The generality of neuronal architecture related to vastly diverse functions renders it likely that, beyond specific signal processing, there must be a generic function common to all cortical areas in animals and humans. We hypothesize that neocortex is a giant associative storage device, which handles flexible combinations of sensory, motor and cognitive functions that the individual has learned in his/her life.
To verify this hypothesis, we firstly need to clarify how signals are represented within neocortical networks and what role the confusing multitude of neuronal components plays (e.g. the six neocortical layers, or the various types of excitatory and inhibitory neurons). Second, it must be resolved how separate areas are linked and whether the link and concurrent signal processing make use of the same neural elements and activities, or whether they can be separated.
Regarding the close similarity of neocortex in animals and humans it is very likely that basic scientific knowledge that we gain in animals can be generalized very easily to understand also principles of function or dysfunction in humans and patients. Of course, future applications for the better of humans suffering from neocortical diseases such as Alzheimer's and Parkinson’s disease, schizophrenia, or depression, need future progress in applied and translational neuroscience. However, before this can happen, a thorough understanding of the bases of neocortical function has to be reached. This is the purpose of our research.
Beyond the goal to understand the function of neocortex we have started to direct our research toward possible future applications. We work toward the establishment of cortical sensory neuroprostheses, that in the future might help those help patients, who lost a sense due to a disease of the central nervous system. A major problem is that percepts produced by electrical activation of cortical networks depend very much on the sensory and behavioral context. Our solution to this problem is to establish intelligent implants that measure neural activity to assess information about contexts (i.e. the associative state of the cortical tissue to be activated) and use this to increase precision with which sensory signals can be imprinted into central neuronal structures and reach perception.
This research therefore requires the combination of a macroscopic and microscopic view – i.e. the study of representation of memories on the cellular level locally and their linkage between cortical areas globally. We employ modern methods of multiple neuron electrophysiology and optical imaging and combine it with behavioral observation at highest precision. Our model for studying these questions is the sensorimotor vibrissal system (vibrissae = whiskers) of rodents. These animals use an 'active' strategy of sampling tactile information about their immediate environment by actively moving their vibrissae across objects in their vicinity. We examine firstly tactile representations, how they are formed into a percept, and how they are coupled to motor representations to optimize tactile exploration. Secondly, we study the interaction of sensory and so-called higher cortical areas, during decisions making. Thirdly, the formation of coupling of neocortical representations and underlying morphological plasticity is studied during associative learning tasks.
- Operant conditioning of rodents and psychophysics
- Real-time registration of movement and precise sensory stimulation
- Electrophysiological recording via implanted microelectrode arrays
- 2 Photon Microscopy
- Optogenetic interference
- Multi-electrode stimulation
- Stüttgen M.C. and Schwarz C. (2008) Psychophysical and neurometric detection performance under stimulus uncertainty. Nat. Neurosci. 11:1091-1099
- Waiblinger, C., Brugger, D., Schwarz C. (2015) Vibrotactile discrimination in the rat whisker system is based on neuronal coding of instantaneous kinematic cues. Cereb Cortex 25:1093–1106
- Joachimsthaler, B., Brugger, D., Skodras, A., Schwarz, C. (2015) Spine loss in primary somatosensory cortex during trace eyeblink conditioning J Neurosci, 35:3772-3781
- Chakrabarti S., Schwarz C. (2018) Cortical modulation of sensory flow during active touch in the rat whisker system. Nat. Commun. 9:3907.
- Bhattacharjee A., Braun C., and Schwarz C. (2021). Humans use a temporally local code for vibrotactile perception. eNeuro 8:ENEURO.0263-21.2021.
- Schwarz C, Thier P (1999) Binding of signals relevant for action: towards a hypothesis of the functional role of the pontine nuclei. Trends Neurosci. 22: 443-451.
- Feldmeyer, D., Brecht, M., Helmchen, F., Petersen, C.C.H., Poulet, J., Staiger, J., Luhmann, H., Schwarz C. (2013) Barrel cortex function. Progress in Neurobiology 103: 3–27
- Schwarz C. (2016) The slip hypothesis: Tactile perception and its neuronal bases. Trends Neurosci 39:449–462. doi: 10.1016/j.tins.2016.04.008
- Stüttgen M.C., Schwarz C. (2018) Barrel cortex: What is it good for? Neuroscience 368: 3–16