Overview of neuroscience research topics

Neuroscience examines nervous system function across a continuum spanning molecules, cells, circuits, systems, and behavior. Core concepts center on defining cell diversity, mapping synaptic connectivity across scales, recording dynamic neural activity, and establishing causal links between neural circuits and behavior. Current research domains prioritize advanced neurotechnologies, computational theory, artificial intelligence, translational circuit therapeutics, and neuroethics.

Multiscale Nervous System Organization

Neuroscience research addresses a continuum of biological organization that spans molecules, cells, circuits, systems, and behavior in order to achieve a comprehensive understanding of the brain in action ^[1]. Recent strategic priorities emphasize developing and using new tools and neurotechnologies to study, understand, and ultimately learn how to control nervous-system function at the level of circuits ^[2]. Truly understanding a circuit requires identifying and characterizing the component cells, defining their synaptic connections with one another, observing their dynamic patterns of activity as the circuit functions in vivo during behavior, and perturbing these patterns to test their significance ^[3]. In addition, circuit analysis requires understanding the algorithms that govern information processing within a circuit and between interacting circuits in the brain as a whole ^[4]. Symposia and research priorities also examine biological processes extending from cells to behavior ^[5].

Cellular Diversity and Multiscale Circuit Mapping

A high priority within neuroscience is to identify and provide experimental access to different brain cell types to determine their roles in health and disease ^[6]. Researchers envision an integrated, systematic census of neuronal and glial cell types, alongside new genetic and non-genetic tools to deliver genes, proteins, and chemicals to cells of interest in non-human animals and in humans ^[7]. Structural research aims to generate circuit diagrams that vary in resolution from synapses to the whole brain ^[8]. Investigating connectivity across scales serves as a designated conference and research topic ^[9]. Scientists envision improved, scalable, faster, and less expensive technologies for anatomic reconstruction of neural circuits at all scales, from non-invasive whole human brain imaging to dense reconstruction of synaptic inputs and outputs at the subcellular level ^[10].

Dynamic Activity Monitoring and Causal Manipulation

Capturing the brain in action involves recording dynamic neuronal activity from complete neural networks, over long periods, in all areas of the brain ^[11]. Opportunities exist for improving existing technologies and developing new recording methods based on electrodes, optics, molecular genetics, and nanoscience to encompass different facets of brain activity ^[12]. By directly activating and inhibiting populations of neurons, neuroscience progresses from observation to causation ^[13]. To enable circuit manipulation, a new generation of tools for optogenetics, chemogenetics, and biochemical and electromagnetic modulation is sought for use in animals and eventually in human patients ^[14].

Theory, Data Science, and NeuroAI

Rigorous theory, modeling, and statistics advance the understanding of complex, nonlinear brain functions where human intuition fails ^[15]. Because vast quantities of data are generated, research areas also prioritize secondary analysis and data re-use ^[16], alongside infrastructure such as the BRAIN Knowledgebase ^[17]. Progress in theory and data analysis requires fostering collaborations between experimentalists and scientists from statistics, physics, mathematics, engineering, and computer science ^[18]. Innovation domains encompass BRAIN NeuroAI ^[19], complemented by programs that support pre- and post-doctoral training in biomedical informatics, data science, and artificial intelligence/machine learning (AI/ML) ^[20]. This foundation gives trainees the ability to adopt new computational theory and methodology and apply these methods to relevant questions in health and disease ^[21].

Translational Neuroscience and Neuroethics

Consenting humans who undergo diagnostic brain monitoring or receive neurotechnology for clinical applications provide an extraordinary opportunity for scientific research ^[22]. This setting enables research on human brain function, the mechanisms of human brain disorders, the effect of therapy, and the value of diagnostics ^[23]. Specific innovation domains emphasize accelerating human neuroscience ^[24] and precision molecular circuit therapies ^[25]. Academic training initiatives also develop and implement short courses on neurotherapeutics development for academic neuroscientists ^[26]. Because these scientific investigations study and control circuit function, results may change understanding of the brain, how it works, and its relationship to concepts including consciousness, agency, and human nature ^[27]. In projects involving research with humans or nonhuman primates, neuroethics expertise and principles are considered throughout the entire life cycle of a neuroscience research project ^[28]. Collaboration with neuroethicists facilitates ethical neuroscience and provides opportunities to create high-impact work that considers broader societal implications ^[29].

Key facts

• Understanding the brain in action encompasses molecules, cells, circuits, systems, and behavior ^[1].
• Circuit comprehension requires identifying component cells, defining synaptic connections, recording in vivo dynamic activity during behavior, and perturbing activity patterns to test significance ^[3].
• Circuit analysis also requires understanding algorithms governing information processing within and between circuits ^[4].
• Cell diversity goals focus on generating a systematic census of neuronal and glial cell types and developing molecular delivery tools ^[7].
• Circuit mapping involves anatomic reconstructions spanning subcellular synaptic inputs and outputs up to non-invasive whole human brain imaging ^[10].
• Monitoring complete neural networks over long durations utilizes electrodes, optics, molecular genetics, and nanoscience ^[11][12].
• Demonstrating causality relies on activating and inhibiting neuron populations via optogenetics, chemogenetics, and biochemical and electromagnetic modulation ^[13][14].
• Theoretical and computational areas utilize modeling, statistics, data re-use, and artificial intelligence frameworks such as BRAIN NeuroAI ^[15][16][19].
• Clinical neuroscience settings with consenting patients facilitate research into human brain function, disorder mechanisms, diagnostic value, and therapies ^[22][23].
• Neuroethics integration addresses broader societal implications and concepts such as consciousness, agency, and human nature throughout research life cycles ^[27][28][29].