech prosthetic for some of the parts of the brain that are damaged by stroke or injury? These are questions that we can now consider in relation to this part of the brain,” said study author and Baylor neurosurgery resident Kalman Katlowitz.
While these results are promising, the team acknowledged the study’s limitations. The research focused only on propofol-based general anesthesia, so the results may not apply to other unconscious states such as natural sleep or coma. Additionally, the researchers examined only the hippocampus, so they cannot yet determine how broadly this type of unconscious processing occurs in other brain regions.
“This work pushes us to rethink what it means to be conscious,” Sheth concluded. “The brain is doing much more behind the scenes than we fully understand.”
Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds an MBA, a Bachelor of Science in Business Administration, and a data analytics certification. His work focuses on breaking scientific developments, with an emphasis on emerging biology, cognitive neuroscience, and archaeological discoveries.
In a groundbreaking study soon to redefine neuroscientific understanding of memory mechanisms, researchers have uncovered the pivotal role played by Neurensin-2 (NRSN2) in regulating hippocampal synaptic plasticity and memory functionality. This newly published research reveals how deficiency in NRSN2 leads to profound impairments in memory, traced back to disrupted excitatory synaptic transmission and weakened long-term potentiation (LTP) within the hippocampus, a brain region critically involved in memory formation and cognitive processing.
The hippocampus serves as the brain’s memory hub, integrating myriad neuronal signals to encode and retrieve information efficiently. Central to this integration is the function of excitatory synapses that employ glutamate receptors, especially the N-methyl-D-aspartate (NMDA) receptor, which plays an essential role in synaptic plasticity—the ability of synapses to strengthen or weaken over time. This plasticity underlies learning and memory. The study elucidates how NRSN2 exerts a regulatory influence on the expression of NMDA receptor subunits, with deficiency in NRSN2 tipping the balance unfavorably and compromising synaptic efficacy.
Utilizing advanced genetic models, the investigators engineered mice lacking NRSN2 to dissect its functional contributions. Behavioral assays showcased a marked decline in memory performance, particularly in spatial and recognition tasks reliant on hippocampal circuits. These deficits were not attributed to developmental anomalies but to disrupted synaptic physiology, signaling a direct role for NRSN2 in maintaining synaptic integrity and plasticity during adult cognition.
At the molecular scale, the absence of NRSN2 triggered a significant downregulation of key NMDA receptor subunits, notably NR1, NR2A, and NR2B. These subunits orchestrate receptor assembly and gating properties critical for calcium influx, a signal cascade necessary for potentiation of synaptic strength. The reduction in their expression correlated tightly with the inhibition of LTP induction, a process considered the cellular analog of memory encoding, confirming the hypothesis that NRSN2 deficiency impairs memory by hampering core synaptic mechanisms.
Electrophysiological recordings from hippocampal slices further substantiated the disrupted synaptic function. In control animals, robust LTP was readily induced by theta burst stimulation—a protocol mimicking physiological neuronal firing during learning. Conversely, hippocampi from NRSN2-deficient mice exhibited significantly weakened potentiation, underscoring the protein’s critical role in modulating synaptic responsiveness. This impairment was not a general defect of synaptic transmission but selectively impacted excitatory plasticity mediated through NMDA receptors.
Delving deeper, the team explored the intracellular cascades influenced by NRSN2, discovering that its absence perturbed the trafficking and surface expression of NMDA receptor complexes. NRSN2 appears to act as a chaperone or scaffold protein, ensuring proper receptor assembly and synaptic localization. Without it, receptor subunits fail to achieve adequate membrane insertion, resulting in diminished postsynaptic sensitivity to glutamate and compromised signal transduction.
This mechanistic insight offers a fresh perspective on how synaptic architecture and molecular composition govern cognition. The study’s integration of molecular biology, electrophysiology, and behavioral neuroscience draws a comprehensive picture of how a single protein’s deficit can destabilize the neural substrates of memory. Such findings not only enrich fundamental neuroscience but also hint at novel targets for cognitive-enhancing therapies.
Intriguingly, alterations in NRSN2 expression and NMDA receptor dysfunction have been implicated in various neuropsychiatric disorders, including schizophrenia and major depressive disorder. By illuminating this molecular nexus within the hippocampus, the research opens doors to understanding disease pathophysiology at a finer scale and may spur development of precision interventions aimed at restoring synaptic balance in affected individuals.
The investigators also examined compensatory mechanisms that might mitigate NRSN2 absence. While some plasticity-related proteins showed upregulation, these changes failed to rescue the deficits in NMDA receptor expression and synaptic potentiation. This highlights the non-redundant and indispensable nature of NRSN2 in maintaining synaptic homeostasis and cognitive function.
Beyond the laboratory findings, the study raises fascinating questions about how synaptic proteins coordinate to sustain the dynamic range of neural connectivity required for adaptive learning. The delicate equilibrium modulated by NRSN2 and NMDA receptors underscores the complexity of neuronal networks and their vulnerability when key molecular elements are compromised—insights that are pivotal as the field seeks to decode the neural basis of memory disorders.
Future research directions spawned by this work include investigating how NRSN2 interacts with other synaptic scaffold proteins and cytoskeletal elements, potentially shaping the three-dimensional organization of the postsynaptic density. Additionally, exploring the developmental timeline of NRSN2 expression could reveal critical periods during which intervention might prevent or reverse memory impairments.
From a translational perspective, the study’s revelations beckon the clinical neuroscience community to consider NRSN2 and its pathways as therapeutic candidates. Pharmacological strategies aimed at upregulating NRSN2 or mimicking its stabilizing effects on NMDA receptors could hold promise for enhancing cognition or slowing neurodegenerative progression in disorders marked by synaptic decline.
In sum, this landmark research defines NRSN2 as a vital regulator of excitatory synaptic plasticity and memory formation. Its deficiency causes a cascade of molecular disturbances culminating in impaired NMDA receptor expression and disrupted LTP, ultimately compromising hippocampal-dependent memory functions. This work not only advances our understanding of the molecular machinery underlying memory but also charts new territory in the quest to ameliorate cognitive dysfunction.
As neuroscience inches closer to mapping the intricate cellular and molecular landscape of cognition, findings such as these underscore the profound impact a single synaptic protein can have on brain function. The compelling evidence presented lays a robust foundation for future explorations into synaptic plasticity and memory, promising strides in both basic science and clinical applications that may soon transform lives burdened by memory loss.
Subject of Research: Impact of Neurensin-2 (NRSN2) deficiency on hippocampal memory functions and synaptic plasticity
Article Title: Impact of NRSN2 deficiency on memory: Altered excitatory synaptic plasticity associated with reduced expression of NMDA receptor subunits and impaired LTP in the hippocampus.
Article References:
Wei, J., Wu, Y., Yi, Y. et al. Impact of NRSN2 deficiency on memory: Altered excitatory synaptic plasticity associated with reduced expression of NMDA receptor subunits and impaired LTP in the hippocampus. Transl Psychiatry (2026). https://doi.org/10.1038/s41398-026-04163-7
Image Credits: AI Generated
Scientists have often wondered how the brain can take in new experiences without erasing stored memories. However, a new study in Nature now identifies a circuit-level mechanism that may help answer this question—and it may also offer clues for improving artificial intelligence.
Researchers at NYU Langone Health recorded the activity of hundreds of neurons simultaneously across several brain regions in mice. By tracking how signals move from the hippocampus to the neocortex, where long-term memories are kept, they found that a subset of hippocampal neurons appears to participate in routing information between regions in distinct patterns. These cells participate in both incoming and outgoing signaling, but do so using distinct patterns of activity.
The study focused on a series of interconnected brain regions: CA3, which processes rapidly changing information; CA1, which serves as a central hub; and the retrosplenial cortex, which is important for navigation and spatial memory. About one in four CA1 neurons receives most of the signals from CA3. When these same neurons send signals to the retrosplenial cortex, they fire in a different pattern, creating a separate outgoing channel using the same cells.
Rather than using new neurons, the brain separates these channels by changing how the same neurons fire together. The researchers suggest this arrangement may help reduce interference between new learning and more stable cortical memories.
“Our findings help explain how memory can be both moldable and enduring,” said co-lead author Joaquín Gonzalez, PhD, a postdoctoral fellow in the Department of Psychiatry at NYU Grossman School of Medicine. “By changing how the same cells fire together instead of turning on new cells, the brain can keep information organized and protect older memories.”
The CA1 neurons involved in learning during the day also stay active at night. The researchers found that these cells remain busy during sleep events called sharp-wave ripples, which are bursts of activity the hippocampus uses to replay and strengthen memories from the day.
Since overlapping neurons are recruited during both waking activity and sleep replay, the same circuit elements appear to participate in both learning and consolidation. This theoretically allows the brain to use a single system for both learning and storing memories, without the two processes interfering with each other.
“Our study shows how learning and memory consolidation can coexist in the same network,” said co-lead author Mihály Vöröslakos, MD, PhD. “Our discovery was made possible because for the first time, we were able to record hundreds of individual neurons across all the key regions simultaneously in animals that were moving around naturally.”
The system identified in this research may help explain how memory disorders begin. In Alzheimer’s disease, for example, the hippocampal circuits examined here are some of the earliest to deteriorate. These networks are essential for sorting and organizing new experiences.
“Our discovery of a ‘memory switchboard’ deep in the hippocampus may provide clues as to how memory circuits fail in Alzheimer’s disease,” said co-senior author Zhe S. Chen, PhD, a professor in the Departments of Psychiatry and Neuroscience at NYU Grossman School of Medicine.
Artificial intelligence systems have a hard time holding onto what they’ve already learned when faced with new tasks, a problem researchers call catastrophic forgetting. The human brain appears able to update memories without catastrophic forgetting by altering the use of existing neural circuits. By studying how our brains pull this off, scientists hope to design AI that can keep learning new things without forgetting the old.
“By showing how the mammalian brain can safeguard memories during learning, our research may offer a biological blueprint for designing next-generation AI technology that can update itself continuously without overwriting what it has already acquired,” said co-senior author György Buzsáki, MD, PhD, the Biggs Professor of Neuroscience at NYU Grossman School of Medicine.
The researchers plan to investigate whether similar switchboard-like channels exist in other memory circuits. The authors caution that their findings in mice under controlled conditions do not yet allow conclusions about the human brain.
Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds an MBA, a Bachelor of Science in Business Administration, and a data analytics certification. His work focuses on breaking scientific developments, with an emphasis on emerging biology, cognitive neuroscience, and archaeological discoveries.
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