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Mechanisms underlying feature selectivity in primary sensory - - PowerPoint PPT Presentation
Mechanisms underlying feature selectivity in primary sensory - - PowerPoint PPT Presentation
Mechanisms underlying feature selectivity in primary sensory cortices Thomas Bessah In other to get access to the speakers comments, click on: Comments\show comments list Kaniza Triangle 0 o A 90 o L 90 o R A L A R pulvinar pretectum
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Kaniza Triangle
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0o 90oL 90oR A
AL AR
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LGN Optic tract Optic radiation pulvinar pretectum
- Post. commissure
Medial geniculate caudate fornix
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1,2 = magnocellular (M); 3,4,5,6 = parvocellular (P) 1,4,6 = contralateral; 2,3,5 = ipsilateral ON and OFF cells separated in P layers (not M layers) Six layers Why? Optic tract
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ON-center and OFF-center LGN cells
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Retinotopic organization – “simple” but “distorted”
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Anterograde transsynaptic degeneration due to loss of right eye
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LGN receptive fields: same as in retina M cells (10%)– large, motion sensitive, no color selectivity P cells (80%) – small, center-surround, color selective
In foveal representation the pathway is one to one: RGC LGN Layer IVC of area 17
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Waking state
The gate is open Thalamic reticular nucleus (RNT)
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Sleep
The gate is closed
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M-cells
- orientation selective
- direction selective
- stereoscopically sel.
- just like LGN Mcell RFs
To extrastriate cortex (MT) pia white matter
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Orientation selectivity of cortical cells
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On-center RF of cell in IVB Off-center RF of cell in IVB RGC LGN IVCα IVB
Retina thalamus striate cortex
M-cell pathway
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Orientation selectivity
Hubel and Wiesel, 1962
IVCalpha IVB
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The Feedforward Model of Orientation Selectivity in Primary Visual Cortex
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Contrast Invariance of Orientation Tuning
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Contrast Invariance of Orientation Tuning
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Trial-to-Trial Response Variability and the Origin of Contrast- Invariant Orientation Tuning in Simple Cells
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The Biophysical Mechanisms Underlying stimulus dependant changes in spike threshold of V1 Simple Cells
INA ANA
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The Biophysical Mechanisms Underlying the Response Properties of V1 Simple Cells
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Lateral connectivity! (similar to retina)
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Reference RF # Reference RF recorded at the asterisk doesn’t change
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Kaniza Triangle a b c
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Schizophrenia and Visual Discrimination
Spencer et al., Proc Nat Acad Sci. 101:17288-17293, 2004 Normal Schiz
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Cat V1 Layer IV simple cell
FF > 1.0
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Precise but not reliable Reliable but not precise
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Mainen and Sejnowski, 1995
Biophysical Limits?
CNQX + APV + bicuculline
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Reinagel and Reid, 2000
Synaptic Limits? Lateral Geniculate Nucleus
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Stone et al., 1979
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What about visual cortex?
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What about visual cortex?
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LGN Layer IV
Excitatory Synapse
Bright Stimulus LGN Layer IV
Excitatory Synapse Inhibitory Synapse (via interneuron, not shown)
Bright Stimulus Push-Pull Push only
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A better stimulus: contrast modulated Gabor patch
Spatial location Spatial frequency Orientation Spatial Phase Length Width
Jones and Palmer, 1987a,b,c
Optimization:
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Methods
- Extracellular recording in vivo, barbiturate anesthetized cat
- LGN X- and Y-cells, Layer IV Simple cells in Area 17 (V1)
- Contrast modulated Gabor patch optomized for each cell
- Contrast drawn from Gaussian distribution (mean = 0, SD = 31%) at 125 Hz
- Spike timing is acquired with a time resolution of 0.1 ms and spike times are
rebinned using 1 ms bins (typically ISImin > 2 ms, therefore only 1 spike/bin).
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X = 46 Y = 24 S = 50 Number of events
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Key question
- How is the cortex able to maintain the precision of
its principle inputs? The stimulus itself – produces synchronous activation of LGN cells
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69% 77% 75% 69%
LGN neurons of the same cell type respond similarly given the same Gabor patch sequence.
Suggests: All LGN neurons located within a lobe of simple cell’s receptive field, respond similarly.
Similarity of LGN input across cells and cats
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The responses of on-centered, LGN neurons are similar to the responses of off-centered, LGN neurons to inverted version of the same stimulus. Similarity of LGN ON-NS/OFF-IS inputs to Cortex
Suggests: Our stimulus synchronously activates all the LGN afferents of Layer IV simple cells.
70% 75%
Time (s) Time (s) Time (s)
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Σ Σ
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Summed ON-ns and OFF-is LGN Response Simple Cell
Simple cells are as precise as any one of their inputs and more precise than the sum of their inputs.
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Key questions
- How is the cortex able to maintain the precision of
its principle inputs?
Cortical cells are sensitive to highly synchronous
input from LGN afferents
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Excite two non-overlapping populations of LGN afferents at different times relative to each other.
Methods A B
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Facilitation and suppression of the response Bar A suppresses Bar B
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Intracellular recording (sharpies)
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Intracellular recording (sharpies)
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Supralinear for spikes but sublinear for EPSPs
Can be explained by the accelerating non-linearity in the spike generating mechanism (Reid, et al., 1987; DeAngelis et al., 1993a,b; Anzai et al., 1999; Carandini & Ferster, 2000; Nykamp & Ringach,
2002)
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- LGN X and Y cells and cortical simple cells have highly stereotyped responses to
stimuli containing rapid transients
- Simple cells are as precise as any one of their LGN X-cell inputs and more precise
than their putative pooled input
- Membrane potential in simple cells follows the pooled LGN input closely
- Biophysical mechanisms related largely to the spike generation in simple cells render
the response to synchronized thalamic input larger and more precise than expected
- The stimulus…
- Coincidence detection……