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The brain evolved to produce behaviors that help an animal inhabit the natural world. During natural behaviors, the brain is engaged in many levels of activity from the detection of sensory inputs to decision-making to motor planning and execution. To date, most brain studies have focused on small numbers of neurons that interact in limited circuits. This allows analyzing individual computations or steps of neural processing. During behavior, however, brain activity must integrate multiple circuits in different brain regions. The activities of different brain regions are not isolated, but may be contingent on one another. Coordinated and concurrent activity within and across brain areas is organized by (1) sensory information from the environment, (2) the animal's internal behavioral state, and (3) recurrent networks of synaptic and non-synaptic connectivity. Whole-brain recording with cellular resolution provides a new opportunity to dissect the neural basis of behavior, but whole-brain activity is also mutually contingent on behavior itself. This is especially true for natural behaviors like navigation, mating, or hunting, which require dynamic interaction between the animal, its environment, and other animals. In such behaviors, the sensory experience of an unrestrained animal is actively shaped by its movements and decisions. Many of the signaling and feedback pathways that an animal uses to guide behavior only occur in freely moving animals. Recent technological advances have enabled whole-brain recording in small behaving animals including nematodes, flies, and zebrafish. These whole-brain experiments capture neural activity with cellular resolution spanning sensory, decision-making, and motor circuits, and thereby demand new theoretical approaches that integrate brain dynamics with behavioral dynamics. Here, we review the experimental and theoretical methods that are being employed to understand animal behavior and whole-brain activity, and the opportunities for physics to contribute to this emerging field of systems neuroscience.
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http://dx.doi.org/10.1038/s42254-022-00430-w | DOI Listing |
Nat Commun
September 2025
Institute of Neurosciences and Medicine, Brain & Behaviour (INM-7), Research Centre Juelich; Wilhelm-Johnen-Straße 1, Juelich, Germany.
Autism is a neurodevelopmental condition associated with altered resting-state brain function. An increased excitation-inhibition ratio is discussed as a pathomechanism but in-vivo evidence of disturbed neurotransmission underlying functional alterations remains scarce. We compare local resting-state brain activity and neurotransmitter co-localizations between autism (N = 405, N = 395) and neurotypical controls (N = 473, N = 474) in two independent cohorts and correlate them with excitation-inhibition changes induced by glutamatergic (ketamine) and GABAergic (midazolam) medication.
View Article and Find Full Text PDFBrain Behav
September 2025
Centre For Cognitive and Clinical Neuroscience, College of Health, Medicine and Life Sciences, Brunel University of London, London, UK.
Introduction: There is an ongoing debate about the neural mechanisms and subjective preferences involved in the processing of social rewards compared to non-social reward types.
Methods: Using whole-brain functional magnetic resonance imaging (fMRI), we examined brain activation patterns during the anticipation and consumption phases of monetary and social rewards (using the Monetary and Social Incentive Delay Task-MSIDT, featuring human avatars) and their associations with self-reported social reward preferences measured by the Social Reward Questionnaire (SRQ) in 20 healthy right-handed individuals.
Results: In the anticipation phase, all reward types activated the dorsal striatum, middle cingulo-insular (salience) network, inferior frontal gyrus (IFG), and supplementary motor areas.
Biol Psychiatry Cogn Neurosci Neuroimaging
September 2025
University of Illinois at Chicago, Department of Psychiatry. Electronic address:
Background: Late-life depression (LLD) is associated with negative outcomes including high rates of recurrence and cognitive decline. However, the neurobiological changes influencing such outcomes in LLD are not well understood. Disequilibrium in large-scale brain networks may contribute to LLD-related cognitive decline.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
Revealing the neural underpinnings of pain sensitivity is crucial for understanding how the brain encodes individual differences in pain and advancing personalized pain treatments. Here, six large and diverse functional magnetic resonance imaging (fMRI) datasets (total N = 1046) are leveraged to uncover the neural mechanisms of pain sensitivity. Replicable and generalizable correlations are found between nociceptive-evoked fMRI responses and pain sensitivity for laser heat, contact heat, and mechanical pains.
View Article and Find Full Text PDFbioRxiv
August 2025
Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile.
Whole-brain models are valuable tools for understanding brain dynamics in health and disease by enabling the testing of causal mechanisms and identification of therapeutic targets through dynamic simulations. Among these models, biophysically inspired neural mass models have been widely used to simulate electrophysiological recordings, such as MEG and EEG. However, traditional models face limitations, including susceptibility to hyperexcitation, which constrains their ability to capture the full richness of neural dynamics.
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