Experimental and theoretical studies have tried to gain insights into the involvement of the Temporal Parietal Junction (TPJ) in a broad range of cognitive functions like memory, attention, language, self-agency and theory of mind. Recent investigations have demonstrated the partition of the TPJ in discrete subsectors. Nonetheless, whether these subsectors play different roles or implement an overarching function remains debated. Here, based on a review of available evidence, we propose that the left TPJ codes both matches and mismatches between expected and actual sensory, motor, or cognitive events while the right TPJ codes mismatches.

These operations help keeping track of statistical contingencies in personal, environmental, and conceptual space. We show that this hypothesis can account for the participation of the TPJ in disparate cognitive functions, including “humour”, and explain: a) the higher incidence of spatial neglect in right brain damage; b) the different emotional reactions that follow left and right brain damage; c) the hemispheric lateralisation of optimistic bias mechanisms; d) the lateralisation of mechanisms that regulate routine and novelty behaviours.

We propose that match and mismatch operations are aimed at approximating “free energy”, in terms of the free energy principle of decision-making. By approximating “free energy”, the match/mismatch TPJ system supports both information seeking to update one’s own beliefs and the pleasure of being right in one’s own’ current choices. This renewed view of the TPJ has relevant clinical implications because the malfunctioning of TPJ-related “match” and “mismatch” circuits in unilateral brain damage can produce low-dimensional deficits of active-inference and predictive coding that can be associated with different neuropsychological disorders.

NAP (davunetide, AL-108, CP201), a drug candidate derived from activity-dependent neuroprotective protein (ADNP) provides neuroprotection through microtubule fortification. ADNP knockout is lethal and ADNP haploinsufficiency coupled with heterozygous toxic gain of function truncation mutation leads to early-onset Alzheimer’s disease (AD) -like tauopathy, accentuated in male mice and corrected by NAP. In humans, de novo, or somatic mutations in ADNP lead to the neurodevelopmental ADNP syndrome, exhibiting early onset tauopathy, or correlating with AD tauopathy, toward NAP future development.

The human brain is flexible. Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization in the language network with neurostimulation and neuroimaging. I will argue that short-term plasticity enables flexible adaptation to challenging conditions, via functional reorganization.

The key hypothesis of Prof. Hartwigsen is that disruption of higher-level cognitive functions such as language can be compensated for by the recruitment of domain-general networks in our brain. The talk will cover examples from healthy young, aging, and lesioned brains. Collectively, these results challenge the view of a modular organization of the human brain and argue for a flexible redistribution of function via systems plasticity.

How can we understand ourselves as sentient creatures? And what are the principles that underwrite sentient behaviour? This presentation uses the free energy principle to furnish an account in terms of active inference.

First, we will try to understand sentience from the point of view of physics; in particular, the properties that self-organising systems—that distinguish themselves from their lived world—must possess. We then rehearse the same story from the point of view of a neurobiologist, trying to understand functional brain architectures.

The narrative starts with a heuristic proof (and simulations of a primordial soup) suggesting that life—or biological self-organization—is an inevitable and emergent property of any dynamical system that possesses a Markov blanket.

This conclusion is based on the following arguments: if a system can be differentiated from its external milieu, then its internal and external states must be conditionally independent. These independencies induce a Markov blanket that separates internal and external states. Crucially, this equips internal states with an information geometry, pertaining to probabilistic beliefs about something; namely external states. This free energy is the same quantity that is optimized in Bayesian inference and machine learning (where it is known as an evidence lower bound). In short, internal states will appear to infer—and act on—their world to preserve their integrity. This leads to a Bayesian mechanics, which can be neatly summarised as self-evidencing.

In the second half of the talk, we will unpack these ideas using simulations of Bayesian belief updating in functional brain architectures – and relate them to predictive processing and how we respond to affordances in our world.

The multidisciplinary approaches that are currently being used in my lab to gain access to functional and electrophysiological information of human synapses in Schizophrenia and Alzheimer’s disease.

Because synapses are major targets of pathological events characterizing these disorders, accessing this information, and integrating it in the context of molecular and biochemical changes, helps in understanding the association between synaptic alterations and the presentation of behavioral symptoms. We will also discuss how these synaptic alterations participate in the excitation to inhibition balance that has been proposed to be affected in these disorders opening the possibility to the development of new therapeutic strategies.

The overarching goal of neuroscience is to decode the complexities of the brain and enhance our understanding of cognition, behaviour, as well as neurobiological and neuropsychiatric disorders. In an era where the field is experiencing exponential growth, this panel discussion featuring Prof. Thomas Nowotny, Dr. Shabnam Kadir and Dr. Christoph Metzner delves into the most promising approaches likely to catalyse breakthroughs, as well as into the conceptual and methodological limitations that need to be overcome to that end.