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Neural Mechanisms of Perception, Memory & Decision

Memory is a major driver of decision-making, as we decide based on the outcomes of previous decisions, but the mechanisms and pathways involved in memory-driven behaviors are still unknown. Failures of such mechanisms, such as manifested in Dementia, Alzheimer’s Disease, Depression and Schizophrenia, constitute a major social challenge, and were the 5th leading cause of global deaths in 2016, rising from 14th in 2000 (WHO 2016).

To face such a challenge, it is imperative that we invest resources in dissecting brain circuits and mechanisms affected in the above conditions. Memory and thereof dependent behaviors rely on a permanent dialogue between the medial temporal cortical region called hippocampus, and other multiple cortical and subcortical regions.

In our lab, we use, a) in vivo electrophysiology with a scalable device harboring 32-independently movable tetrodes (Liang et al. 2017) targeting relevant brain areas, b) genetically-encoded neural actuators expressed in specific neuronal populations in the brain via viral vectors delivered stereotaxically (Jiang, Cui, and Rahmouni 2017), c) behavioral protocols we can manipulate using distinct stimuli-driven contextual manipulations, d) all managed by the same computer using a single software workflow, allowing us unprecedent control over the animal, the environment, and neural circuits.

The possibility of simultaneously interacting with the animal’s behavior and with the brain physiology in real-time gives us an extremely powerful preparation with which to dissect the neural-circuit mechanisms underlying memory-guided behaviors.

Research Team

Ana Cruz
PhD Student

Bárbara Pinto Correia
PhD Student

Gonçalo A. Oliveira
Postdoctoral Researcher

Inês Marques-Morgado
PhD Student

Joana Ribeiro
PhD Student

Jorge Miguel Claro Cardoso
PhD Student

Marcelo Dias
PhD Student

Patrícia Caldeira Bernardo
MSc Student

Sara A. Cruz
MSc Student

Catarina Mesquita
MSc Student

Research Areas

Goal-directed behavior (Brown and Pluck 2000) starts with the attention-guided selection of sensory signals, followed by the storage of a mental representation of context in memory, to be retrieved by other brain areas for further cognitive functions. This process is known to be defective in the three most common neurological disorders, the already mentioned SCZ, AD, and also Autism Spectrum Disorders ASD (Fries 2005; Schnitzler and Gross 2005; Varela et al. 2001), but its mechanisms are largely unknown. To understand them, our research has been focusing on three main questions:

How does sensory information find its way into episodic memory?

Episodic memories, whose sensory details are often overwhelming, depend on the hippocampus (HIPP) (Larry R. Squire 2013). However, HIPP responses to sensory stimuli are neither clear, nor simple. A few studies specifically implicate the secondary occipital area (Oc2M) in signaling, and persistently storing, the spatial source of auditory stimuli (Sánchez et al. 1997; Nakamura 1999; Chen et al. 1994; Raposo et al. 2012).

Our preliminary data indicates that Oc2M neurons oscillate with the HIPP theta rhythm (5-10 Hz), and respond to HIPP memory retrieval events (Miguel Remondes, 2013, umpublished), suggesting its involvement in both sensory processing and memory. In the past 4 years we have identified synapses connecting primary sensory areas, Oc2M, and HIPP (Quintino and Remondes, MSc Thesis), Oc2M neural responses to contextual sound and light stimuli (Cardoso and Remondes, MSc Thesis), associative memory deficits when Oc2M is silenced (Cardoso and Remondes, MSc Thesis), and hippocampal responses to sound, visual and combined (sound+light) stimuli (Cardoso, Ferreira and Remondes, MSc Thesis in prep.).

These preliminary findings point to a circuit connecting primary sensory cortices, Oc2M and hippocampus, responsive to single and multi-mode stimulation. Since we have identified HIPP responses to visual, auditory, and combined stimuli, we are currently testing whether these are dependent on the main sensory gateway into the HIPP, the entorhinal cortex (EC) or rather receives such information from Oc2M. We have used DREADDs to silence EC and are currently analyzing these results.

How is time encoded in episodic memory?

Recent data suggests that HIPP neurons encode context in the temporal dimension. The few studies addressing time processing in episodic memory have identified neurons in the HIPP (Howard and Eichenbaum 2013; Kraus et al. 2013; Eichenbaum 2014; Pastalkova et al. 2008) that signal particular moments of elapsed time, possibly encoding its "when" component. Two major caveats of existing studies, animal locomotion and lack of reward contingent on time judgement, led us to train rats to wait for a specific time lapse (2+ sec) before running down a linear track for a reward while we record neural activity.

We then recorded neural activity from motionless rodents waiting for the right moment to self-initiate a trajectory (a novel task we developed, and whose publication we are preparing currently). This allows us to ask whether time and place coding are associated in the same neuronal populations and test, via optogenetic silencing, which specific synapses are critical for encoding episodic time and place, and for their integration. My lab is currently analyzing data from four animals successfully recorded from, while performing the task, and we have preliminary data suggesting that HIPP neurons do indeed code the passage of time in motionless animals.

In a parallel study, we have used DREADDS, a molecular tool to silence neurons on-demand, too interfere with entorhinal activity, and found that silencing EC impairs the rat’s ability to judge time and behave accordingly (Ferreira, Vieira-Dias and Remondes, MSc Thesis, PhD Thesis, and manuscripts in preparation).

How is mnemonic information used to guide GDB?

The mechanisms responsible for bringing mnemonic information from the HIPP onto medial mesocortical (MMC) areas involved in flexible decision-making are intensely researched but still largely unknown (Delbeuck, Collette, and Van der Linden 2007; Minshew and Williams 2007; Fries 2005; Schnitzler and Gross 2005; Varela et al. 2001; Young, McNaughton, and Canada 2009; Jones and Wilson 2005; Miguel Remondes and Schuman 2004; Ito et al. 2015; Miguel Remondes and Wilson 2013). To dissect them, we have started by describing the patterns of synchronous oscillations linking HIPP with MMC in distinct behavioral epochs: decision-making (Miguel Remondes and Wilson 2013) and memory retrieval (Miguel Remondes and Wilson 2015; Jadhav et al. 2016; Miguel Remondes and Wilson 2013).

Recently we reported that HIPP and MMC are connected directly by a population of neurons from HIPP subregion CA1, following a caudorostral gradient in which a dense, dual (excitatory/inhibitory), and layer-specific projection is progressively converted in a sparse, excitatory, and diffuse projection. This gradient is reflected in the pattern of spontaneous oscillatory synchronicity found in the awake-behaving animal, compatible with the known functional similarity of hippocampus with retrosplenial cortex and contrasting with cingulate cortex (Ferreira-Fernandes, Quintino, and Remondes 2019, accepted for publication at Cell Reports). We are currently analyzing MCC-HIPP neural activity and synchrony during correct vs incorrect trials in a short-term memory task (delayed non-matching to trajectory, DNMT as in Yamamoto and Tonegawa 2017), as well as during the replay of hippocampal memories where we identified significant cortical responses (M. Remondes and Wilson 2015) (manuscripts in preparation), and also manipulating stations in this circuit to test its role in cognition (Uhlhaas and Singer 2012).

Our experiments, using synapse silencers DREADDs and the third-generation optogenetic silencer eNpHR3.0 (a molecular tool triggered by orange light delivered intra-cerebrally) at specific epochs of a short-term memory task (delayed non-matching to trajectory, DNMT as in Yamamoto and Tonegawa 2017), indicate that silencing the anterior regions of the medial mesocortex (ACC) after contextual acquisition impair memory-dependent decision-making.

The possibility of simultaneously interacting with the animal’s behavior and with the brain physiology in real-time gives us an extremely powerful preparation with which to dissect the neural-circuit mechanisms underlying memory-guided behaviors.

Ongoing Research Projects

2019/2021 The physiological role of circadian rhythms in memory. Co-Coordinator: Miguel Remondes. Funding Agency: Fundação BIAL.

2018/2021 Coordenação hipocampo-cortical e mecanismos cognitivos: a formação e recuperação de memórias episodicas durante o comportamento decisional. Coordinator: Miguel Remondes. Funding Agency: Fundação para a Ciência e a Tecnologia.


2019 BIAL Award 2019, as co-investigator with Luisa V. Lopes. "The Physiological Role of Circadian Rhythms in Memory"

2015 iMM Director's Fund Award

2014 FCT Exploratory Grant

2005 Postdoctoral fellowship from FCT-Portugal

2013 FCT Investigator Grant – PI at iMM, Faculty of Medicine, University of Lisbon

1999 Doctoral fellowship from FCT-Portugal, within the Gulbenkian Ph.D. Program in Biology and Medicine

Graduation Awards by the Portuguese Society for Veterinary Sciences:

1993 Bernardo Lima Award for outstanding academic achievements in the areas of: Biomathematics, Genetics and Economics

1993 Ildefonso Borges Award for outstanding academic achievements in the areas of: Parasitology and Parasitic Diseases

1993 Ferreira Lapa Award for outstanding academic achievements in the areas of: Biochemistry, Microbiology and Immunology

Selected Publications

Ferreira-Fernandes, E., Quintino, C., and Remondes, M * (2019). A Gradient of Hippocampal Inputs to the Medial Mesocortex. BioRxiv 535047. DOI: 10.1101/535047.

Liang L, Kirk JC, Schmitt LI, Komorowski RW, Remondes M, Halassa MM and Oline SN (2017). Scalable, Lightweight, Integrated and Quick-to-assemble (SLIQ) hyperdrives for functional circuit dissection. Front. Neural Circuits 11:8. doi: 10.3389/fncir.2017.00008.

Remondes M * and Wilson M (2015) Slow-gamma rhythms coordinate cingulate cortical responses to hippocampal sharp-wave ripples during choice behavior, 2015 Nov 05, Cell Reports doi: 10.1016/j.celrep.2015.10.005.

Wilson M*, Varela C and Remondes M * (2015) Phase organization of network computations Curr Opin Neurobiol, 2015 Feb 10, 31C:250-253 doi: 10.1016/j.conb.2014.12.011.

Wilson M, Varela C* and Remondes M * (2014) Phase regulation of limbic networks, Current Opinions in Neurobiology (invited review, in preparation for a special issue on "Brain rhythms and dynamic coordination").

Remondes M * and Wilson M (2014) Slow-gamma rhythms coordinate cingulate cortical responses to hippocampal sharp-wave ripples during choice behavior (under peer-review at Neuron).

Remondes M * and Wilson M (2013) Cingulate-Hippocampus Coherence and Trajectory Coding in a Sequential Choice Task, Neuron, 80(5), 1277-1289.

Remondes M and Schuman E M (2004) Role for a cortical input to hippocampal area CA1 in the consolidation of a long-term memory, Nature 431, 699-703.

Remondes M and Schuman E M (2003) Molecular Mechanisms Contributing to Long-Lasting Synaptic Plasticity at the Temporoammonic-CA1 Synapse, Learning and Memory 10, 247-252.

Remondes M and Schuman E M (2002) Modulation of Plasticity and Spiking in CA1 Pyramidal Neurons by a Direct Cortical Input, Nature 416, 736-740.

Remondes M and Schuman E M (2002) Direct Cortical Input Modulates Plasticity and Spiking in CA1 Pyramidal Neurons, Nature 416, 736-740.

Useful Links

group leader :
Miguel Remondes