
Karl Deisseroth
· D. H. Chen Professor, Professor of Bioengineering and of Psychiatry and Behavioral SciencesVerifiedStanford University · Bioengineering
Active 1990–2026
About
Karl Deisseroth is the D. H. Chen Professor, Professor of Bioengineering, and of Psychiatry and Behavioral Sciences at Stanford University. His research focuses on bioengineering and behavioral sciences, contributing to the understanding and development of innovative techniques in these fields. As a prominent figure in his discipline, he has made significant contributions to the intersection of bioengineering and mental health, advancing both scientific knowledge and practical applications in these areas.
Research topics
- Neuroscience
- Biology
- Computer Science
- Artificial Intelligence
- Psychology
- Cell biology
- Chemistry
- Medicine
- Materials science
- Biochemistry
- Nanotechnology
- Genetics
- Computational biology
- Control engineering
- Internal medicine
- Engineering
- Cognitive science
- Endocrinology
- Evolutionary biology
- Electrical engineering
- Business
Selected publications
Three-photon holographic microscopy for deep precise optogenetics
Research Square · 2026-04-23
preprintOpen accessResearch Square · 2026-04-26
preprintOpen accessSenior authorRaster photostimulation of large-scale neural populations
bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-24
articleOpen accessAbstract Neural computations are implemented by distributed neural populations that often span multiple brain areas. Causal photo-activation experiments done simultaneously with neural recordings can greatly improve our understanding of these computations, but such methods are typically limited to small subsets of neurons in restricted fields of view. Here we describe a new system called raster photostimulation for photo-activating and recording thousands of neurons, over a short 300 ms time window and over a large 5 mm field-of-view on a two-photon mesoscope. The photo-activation is precisely matched to the neural recording configuration, as it uses the same optical path, although with a different laser that is independently gated. We demonstrate pixel-level precision, frame-by-frame mask updating, and single-frame photostimulation of thousands of neurons. While this method lacks the precise temporal control of alternative methods, it compensates with ease-of-use, spatial precision, cost of implementation and by pushing the limits on the number of near-simultaneously stimulated neurons.
Conserved brain-wide emergence of emotional response from sensory experience in humans and mice
Science · 2025-05-29 · 18 citations
articleOpen accessSenior authorCorrespondingEmotional responses to sensory experience are central to the human condition in health and disease. We hypothesized that principles governing the emergence of emotion from sensation might be discoverable through their conservation across the mammalian lineage. We therefore designed a cross-species neural activity screen, applicable to humans and mice, combining precise affective behavioral measurements, clinical medication administration, and brain-wide intracranial electrophysiology. This screen revealed conserved biphasic dynamics in which emotionally salient sensory signals are swiftly broadcast throughout the brain and followed by a characteristic persistent activity pattern. Medication-based interventions that selectively blocked persistent dynamics while preserving fast broadcast selectively inhibited emotional responses in humans and mice. Mammalian emotion appears to emerge as a specifically distributed neural context, driven by persistent dynamics and shaped by a global intrinsic timescale.
Serotonergic neuron-glioma interactions drive high-grade glioma pathophysiology
bioRxiv (Cold Spring Harbor Laboratory) · 2025-12-12 · 2 citations
preprintOpen accessAbstract High-grade gliomas are lethal brain cancers that are powerfully regulated by glutamatergic neurons through activity-dependent paracrine factors and functional neuron-to-glioma synapses. Here, we report that serotonergic neurons promote the proliferation of high-grade gliomas throughout the brain. Serotonergic neuronal activity drives circuit-specific increases in high-grade glioma proliferation, calcium transients, and reduced survival. This growth-promoting effect is chiefly mediated by activation of the serotonin (5-hydroxytryptamine; 5HT) receptor 5HT 2A on glioma cells. Knock out or pharmacological blockade of 5HT 2A receptors in glioma abrogated the glioma growth-promoting effects of serotonergic neuronal activity, while serotonergic psychedelic drugs robustly promote malignant cell proliferation. Gliomas alter serotonergic neuronal activity patterns, resulting in elevated serotonin release into the tumor microenvironment. Together, these findings uncover pathogenic, feed-forward interactions between serotonergic neurons and glioma cells.
Selective Vulnerability of Dopamine-Glutamate Neurons in Aging Weakens Entorhinal Dopamine Signaling
bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-07
preprintOpen accessThe lateral entorhinal cortex (LEC) is selectively vulnerable to age-related decline and is essential for novelty detection and episodic memory. While DAergic (DAergic) input is known to modulate LEC function, how aging impacts this circuitry remains unclear. Here, we used two viral labeling strategies to investigate projections from the ventral tegmental area (VTA) to the LEC. First, we employed an INTRSECT dual-recombinase approach in TH-Flp::VGLUT2-Cre mice to selectively label dopamine-only (DA-only) and dopamine-glutamate co-releasing (DA-GLU) neurons. Next, we used a DAT-Cre-driven ChR2-YFP strategy to broadly label all DA axons. We found that both DA-only and DA-GLU populations innervate the LEC. With age, we observed a selective reduction in tyrosine hydroxylase (TH) signal within DA axons in the LEC, despite preserved axonal structure as revealed by YFP labeling. VGLUT2 signal within DA-GLU terminals appeared less affected. In the VTA, TH+ neuron density declined with age, with distinct spatial patterns along the anterior-posterior axis. These findings reveal an age-related vulnerability of DAergic projections to the LEC and suggest a circuit-level mechanism may contribute to memory impairments in aging.
Mapping the cellular etiology of schizophrenia and complex brain phenotypes
Nature Neuroscience · 2025-01-20 · 43 citations
articleOpen accessPsychiatric disorders are multifactorial and effective treatments are lacking. Probable contributing factors to the challenges in therapeutic development include the complexity of the human brain and the high polygenicity of psychiatric disorders. Combining well-powered genome-wide and brain-wide genetics and transcriptomics analyses can deepen our understanding of the etiology of psychiatric disorders. Here, we leverage two landmark resources to infer the cell types involved in the etiology of schizophrenia, other psychiatric disorders and informative comparison of brain phenotypes. We found both cortical and subcortical neuronal associations for schizophrenia, bipolar disorder and depression. These cell types included somatostatin interneurons, excitatory neurons from the retrosplenial cortex and eccentric medium spiny-like neurons from the amygdala. In contrast we found T cell and B cell associations with multiple sclerosis and microglial associations with Alzheimer's disease. We provide a framework for a cell-type-based classification system that can lead to drug repurposing or development opportunities and personalized treatments. This work formalizes a data-driven, cellular and molecular model of complex brain disorders.
33. Ketamine Increases Theta Oscillations and Cortical Connectivity of the Human Hippocampus
Biological Psychiatry · 2025-04-09
articleSenior authorExperience-Dependent Plasticity of Thalamoprefrontal Circuitry Characterizes Learning Across Species
bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-25
preprintOpen accessAbstract Learning is an adaptive process which is thought to require precise coordination among multiple brain regions over time. Thalamoprefrontal circuitry is central to multiple domains of cognitive control and executive function, yet its evolution during learning is not characterized. In this study, we explored thalamoprefrontal circuit signaling in mice and connectivity dynamics in humans over the course of learning a homologous psychomotor task. In mice, we targeted a genetically encoded Ca 2+ indicator to the mediodorsal-prefrontal (MdT-dmPFC) projection and used fiber photometry to record synaptic dorsomedial PFC (dmPFC) activity. As learning sessions progressed, all mice demonstrated a decrease in reaction time (RT) performance on successful trials (p<0.001). In concomitant synaptic MdT-dmPFC circuit activity across sessions, we observed a significant increase in activity during the anticipatory (p<0.01) and reward retrieval (p<0.01) periods, and a non-significant trend towards an increase in preparatory activity (p<0.15). However, following the learning period, during task re-exposure, we observed a significant shift in circuit activity, away from anticipatory (p<0.001) and towards the preparatory period (p<0.001) over the course of re-exposure sessions. Furthermore, we observed an emergence of a learner (decrease in RT) and a non-learner group (increase in RT) during the task re-exposure period. Over the course of a single analogous task session in humans, we also observed a learner and a non-learner group. When analyzing the thalamoprefrontal regional connectivity dynamics of early and late trials for learners, we observed a significant increase in low frequency and decrease in high frequency synchrony (connectivity tilt) in thalamoprefrontal pathways during preparatory and anticipatory periods. Interestingly, pairwise interactions specifically between the anterior corona radiata (ACR) and superior frontal gyrus (SFG), the human homolog to the genetically targeted MdT-dmPFC circuitry in mice, in fact demonstrated a robustly opposite connectivity tilt effect distinguishing learners from non-learners (Cohens d > 2). Overall, these findings may provide cross-species evidence of novel, conserved thalamoprefrontal circuit mechanisms of adaptive learning.
Negative Affect Circuit Subtypes and Neural, Behavioral, and Affective Responses to MDMA
JAMA Network Open · 2025-04-30 · 8 citations
articleOpen accessImportance: Rapidly acting therapeutics like 3,4-methylenedioxymethamphetamine (MDMA) are promising treatments for disorders such as posttraumatic stress disorder (PTSD). However, understanding who benefits most and the underlying neural mechanisms remains a critical gap. Stratifying individuals by neural circuit profiles could help differentiate neural, behavioral, and affective responses to MDMA, enabling personalized treatment strategies. Objective: To investigate whether baseline stratification of individuals based on negative affect circuit profiles, particularly in response to nonconscious threat stimuli, can differentiate acute responses to MDMA. Design, Setting, and Participants: This randomized clinical trial, implementing a double-blinded, within-participant, placebo- and baseline-controlled design, was conducted at Stanford University School of Medicine between November 2, 2021, and November 9, 2022, for wave 1 data collection. Participants had used MDMA on at least 2 prior occasions, but not in the past 6 months, and had subthreshold PTSD symptoms and early life trauma but no current psychiatric disorders. Data were analyzed from March 1, 2023, to January 1, 2024. Interventions: Participants completed 4 visits: 1 baseline session followed by 1 placebo session and 2 MDMA sessions in a randomized order, totaling 64 visits. Baseline functional magnetic resonance imaging (fMRI) assessed the negative affect circuit using a nonconscious threat processing task (NTN). Main Outcomes and Measures: Primary outcomes included activity and connectivity of amygdala and subgenual anterior cingulate cortex (sgACC) defining the negative affect circuit. Secondary outcomes were behavioral measures of implicit threat bias, likability of threat expressions, and affective assessments. Results: Sixteen participants (10 [63%] female; mean [SD] age, 40.8 [7.6] years) were stratified into subgroups with high and low levels of NTN activity in the amygdala (NTNA+ [n = 8] and NTNA- [n = 8], respectively), based on a median split of baseline nonconscious threat-evoked fMRI responses. Following administration of the 120 mg of MDMA vs placebo, the NTNA+ subgroup showed significant reductions in amygdala (contrast estimate [CE], -1.43; 95% CI, -2.60 to -0.27; Cohen d, -1.22; P = .02) and sgACC activity (CE, -1.48; 95% CI, -2.42 to -0.54; Cohen d, -1.56; P = .004), increased sgACC-amygdala connectivity (CE, 0.65; 95% CI, 0.02-1.28; Cohen d, 1.02; P = .04), and increased likability of threat expressions (CE, 14.38; 95% CI, 1.46-27.29; Cohen d, 0.86; P = .03) compared with the NTNA- subgroup. Conclusions and Relevance: In this randomized clinical trial of MDMA's acute profiles, 120 mg of MDMA acutely normalized negative affect circuit reactivity in participants stratified by heightened amygdala reactivity at baseline, demonstrating the potential of neuroimaging to identify prospective biomarkers and guide personalized MDMA-based therapies. Trial Registration: ClinicalTrials.gov Identifier: NCT04060108.
Recent grants
Single-cell causality in origination, propagation, and resolution of drug-altered brain states
NIH · $45.2M · 2017–2028
NIH · $2.6M · 2012
Channel structure-based tools for precise interrogation of circuitry and behavior
NIH · $7.3M · 2018–2023
NIH · $23.0M · 2018
NeuroNex Technology Hub: Integrated Circuit Cracking (ICC) with Linked Tools for Diverse Systems
NSF · $9.2M · 2017–2022
Frequent coauthors
- 272 shared
Charu Ramakrishnan
Stanford University
- 136 shared
Lief E. Fenno
The University of Texas at Austin
- 81 shared
Thomas J. Davidson
Howard Hughes Medical Institute
- 75 shared
Kay M. Tye
University of California, San Diego
- 71 shared
Clay Reid
- 67 shared
Talia N. Lerner
Research Network (United States)
- 66 shared
M. L. Roukes
California Institute of Technology
- 66 shared
Lisa A. Gunaydin
University of California, San Francisco
Labs
1-2 sentence research focus
Education
- 1995
B.S., Electrical Engineering and Computer Science
Massachusetts Institute of Technology (MIT)
- 1997
M.S., Bioengineering
Stanford University
- 2000
Ph.D., Bioengineering
Stanford University
Awards & honors
- Investigator of the Howard Hughes Medical Institute
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