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Studying cognitive processes in freely behaving rodents: neurons, oscillations, and behaviour (focusing on hippocampal formation). Colin Lever Institute of Psychological Sciences University of Leeds ART PhD student Day, 15 th March 2011. Plan of the talk.
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Studying cognitive processes in freely behaving rodents: neurons, oscillations, and behaviour (focusing on hippocampal formation) Colin Lever Institute of Psychological Sciences University of Leeds ART PhD student Day, 15th March 2011
Plan of the talk Why focus on the hippocampus? Which regions degenerate first in classic AD? Outline characteristics of neurons supporting spatial cognition and memory in Hippocampal formation Outline Theta oscillation-related changes in environmental novelty (encoding-related changes?) THEN: 2 rodent AD models: one with theta-related impairments, one with CA1 place cell impairments
Why focus on the hippocampal formation? Hippocampus has been linked to memory since H.M.’s devestating memory loss following removal of hippocampus & surrounding tissue In animal literature, two key discoveries in the early 1970s: LTP (Bliss and Lomo, 1973) Place cells (O’Keefe and Dostrovsky, 1971) The Hippocampus is the first region to degenerate in ‘classic’ Alzheimer’s dementia
Stages in Alzheimer’s disease: The spread from entorhinal cortex & CA1 Groups 1, 2, 3, 4, 5, 6, 7 Densities of Neurofibrillary tangles in mm2 in various brain regions amongst 7 groups defined by patterns of damage. These groups are then used ‘post hoc’ to predict clinical features. Groups 1, 2, 3, 4, 5, 6, 7 Corder et al, 2000, Exp Gerontol
Stages in Alzheimer’s disease: The spread from entorhinal cortex & CA1 Groups 1, 2, 3, 4, 5, 6, 7 Group 1 = ‘normal aged’, Groups 2 & 3 = ‘possible AD’, Group 4, 5, & 6 = ‘probable AD’ Group 7 = ‘definite AD’ Corder et al, 2000, Exp Gerontol
Layer II entorhinal cells are critical Profound Loss of Layer II Entorhinal Cortex Neurons Occurs in Very Mild Alzheimer's Disease Teresa Gómez-Isla, Joseph L. Price, Daniel W. McKeel Jr., John C. Morris, John H. Growdon, andBradley T. Hyman Journal of Neuroscience, 1996, 16: 4491-4500 ‘A marked decrement of layer II neurons distinguishes even very mild AD from nondemented aging’. Basic findings replicated by: Kordower et al, 2001, Annals of Neurology 49: 202-213 MCI and mild AD = fewer/atrophied Entorhinal layer II neurons
Layer II entorhinal cells are critical No cog impairment Layer 2 ‘islands’ Layer 2 ‘islands’ Mild cog impairment Alzheimer’s disease Kordower et al, 2001, Annals of Neurology 49: 202-213
Layer II entorhinal cells are critical No cog impairment Layer 2 ‘islands’ Layer 2 ‘islands’ Mild cog impairment Very few layer 2 neurons Alzheimer’s disease Kordower et al, 2001, Annals of Neurology 49: 202-213
Layer II entorhinal cells are critical No cog impairment Layer 2 ‘islands’ Layer 2 ‘islands’ Mild cog impairment Very few layer 2 neurons Alzheimer’s disease Very few layer 2 neurons Kordower et al, 2001, Annals of Neurology 49: 202-213
Stages in Alzheimer’s disease: The spread from entorhinal cortex No cognitive impairment -> Mild cognitive impairment -> Early stage AD -> Developed AD Entorhinal cortex (esp. layer 2) -> CA1 -> Subiculum CA3 -> MTL and temporal cortex -> Other neocortex and subcortical regions
Where to focus in the hippocampal formation? The Hippocampal formation (HF) is the first region to degenerate in ‘classic’ Alzheimer’s dementia Regions affected early on: Entorhinal cortex, CA1, Subiculum The HF is part of ‘septo-hippocampal’ theta system. Medial Septum/DBB has an important role in controlling hippocampal theta. So to develop useful rodent AD models, we need to establish normal physiology and function of neurons and oscillations in the rodent HF. How can we go about doing that?
Extracellular recording in freely moving rodent Example configuration of 1 drive Histology confirms the recording sites of the electrodes Electrodes gradually lowered to target site over days/weeks e.g. one site is CA1 pyramidal layer e.g. other site is Hpc fissure Multi-site dual-drive extracellular recording (64ch)
Extracellular recording in freely moving rodent Example configuration of 1 drive Histology confirms the recording sites of the electrodes Electrodes gradually lowered to target site over days/weeks e.g. one site is CA1 pyramidal layer e.g. other site is Hpc fissure Multi-site dual-drive extracellular recording (64ch) camera Spikes & LFP Track Head position & orientation: LEDs on front & back of head
Extracellular recording in freely moving rodent Example configuration of 1 drive Histology confirms the recording sites of the electrodes Electrodes gradually lowered to target site over days/weeks e.g. one site is CA1 pyramidal layer e.g. other site is Hpc fissure Place cell Firing rate map 10.1 peak rate (Hz) HP Multi-site dual-drive extracellular recording (64ch) camera Spikes & LFP Track Head position & orientation: LEDs on front & back of head Place cell Spike location plot Recording Environment (bird’s eye view)
Extracellular recording in freely moving rodent Example configuration of 1 drive Histology confirms the recording sites of the electrodes Electrodes gradually lowered to target site over days/weeks e.g. one site is CA1 pyramidal layer e.g. other site is Hpc fissure Multi-site dual-drive extracellular recording (64ch) camera Spikes & LFP Track Head position & orientation: LEDs on front & back of head LFP showing theta oscillation Dashed Lines indicate theta peak ‘Raw’ theta (broad low-pass filter) Amplitude (mV) Analytic theta(apply offline 6-12 Hz filter, then Hilbert transform) Time (seconds)
Extracellular recording in freely moving rodent: Recording many neurons simultaneously HP Extracellular spike waveform on each of 4 tetrode tips ‘Place cells’ in CA1 Bird’s eye view of recording environment Coloured square indicates where rat was when cell fired Firing rate maps (taking dwell time into account) All spikes Averaged spike
What do neurons do in different hippocampal regions? CA1 pyramidal cells are ‘place cells’. Entorhinal cortex contains different types of spatial cells. Layer 2 cells are often ‘grid cells’. Subiculum contains different types of spatial cells. Some act like place cells. Some are boundary vector cells. Some are grid cells. We need to develop some idea of how neurons function normally, before we know how to look for impairment.
What do neurons do in region CA1? CA1 pyramidal cells are ‘place cells’. CA1 place cells show context-specific firing (later slides).
Simultaneously recorded CA1 place cells A few cells cover the whole environment The active cells in that environment embody the ‘Cognitive Map’ of that environment They code for location AND spatial context Lever et al, Nature, 2002
What do neurons do in entorhinal cortex? Entorhinal cortex cells are heterogenous population: Grid cells most striking discovery (Hafting et al, Nature, 2005). Many Layer II stellate cells are grid cells. So this may be the first thing that goes wrong in human AD. And if a rat AD model could recapitulate human disease progression, you must understand grid cells.
Grid cells (found in EntorhinalCtx, presubiculum, parasubiculum, and subiculum) 17.5 13.2 Hz Large scale Long distance between peaks ~ 100 cm 9.7 Intermediate scale 5.8 Small scale Short distance between peaks ~30 cm
Grid cells (found in EntorhinalCtx, presubiculum, parasubiculum, and subiculum) 17.5 13.2 Hz Large scale Long distance between peaks ~ 100 cm Mammalian brain divides the environment into triangular grids (broadly equilateral) Each grid cell has a characteristic spatial scale 9.7 Intermediate scale 5.8 Small scale Short distance between peaks ~30 cm
Theta frequency & gain of movement-speed signal Grid cells Spatial scale related to systematic variation in the gain of a movement-speed signal (theta frequency changes) Lower theta frequency MPOs in ventral Entorhinalgrids, where grids have large spatial scale Higher theta frequency MPOs in dorsal EC grids, where grids have small spatial scale Grids seem to provide a strong spatial metric signal, encode distance travelled? 17.5 13.2 Hz Large scale Long distance between peaks ~ 100 cm 9.7 Intermediate scale 5.8 Small scale Short distance between peaks ~30 cm
Head direction cells (presubiculum, entorhinalctx) Code for Head Direction irrespective of location e.g. the 4 quadrants of a cylinder Burgess et al Hippocampus 2005 The brain’s compass Parallel vectors The four vectors do not converge on a point in the distance
What do neurons do in Subiculum? Subiculum contains different types of spatial cells. Some act like place cells (shown). Some are grid cells (shown) Some are boundary vector cells (next slides).
Boundary Vector cells in the Subiculum (Lever et al, 2009, Journal of Neuroscience)
What constitutes a boundary? Wall-less Environments 13.2 Hz 50-cm high walls No walls (drop) No walls (drop) 10 cm gap between the 3 squares
What constitutes a boundary? Wall-less Environments 13.2 Hz 50-cm high walls No walls (drop) No walls (drop) 10 cm gaps between the 3 squares Rat walks across drop
What constitutes a boundary? Wall-less Environments 13.2 Hz 50-cm high walls No walls (drop) No walls (drop) 10 cm gaps between the 3 squares Rat walks across drop
What constitutes a boundary? Wall-less Environments 13.2 Hz 50-cm high walls No walls (drop) No walls (drop) 10 cm gaps between the 3 squares
What constitutes a boundary? Wall-less Environments 13.2 Hz So Subicular boundary vector cells appear to function as high-level spatial perceptual cells Wall and drop don’t share the same visual properties. And BVCs fire in darkness. Function? Spatial Inputs to place cells Anchor grids to external boundaries?
Are these cell types found in humans? Yes, and if not, seems very probable. Place cells: monkeys, humans (Ekstrom et al, Nature, 2003) Head direction cells: in monkey presubiculum. Grid cells: Indirect fMRI evidence (Doeller et al, Nature, 2010) Boundary vector cells: not yet looked for (recent discovery)
Population signal of predicted grid cell activity in right entorhinal cortex
Strong links between spatial/context memory system in rats and autobiographical memory in humans So if we understand the hippocampal system in rodents at the level of neurons and oscillations we will be able to create more precise rodent AD models of episodic/autobiographical memory deficits and provide a more accurate platform for testing therapeutic agents
Do hippocampal neurons show learning? What does it look like at the neuron level? Contextual discrimination learning Square vs Circle
Do hippocampal neurons show learning? What does it look like at the neuron level? Slow Contextual discrimination learning: Can we observe learning develop over time? Can we see memory after a delay? Incidental learning paradigm: Experimenter does nothing to encourage the discrimination learning
Do hippocampal neurons show learning? What does it look like at the neuron level? Slow Contextual discrimination learning: Quite a hard task for the rat? Like too-similar floors in car park? – Takes a while to discriminate.
Contextual discrimination in place cells Fields initially similar
Contextual discrimination in place cells Fields initially similar, then over time cells develop discriminatory firing (slow remapping) Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002
Contextual discrimination in place cells Fields initially similar, then over time cells develop discriminatory firing (slow remapping): Cell fires in one environment, but not in another Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002
Contextual discrimination in place cells Fields initially similar, then over time cells develop discriminatory firing (slow remapping): Cell fires in one environment, but not in another, or Cell fires in different locations in each environment (less common) Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002
Contextual discrimination in place cells Fields initially similar, then over time cells develop discriminatory firing (slow remapping) Day 1: 3/3 similar Day 3: 2/7 similar Day 5: 1/7 similar Day 7: 0/5 similar Observe development of learning! Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002
Memory for what has been learned? Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002 Representations initially similar Over time, cells learn to discriminate the 2 shapes Long-term memory
Memory for what has been learned? YES! Lever, Wills, Cacucci, Burgess, O’Keefe, Nature, 2002 Representations initially similar Over time, cells learn to discriminate the 2 shapes Long-term memory
Summary: CA1 neurons ‘learn’ to discriminate Individual CA1 neurons show ‘long-term plasticity’ Discrimination is observed to increase with more experience of contexts Once learned, the discrimination is remembered after month-long delay
Context-specific firing can develop rapidly if contexts are significantly different 1st 2nd 3rd 4th 5th 6th Trial Sequence Environment Standard Altered (3rd, 4th) Days 1 to 5 Day 6, 8, 10 Holding platform Both walled environments: Intentionally very different spatial contexts
Context-specific firing can develop rapidly if contexts are significantly different Rat 1 Rat 2 Rat 3 Cell 1 Cell 2 Cell 1 Cell 2 Cell 1 Cell 2 Lever et al, unpublished data In this experiment, place cells have ‘remapped’ the different contexts already within the 10-15 minute total trial time in each context
Context-specific firing can develop rapidly if contexts are significantly different Rat 1 Rat 2 Rat 3 Cell 1 Cell 2 Cell 1 Cell 2 Cell 1 Cell 2 As with slow discrimination for subtly-differing context, a) a place cell can discriminate by firing in one context but not another, or by firing in both contexts but in different locations b) it’s incidental learning
The hippocampal theta oscillation is sensitive to novel contexts
Theta Phase and Memory states Hippocampal LTP protocols are optimal using stimulation at theta frequency Theta phase determines whether LTP is achieved, e.g. in CA1 stimulate at theta peak -> strongest LTP LTP Well-established result LTD or no change results Model (Hasselmo et al, 2002) links these plasticity results to memory states. In novelty-elicited encoding there should be: a bias -> information from entorhinal cortex, presumed to arrive near peak of principal-cell layer theta Vs in retrieval, a bias -> predictive CA3 input (arriving at trough)