Neurophysiological regulation and learning | Dipartimento di Psicologia e Scienze Congnitive

Andrea Caria

Overview

Human behavior and cognition results from dynamic changes of brain patterns. Even the simplest behavioral responses are created through the integrative activity of large networks in cortical and subcortical brain systems. Increasing and decreasing of neuronal connections are the necessary ingredients of dynamic changes of brain patterns and behavior.

These dynamic interactions follow the rules of associative learning (Hebb, 1949) where learned associations between stimuli induces changes in neuronal circuits. Learning in small-world networks such as the brain depends on the contingent (time synchronous) strengthening of synaptic connections. Creation of new skills and cognitive interactions needs creation and strengthening as well as interruption and weakening of neuronal connections. At the same time, many brain disorders result from disturbances of these dynamic connectivity patterns.

The principal objective of this research area is understanding the mechanisms underlying associative learning and neurophysiological regulation, as well as manipulation of network connectivity using both non-invasive (fMRI, EEG, TMS) and invasive techniques (implanted devices) to induce brain plasticity.

Research directions

Neural correlates of associative learning

Associative is a type of learning where a specific behavior is shaped as a result of the occurrence of events made contingent on the behavior. An existing behavior can be modified or a new behavior can be initiated when a new association between stimulus and response is manipulated either via classical or instrumental conditioning. Voluntary learning takes place by reinforcing, with positive or negative reward, the desired behavior and thus by establishing a causal relationship between reaction and reinforcer. During instrumental conditioning a new association between actions and selected goals is formed throughout a trial and error procedure that minimizes the discrepancy between the expected and the actual outcome (Pearce and Hall, 1980; Rescorla, 1984).

Using combined techniques like fMRI, EEG and TMS the neuronal mechanisms underlying associative learning are explored.

Self-regulation of localized brain activity using real-time fMRI

In the last decade, several instrumental learning studies based on real-time fMRI demonstrated that blood oxygen level dependent (BOLD) response feedback allows healthy individuals and patients to learn to control localized brain activity; moreover, learned control of fMRI signal induced changes in behavior. By providing real-time fMRI feedback to a human participant, learned regulation of the BOLD signal in few training sessions has been demonstrated in several brain areas involved in sensorimotor, cognitive and emotional processing.

In real-time fMRI feedback experiments individuals are trained through a certain number of sessions, consisting for instance of regulation blocks alternated to rest, to enhance or reduce the BOLD response in selected target regions. Participants can monitor the ongoing level of BOLD signal in the target region by visual feedback and they are usually provided with some general instructions on how to potentially achieve successful regulation, however they are often encouraged to explore their own strategies.

This approach enables the investigation of structure-function and brain-behavior relationships. It thus represents an inspiring alternative methodology in cognitive neuroscience that complements traditional neuroimaging techniques by providing more causal insights into the functional role of brain regions in behavior.

Furthermore, instrumental learning of metabolic signals might constitute an interesting potential approach for treating brain disorders as several studies have shown that feedback training, besides allowing specific control of localized BOLD signal, is also associated with changes in participants’ behavioral response (Caria et al., 2016, 2012; Weiskopf, 2011).

Enhancing brain connectivity using bidirectional-brain computer interfaces

Bidirectional Brain-Computer-Interfaces (BBCIs) are a promising technology that allows either invasive or non-invasive bidirectional interaction with the brain by simultaneously recording and stimulating neuronal populations.
Specific and localized stimulation to a brain area can be then delivered in real-time contingently to recorded neural activity in one or more neuronal sites. Using this approach spike-timing-dependent plasticity has been demonstrated after an artificial connection between two sites in the motor cortex of freely behaving primates by electrically stimulating one site contingently to action potentials recorded on another site (Jackson et al. 2006).

However, to date, several questions still remain unanswered about the mechanisms of BBCIs-induced neuroplasticity, especially in case of brain networks, for instance: what type of brain stimulation, e.g. in terms of signal types as well as of duration, frequency and amplitude of delivered signals, can more efficaciously induce short-scale and long-scale neuronal connections plasticity? Contingent to what kind of recorded activity in multiple brain regions stimulation should be delivered to other brain sites? And additionally, what are the exact neuronal mechanisms inducing long lasting (de-)potentiation of synaptic connections?

Ultimately, a non-invasive BBCI can be also implemented by combining non-invasive techniques (fMRI, EEG, TMS) and applied in order to manipulate brain connectivity in humans. In this line of research some of the previous questions are addressed using both non-invasive and invasive BBCIs.

External collaborations

Institute of Medical Psychology and Behavioral Neurobiology, Tübingen, Germany
Max Planck Institute for Biological Cybernetics, Tübingen, Germany
RIKEN Brain Science Institute, Wako, Japan
Division of Neuroscience & Experimental Psychology, University of Manchester, UK
Dipartimento di Psicologia, Università di Padova, Italy
Department of Cognitive Neuroscience, Maastricht University, Netherlands.
Sackler Centre for Consciousness Science, University of Sussex, UK
Dipartimento di Psicologia, Università della Campania, Italy

Selected publications

Scientific articles:

Caria, A. Self-Regulation of Blood Oxygenation Level Dependent Response: Primary Effect or Epiphenomenon? FRONTIERS in NEUROSCIENCEe v.10 10.3389/fnins.2016.00117, 2016.
Emmert, K.; Kopel, R.; Sulzer, J.; Brühl, A.B.; Berman, B.D.; Linden, D.E.J.; Horovitz, S.G.; Breimhorst, M.; Caria, A.; Frank, S.; Johnston, S.; Long, Z.; Paret, C.; Robineau, F.; Veit, R.; Bartsch, A.; Beckmann, C.F.; Van De Ville, D.; Haller, S. Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated? NEUROIMAGE 124: 806-12, 2016
Malekshahi R, Mathews Z, Papanikolaou A, Seth, A, Birbaumer N, Verschure P.F.M.J., Caria A. Visual prediction differentially biases implicit and explicit detection of deviant stimuli. NATURE SCIENTIFIC REPORTS 24350, 2016.
Caria A. de Falco S. Anterior insular cortex regulation in autism spectrum disorders. FRONTIERS IN BEHAVIORAL NEUROSCIENCE. v.9 DOI:10.3389/fnbeh.2015.00038, 2015.
Ramos-Murguialday A, Broetz D, Rea M, Laer , Yilmaz Ö, Brasil F , Curado M, Garcia E, Viziotis A, Cho W, Agostini M, Soares E, Soekadar S, Caria A, Cohen LG , Birbaumer N. Brain-machine interface (BMI) in chronic stroke: a controlled double-blind study. ANNALS OF NEUROLOGY. 74:100-8, 2013.
Ruiz S, Lee S, Soekadar S, Caria A, Veit R, Birbaumer N, Sitaram R. Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia. HUMAN BRAIN MAPPING. 34:200-12, 2013.
Caria A, Sitaram R, Birbaumer N. Real-time fMRI: a tool for local brain regulation. Neuroscientist. 18(5):487-501, 2012.
Caria A, Weber C, Brötz D, Ramos A, Ticini LF, Gharabaghi A, Braun C, Birbaumer N. Chronic stroke recovery after combined BCI training and physiotherapy. A case report. Psychophysiology. 48(4):578-582, 2011.
Caria A, Sitaram R, Veit R, Begliomini C, Birbaumer N. Volitional control of anterior insula modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biological Psychiatry. 68(5) 425-432, 2010.
Caria A, Veit R, Sitaram R, Lotze M, Weiskopf N, Grodd W, Birbaumer N. Regulation of Anterior Insular Cortex Activity using Real-time fMRI. NeuroImage, 35, 1238-46, 2007.